Complex Characteristics Research Articles

Machine learning-assisted effective thermal management of rotor-stator systems

Rotor-stator systems are widely used to facilitate highly effective energy management and process intensification but have complex design characteristics, such as skittish flow and heat transfer. Due to the difficulty in obtaining heat transfer data for thermal management of rotor-stator systems, uneconomical designs with large margins often occur. Here, we propose a comprehensive design process using machine learning guided by convective heat transfer experimental data. We organize domain knowledge involving advection and convective heat transfer using a test rig employing a naphthalene sublimation method on large surfaces. Detailed heat transfer data elucidates that local thermal-fluid characteristics are non-linear as the operating conditions change, which is supported by numerical simulation models. We develop a machine learning-based heat transfer prediction model using pure experimental data and derive the optimal algorithm model. Thermal analysis via 2D thermal circuits provides an effective design process and enables rapid quantified evaluation of critical performance considerations. An improved rotor-stator system simultaneously achieves high heat flux of 1.9 kW/m2 and low thermal resistance of 17.1 K/W to both disks. We expect our experiment-based machine learning-assisted thermal management will serve as a robust and informative indicator for improving the efficiency and feasibility of applications with multivariate thermal-fluid systems.

Analyzing thermal maturity effect on shale organic matter via PeakForce quantitative nanomechanical mapping

Organic-rich shales have gained significant attention in recent years due to their pivotal role in unconventional hydrocarbon production. These shale rocks undergo thermal maturation processes that alter their mechanical properties, making their study essential for subsurface operations. However, characterizing the mechanical properties of organic-rich shale is often challenging due to its multiscale nature and complex composition. This work aims to bridge that knowledge gap to fully understand the nanomechanical properties of Shale organic matter at various thermal maturation stages. This study employs PeakForce Quantitative Nanomechanical Mapping (PF-QNM) using Atomic Force Microscopy (AFM) to investigate how changes at the immature, early mature, and peak mature stages impact the mechanical properties of the Bakken Shale organic matter. PF-QNM provides reliable mechanical measurements, allowing for the quantification and qualification of shale constituents' elastic modulus (E). We also accounted for the effect of probe type and further analyzed the impact of probe wear on the nanomechanical properties of shale organic matter. In immature shale, the average elastic modulus of organic matter is approximately 6 ​GPa, whereas in early mature and peak mature shale, it decreases to 5.5 ​GPa and 3.8 ​GPa, respectively. Results reveal a mechanical degradation with increasing thermal maturation, as evidenced by a reduction in Young's modulus (E). Specifically, the immature shale exhibits an 8% reduction in E, while the early mature and peak mature shales experience more substantial reductions of 31% and 37%, respectively. This phenomenon could be attributed to the surface probing of low-modulus materials like bitumen generated during heating. The findings underscore the potential of AFM PF-QNM for assessing the nanomechanical characteristics of complex and heterogeneous rocks like shales. However, it also highlights the need for standardized measurement practices, considering the diverse components in these rocks and their different elastic moduli.

Applications of Fractional Time Delayed Grey Model in Primary Energy Consumption Prediction

The prediction of total energy consumption is crucial across various domains including the economy, environment, market, and geopolitics. Accurate forecasts can guide policy-making, investment decisions, and international strategies, contributing to sustainable development and energy security. Fractional models have been proven to better capture the long-term memory effects and complex dynamic characteristics of systems, with time delay playing a crucial role in capturing dynamic behaviors. Such models enhance the accuracy and reliability of predicting future trends and behaviors. For the prediction of primary energy consumption in South and Central America, the Middle East, and Africa, this study opts for the existing fractional time delayed grey model, optimizing the fractional order using the particle swarm optimization algorithm. Experimental results demonstrate that in most cases, the predictive capability of the fractional time delayed grey model surpasses that of other grey models. This indicates the effectiveness and reliability of the model in forecasting energy consumption, providing valuable references and foundations for decision-making in relevant fields.

Machine learning ground motion models for a critical site with long-term earthquake records

Ground motion models derived using data from widespread stations and earthquakes induce significant aleatory variability when applied to predict ground motions for a single site. This issue can be even worse when the sites of interest show complex site response characteristics and do not have enough similar sites in the ground motion model development dataset. This work provides a machine-learning-based ground motion modeling framework for sites with numerous earthquake recordings. The Onahama Port Array, a liquefiable site in Japan that has recorded more than 1200 earthquakes in the last 25 years, was selected as a case study. The gradient boosting method was employed to predict response spectra with periods from 0.01 to 10 s for earthquakes with Japan Meteorological Agency (JMA) magnitude ranging from 2.4 to 9.0. Different predictor combinations were tested, and two gradient boosting models were recommended: the basic model that requires earthquake magnitude and epicentral distance as inputs, and the optimal model that requires three additional inputs, focal depth, azimuth, and rainfall. The basic and optimal gradient boosting models have the root mean square error of 0.004 and 0.001 g, average r2 of 5-fold cross validation of 0.915 and 0.983, respectively. The results shed light on seismic hazard assessment for critical sites with long-term earthquake recordings.

Analysis and Applications of the Chaotic Hyperbolic Memristor Model with Fractional Order Derivative

This work presents a new five-dimensional fractional-order chaotic system that includes a feedback memristor. A Lorenz-Stenflo-based fractional-order chaotic system with five dimensions that contains feedback memristor dynamics is used to do this. This work focuses on chaotic models through the ABC fractional derivative, a concept we rigorously examine. We designed and usedsophisticated numerical algorithms to model fractional-order dynamics with the utmost precision to understand this system’s complex characteristics. These numerical approaches excel at non-integer order differentiation, which standard numerical methods struggle with. Our research uses fractional calculus to increase the system’s complexity and robustness, revealing its hyperchaotic nature. We demonstrate that the system is chaotic and stable over fractional orders using eigenvalues, Lyapunov exponents, Kaplan-Yorke dimensions, maximal exponents, phase portraits, and equilibrium points. Our conclusions are strengthened by using these numerical systems, intended for this work, and analytical tools. We improve our understanding of fractional-order chaotic systems with our research. It illuminates how to improve electrical integrations and create more sophisticated nonlinear dynamical systems. This work establishes the approach and insights for future research, guiding the development of new systems with enhanced dynamical features

The relationship between clinical presentation and the nature of care in adults with intellectual disability and epilepsy - national comparative cohort study.

A quarter of People with Intellectual Disabilities (PwID) have epilepsy compared with 1% of the general population. Epilepsy in PwID is a bellwether for premature mortality, multimorbidity and polypharmacy. This group depends on their care provider to give relevant information for management, especially epilepsy. There is no research on care status relationship and clinical characteristics of PwID and epilepsy. Explore and compare the clinical characteristics of PwID with epilepsy across different care settings. A retrospective multicentre cohort study across England and Wales collected information on seizure characteristics, intellectual disability severity, neurodevelopmental/biological/psychiatric comorbidities, medication including psychotropics/anti-seizure medication, and care status. Clinical characteristics were compared across different care settings, and those aged over and younger than 40 years. Of 618 adult PwID across six centres (male:female = 61%:39%), 338 (55%) received professional care whereas 258 (42%) lived with family. Significant differences between the care groups existed in intellectual disability severity (P = 0.01), autism presence (P < 0.001), challenging behaviour (P < 0.001) and comorbid physical conditions (P = 0.008). The two groups did not vary in intellectual disability severity/genetic conditions/seizure type and frequency/psychiatric disorders. The professional care cohort experienced increased polypharmacy (P < 0.001) and antipsychotic/psychotropic use (P < 0.001/P = 0.008).The over-40s cohort had lower autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) comorbidity (P < 0.001/P = 0.007), increased psychiatric comorbidity and challenging behaviour (P < 0.05), physical multimorbidity (P < 0.001), polypharmacy (P < 0.001) and antipsychotic use (P < 0.001) but reduced numbers of seizures (P = 0.007). PwID and epilepsy over 40 years in professional care have more complex clinical characteristics, increased polypharmacy and antipsychotic prescribing but fewer seizures.

Analysis of dynamic characteristics of whipping effect on l-shaped main steam pipe considering fluid-structure interaction effect

To investigate the whipping effect on the L-shaped main steam pipe utilized in the marine steam systems, the fluid-structure interaction (FSI) method is utilized to numerically analyze its dynamic characteristics. The numerical results illustrate that the dynamic response of whipping effect with rupture position B on the oblique pipe section is more severe with the significantly larger displacement of L-shaped pipe and anti-whip restraints and more complex frequency characteristics than that of whipping effect with rupture position A on the right-angled elbow. The mode transition phenomenon is also observed in the case with rupture position B. The maximum deformation concentrates on different parts when burst of pipes occurs at different positions and the deformation with rupture position B is several times larger than that with rupture position A. The increase of gap between anti-whip restraints intensifies the whipping effect, but it also reduces the maximum restraint force. The friction acts as the resistance in the slip process and thus contributes to the protection against whipping effect. The anti-whip restraints E closed to rupture position B on the oblique pipe section has better performance than anti-whip restraints D in the protection against horizontal whipping effect.

Analysis of Aroma Components of Enzymatic Hydrolysis Products of Oak Lignin from Different Producing Areas

The morphology and structure of lignin in French oak, American oak and Chinese Mongolian oak were observed and compared by scanning electron microscopy (SEM). The results showed that the surface of lignin after enzymatic hydrolysis was more irregular and the contact area was obviously increased. GC-MS detected 3 kinds of lignin, 4 kinds of components and 30 kinds of volatile substances. The lignin content of French oak was the highest (8911.5 ± 512.2 μg/L, 29 kinds), followed by that of American oak (8071.7 ±541.9 μg/L, 26 kinds), and that of Mongolian oak was the least (7903.3 ± 492.5 μg/L, 26 kinds). The results of aroma characteristics analysis, principal component analysis and heat map analysis showed that the aroma components of the three kinds of oak lignin were significantly different. French oak lignin could provide more volatile phenols, with obvious smoky, woody and sweet flavor. Mongolian oak lignin carries more phenolic and ester compounds, providing a relatively soft floral, fruity flavor. American oak lignin has a relatively average aroma substance content, which can bring strong and complex complex aroma characteristics.

Silent Letters in the Balinese Script | | Adeg Adeg: A Graphetic and Graphematic Feature Analysis

The concept of “silent letters” relates to graphic symbols that are not pronounced or that do not have mapping with a specific linguistic unit. In the context of processing the mapping of sequences of linguistic units to writing, this concept often results in ambiguity. The Balinese script, which refers to a silent letter, appears in a basic shape || adeg adeg. Scholars of Balinese script define adeg adeg as a process to eliminate characters (Akshara’s), resulting in consonants without inherent vowels. This explanation is very metaphorical, ambiguous, and not based on adequate terms to describe graphetic and graphematic features that are related to mappings between graphic unit sequences and linguistic unit sequences. Balinese script || adeg adeg as primary data comes from the 16.162 lemma in the Balinese dictionary - Indonesian with Latin and Balinese script. Adeg adeg is analyzed both graphically and graphematically to identify its characteristics, with the stages of analysis adapted from the Multimodular Model of Writing System proposed by Meletis (2018). Graphetic analysis shows that the adeg adeg is identified as basic shapes || with three salient graphetic features: -recodability, -paired variants, and +additive. Graphematically, adeg-adeg is defined as a grapheme &lt;&gt; with the following features: +lexical distinctiveness, +linguistic value, and +minimality. The clarity of graphetic and graphematic characteristics significantly contributes to a more comprehensive and transparent cognitive-linguistic mechanism depiction, especially in deciphering writing systems based on Akshara’s highly complex characteristics.

Effect of pore structure characteristics on gas-water seepage behaviour in deep carbonate gas reservoirs

The study of gas-water two-phase flow behavior has always been a focus and a difficult problem in the field of oil and gas seepage, and it is related to the formulation of reasonable development plans for oil and gas reservoirs. Deep carbonate gas reservoirs (depth>4500m) develop cross-scale porous media, which have extremely strong heterogeneity and very complex seepage characteristics. To the best of our knowledge, there has been no systematic study on the two-phase flow patterns of gas and water in deep carbonate gas reservoirs. This paper uses cast thin sections, scanning electron microscopy (SEM) and nuclear magnetic resonance (NMR) to study the influence of carbonate rock pore structure characteristics on gas storage and seepage capabilities. The results show that the existence of cavities enhances the gas storage capacity of the reservoir and improves the seepage capacity of pore-throat space near the cavity. Fractures can effectively communicate with isolated cavities, enhance reservoir connectivity, and thereby significantly improve the overall seepage capacity of the reservoir. The centrifugal technique was combined with NMR to study the movable fluid characteristics of carbonate reservoirs. The critical flow throat radius and movable fluid saturation of the reservoir reveal that the degree of development of cavities and fractures determines the mobility of the fluid in the reservoir. The fluid mobility in the fracture-cavity-type reservoir is the strongest, while the fluid mobility in the pore-type reservoir is the weakest. Analysis of the normalized curve of gas-water relative permeability under high temperature and pressure reveals that formation water preferentially enters connected pores with low seepage resistance, and the strong storage capacity of cavities can effectively delay the non-uniform intrusion of formation water. The results of water invasion simulation experiments show that the water invasion phenomenon can improve the gas production rate and recovery rate of pore-type reservoirs. However, the formation water flow and channeling phenomena caused by reservoir heterogeneity will cause a large amount of gas to be sealed in the pore space of cavity-type and fracture-cavity-type reservoirs, reducing the recovery rate and economic benefits of these reservoirs. These findings further provide solid fundamentals for efficient and effective exploitation of deep carbonate gas reservoirs.

High-Sensitivity Detection of Carbon Fiber-Reinforced Polymer Delamination Using a Novel Eddy Current Probe

The demand for non-destructive testing of carbon fiber-reinforced polymer (CFRP) is becoming increasingly pressing to ensure its safety and reliability across different fields of use. However, the complex structural characteristics and anisotropic bulk conductivity of CFRP make achieving high sensitivity in detecting internal defects such as delamination extremely challenging. To address this issue, a novel triple rectangular coil probe with high sensitivity developed for detecting delamination in CFRP is presented in this paper. A finite element model using COMSOL Multiphysics was developed for CFRP delamination eddy current testing with the designed probe. Based on this model, the probe parameters were determined through orthogonal experiments. By analyzing the eddy current distribution in CFRP samples, the scanning mode was defined. Following this, the detection voltage was evaluated for various delamination parameters, and the sensitivity of different probes was compared. Results indicate that, under the same excitation coil parameters, for a 5 mm delamination lateral dimension change, the single pancake and single rectangular coil probes exhibit sensitivities of 88.24% and 72.55%, respectively, compared with the designed probe. For a 0.5 mm delamination thickness change, their sensitivities are 49.04% and 56.69% of those of the designed probe. The designed probe meets the demand for high-sensitivity detection.

Лексикографическое портретирование лексемы «абсурд»

The aim of the research is to provide a lexicographic representation of the word ‘абсурд’ (absurd), compiled on the basis of data from various linguistic dictionaries. To compile a lexicographic portrait of this word in accordance with the theory of Yu. D. Apresyan, it was necessary to consider it from various sides: etymological, word-formation, grammatical, syntactic, stylistic, phraseological, pragmatic. This became the subject of the research and determined the structure of the work. The paper clarifies the lexical meaning of this word and gives its complex characteristics in various aspects. The scientific novelty lies in a comprehensive linguistic description of the lexical unit under study, which allows us to identify the history of its appearance in the language in the middle of the 19th century, trace its development up to the present day, show its collocability and speech functioning. As a result of the research, it was revealed that the lexical meaning of the lexeme ‘абсурд’ has practically not changed since its appearance in the Russian language, however, it has received quite significant clarifications, which is manifested in its collocability and systemic connections.

Study on Prevention and Countermeasures of Payment and Settlement Risks of Commercial Banks

The prevention and countermeasures research of commercial banks' payment settlement risks have always been important issues in the financial field. With the rapid development of electronic payments and internet finance, payment settlement risks have increasingly demonstrated diversified and complex characteristics. This paper aims to study the prevention and countermeasures of payment settlement risks in commercial banks to enhance the security and stability of their payment settlement business. Through the analysis of the concept, characteristics, and influencing factors of payment settlement risks, various prevention strategies are discussed. Furthermore, methods and tools for risk assessment and monitoring, as well as optimization and innovation directions for risk management of payment settlement in commercial banks, are explored. This paper aims to provide theoretical support and practical guidance for the management of payment settlement risks in commercial banks.

Pea protein isolate-soluble soybean polysaccharides electrostatic assembly: effect of pH, biopolymer mass ratio and heat treatment.

In past years, thousands of protein-polysaccharide complexes have been investigated to modify protein characteristics and functionality in food systems. However, the interaction between pea protein isolate (PPI) and soluble soybean polysaccharide (SSPS) has not been thoroughly characterized yet. In the present study, the phase behavior of PPI and SSPS mixtures was analyzed as a function of PPI:SSPS mixing ratio (1:1 to 1:0.10) and pH (7.0 to 2.0), showing that these biopolymers could be electrostatically assembled at 1:1 to 1:0.25 mixing ratios and 4.0 to 3.0 pH values. Then, the characteristics of the PPI-SSPS complexes were studied before and after heating (90 °C and 30 min) by ζ-potential, surface hydrophobicity, protein solubility, particle size distribution and physical stability for 56 days. By lowering the pH and PPI:SSPS mixing ratio, the complexes showed increased solubility, changed 𝜁-potential and higher physical stability. By heating, the complexes presented increased hydrophobicity and physical stability. Overall, PPI-SSPS complexes increased the protein solubility, reduced the particle size, and changed both the ζ-potential and the surface hydrophobicity with respect to PPI control, allowing stabilization of the colloidal system and broadening the possible applications of these high-quality proteins in acidic food systems. © 2024 Society of Chemical Industry.

Analysis of Current Situation, Problems and Countermeasures of Big Data in the Field of Engineering Management

Currently, the field of engineering management is experiencing rapid development and has become a significant force in promoting economic and social growth. Due to its complexity, creativity, systematization, and risk characteristics, the field of engineering management presents individuals with significant technical needs and processing difficulties. Big data has achieved significant advancements in the engineering management field due to its characteristics, including large data volumes, various types, and predictability. By utilizing big data, a sizable amount of engineering data can be rapidly analyzed and optimized for design solutions, resulting in improved efficiency and increased accuracy in decision-making while also reducing costs. However, the role of big data in engineering management is limited by issues such as data insecurity, low quality, and a shortage of professionals. This paper proposes solutions to address these challenges, including strengthening data security, enhancing data quality control, and improving personnel training and technological innovation.

Dynamics and Complexity Analysis of Fractional-Order Inventory Management System Model

To accurately depict inventory management over time, this paper introduces a fractional inventory management model that builds upon the existing classical inventory management framework. According to the definition of fractional difference equation, the numerical solution and phase diagram of an inventory management system are obtained by MATLAB simulation. The influence of parameters on the nonlinear behavior of the system is analyzed by a bifurcation diagram and largest Lyapunov exponent (LLE). Combined with the related indexes of time series, the complex characteristics of a quantization system are analyzed using spectral entropy and C0. This study concluded that the changing law of system complexity is consistent with the LLE of the system. By analyzing the influence of order on the system, it is found that the inventory changes will be periodic in some areas when the system is fractional, which is close to the actual conditions of the company’s inventory situation. The research results of this paper provide useful information for inventory managers to implement inventory and facility management strategies.

Multi-institution single geometry plan complexity characteristics based on IROC phantoms.

Clinical intensity modulated radiation therapy plans have been described using various complexity metrics to help identify problematic radiotherapy plans. Most previous studies related to the quantification of plan complexity and their utility have relied on institution-specific plans which can be highly variable depending on the machines, planning techniques, delivery modalities, and measurement devices used. In this work, 1723 plans treating one of only four standardized geometries were simultaneously analyzed to investigate how radiation plan complexity metrics vary across four different sets of common objectives. To assess the treatment plan complexity characteristics of plans developed for Imaging and Radiation Oncology Core (IROC) phantoms. Specifically, to understand the variability in plan complexity between institutions for a common plan objective, and to evaluate how various complexity metrics differentiate relevant groups of plans. 1723 plans treating one of four standardized IROC phantom geometries representing four different anatomical sites of treatment were analyzed. For each plan, 22 MLC-descriptive plan complexity metrics were calculated, and principal component analysis (PCA) was applied to the 22 metrics in order to evaluate differences in plan complexity between groups. Across all metrics, pairwise comparisons of the IROC phantom data were made for the following classifications of the data: anatomical phantom treated, treatment planning system (TPS), and the combination of MLC model and treatment planning system. An objective k-means clustering algorithm was also applied to the data to determine if any meaningful distinctions could be made between different subgroups. The IROC phantom database was also compared to a clinical database from the University of Wisconsin-Madison (UW) which included plans treating the same four anatomical sites as the IROC phantoms using a TrueBeam™ STx and Pinnacle3 TPS. The IROC head and neck and spine plans were distinct from the prostate and lung plans based on comparison of the 22 metrics. All IROC phantom plan group complexity metric distributions were highly variable despite all plans being designed for identical geometries and plan objectives. The clusters determined by the k-means algorithm further supported that the IROC head and neck and spine plans involved similar amounts of complexity and were largely distinct from the prostate and lung plans, but no further distinctions could be made. Plan complexity in the head and neck and spine IROC phantom plans were similar to the complexity encountered in the UW clinical plans. There is substantial variability in plan complexity between institutions when planning for the same objective. For each IROC anatomical phantom treated, the magnitude of variability in plan complexity between institutions is similar to the variability in plan complexity encountered within a single institution database containing several hundred unique clinical plans treating corresponding anatomies in actual patients.

When Do Users Prefer Voice Control Systems in Vehicles? A Survey of Chinese Drivers

Voice control systems (VCSs) are becoming increasingly common in modern vehicles, but concerns are still expressed by drivers about adopting them in smart cockpits. Previous research on privacy and recognition accuracy may not fully address users’ needs with regard to VCSs. In addition, studies on the safety impacts of different interaction modalities may not reveal drivers’ preference for interaction modalities, given that driver choice may not be solely based on interaction safety. Thus, to better understand and optimize VCSs design, an online survey was conducted in China to investigate drivers’ choices between VCSs and manual interaction. In total, we analyzed 168 drivers’ preferred interaction modality (i.e., either VCSs or manual interaction) in different scenarios defined by passenger presence (i.e., present versus absent), traffic complexity (i.e., low versus high traffic density), roadway type (i.e., urban road versus highway), and task characteristics (i.e., six in-vehicle interaction tasks). Compared with manual interactions, drivers preferred VCSs when driving alone, driving on highways, and driving in complex traffic. Further, drivers preferred VCSs when in-vehicle tasks were more distracting and time-demanding (e.g., compiling a text message). The preference for interaction modalities could also be affected by the characteristics of drivers: those with lower driving frequencies and higher VCSs familiarity and those who perceived higher VCSs usability tended to choose VCSs as an interaction modality for in-vehicle interaction tasks. These findings offer insights for adaptive interface design and future optimization of VCSs.

Strengthen Financial Risk Prevention and Control Capabilities and Improve the Quality and Efficiency of Financial Supervision

The book Research on the Formation and Prevention of Systemic Risks in the Banking Industry from the Perspective of Platform Finance combines the complex network characteristics of the real banking industry and brings the two relatively independent financial markets of platform finance and banking industry into the same complex network framework. The analysis breaks through the traditional systemic risk research paradigm, fills the shortcomings of traditional economic methods in analyzing the internal structure of the system, provides a new way to study the topological structure characteristics of bank networks, and broadens the perspective of systemic risk research.

Investigation of the Internal Flow Characteristics of a Tiltrotor Aircraft Engine Inlet in a Gust Environment

In the vertical take-off and landing (VTOL) state of tiltrotor aircraft, the inlet entrance encounters the incoming airflow at a 90° attack angle, resulting in highly complex internal flow characteristics that are extremely susceptible to gusts. Meanwhile, the flow quality at the inlet exit directly affects the performance of the aircraft’s engine. This work made use of an unsteady numerical simulation method based on sliding meshes to investigate the internal flow characteristics of the inlet during the hover state of a typical tiltrotor aircraft and the effects of head-on gusts on the inlet’s aerodynamic characteristics. The results show that during the hover state, the tiltrotor aircraft inlet features three pairs of transverse vortices and one streamwise vortex at the aerodynamic interface plane (AIP). The transverse vortices generated due to the rotational motion of the air have the largest scale and exert the strongest influence on the inlet’s performance, which is characterized by pronounced unsteady features. Additionally, strong unsteady characteristics are present within the inlet. Head-on gusts mainly affect the mechanical energy and non-uniformity of the air sucked into the inlet by influencing the direction of the rotor’s induced slipstream, thereby impacting the performance of the inlet. The larger head-on gusts have beneficial effects on the performance of the inlet. When the gust velocity reaches 12 m/s, there is a 1.01% increase in the total pressure recovery (σ) of the inlet, a 25.72% decrease in the circumferential distortion index (DC60), and a reduction of 62.84% in the area where the swirl angle |α| exceeds 15°. Conversely, when the gust velocity of head-on gusts reaches 12 m/s in the opposite direction, the inlet’s total pressure recovery decreases by 1.13%, the circumferential distortion index increases by 14.57%, and the area where the swirl angle exceeds 15° increases by 69.59%, adversely affecting the performance of the inlet. Additionally, the presence of gusts alters the unsteady characteristics within the inlet.