Stability Requirements Research Articles

Enhancing Mechanical Properties of Expansive Soil Through BOF Slag Stabilization: A Sustainable Alternative to Conventional Methods

This study investigates the stabilization of expansive soil using basic oxygen furnace (BOF) slag, an eco-friendly steel by-product, as an alternative to conventional stabilizers like ordinary Portland cement. By evaluating varying concentrations of BOF slag and lime as an activator, the research aims to improve the soil’s mechanical properties, addressing issues like low bearing capacity and high shrink–swell potential. Bentonite clay was treated with different BOF slag ratios (10%, 20%, and 30%) and activated with lime (1%, 3%, and 5%). After mixing and compaction, samples were cured and tested for unconfined compressive strength (UCS), shear wave velocity (BE), and free swell. Microscopic analyses (SEM) provided insight into structural changes post-stabilization, revealing improved properties with increased BOF and lime concentrations. Notably, stabilization with 30% BOF slag and 5% lime achieves a compressive strength of 810 kPa, meeting the minimum subgrade soil stabilization requirement (700 kPa) set by the Federal Highway Administration. This research underscores the potential of BOF slag as a sustainable and practical material for bentonite clay stabilization, offering a promising solution for enhancing soil properties while contributing to environmental sustainability through industrial by-product repurposing.

Perceived Risk Assessment Criteria for Public–Private Partnership Projects in the Water and Sewage Sector: Comparison of Perspectives from Iranian Public and Private Sectors

This research used the SWARA approach to analyze risk assessment criteria for public–private partnership (PPP) projects in Iran’s water and sewage sectors to identify and prioritize the most significant elements influencing project success from public and private viewpoints. Key results show that the public sector considers “risk probability” to be the most important aspect, highlighting the requirement for stability and predictability in project outcomes. In contrast, the private sector prioritizes the “ability to predict and discover risk”, emphasizing efficiently anticipating and managing uncertainty. Furthermore, this study revealed five common major risk characteristics, including “risk manageability” and “uncertainty of risk”; however, their rankings differ per industry, demonstrating various risk prioritizing methodologies. This study is unique in that it focuses only on Iran’s water and sewage infrastructure, an area historically neglected in PPP research, providing a rare investigation of sector-specific hazards as well as the interaction between public and private interests in a developing country environment. The paper makes specific suggestions, calling for more openness, improved communication, and the use of sophisticated risk management techniques to bridge the gap across sectors. These findings not only add to the scholarly knowledge of PPP dynamics in emerging countries but also provide practical recommendations for governments and private investors navigating Iran’s infrastructure issues.

Generalization Limits of Data-Driven Turbulence Models

AbstractMany industrial applications require turbulent closure models that yield accurate predictions across a wide spectrum of flow regimes. In this study, we investigate how data-driven augmentations of popular eddy viscosity models affect their generalization properties. We perform a systematic generalization study with a particular closure model that was trained for a single flow regime. We systematically increase the complexity of the test cases up to an industrial application governed by a multitude of flow patterns and thereby demonstrate that tailoring a model to a specific flow phenomenon decreases its generalization capability. In fact, the accuracy gain in regions that the model was explicitly calibrated for is smaller than the loss elsewhere. We furthermore show that extrapolation or, generally, a lack of training samples with a similar feature vector is not the main reason for generalization errors. There is actually only a weak correlation. Accordingly, generalization errors are probably due to a data-mismatch, i.e., a systematic difference in the mappings from the model inputs to the required responses. More diverse training sets unlikely provide a remedy due to the strict stability requirements emerging from the ill-conditioned RANS equations. The universality of data-driven eddy viscosity models with variable coefficients is, therefore, inherently limited.

Stability analysis of moored floating offshore seamarks

In maritime channels, seamark is a critical navigation device that provides an aid to identify approximate positions of the sea area. Appropriate mooring strategies during the design and deployment of seamarks are crucial for enhancing their functionality and ensuring safer navigational guidance. Previous research has attempted simulations of buoys with moorings, but without specifically focusing on their stability requirements. This paper investigates the stability of a seamark affected by the waves. Numerical simulations of a seamark with moorings under regular and unsteady wave impacts are conducted to analyze the stability of the seamark. The results showed inclining behaviors of the seamark under the impact of waves. The mooring line ensures the stability of the seamark, allowing periodic motion but not moving away, and this behavior remains consistent regardless of variations in wave height.

A universal calibration framework for mixed-reality assisted surgery

Background:Mixed-reality-assisted surgery has become increasingly prominent, offering real-time 3D visualization of target anatomy such as tumors. These systems facilitate translating preoperative 3D surgical plans to the patient’s body intraoperatively and allow for interactive modifications based on the patient’s real-time conditions. However, achieving sub-millimetre accuracy in mixed-reality (MR) visualization and interaction is crucial to mitigate device-related risks and enhance surgical precision. Objective:Given the critical role of camera calibration in hologram-to-patient anatomy registration, this study aims to develop a new device-agnostic and robust calibration method capable of achieving sub-millimetre accuracy, addressing the prevalent uncertainties associated with MR camera-to-world calibration. Methods:We utilized the precision of surgical navigation systems (NAV) to address the hand-eye calibration problem, thereby localizing the MR camera within a navigated surgical scene. The proposed calibration method was integrated into a representative surgery system and subjected to rigorous testing across various 2D and 3D camera trajectories that simulate surgeon head movements. Results:The calibration method demonstrated positional errors as low as 0.2 mm in spatial trajectories, with a standard error also at 0.2 mm, underscoring its robustness against camera motion. This accuracy complies with the accuracy and stability requirements essential for surgical applications. Conclusion:The proposed fiducial-based hand-eye calibration method effectively incorporates the accuracy and reliability of surgical navigation systems into MR camera systems used in intraoperative applications. This integration facilitates high precision in surgical navigation, proving critical for enhancing surgical outcomes in mixed-reality-assisted procedures.

The Structural, Elastic, and thermodynamic properties of Sr2P7Br Double Zintl salt with heptaphosphanortricyclane configuration

We investigated the effects of externally applied pressure on the Sr2P7Br compound’s properties, specifically its crystalline structure, elasticity, and thermodynamics. This investigation was carried out using the pseudopotential plane wave method within the framework of density functional theory. We used the well-known PBEsol variant of the exchange–correlation general gradient approximation specifically designed for solid-state analysis. This is the first endeavor to investigate the effects of pressure on the Sr2P7Br material using a theoretical approach. The computed equilibrium structural parameters closely match the relevant experimental counterpart values. The determined elastic constants, obtained under both ambient pressure and hydrostatic pressures up to 18 GPa, satisfy the mechanical stability requirements. Based on the computed Pugh’s ratio, Cauchy pressure, and Poisson’s ratio, it can be concluded that the Sr2P7Br compound exhibits ductile behavior. The polycrystalline elastic moduli, including the isotropic bulk modulus, shear modulus, Young’s modulus, and Poisson’s ratio, at ambient pressure and under pressure effects, were derived from the single-crystal elastic constants. Additionally, associated parameters, such as average sound velocity, Debye temperature, minimum thermal conductivity, and Vickers hardness, were examined under pressure influences. The quasi-harmonic Debye approximation was used to investigate the relationship between temperature and some macroscopic physical parameters, such as lattice parameter, bulk modulus, Debye temperature, volume thermal expansion coefficient, and isobaric and isochoric heat capacities, at fixed pressures of 0, 4, 8, 12, and 16 GPa. The results derived from the elastic constants exhibit substantial concordance with those computed using the Debye quasi-harmonic model, thereby validating the reliability of our findings.

Comparison of different longitudinal injection scenarios for achieving optimal performance in SAPS

The Southern Advanced Photon Source (SAPS) is a proposed fourth-generation diffraction-limited storage ring (DLSR) designed with a modified hybrid multibend achromat lattice, achieving a natural emittance as low as 33 pm. Given its limited dynamic aperture, the SAPS is not well suited to off-axis injection, with on-axis injection schemes proving a more favourable option. This paper highlights the advantages of longitudinal injection for SAPS, which employs a fast pulse kicker and multi-frequency RF systems. A systematic comparison is presented of the longitudinal injection schemes for double-frequency and triple-frequency RF systems. The effects of these schemes on circulating beam stretching, the time structure of the fast pulse kicker, RF parameter stability requirements, storage ring acceptance, and injection efficiency are considered. Based on these results, reasonable hardware specifications for the fast stripline kicker and RF system, as well as injector parameter requirements, are provided. These findings are crucial for SAPS to achieve longitudinal injection and can also serve as a reference for similar light sources.

Branched CuAu nano-alloy for N2H4 oxidation-assisted H2 production and nitrite detection in water solution.

The H2 production using N2H4 splitting (OHzS) was often constrained by the requirement for insufficient stability, distinct catalysts at the anode and cathode, and the high-cost electrocatalyst associated with confined activity. This work verified the efficacy of surfactant-free branched CuAu nano-alloy as a bifunctional electrocatalyst for H2 production. Benefiting from its favorable electronic structure and surfactant-free surface, surfactant-free CuAu nano-alloy demonstrated a reduced over-potential compared withpure Cu, pure Au, and CuAu nano-alloy prepared by surfactant. When using branched CuAu nano-alloy as both cathodic and anodic electrodes, a cell voltage of 0.768V was required to drive a current density of 10mA/cm2. After 2550min of H2 generation, the amplitude of the working potential for anodic reactions was found to be less than 0.92%. The enhanced electrocatalytic activity could be also applied to H2O2 and NaNO2 sensors. The CuAu nano-alloy exhibited a 2.35-folds increase in sensitivity compared to pure Au nano-crystals in the detection of H2O2. Moreover, the detection of NaNO2 in water solution has been successfully achieved. The detection range 0-175.0mM was much wider than that ofsensors in previous works.

Integral predictive sliding mode control for high-speed trains: A dynamic linearization and input constraint-based data-driven scheme

A control scheme with high reliability and excellent tracking performance is essential for the automatic operation of high-speed trains (HSTs). In this study, a novel discrete-time data-driven predictive sliding mode control (DDPSMC) scheme is proposed for multi-power unit HSTs. Initially, a nonlinear integral terminal sliding mode surface was designed to replace the traditional linear sliding mode function, thereby achieving a rapid system error convergence and alleviating chattering. Then, receding horizon optimization was integrated into predictive control, which allowed the predicted sliding mode state to follow the expected trajectory of a predefined continuous convergence law. This scheme enabled the system to obtain higher output error accuracy and explicitly handle input constraints. Moreover, to enhance robustness, a parameter update law and disturbance delay estimation algorithm were introduced to calculate the control gain and total uncertainty, respectively. Finally, a comparative test of the proposed control scheme was conducted using a CRH380A HST simulation experimental platform in a laboratory setting. Simulation results demonstrate that the velocity error range of each power unit of the HST under the proposed control scheme is within [−0.176 km/h, 0.152 km/h], while the control force and acceleration are within [−55.7 kN, 44.8 kN] and [−0.564 m/s2, 0.496 m/s2], respectively, with stable variation, and other performance indicators are also better than other comparison methods. These results satisfy the safety, stability, and punctuality requirements of the train.

Initial results from neoclassical tearing mode stabilization experiment in KSTAR high normalized beta plasmas

Abstract Active stabilization of neoclassical tearing modes (NTMs) is critical for high beta plasma operation in the KSTAR tokamak. In recent device operation, an experiment was conducted to develop a m/n = 2/1 NTM stabilization in high normalized beta (βN) plasmas having βN > 3 by using electron cyclotron current drive (ECCD). The experiment is designed to first demonstrate the direct mode stabilization effect of the device EC system by varying the ECCD deposition location around the mode rational surface to prepare for future NTM stabilization in KSTAR using feedback schemes. In the experiment, the toroidal magnetic field strength, BT, is reduced to 1.5–1.6 T to create a highly localized ECCD profile on a large island width expected to produce a high stabilization effect. To align the ECCD with the mode, BT is varied between discharges by keeping the EC wave injection angles fixed to move the current deposition location across the q = 2 mode rational surface in ~1 cm steps along the plasma midplane. The result shows a prompt reduction of the mode amplitude by ~60% with a partial recovery of the loss of stored energy when the ECCD with 0.7 MW power is applied promptly after the mode onset at BT = 1.54 T. This abrupt reduction of the mode amplitude is significantly weaker or disappears in other discharges having slightly different BT in which the ECCD is deposited a few centimeters away. This result indicates a direct interaction between the driven EC current and the radially localized island structure first observed in the device. The EC ray-tracing analysis using the TORAY code shows that the applied EC-driven current aligns with the mode rational surface when the mode amplitude is observed to decrease. The stability of the observed 2/1 NTM is examined by constructing the modified Rutherford equation (MRE). The calculated EC power requirement for complete mode stabilization by assuming perfect alignment of ECCD on the mode is 0.8-1.7 MW by considering the uncertainties in the equation. This MRE-computed mode stability agrees with the experiment. The result projects that the present KSTAR EC system can stabilize the 2/1 NTM disrupting high βN plasmas, and provides the requirement of the mode-ECCD alignment for complete mode stabilization in future experiments in which an accurate alignment is planned to be made by feedback schemes being developed.

Accelerating Discovery of Mechanically Stable Metal-Organic Frameworks for Vinylidene Fluoride Storage by Active Learning.

Metal-organic frameworks (MOFs) are versatile nanoporous materials for a wide variety of important applications. Recently, a handful of MOFs have been explored for the storage of toxic fluorinated gases (Keasler et al. Science, 2023, 381, 1455), yet the potential of a great number of MOFs for such an environmentally sustainable application has not been thoroughly investigated. In this work, we apply active learning (AL) to accelerate the discovery of hypothetical MOFs (hMOFs) that can efficiently store a specific fluorinated gas, namely, vinylidene fluoride (VDF). First, a force field was developed for VDF and utilized to predict the working capacities (ΔN) of VDF in an initial data set of 4502 MOFs from the computation-ready experimental MOF (CoRE-MOF) database that successfully underwent featurization and grand-canonical Monte Carlo simulations. Next, the initial data set was diversified by Greedy sampling in an unexplored sample space of 119,387 hMOFs from the ab initio REPEAT charge MOF (ARC-MOF) database. A budget of 10,000 samples (i.e., <10% of total ARC-MOFs) was selected to train a random forest model. Then, ΔN in the unlabeled ARC-MOFs were predicted and top-performing ones were validated by simulations. Integrating with the stability requirement, mechanically stable ARC-MOFs were finally identified, along with high ΔN. Furthermore, by Pareto-Frontier analysis, we revealed that long linear linkers can enhance ΔN, while bulkier multiphenyl linkers or interpenetrated frameworks improve mechanical strength. From this work, we efficiently discover top-performing MOFs for VDF storage by AL and also demonstrate the importance of integrating stability to identify stable promising MOFs for a practical application.

Artificial intelligence literacy among university students—a comparative transnational survey

Artificial intelligence (AI) literacy is a crucial aspect of media and information literacy (MIL), regarded not only as a human right but also as a fundamental requirement for societal advancement and stability. This study aimed to provide a comprehensive, cross-border perspective on AI literacy levels by surveying 1,800 university students from four Asian and African nations. The findings revealed significant disparities in AI literacy levels based on nationality, scientific specialization, and academic degrees, while age and gender did not show notable impacts. Malaysian participants scored significantly higher on the AI literacy scale than individuals from other countries. The results indicated that various demographic and academic factors influenced respondents’ perceptions of AI and their inclination to utilize it. Nationality and academic degree were identified as the most influential factors, followed by scientific specialization, with age and gender exerting a lesser influence. The study highlights the necessity of focusing research efforts on the detailed dimensions of the AI literacy scale and examining the effects of previously untested intervening variables. Additionally, it advocates for assessing AI literacy levels across different societal segments and developing the appropriate measurements.

An Observational Study on Clinical Benefits of CytoSorb in Patients with Severe Sepsis

Background and Aim: Sepsis is a well-recognized healthcare issue worldwide. Despite research, the ability to positively influence outcome remains limited. Newer evidences have pointed that using adsorption of cytokines is beneficial during endotoxemia and sepsis. Therefore, this study was aimed to determine the clinical benefits of CytoSorb usage in patients with severe sepsis admitted in intensive care units (ICU). Study Design: Prospective, observational, comparative study. Material and Methods: Forty patients with sepsis admitted to ICU were included. The CytoSorb group included 20 patients who received CytoSorb therapy in addition to Standard-care (SOC) and 20 patients in SOC group who received SOC alone as per routine ICU protocols. Clinical and laboratory parameters were analyzed pre/post-treatment in both groups and compared. Results: CytoSorb and SOC groups were comparable at baseline. There was significant reduction in serum creatinine (2.59±2.0 vs. 2.89±1.2, mg/dl; P=0.042), serum lactate (3.26±1.1 vs. 3.27±0.9, mmol/lit; P&lt;0.001), serum procalcitonin (2.75±2.4 vs. 3.39±3.5, ng/ml; P&lt;0.001), serum CRP (90.2±57.4 vs. 175.6±100.9, mg/dl; P&lt;0.001) and serum IL6 (1769.7±4444.1 vs. 256.8±392.4, pg/ml; P=0.03) levels in CytoSorb compared to SOC. There was significant improvement in mean arterial pressure (MAP) (65.75±1.8 vs. 62.75±2.8, mmHg; P&lt;0.001) and reduction in norepinephrine dose (6.47±2.7 vs.10.65±3.6, mcg/min; P&lt;0.001) in CytoSorb group reflecting better hemodynamic stability. The post-treatment increase in SOFA score was lesser in CytoSorb group (11.85±2.9) than SOC group (12.3±2.3), but was not significant (P=0.135). Conclusion: CytoSorb therapy along with SOC was associated with significant improvements in hemodynamic stability, MAP and Norepinephrine requirements than SOC alone in severe sepsis.

Three-stage resilience enhancement via optimal dispatch and reconfiguration for a microgrid

Extreme weather causes an increase in power system failure. Previous studies on system resilience have often overlooked the user-side of a microgrid. This study proposes composite resilience indices (RI) based on the power supply of a large-scale manufacturing campus microgrid to quantify its ability to withstand extreme events. The proposed RI consider load priority, minimum supply load, total energy supplied, and the performance recovery-to-degradation slope ratio in an islanding microgrid. Accordingly, this study presents a three-stage resilience optimal dispatch and reconfiguration strategy, including energy-level scheduling, grid-level reconfiguration, and dynamic-level verification. A multi-objective optimization approach is used for energy scheduling, followed by system reconfiguration via DIgSILENT system modeling to meet the grid code and maximize load supply. Value at Risk methods are used to verify microgrid stability and load shedding requirements, supported by the virtual synchronous generator control of the energy storage system. The test results from a practical large-scale manufacturing campus microgrid validate the proposed approaches for enhancing system resilience considering load values.

Conceptual design of an autonomous single-container vessel

The growth of maritime shipping is leading to the creation of larger vessels. However, this expansion in size brings with it several challenges, including the development of maritime infrastructure, the potential for growth in third-world countries, and the emission of greenhouse gases. In response to these challenges, this research explores the feasibility of designing an autonomous ship capable of transporting a single standardized 40 ft. container overseas using mainly passive propulsion methods. Using advanced design tools, including CAD software and CFD simulations, as well as conducting a comprehensive analysis of relevant literature, the designs for a hull and sails were developed, and an overview of the potential active control systems required for autonomous operation was provided. The study also performed an initial analysis of strength, stability, and velocity to validate the design choices. The ship proves to adhere to the basic strength and stability requirements while reaching its maximum hull velocity at certain wind speeds. The results of the study indicate that it is possible to design and manufacture a mainly passively propelled ship capable of transporting a 40 ft. standardized container overseas and rethink the logistics at scale.

Comparative Analysis of the Intrinsic Disorder Within the Layers of the Human Cornea.

The human cornea is essential for vision, providing structural integrity and refractive power to the eye. Recent advancements have deepened our understanding of the corneal molecular composition, yet the role of intrinsically disordered proteins within the cornea is unexplored. We analyzed 3,250 corneal proteins identified by Dyrlund et al, focusing on the epithelium, stroma, and endothelium layers. We performed a bioinformatics analysis to characterize the amino acid composition, the propensity for intrinsic protein disorder, and the distribution of protein types in 3 corneal layer proteome. Our study demonstrates that each corneal layer exhibited unique patterns in amino acid composition related to protein disorder. Order-promoting amino acids were generally depleted except for leucine, whereas disorder-promoting amino acids like arginine and glutamic acid were enriched across all layers. Significant variations were observed in the levels of intrinsic disorder among the different corneal layers, with substantial proportions of highly disordered proteins present in each. Analysis of protein class type in each layers revealed that no significant differences were detected in the distribution of protein classifications across the layers, suggesting a consistent population of the protein types across all corneal layers. Our findings reveal a sophisticated landscape of protein structures where intrinsic disorder varies across layers, suggesting an adaptation of the corneal proteome to the unique physiological demands of each layer. These structural variations may reflect the intricate requirements for corneal transparency, biomechanical stability, and environmental responsiveness.

Synthesis of dynamic modelling framework and optimal control strategy for virtually coupled train sets with guaranteed safety

Virtual coupling represents a novel railway operational mechanism, wherein several trains share state information and adjust their behaviours based on control objectives, which include safety (collision avoidance) assurance and stability (uniform velocity and constant spacing between trains) maintenance. However, the conflict between safety and stability requirements becomes more apparent, as the closer spacing between trains. Moreover, the hybrid nature of the train platoon operation, which involves both discrete events and continuous dynamics, also poses a significant barrier to the control strategy synthesis. This paper presents the Virtually Coupled Train Sets (VCTS) dynamic modelling framework and strategy synthesis approach to address these problems. A Hybrid Markov Decision Process (HMDP) is adopted for relative longitudinal dynamics modelling of trains, considering the influence of the uncertainty dynamic of trains ahead. A Stackelberg game-based strategy synthesis algorithm is applied for the safe guarantee by overcoming the uncertainty, and a Q-learning method is used for stability strategy selection from the safe strategy. The results showed a 17.95% expansion in the safe state space when compared to the general relative braking scheme (which assumes maximal acceleration during the delay horizon). In a four-train tracking operation scenario, compared with Q-learning without safe constraints, our approach gives similar stability performance; compared with Q-learning with general relative braking safe constraints, our approach not only assurance safety but has a better stability performance.

Hydrodynamic performance characteristics of small-scale in-situ buoys with critical motion requirements

As the accuracy of high-precision oceanographic measurement instruments increases, the operational requirements for buoy motion become critical. This study focuses on the small-scale in-situ buoy, optimizing buoy configuration to ensure stability and performance. Aiming at the special structure which consists of a large floating column and several small tube connectors, a method for evaluating the hydrodynamic performance is proposed which combines potential flow theory with Morison equation. And the method validity is confirmed using experimental data. The performances analysis of different type buoy with catenary or taut mooring system are developed. According to the critical motion requirements for the long-term stability, the cylindrical type buoy equipped with a catenary mooring system is regarded as the most stable and economical choice, exhibiting a surge motion response of 4.07 m, a heave motion response of 2.89 m, and a pitch motion response of 9.37°. Furthermore, the anchor chain acts as an elastic damper which can mitigate the transient impact of the environmental loads, greatly limiting the amplitude of the longitudinal and heaving motions. And the maximum mooring line tension is 249.28 kN, which is significantly lower than other schemes. The evaluation method offers a technical support for engineering applications.

New stability theory of model predictive control: modified stage cost approach

This paper presents a promising new approach to establish the stability of finite receding horizon control with a terminal cost. Departing from the traditional approaches of using the property of the terminal cost or relaxed Lyapunov inequalities, this paper establishes its stability based on the property of a modified stage cost. First, we rotate the stage cost with the terminal cost. Then a one-step optimisation problem is defined based on this augmented stage cost. It is shown that a slightly modified Model Predictive Control (MPC) algorithm is stable if the value function of the augmented one-step cost (OSVF) is a Control Lyapunov Function (CLF). Stability for MPC algorithms with zero terminal cost or even negative terminal cost can be unified with this new approach. Combining it with the existing MPC stability theories, we are able to significantly relax the stability requirement on MPC and extend the stabilising MPC design space to the region that no existing MPC stability theories can cover. The proposed stage cost-based approach will help to further reduce the gap between stability theory and practical applications of MPC and other optimisation-based control methods.

Stability Analysis of Surface Wellhead Retention in Offshore Exploration Wells

Abstract When offshore exploration wells are carried out, a narrow operating window and prolonged construction period may be encountered, which may lead to the evacuation of the drilling platform. The conductor will be left freestanding in the sea water, posing a great risk to wellhead stability. In this paper, based on finite element simulation of offshore exploratory well freestanding conductors, the stability analysis method is built and evaluation of a well is carried out. It is concluded that in 1 year return period and sea conditions by hanging load return period of 10 years of sea condition, the stability all meet the conditions, but there in 10 years return period of sea state by hanging load and 50 years return period of sea condition did not meet the requirements of stability. In cases where stability requirements are not met, alternative means of retaining the wellhead are recommended. This study has certain guiding significance for the safe and efficient operation of offshore exploration wells.