Model For Instability Research Articles

Prediction of fishbone linear instability in tokamaks with machine learning methods

Abstract A machine learning based surrogate model for fishbone linear instability in tokamaks is constructed. Hybrid simulations with the kinetic-magnetohydrodynamic (MHD) code M3D-K is used to generate the database of fishbone linear instability, through scanning the four key parameters which are thought to determine the fishbone physics. The four key parameters include (1) central total beta of both thermal plasma and fast ions, (2) the fast ion pressure fraction, (3) central value of safety factor q and (4) the radius of q = 1 surface. Four machine learning methods including linear regression, support vector machines (SVM) with linear kernel, SVM with nonlinear kernel and multi-layer perceptron are used to predict the fishbone instability, growth rate and real frequency, mode structure respectively. Among the four methods, SVM with nonlinear kernel performs very well to predict the linear instability with accuracy ≈ 95 % , growth rate and real frequency with R 2 ≈ 98 % , mode structure with R 2 ≈ 98 % .

Large Eddy Simulation of large-scale hydrogen deflagrations using the Thickened Flame Model with stretch sensitivity adaptation and thermo-diffusive instability modeling

Due to the high costs associated to experimental testing of hydrogen (H2) explosions, numerical simulations play an essential role in the design of safe industrial systems. In this work, we investigate the use of the Thickened Flame Model (TFM) to perform simulations of H2 deflagrations. Specific issues arise when considering hydrogen: (i) due to differential diffusion, the flame is very sensitive to stretch; (ii) instabilities of the flame front are generated and lead to an increased flame propagation speed. Both of these phenomena are affected by flame thickening. First, the flame sensitivity to stretch is artificially increased by the thickening. The recently developed Ma-TFM model proposes a correction of diffusive fluxes to reach the correct Markstein length and is selected in this work. Secondly, thermo-diffusive and hydrodynamic flame instabilities are also altered by thickening. By computing the dispersion relationship for a hydrogen/air mixture, we show that the instability scales are proportional to the thickening factor F. A simple subgrid scale (SGS) model, based on the computations of laminar unstable 2-D and 3-D flames, is then considered to take into account the effect of instabilities. The Ma-TFM and SGS instability models are applied together for the first time on a semi-industrial vented lean hydrogen deflagration, leading to promising results. In particular, it is found that considering 3-D unstable flames is necessary to accurately predict the experimental pressure peaks.

Model for Local Cavitation Instabilities in 2-Bladed Turbopump Inducers

Abstract Various local cavitation instabilities in turbopump inducers (e.g., alternate blade cavitation, super-synchronous rotating cavitation, etc.) have previously been experimentally identified. However, a model, which is capable of predicting such local instabilities is still lacking. Therefore, a new model, which models an N-bladed inducer as a system of N coupled mass- spring-damper systems, is presented to predict post-onset behavior of alternate blade cavitation instabilities. The model predicts alternate blade cavitation to occur. As the flow coefficient is decreased, the model predicts the magnitude of alternate blade cavitation to first increase and then decrease, and then finally vanish. If the flow coefficient is further decreased beyond the range of alternate blade cavitation, sudden increase in equilibrium incidence is predicted. All of these predictions agree with the previous experimental findings. Furthermore, simultaneous in-phase oscillations of the blade cavities are predicted during alternate blade cavitation. These in-phase oscillations of the cavities correspond to the surge mode oscillation, which had been previously mistakenly categorized as a global (system) instability. Finally, it is proposed that the above post-onset behaviors of alternate blade cavitations are general in two-bladed inducers, as long as the change in incidence on the following blade has a local minimum when it is expressed as a function of leading blade's incidence.

A semi-analytical prediction model for fluid elastic instability in the streamwise direction of a normal triangular tube array

Fluid elastic instability (FEI) is widely regarded as the most destructive mechanism of flow-induced vibration. Numerous failures of heat exchanger tubes have been attributed to this phenomenon. This paper focuses on a normal triangular tube array and develops a semi-analytical time-domain solving model to address FEI in the streamwise direction. Utilizing computational fluid dynamics simulations and image processing techniques, a comprehensive set of tube-in-channel model parameters is derived, including the area perturbation amplitude, phase difference, mean area along the flow channel, and steady-state term of flow velocity. Tube motion in the streamwise direction generates a disturbance distinct from that caused by transverse flow, leading to revisions in the expressions of relevant model parameters. Furthermore, variations in these parameters across different positions and velocities are quantitatively analyzed through function fitting, yielding specific mathematical formulas. Ultimately, the derived tube-in-channel model parameters applicable to streamwise FEI are validated against experimental data, affirming the model's accuracy.

Numerical modeling and suppression of combustion instabilities in a partially premixed combustor

To suppress the combustion instabilities faced in the lean premixed combustion, the impacts of swirler hub configurations on combustion instabilities under elevated pressure are investigated using large eddy simulation combined with a flamelet generation manifold model. Good agreement between the numerical predictions and experimental data is achieved. The flow fields of the combustors with three distinct swirler configurations are simulated: prototype, swirler with lobes on the hub of pilot stage, and with lobes on the hub of the first main stage. Furthermore, dynamic mode decomposition (DMD) is used to extract the dynamic characteristics, and a flame transfer function (FTF) is employed to characterize the fluctuation characteristics. The results show that the prototype combustor demonstrates a coupled fluctuation between flow and heat release. Influenced by the precessing vortex core (PVC), the flame angle varies between 70° and 90° and the first DMD modes of axial velocity, temperature, and heat release rate are all at a frequency of 470 Hz. The lobes on the hub of the pilot stage suppress the formation of PVC, making the combustion very stable. The flame angle remains constant at 80°, and the gain of FTF is lower than 1. However, adding lobes to the first main stage makes the combustion extremely unstable. The flow field structure undergoes drastic changes, mimicking a “breathe” process. The flame surface is highly distorted, and flashback phenomena occur.

Numerical Modeling of Hydrological Mechanisms and Instability for Multi-Layered Slopes

The process of rainwater infiltration into unsaturated multi-layered slopes is complex, making it extremely difficult to accurately predict slope behaviors. The hydrological mechanisms in multi-layered slopes could be significantly influenced by the varying hydraulic characteristics of different soils, thus influencing slope stability. A numerical model based on Hydrus 2D was constructed to investigate the hydrological mechanisms of multi-layered slopes under different slope inclinations and rainfall intensities. The results revealed hydraulic processes in response to rainfall in unsaturated multi-layered slopes, in which layered soils retard the advance of wetting fronts and affect seepage paths in the slope. The results also showed the characteristics of hydraulic parameters, including pore water pressure and moisture content, under different conditions, and explained the crucial factors at play in maintaining slope stability.

Large-deformation finite-element modelling of face instability during tunnelling in clayey soils: Incorporating dynamic excavation process

Earth pressure balance (EPB) shield tunnelling plays a crucial role in urban infrastructure development but faces challenges due to potential face instability. Previous studies often overlook the impact of dynamic excavation processes on face stability, particularly in clayey soils. This study proposes a three-dimensional coupled Eulerian-Lagrangian (CEL) large-deformation approach to explore the failure process of tunnel face in clayey soils during both EPB shutdown and excavation conditions by incorporating the influence of dynamic excavation process. The findings reveal that the face stability during dynamic excavation conditions is consistently lower than that during EPB shutdown, indicating that neglecting dynamic excavation effects could overestimate face stability, potentially compromising construction safety. Moreover, when considering the dynamic excavation process, the opening ratio ξ (the ratio between the cross-section area of cutterhead opening to the total area of tunnel face) is a critical factor affecting face stability. As expected, the face is more stable for a small opening ratio (e.g., ξ = 15 %) while face stability is reduced for a large opening ratio (e.g., ξ = 30 % and 50 %). This is because for large opening ratio, the soil disturbance caused by the cutterhead excavation process exceeds the supportive effect that the cutterhead panels can provide to the face. Finally, the obtained numerical results were used to calculate support pressure in a real tunnel project considering the dynamic excavation process, which matches well with the measured data in the project, validating the effectiveness and superiority of the current CEL approach in modelling face instability and estimating face support pressure. This study offers a significant advancement over the traditional methods for the design of support pressure in clayey soils, providing new insight into the dynamic cutterhead-soil interaction and valuable guidance for reducing the risk of face collapse.

Large-Deformation Modeling of Surface Instability and Ground Collapse during Tunnel Excavation by Material Point Method

Recent rapid urbanization has led to an increase in tunnel construction, escalating the prevalence of ground collapses. Ground collapses, characterized by large deformation and strain-softening, pose a significant challenge for classical numerical theories and simulation methods. Consequently, a numerical framework combining the material point method (MPM) and strain-softening Drucker–Prager plasticity is introduced in this study to more accurately describe the evolution process and failure mechanism of the subgrade during tunnel excavation. The proposed numerical framework was validated against an analytic solution employing a typical ‘dry bottom’ dam model with solid non-linearity and large deformation; some of the results are also compared with those of the SPH method and centrifugal modeling tests to verify the validity of the MPM method in this paper. The validated model was used in this study to conduct a comprehensive analysis of surface instability and ground collapse under varying soil conditions. This included factors such as strata thickness, cohesion, internal friction angle, and a quantitative description of the development of longitudinal subsidence of the surface. The aim was to clarify deformation responses, failure patterns, and excavation mechanisms, providing insights for underground tunneling practices.

Complete quasilinear model for the acceleration-driven lower hybrid drift instability and a computational assessment of its validity.

A complete quasilinear model is derived for the electrostatic acceleration-driven lower hybrid drift instability in a uniform two-species low-beta plasma in which current is perpendicular to the background magnetic field. The model consists of coupled nonlinear velocity space diffusion equationsfor the volume-averaged ion and electron distribution functions. Each species' diffusion coefficient depends on a time-evolving spectral density of the electric-field energy per unit volume and a time-evolving dispersion relation. The dispersion relation is expressed analytically in integral form without the use of asymptotic limits and applies to arbitrary distribution functions, so long as they can be expressed as a function of one velocity coordinate, e.g., f(v_{y}) or f(v_{⊥}). The quasilinear model conserves energy and is complete in that it fully describes the evolution of the distribution functions, including resonant and nonresonant particle-wave interactions, while accounting for distribution-function-dependent mixed-complex frequencies. The quasilinear diffusion model is solved numerically and self-consistently using a Crank-Nicolson temporal discretization and a second-order finite-volume velocity-space discretization. Numerical solutions are compared to nonlinear fourth-order accurate continuum kinetic Vlasov-Poisson simulations. Evolution of electric-field energy, growth rates, distribution functions, and diffusion coefficients are shown to be in agreement with Vlasov simulations. The quasilinear model is shown to predict anomalous transport terms, like resistivity and heating, to within a factor of order unity. Discrepancies between the quasilinear model and Vlasov simulations are assessed and attributed primarily to lack of damping in the quasilinear description and to the use of unperturbed-orbit susceptibilities in the linear theory dispersion relation. The results illuminate the predictive accuracy of the quasilinear model, place approximate bounds on its validity, and provide much needed vetting of quasilinear theory's ability to predict the nonlinear state of a microturbulent plasma.

A Decision Tree Model to Help Treatment Decision-Making for Unruptured Intracranial Aneurysms: A Multi-center, Long-Term Follow-up Study in a Large Chinese Cohort.

Chinese population have a high prevalence of unruptured intracranial aneurysm (UIA). Clinical and imaging risk factors predicting UIA growth or rupture are poorly understood in the Chinese population due to the lack of large-scale longitudinal studies, and the treatment decision for UIA patients was challenging. Develop a decision tree (DT) model for UIA instability, and validate its performance in multi-center studies. Single-UIA patients from two prospective, longitudinal multicenter cohort studies were analyzed, and set as the development cohort and validation cohort. The primary endpoint was UIA instability (rupture, growth, or morphological change). A DT was established within the development cohort and validated within the validation cohort. The performance of clinicians in identifying unstable UIAs before and after the help of the DT was compared using the area under curve (AUC). The development cohort included 1270 patients with 1270 UIAs and a follow-up duration of 47.2 ± 15.5months. Aneurysm instability occurred in 187 (14.7%) patients. Multivariate Cox analysis revealed hypertension (hazard ratio [HR], 1.54; 95%CI, 1.14-2.09), aspect ratio (HR, 1.22; 95%CI, 1.17-1.28), size ratio (HR, 1.31; 95%CI, 1.23-1.41), bifurcation configuration (HR, 2.05; 95%CI, 1.52-2.78) and irregular shape (HR, 4.30; 95%CI, 3.19-5.80) as factors of instability. In the validation cohort (n = 106, 12 was unstable), the DT model incorporating these factors was highly predictive of UIA instability (AUC, 0.88 [95%CI, 0.79-0.97]), and superior to existing UIA risk scales such as PHASES and ELAPSS (AUC, 0.77 [95%CI, 0.67-0.86] and 0.76 [95%CI, 0.66-0.86], P < 0.001). Within all 1376 single-UIA patients, the use of the DT significantly improved the accuracy of junior neurosurgical clinicians to identify unstable UIAs (AUC from 0.63 to 0.82, P < 0.001). The DT incorporating hypertension, aspect ratio, size ratio, bifurcation configuration and irregular shape was able to predict UIA instability better than existing clinical scales in Chinese cohorts. CLINICAL TRIAL REGISTRATION: IARP-CP cohort were included (unique identifier: ChiCTR1900024547. Published July 15, 2019. Completed December 30, 2020), with 100-Project phase-I cohort (unique identifier: NCT04872842, Published May 5, 2021. Completed November 8, 2022) as the development cohort. The 100-Project phase-II cohort (unique identifier: NCT05608122. Published November 8, 2022) as the validation cohort.

Study of wellbore instability in shale formation considering the effect of hydration on strength weakening

Shale formations often contain a high proportion of clay minerals, which, upon contact with drilling fluid, undergo hydration expansion. This leads to wellbore instability, a problem that poses significant challenges globally. This study aims to investigate the variation of mechanical properties of shale with respect to hydration time. We employ an empirical model that relates shale strength parameters to the time of drilling through geological formations. Additionally, we consider both shear failure along the wellbore boundary and shear sliding along bedding planes in the analysis. We establish a predictive model for wellbore instability in shale formations. The model quantitatively analyzes the variation of wellbore collapse pressure with drilling time. The research findings indicate that, when the influence of bedding is considered, both the wellbore collapse pressure and the optimal well trajectory undergo significant changes, in addition, for some wellbore trajectories, the collapse pressure can increase by more than 30%. Therefore, it is essential to account for the influence of bedding in wellbore stability analysis in shale formations. As the bedding dip angle changes, both the numerical values and distribution range of wellbore collapse pressure and the optimal well trajectory change noticeably. Changes in bedding dip direction, however, do not affect the numerical values of collapse pressure but do influence the distribution region of the optimal well trajectory. Thus, in wellbore trajectory design within shale formations, it is crucial to determine the orientation of bedding and adjust the well trajectory accordingly to enhance wellbore stability. Furthermore, shale hydration does not impact the optimal well trajectory for a block, but with prolonged hydration, the minimum drilling fluid density required to maintain wellbore stability gradually increases. This suggests that hydration intensifies the weakening effect on bedding plane strength. The research results are helpful to understand the effect of hydration on shale wellbore stability and ensure shale wellbore stability during drilling cycle.

Investigation of Thermo-Electrical Instabilities in a Semiconductor as 2D Dynamical Systems

A semiconducting sample placed in cryogenic media with applied electric field generates low frequency oscillations of electric current and sample temperature and known to be thermo-electrical instabilities. Although observation of current oscillations on oscilloscope is possible, change of sample temperature cannot be detected experimentally. Description of the phenomenon through mathematical equations helps to understand relationship of the two variables as well as their connection to deep trap behavior that are involved in supporting the instability. Mathematical model for thermo-electrical instabilities in an n type semiconductor based on the two deep trap level model with non-degenerate electron statistics has been introduced in order to investigate the unique relationship between the change in time of both electric current flowing through a semiconductor sample and the sample temperature. The 3D dynamical system of nonlinear inhomogeneous ordinary differential equations has been investigated as component 2D dynamical systems (n,T), (n,n&amp;lt;sub&amp;gt;t&amp;lt;/sub&amp;gt;) and (n&amp;lt;sub&amp;gt;t&amp;lt;/sub&amp;gt;,T) for local behavior at isolated equilibrium and at points on individual trajectories, where n, n&amp;lt;sub&amp;gt;t&amp;lt;/sub&amp;gt; and T are free electron concentration at conduction band, electron concentration at deep traps and temperature of a semiconductor sample accordingly. Each of the planar systems is expressed in canonical form and investigated as a Cauchy problem with a set of appropriate initial values. This paper presents investigation results of phase trajectories of the planar systems depending on a single parameter – the temperature of cooling media T&amp;lt;sub&amp;gt;0&amp;lt;/sub&amp;gt;. Based on obtained calculation results of time sequences of the three variables n, n&amp;lt;sub&amp;gt;t&amp;lt;/sub&amp;gt; and T, phase differences among these variables have been determined for different values of T&amp;lt;sub&amp;gt;0&amp;lt;/sub&amp;gt;. It has been established that the change in sample temperature lags behind change in current and this lag increases with T&amp;lt;sub&amp;gt;0&amp;lt;/sub&amp;gt;. Clearly defined correlations among systems (n,T), (n,n&amp;lt;sub&amp;gt;t&amp;lt;/sub&amp;gt;) and (n&amp;lt;sub&amp;gt;t&amp;lt;/sub&amp;gt;,T) are seen, being the result of balance between field aided and thermal ionization mechanisms for charge carrier generation and recombination processes. Thermal and field assisted generation mechanisms compete with one another in achieving steady non equilibrium state in the system depending on temperature of cooling media T&amp;lt;sub&amp;gt;0&amp;lt;/sub&amp;gt;.

설명 가능한 인공지능을 활용한 주거불안 예측모형 개발

Korea has witnessed a significant increase in the number of vulnerable single-person households facing housing instability, particularly in the Seoul Metropolitan Area. Hence, identifying potential policy targets and implementing preventive measures before such households experience severe instability are essential. In this study, we utilized explainable artificial intelligence—specifically, ensemble-based machine learning techniques (e.g., bagging, random forests, boosting) that use multiple trees to enhance predictive performance—to develop a predictive model for housing instability. This model outperformed traditional classification models (e.g., logistic regression) in predictive accuracy and can help streamline the identification process for households at risk of housing crises. Further, it is valuable for resource-constrained public organizations.

Modeling of wetlands storage instabilities using an optimized slffn machine learning using evolutionary computation considering the RROC analysis and PDF techniques

Modeling of wetlands storage instabilities using an optimized slffn machine learning using evolutionary computation considering the RROC analysis and PDF techniques

Mathematical Model for Thermo-Electrical Instabilities in Semiconductors

Crystalline semiconductors under specific conditions, with an applied electric field, switch or oscillate between two conductive states, thus producing low frequency oscillations of electric current flowing through the sample and as a result of Joule heating oscillations of sample temperature. These phenomena are recognized to be thermo - electrical instabilities. Although current oscillations can be detected and registered experimentally, there is no device that can detect, register and allow us to study the sample temperature change in time. The purpose of this study is to learn about the relationship of electric current and sample temperature coupled with deep traps that play an important part in supporting the phenomenon. This can be done only by setting up a mathematical model that describes the phenomenon in detail. The equations that make up the model are continuity equations for free electron and deep traps carrier populations, as well as a heat conduction equation – a set of ordinary nonlinear inhomogeneous differential equations. The system is transformed into a so called “canonical form” as a result of linearization of the system at isolated equilibrium. It is achieved by expansion of the right hand sides of the equations into two variable Taylor series at isolated equilibrium involving linear non-singular transformation. The mathematical model for thermo-electrical instabilities in an n-type semiconductor with non-degenerate electron statistics has been studied as 3D dynamical system. The system of differential equations is broken down into component planar systems, each of them being tested for existence of limit cycles on a determined phase plane, followed by quantitative investigation of their local behavior at isolated equilibrium and at points on individual trajectories on phase plane dependant on single parameter T&amp;lt;sub&amp;gt;0&amp;lt;/sub&amp;gt;. Solutions of sets of initial value problems as time series of the variables: free electron concentration; sample temperature; deep trap population is presented. The investigation results show that oscillations of sample temperature follow those of current. Change in T&amp;lt;sub&amp;gt;0&amp;lt;/sub&amp;gt; forces the system to adjust to new thermodynamical state by changing frequency and amplitude of the oscillations as well as dynamics of deep trap population.

A unified model for deformation instability based on energy inflection

The critical state of plastic instability preceding the fracture of metals, such as necking under tension and shear banding under torsion, was carefully analyzed from thermodynamics considerations. A unified criterion based on energy inflection (EI criterion) was established which takes stress states and loading rates into account. Different from many other criteria that are based on a specified energy, the proposed criterion assumes deformation instability would occur at the point of energy inflection. Through calibrating the parameters that governed the entropy evolution, the EI criterion was shown to exhibit significant efficacy in predicting the critical strain at which instability occurred for Ti-6Al-4V, aluminum alloy, and pure copper under various loading conditions. Furthermore, a comparison of the proposed EI criterion was made with other criteria in the literature.

Reduced model and nonlinear analysis of localized instabilities of residually stressed cylinders under axial stretch

In this paper, we present a dimensional reduction to obtain a one-dimensional model to analyze localized necking or bulging in a residually stressed circular cylindrical solid. The nonlinear theory of elasticity is first specialized to obtain the equations governing the homogeneous deformation. Then, to analyze the nonhomogeneous part, we include higher-order correction terms of the axisymmetric displacement components leading to a three-dimensional form of the total potential energy functional. Details of the reduction to the one-dimensional form are given. We focus on a residually stressed Gent material and use numerical methods to solve the governing equations. Two loading conditions are considered. First, the residual stress is maintained constant, while the axial stretch is used as the loading parameter. Second, we keep the pre-stretch constant and monotonically increase the residual stress until bifurcation occurs. We specify initial conditions, find the critical values for localized bifurcation, and compute the change in radius during localized necking or bulging growth. Finally, we optimize material properties and use the one-dimensional model to simulate necking or bulging until the Maxwell values of stretch are reached.

Artificial neural network-substituted transition model for crossflow instability: Modeling strategy and application prospect

Data-driven approaches have made preliminary inroads into the area of transition–turbulence modeling, but are still in their infancy with regard to widespread industrial adoption. This paper establishes an artificial neural network (ANN)-based transition model to enhance the capacity of capturing the crossflow (CF) transition phenomena, which are frequently identified over a wide range of aerodynamic problems. By taking a new CF-extended shear stress transport (SST) transition-predictive (SST-γ) model as the baseline, a mapping from mean flow variables to transition intermittency factor (γ) is constructed by ANN algorithm at various Mach and Reynolds numbers of an infinite swept wing. Generalizability of the resulting ANN-based (SST-γANN) model is fully validated in the same infinite swept wing, an inclined 6:1 prolate spheroid, and a finite swept wing in extensive experiment regimes, together with two effective a priori analysis strategies. Furthermore, the calculation efficiency, grid dependence, and performance of the present model in non-typical transitional flow are also assessed to inspect its industrial feasibility, followed by the elucidation of rationality behind the preliminary success and transferability of present framework. The results manifest that the SST-γANN model aligns well with the benchmark SST-γ model, and both can capture the CF transition accurately compared with their experiment counterpart, completely breaking through the disability of original SST-γ model without CF correction. In addition, good properties of efficiency, robustness, and generalizability are achieved for the ANN-alternative transition model, together with the usability of present framework across various transitional flows.

Phase-field modeling of ATG instability in Allen–Cahn framework

The phenomenon of Asaro–Tiller–Grinfeld (ATG) instability is common in the molecular beam epitaxy (MBE) process. In order to investigate the ATG instability, a two-dimensional mathematical model is established, which considers elastic stress. The phase-field method is utilized to simulate the interface evolution and the stress distribution. Furthermore, the Allen–Cahn approach, coupled with the motion of the interface, is used to investigate the morphology evolution. The results show that the thin film becomes unstable when it reaches a critical value. The critical thickness of the thin film is about 5.08 nm. The interface breaks into several parts due to the effect of elastic stress. The validity and correctness of the model are verified by the relevant theoretical results. Moreover, the numerical model can provide the basis for optimizing the ATG instability phenomenon in the MBE process.

A 1D model for the dynamic instability of magnetized beams in leakage flow energy harvesters

This paper presents a one-dimensional fluid–structure interaction model for investigating the dynamic stability of elastic mounted beams under the influence of magnetic forces in a leakage flow energy harvesting environment. The interaction between the beam and external magnetic fields is represented by a nonlinear long range force distribution that is non linearly dependent on the beam displacement. The formulation results in a two way coupled fluid–structure interaction system that is one way coupled with the electromagnetic system. A perturbation technique is utilized to linearize the second order equilibrium equations of the coupled system, which are then transformed into a set of first-order ordinary differential equations in the state space. The effect of the linearized magnetic force coefficient on the eigenvalues and dynamic stability of the system is analyzed through a parametric study. The results indicate the onset of oscillatory dynamics in the coupled magneto-fluid-structural system is a non monotonic function of the magnetic force.