Dominant Instability Mode Research Articles

Identification of dominant instability modes in power systems based on spatial‐temporal feature mining and TSOA optimization

AbstractThe recognition of the transient dominant instability mode is of great significance for rapidly and accurately formulating transient emergency decisions in power systems. In response to the challenge of accurately distinguishing between angle instability and voltage instability, which are coupled in actual power grids, this paper explores the mapping relationship between simulation data and the stable state of the system, as well as the dominant instability mode. The method enables real‐time identification of the dominant instability mode, which bypasses complex physical mechanisms. Firstly, spatio‐temporal feature mining is conducted, where convolutional neural networks are employed to learn crucial local features of transient curves, and bidirectional gated recurrent unit s utilized to learn transient features over time sequences. Next, a multihead attention mechanism is introduced to enhance sensitivity to important time steps in the sequence data. Finally, the transit search optimization algorithm optimizes the global model parameters, further increasing the accuracy of the model. Using the IEEE 10‐machine and 39‐node system as an example for simulation, the results validate that the proposed method exhibits significant advantages in terms of accuracy and applicability compared with other machine learning methods.

Amplification factor transport equation modelling of Mack mode disturbances in hypersonic boundary layers

In the hypersonic boundary layer, the streamwise instability modes are mainly the Mack first mode and the Mack second mode. After the Mach number exceeds 4.0, the Mack second mode becomes the dominant instability mode for boundary layer transition. Currently, there is no complete analytical method to establish an amplification factor transport equation for the second mode. In order to improve the application of the amplification factor transport (AFT) model in hypersonic boundary layer transition prediction, this paper employs boundary layer similarity solutions to conduct stability analysis on the second mode and introduces a function to calculate the growth rate of disturbances. Additionally, a transport equation for the amplification factor of the second mode is formulated. For the non-local variables appearing in the equation, a local calculation method is provided. Combined with the intermittency factor transport equation, a transition prediction model for the second mode is formed. Hypersonic flat plate, wedge, and flared wedge are selected for model validation. The computed results show good agreement with standard stability analysis or experimental results, demonstrating the rationality of the transition model and its high prediction accuracy and reliability.

Flutter in functionally graded conical shell under follower force

Truncated conical shells are essential components of rocket booster nozzles and thrust vector control (TVC) systems for the propulsion of multi-stage launch vehicles. The TVCs assist the ascent of launch vehicles by directing the resultant thrust from the boosters, acting as a follower force that might trigger instability. Previous studies on the instability of aerospace structures have mostly focused on beams, plates, and cylindrical shells. This study analyses a truncated conical shell under a follower force of constant magnitude, considering thickness-wise gradation of material properties employed for thermal management. The governing equations are derived following Hamilton's principle, considering first-order shear deformation theory, and solved using the finite element method. Clamped and free boundaries are assumed at the small and large ends. The influence of mass and stiffness proportional damping is considered. Although strong flutter appears as the dominant instability mode, instances of erratic weak instabilities are also observed for undamped and lightly damped cases. Damping enhances stability, but its effect becomes saturated. The flutter loads are presented for varying non-dimensional parameters, characterizing the shell geometry and material properties.

Intelligent Power System Stability Assessment and Dominant Instability Mode Identification Using Integrated Active Deep Learning.

Simulation analysis is critical for identifying possible hazards and ensuring secure operation of power systems. In practice, large-disturbance rotor angle stability and voltage stability are two frequently intertwined stability problems. Accurately identifying the dominant instability mode (DIM) between them is important for directing power system emergency control action formulation. However, DIM identification has always relied on human expertise. This article proposes an intelligent DIM identification framework that can discriminate among stable status, rotor angle instability, and voltage instability based on active deep learning (ADL). To reduce human expert efforts required to label the DIM dataset when building DL models, a two-stage batch-mode integrated ADL query strategy (preselection and clustering) is designed for the framework. It samples only the most helpful samples to label in each iteration and considers both information contents and diversity in them to improve query efficiency, significantly reducing the required number of labeled samples. Case studies conducted on a benchmark power system (China Electric Power Research Institute (CEPRI) 36-bus system) and a practical large-area power system (Northeast China Power System) reveal that the proposed approach outperforms conventional methods in terms of accuracy, label efficiency, scalability, and adaptability to operational variability.

Complex Deposit Slope Excavation Deformation Mechanism and Seismic Reinforcement Effect Evaluation

Background To further investigate the excavation deformation mechanism and remedial strategies for slope reinforcement in the southwest mountain area, the Baihetan-Jiangsu (Zhejiang) UHV transmission project deposit slope deformation reinforcement was used as a case study. Methods Deep displacement monitoring, on-site testing, and FLAC3D numerical simulation techniques were employed. The assessment of the deposit slope excavation deformation mechanism and the effectiveness of seismic reinforcement for different design options and pile parameters are conducted while analyzing the seismic reinforcement mechanism. Results and Discussions The results showed that (1) The deposit slope composed of “multi-genetic type soil” in the converter station is prone to deformation, where the dominant instability mode is “traction creep and tension failure mode.” (2) Both circular and rectangular anti-slide piles significantly reduce the amount of slope body deformation; employing circular anti-slide piles for addressing this type of deposit slope provides enhanced anti-slide retention and economic benefits. (3) Under the influence of an earthquake, the shear force and bending moment of the anti-slide pile first increase and then decrease with the increase of seismic intensity. Conclusion The distribution law of shear force and bending moment in a pile should be considered comprehensively in slope support design.

Inertia and slip effects on the instability of a liquid film coated on a fibre

To investigate the influence of inertia and slip on the instability of a liquid film on a fibre, a theoretical framework based on the axisymmetric Navier–Stokes equations is proposed via linear instability analysis. The model reveals that slip significantly enhances perturbation growth in viscous film flows, whereas it exerts minimal influence on flows dominated by inertia. Moreover, under no-slip boundary conditions, the dominant instability mode of thin films remains unaltered by inertia, closely aligning with predictions from a no-slip lubrication model. Conversely, when slip is introduced, the dominant wavenumber experiences a noticeable reduction as inertia decreases. This trend is captured by an introduced lubrication model with giant slip. Direct numerical simulations of the Navier–Stokes equations are then performed to further confirm the theoretical findings at the linear stage. For the nonlinear dynamics, no-slip simulations show complex vortical structures within films, driven by fluid inertia near surfaces. Additionally, in scenarios with weak inertia, a reduction in the volume of satellite droplets is observed due to slip, following a power-law relationship.

Principle of fundamental resonance in hypersonic boundary layers: an asymptotic viewpoint

The fundamental resonance (FR) in the nonlinear phase of the boundary-layer transition to turbulence appears when a dominant planar instability mode reaches a finite amplitude and the low-amplitude oblique travelling modes with the same frequency as the dominant mode, together with the stationary streak modes, undergo the strongest amplification among all the Fourier components. This regime may be the most efficient means to trigger the natural transition in hypersonic boundary layers. In this paper, we aim to reveal the intrinsic mechanism of the FR in the weakly nonlinear framework based on the large-Reynolds-number asymptotic technique. It is found that the FR is, in principle, a triad resonance among a dominant planar fundamental mode, a streak mode and an oblique mode. In the major part of the boundary layer, the nonlinear interaction of the fundamental mode and the streak mode seeds the growth of the oblique mode, whereas the interaction of the oblique mode and the fundamental mode drives the roll components (transverse and lateral velocity) of the streak mode, which leads to a stronger amplification of the streamwise component of the streak mode due to the lift-up mechanism. This asymptotic analysis clearly shows that the dimensionless growth rates of the streak and oblique modes are the same order of magnitude as the dimensionless amplitude of the fundamental mode $(\bar {\epsilon }_{10})$ , and the amplitude of the streak mode is $O(\bar {\epsilon }_{10}^{-1})$ greater than that of the oblique mode. The main-layer solution of the streamwise velocity, spanwise velocity and temperature of both the streak and the oblique modes become singular as the wall is approached, and so a viscous wall layer appears underneath. The wall layer produces an outflux velocity to the main-layer solution, inclusion of which leads to an improved asymptotic theory whose accuracy is confirmed by comparing with the calculations of the nonlinear parabolised stability equations (NPSEs) at moderate Reynolds numbers and the secondary instability analysis (SIA) at sufficiently high Reynolds numbers.

Flow Instability Control in a Model Swirl-Stabilized Combustor with Central Jet Injection

Swirling flows often occur in nature and industrial applications. With an increase in swirl intensity, such rotating flows are known to become unstable and undergo a sudden breakdown of the vortex core, resulting in unsteady flow dynamics with intensive pressure fluctuations. In particular, swirling flows are organized in combustion chambers to stabilize the flame around the central recirculation zone, formed due to the vortex core breakdown. However, the impact of large-scale vortex structures, including the precessing vortex core and secondary helical vortices, on unsteady combustion regimes is still unclear. The present paper demonstrates experimentally that for the swirling flow of a model swirl combustor, the injection of a central jet may be used to alter the configuration of coherent flow structures, including helical vortices. In particular, the asymmetric hydrodynamics mode, associated with the precessing vortex core, is suppressed, whereas the symmetrical one becomes dominant. This effect demonstrates the importance of central jet injection to control the dominant mode of flow instability for the design of swirl combustors.

Bidirectional Active Transfer Learning for Adaptive Power System Stability Assessment and Dominant Instability Mode Identification

Deep learning (DL) is a useful tool for power system stability assessment (PSSA) and dominant instability mode (DIM) identification. However, when faced with operational variability, the performance of DL models degrades. This paper proposes a bidirectional active transfer learning (Bi-ATL) framework for more adaptive PSSA and DIM identification, where the DL model is easier to adapt to unlearned operating conditions with fewer newly labeled instances. At the instance level, forward active learning and backward active learning are integrated to progressively build a mixed instance set by actively including the most label-worthy instances of new operating conditions and actively eliminating the most useless original operating condition instances. Then at the model parameter level, the mixed instance set is utilized to fine-tune the original DL model to new operating conditions. The Bi-ATL framework synthesizes three-way information of the instances and model of the original operating condition, and a few labeled instances of new operating conditions for more efficient adaptation. Intensive case studies conducted on a benchmark power system (CEPRI 36-bus system) and a real-world large-scale power system (Northeast China Power System-2131 bus) validate the efficacy and efficiency of the Bi-ATL framework as well as the role of the three-way information.

Encoding Time Series as Images: A Robust and Transferable Framework for Power System DIM Identification Combining Rules and VGGNet

Digital simulation is very important for the safe and economic operation of power systems. Power system dominant instability mode (DIM) identification is an intractable problem in large-scale transient simulation analysis, because transient instability and short-term voltage instability are often intertwined. Deep learning is a promising way to achieve accurate DIM identification. By encoding time series as images, this paper proposes a robust and transferable DIM identification framework combining curve filtering rules and a dual-channel VGGNet (DCVGG) image recognition network. The curve filtering rules can effectively reduce the redundancy of massive time-domain features, the model parameters, and training time. A skillfully designed method is proposed to encode time series as images and improve the feature extraction capability of convolutional neural networks. The proposed DCVGG network is capable of processing rotor angle and voltage images simultaneously and has the potential to become a pre-trained model, making transfer learning between different power systems possible. Case studies conducted on 8-machine 36-bus system and Northeast China Power Grid demonstrate the proposed framework has better performance, scalability, robustness, and transferable ability than contrastive machine learning methods.

Effect of anisotropy and inhomogeneity on the stability of liquid film flowing down a porous inclined plane

We examined the linear stability of a Newtonian liquid film flow past a porous inclined plane. Falling film on inclined permeable planes displays three instability modes: surface, shear, and porous mode. Most of the previous studies have examined the film flow past an isotropic and homogeneous porous medium. We could find only one study that examined the film flow past an anisotropic and inhomogeneous porous inclined plane; however, it focused on parameter regimes where the porous mode remains stable. Here, we explored the parameter regimes where all three modes become unstable and investigated the effect of the anisotropic and inhomogeneous variations in the permeability of the porous medium. The generalized Darcy model is used to describe the flow through the porous medium along with the Beavers–Joseph condition at the fluid–porous interface. We show that there is a switching of dominant instability mode from surface mode to porous mode with variation in anisotropic parameter. Our results clearly show that for a given Darcy number, the surface mode is the critical instability mode for isotropic and homogeneous porous media. However, when an anisotropic porous medium is considered with high wall-normal permeability than the wall-parallel permeability, the porous mode becomes the most unstable mode. We show a similar exchange of dominant instability mode from fluid mode (i.e., surface or shear mode) to porous mode with variations in inhomogeneity parameter. This switching of the most unstable mode from fluid mode to porous mode with variation in anisotropy and/or inhomogeneity in permeability has not been demonstrated in any of the earlier studies in the context of film flows. We also present an energy budget analysis to decipher the mechanism responsible for making the three modes unstable.

Linear instability of a surfactant-laden shear imposed falling film over an inclined porous bed

The influence of externally imposed shear on a surfactant-laden gravity-driven fluid flow over an inclined porous substrate is studied using the linear perturbation theory. The hydrodynamic instability of the flow system corresponding to infinitesimal disturbances is examined in the framework of the Orr–Sommerfeld (OS) boundary value problem. Furthermore, the generalized OS model is obtained by including the Marangoni stress and external shear on the flow dynamics. The formulated stability problem is solved as an eigenvalue problem by the Chebyshev spectral collocation technique. The analysis encounters the existence of different classes of unstable modes, namely, the surface, surfactant, and shear modes. The surface mode instability occurs in the low range of Reynolds number and is the dominant mode of instability in particular parameter ranges. The imposed shear at the top surface along and opposite to the flow direction induces possible destabilization and stabilization of the flow, respectively. The permeability and porosity of the porous medium have a mixed impact on the surface mode instability. The temporal growth rate of the surface mode enhances for a thicker porous medium. The surface mode of the flow contaminated by an insoluble surfactant is less unstable than that of the clean free surface flow. This is due to the co-existence of the damped surfactant mode together with the unstable surface mode. On the other hand, the shear mode instability is identified at higher Reynolds numbers for a very small inclination angle, and the shear mode propagates faster for stronger imposed shear in the downstream direction. This trend is reversed for the upstream imposed shear. Moreover, the Marangoni effects exhibit the stabilizing influence on the shear mode. Conclusively, the external shear force would be helpful in regulating the instability of the surfactant-laden film flow down a porous medium.

Data‐model driven rescheduling considering both rotor angle stability and transient voltage stability constraints

Facing the problem of workforce and time costs caused by the rescheduling of large-scale power grids with renewable energy penetration, and the lack of parallel control research on rotor angle instability and transient voltage instability, a rescheduling method based on trajectory sensitivity and deep reinforcement learning (DRL) is proposed to meet the requirements of rotor angle stability and transient voltage stability at the same time. By introducing the process of rescheduling to meet the transient stability constraint, the Markov decision-making process of rescheduling is first constructed. Then, a simple dominant instability type identification method is proposed according to the occurrence time, location, voltage pattern, and position of the oscillation centre. Moreover, a rescheduling strategy is formulated based on the dominant instability mode identification, trajectory sensitivity calculation, actionable device selection, action amount computation, and action of the device. Next, according to the improved distributed distributive deep deterministic policy gradients (D4PG), a DRL model is established to map the action to actionable generator pairs and capacitors/reactors, so as to realize parallel rescheduling of rotor angle instability and transient voltage instability. Finally, the improved New England 39-bus system and an actual power grid are used to verify the effectiveness and advantages of the method.

Giant configurational softening controls atomic-level process of shear banding in metallic glasses

While the shear banding is a ubiquitous feature for metallic glasses and other disordered solids, the underlying material softening mechanism is still an open question requiring physical interpretation at atomic level. Here, through a set of atomistic simulations, we clarify the origin of flow localization, i.e., the birth of a shear band. The local thermal temperature induced by atomic vibration and configurational temperature attributed to structural disordering are proposed to quantify critical degree of thermal and configurational softening, respectively. The comparison between configurational softening and thermal softening being two potential causes for shear banding emergence is then examined at atomic scale. Numerical evidence from atomistic simulations indicates that configurational-softening-induced strain burst is the dominant instability mode as evidenced through a very large value of configurational temperature rise that commensurate with glass transition temperature. It is also found that configurational softening takes precedence over thermally activated ones. Configurational softening is thus conceivably acting as the root cause for the onset of strain localization and shear banding, while the subsequent thermal softening is its consequence. These results provide important insights into the puzzle about the material weakening mechanism underlying shear banding.

Hybrid Rocket Engine Performance Assessment Using Plume Luminosity Oscillations

Spectral analyses were performed on high-speed video of three nitrous-oxide/paraffin-based hybrid rocket launches and one static test fire of a nitrous/paraffin-based hybrid rocket motor. The imagery was taken to assess the combustion stability and identify any dominant instability modes. A spectral analysis of the image luminosity signals has shown distinct oscillatory modes in the plume flowfield. The plume oscillations have been compared and linked to existing hybrid combustion instabilities reported in the literature and theoretical predictions. The use of high-speed imagery has proven useful as a nonintrusive method of gathering high-frequency data in the analysis of hybrid combustion during launch. Analysis of high-speed imagery from a static test has revealed the time-varying aspect of the dominant oscillatory modes. The first longitudinal acoustic mode, identified in all data sets, has been used in a novel way to determine the characteristic velocity of the operating motor.

Inertia Drives a Flocking Phase Transition in Viscous Active Fluids

How fast must an oriented collection of extensile swimmers swim to escape the instability of viscous active suspensions? We show that the answer lies in the dimensionless combination $R=\rho v_0^2/2\sigma_a$, where $\rho$ is the suspension mass density, $v_0$ the swim speed and $\sigma_a$ the active stress. Linear stability analysis shows that for small $R$ disturbances grow at a rate linear in their wavenumber $q$, and that the dominant instability mode involves twist. The resulting steady state in our numerical studies is isotropic hedgehog-defect turbulence. Past a first threshold $R$ of order unity we find a slower growth rate, of $O(q^2)$; the numerically observed steady state is {\it phase-turbulent}: noisy but {\it aligned} on average. We present numerical evidence in three and two dimensions that this inertia driven flocking transition is continuous, with a correlation length that grows on approaching the transition. For much larger $R$ we find an aligned state linearly stable to perturbations at all $q$. Our predictions should be testable in suspensions of mesoscale swimmers [D Klotsa, Soft Matter \textbf{15}, 8946 (2019)].

Instability of rotating Bose stars

Light bosonic (axion-like) dark matter may form Bose stars - clumps of nonrelativistic Bose-Einstein condensate supported by self-gravity. We study rotating Bose stars composed of condensed particles with nonzero angular momentum $l$. We analytically prove that these objects are unstable at arbitrary $l \ne 0$ if particle self-interactions are attractive or negligibly small. They decay by shedding off the particles and transporting the angular momentum to the periphery of the system until a Saturn-like configuration appears: one (or several) spin-zero Bose stars and clouds of diffuse particles orbit around the mutual center. In the case of no self-interactions we calculate the profiles and dominant instability modes of the rotating stars: numerically at $1 \leq l\leq 15$ and analytically at $l\gg 1$. Notably, their lifetimes are always comparable to the inverse binding energies; hence, these objects cannot be considered long-living. Finally, we numerically show that in models with sufficiently strong repulsive self-interactions the Bose star with $l=1$ is stable.

Stability analysis of a thinning electrified jet under nonisothermal conditions.

The linear stability of a jet propagating under an electric field is analyzed under nonisothermal conditions. The electrified jet of a Newtonian fluid is modeled as a slender filament, and the leaky dielectric model is used to account for the Maxwell stresses within the fluid. The convective heat transfer from high-temperature jet to the surroundings results in formation of thicker fibers owing to increased viscosity upon cooling. The jet exhibiting substantial thinning under the action of tangential electric field is examined for stability toward axisymmetric nonperiodic disturbances. This is in contrast to most prior studies which analyzed the stability of a cylindrical jet of uniform radius without thinning under extensional flow by examining only periodic disturbances. Two case studies of reference fluids differing in viscosity and electrical properties are examined. The spectrum of discrete growth rates for axisymmetric disturbances reveal qualitatively distinct instabilities for the two fluids. For a fluid with high electrical conductivity, the conducting mode driven by the coupling of surface charges and an external electric field is found to be the dominant mode of instability. On the contrary, for low conductivity materials, the surface-tension-driven capillary mode is found to be the most critical mode. Heat transfer from the jet to the surroundings tends to stabilize both types of instability mode. Under sufficiently strong heat transfer, the axisymmetric instability, which is believed to be responsible for producing nanofibers with diametric oscillations in electrospinning process, is suppressed. The stabilization is attributed to the enhancement of viscous stress in the thinning jet upon cooling. It is observed that the stabilization effect is relatively more pronounced in a thinning jet compared to the cylindrical jet of uniform radius. The effects of various material and process parameters on the stability behavior is also examined.

Thermocapillary instability in a viscoelastic liquid layer under an imposed oblique temperature gradient

The linear stability analysis of a viscoelastic (Oldroyd-B) liquid layer subjected to an oblique temperature gradient (OTG) is investigated numerically. For the case of low liquid elasticity, the analysis shows a strong stabilizing effect of the horizontal component (HTG) of the OTG on the two elastic modes emerging due to the presence of the vertical component (VTG) of the OTG. However, if the liquid elasticity is sufficiently large, the HTG fails to stabilize the upstream elastic mode. The liquid elasticity stabilizes the Newtonian interaction mode arising out of the interaction between the HTG and the VTG. The thermocapillary flow introduced by the HTG leads to the development of a new elastic mode absent in the case of a Newtonian liquid layer. The present paper thus shows that the elasticity of the liquid plays a major role in the competition between various instability modes to determine the dominant mode of instability.

Aeroelastic analysis of an idealized landing gear door in subsonic potential flow

Landing gear doors on aircraft have experienced flutter during preliminary flight testing. While designs vary widely, landing gear doors are typically plate-like structures with a relatively rigid actuator attached to their inside surface. To better understand the aeroelasticity of landing gear doors, this study investigates the aeroelastic stability of an idealized model. The model consists of a hinged plate with an interior constraint approximating the actuator attachment. The plate is subject to uniform flow, and an unsteady vortex lattice model is coupled to the structural model to predict critical flow velocities. The location and footprint area of the internal constraint, along with plate aspect and mass ratios, are varied to investigate a large parameter space. Results reveal that the critical flow speed and instability mechanism are sensitive to the postulated actuator placement. In general, flutter is the dominant mode of instability when the actuator is postulated in the leading quarter of the plate. In other postulated locations, divergence dominates. However, the exact shape and location of the boundary between flutter and divergence is configuration dependent and found to be especially sensitive to changes in aspect ratio.