Quasiperiodicity, a partially synchronous state that precedes the onset of forced synchronization in hydrodynamic systems, exhibits distinct geometrical patterns based on the specific route to lock-in. In this study, we explore these dynamic behaviors using recurrence quantification analysis. Focusing on a self-excited hydrodynamic system-a low-density jet subjected to external acoustic forcing at varying frequencies and amplitudes. We generate recurrence plots from unsteady velocity time traces. These recurrence plots provide insight into the synchronization dynamics and pathways of the jet under forced conditions. Further, we show that recurrence quantities are helpful to detect and distinguish between different routes to lock-in.

We present the first application of cluster-based control (CBC), a data-driven feedback control strategy, to suppress self-excited thermoacoustic oscillations. CBC embeds a single scalar time-series measurement in a low-dimensional feature space, partitions that space into a finite set of clusters, and assigns an actuation amplitude to each cluster. The amplitudes are then optimized with a Nelder–Mead simplex search that minimizes a cost function balancing oscillation suppression against actuation effort. Implemented on both a low-order thermoacoustic model and an experimental Rijke tube, CBC is found to reduce the pressure amplitude by nearly 98% while requiring an order of magnitude less actuation power than conventional open-loop time-periodic forcing. The CBC algorithm converges after only several optimization iterations, cutting the total training and tuning time by more than a factor of five relative to recent machine-learning-based strategies. These results demonstrate that CBC can provide a rapid sample-efficient route to model-free feedback control of self-excited thermoacoustic systems and, more broadly, of nonlinear self-excited oscillators governed by coupled multi-scale interactions.

This paper presents the experimental investigation of the spontaneous temporal and spatiotemporal dynamics of a lean-premixed methane-air flame stabilized by a cylindrical bluff-body under different combustor lengths. The dynamic pressure and simultaneous heat release rate measurements, along with the flame visualization as well as the two-dimensional Particle Image Velocimetry (2D-PIV), were conducted to examine the temporal and spatiotemporal evolution of the flame dynamics within the combustion chamber. When continuously increasing the length of the combustor (Lc) at the constant inlet condition (both constant Reynolds number (Re) and equivalence ratio (∅)), we observe that the combustion mode switches from the steady-state combustion to the thermoacoustic combustion and finally to the intermittent combustion. By inspecting the simultaneously acquired time-resolved heat release rate and the dynamic acoustic pressure fluctuations, our study confirms that the steady combustion mode corresponds to a desynchronized aperiodic pattern, the thermoacoustic combustion mode corresponds to a perfect phase synchronized periodic pattern, and the intermittent combustion mode corresponds to an intermediate or transitional state between the previous two (the steady and the thermoacoustic) state. Finally, we investigate the hydrodynamic stability regime corresponding to the above-mentioned three combustion modes. Our study successfully provides comprehensive experimental evidence that even when the inlet conditions are kept constant, increasing the length of the combustor enhances the thermoacoustic positive feedback process, eventually resulting in different hydrodynamic states.

We experimentally investigate the forced synchronization of a turbulent, lean-premixed, bluff-body-stabilized flame undergoing self-excited oscillations due to global hydrodynamic instability. We acoustically force the flame at different amplitudes (alpha) and frequencies (f(f)) around its natural global frequency (f(n)), while measuring its heat release rate (HRR) response via time-resolved CH* chemiluminescence imaging. As alpha increases at a fixed ff, the flame initially oscillates quasiperiodically at both f(n) and f(f), but synchronizes with the forcing above a critical alpha, consistent with the behavior of a canonical self-excited oscillator. The minimum alpha required for synchronization increases with the detuning (|f(f) - f(n)|), but not symmetrically around f(f) / f(n) = 1, resulting in a skewed Arnold tongue. The HRR amplitude grows at small detuning due to resonant amplification but decays at large detuning due to asynchronous quenching. Comparing the globally unstable flame with an equivalent globally stable flame, we find that both exhibit a range of coupled states, including desynchronization, phase synchronization, and generalized synchronization. Crucially, the phase locking value varies spatially throughout the flame body, with the shear layers synchronizing more readily than the wake and recirculation zones. At higher detuning levels (i.e., when the forcing frequency is below 0.9 or above 1.1 times the natural frequency, f(f )/f(n) <0.9 or f(f) /f(n) > 1.1), the HRR amplitude of the globally unstable flame is observed to be lower than that of the globally stable flame. This finding suggests that global hydrodynamic instability in a flame may serve as a passive mechanism to weaken self-excited thermoacoustic oscillations in combustion systems such as gas turbines and rocket engines.

This study explores the effects of price inflation on the optimal performance of a solar-geothermal system capable of combined production of hydrogen, power, freshwater and heat. Multi-objective optimization is applied, with the ground water mass flow rate and the solar collector area as the decision variables, alongside the payback period and the annual production of hydrogen, power, freshwater and heat as the objective functions. The results show that when inflation rises four-fold from 0.05 to 0.20, the ground water mass flow rate drops by 20.1%, while the solar collector area rises by 14.4%. Accompanying this are 15.0%, 12.2% and 12.0% decreases in annual freshwater, power and heat production, respectively, alongside a 9.9% increase in annual hydrogen production. The payback period, meanwhile, increases only modestly, from 6.11 to 7.39 years, demonstrating the economic viability of such a combined solar-geothermal system, even in inflationary times.

In this work, we investigated the combustion and agglomeration characteristics of aluminum-water propellants by replacing the original Al with binary n-Al/CuO metastable intermolecular composites (MICs). Through laser ignition tests and thermogravimetric-differential scanning calorimetry, we evaluated the oxidation reactivity, ignition delay, burning rate, agglomeration properties, and condensed combustion products of aluminum-water propellants containing different CuO loadings. Compared with conventional aluminum-water propellants, the introduction of binary MICs is found to lower the initial temperature of Al and improve its oxidation activity. Both the burning and heating rates scale linearly with the CuO loading, increasing by a factor of 5 and 6, respectively, when the CuO loading reaches 5 wt.%. The combustion efficiency of the modified propellants is found to improve by 5-12 %. The mean size of the condensed combustion products drops from over 400 mu m to around 200 mu m due to MICs addition, indicating weakened agglomeration. The ignition delay time is slightly shortened, and the combustion intensity first increases but then decreases as the CuO loading increases. In summary, this work indicates that replacing Al with binary Al/CuO-MICs can significantly alter the combustion and agglomeration properties of aluminum-water propellants. The experimental data and insight from this work could help guide the development of advanced aluminum-water propellants for various propulsion and energy applications.

This study explores the prediction of airfoil self-noise through Deep Learning whilst focusing more specifically on the so-called turbulent boundary layer trailing edge (TBL-TE) noise. To this end, a predictive model relying on a Deep Neural Network (DNN) is developed, being then trained using an experimental database of TBL-TE noise signatures previously acquired by NASA. The DNN is favorably benchmarked against the test results, demonstrating its superiority over a popular semi-empirical prediction tool, i.e., the BPM model from NASA. Special attention is paid to the sensitivity of the DNN towards its architecture and/or its training extent. All in all, the DNN proves robust and accurate, reproducing faithfully the TBL-TE noise signatures with an average error of about 1.5 similar to 2.5 dB in terms of Sound Pressure Level. Special attention is also paid to sensitivity of the DNN towards the composition of its training dataset, whose consistency is enforced by clustering all datapoints belonging to an identical test configuration. This allows evaluating how far the model constitutes a true prediction tool, i.e., can extrapolate the experimental database instead of merely interpolating it through overfitting. Finally, the sensitivity of the DNN towards its training data is further explored to tentatively discriminate which quantities constituting the experimental database may contribute more significantly to the correct prediction of the noise signatures and - by extension - to their underlying physical mechanisms.

We explore the transition to chaos in a prototypical hydrodynamic oscillator, namely a globally unstable low-density jet subjected to external time-periodic forcing. As the forcing strengthens at an off-resonant frequency, we find that the jet exhibits a sequence of nonlinear states: period-1 limit cycle $\rightarrow $ quasiperiodicity $\rightarrow$ intermittency $\rightarrow$ low-dimensional chaos. We show that the intermittency obeys type-II Pomeau–Manneville dynamics by analysing the first return map and the scaling properties of the quasiperiodic lifetimes between successive chaotic epochs. By providing experimental evidence of the type-II intermittency route to chaos in a globally unstable jet, this study reinforces the idea that strange attractors emerge via universal mechanisms in open self-excited flows, facilitating the development of instability control strategies based on chaos theory.

In this experimental study, we use a data-driven machine learning framework based on genetic programing (GP) to discover model-free control laws (individuals) for suppressing self-excited thermoacoustic oscillations in a prototypical laminar combustor. This GP framework relies on an evolutionary algorithm to make decisions based on natural selection. Starting from an initial generation of individuals, we rank their performance based on a cost function that accounts for the trade-off between the state cost (thermoacoustic amplitude) and the input cost (actuator power). We then breed subsequent generations of individuals via a tournament in which the direct forwarding of elite individuals occurs alongside genetic operations such as mutation, replication, and crossover. We implement this GP control framework in both closed-loop and open-loop forms, followed by benchmarking against conventional open-loop control based on time-periodic forcing. We find that while all three control strategies can achieve similarly large reductions in thermoacoustic amplitude, GP closed-loop control consumes the least actuator power, making it the most efficient. It achieves this efficiency by learning an actuation mechanism that exploits the strong heat-release-rate amplification of the open flame at its preferred mode, even though the GP algorithm has never seen the open flame itself. This study demonstrates the feasibility of using GP to discover new and more efficient model-free individuals for suppressing self-excited thermoacoustic oscillations, providing a promising approach to data-driven feedback control of combustion devices.

The presence of global hydrodynamic instability (GHI) in turbulent premixed flames has been shown to reduce the sensitivity of heat-release-rate (HRR) responses to external acoustic forcing, suggesting that GHI could passively weaken thermoacoustic oscillations detrimental to combustion systems. This study adopts a mutual synchronization approach to investigate the coupled interactions between a bluff-body stabilized turbulent premixed flame containing GHI and the acoustic modes of its surrounding combustor. In the absence of external forcing, flame HRR oscillations and combustor acoustic modes can mutually synchronize , but the impact of mutual synchronization on resulting flame response or acoustic pressure amplitude remains unclear. Therefore, this study systematically investigates mutual synchronization, its dynamical states, and subsequent flame response/acoustic pressure amplitude using temporal and spatial analysis. Simultaneous CH* chemiluminescence imaging and unsteady pressure measurements were conducted in a bluff-body stabilized lean-premixed turbulent combustor. By increasing the combustor length (1200 mm ⩽ L ⩽ 2700 mm) while maintaining a fixed equivalence ratio (ϕ = 0.65) and Reynolds number (Re = 10785), four distinct flame modes were observed: (i) a self-sustained vortex shedding mode due to GHI at L = 1200 mm, also known as the hydrodynamic mode; (ii) a self-sustained 1 combustor mode due to thermoacoustic instability at L = 1700 mm; (iii) a hybrid mode at L = 2500 mm, where both the GHI and thermoacoustic modes coex-ist; and (iv) a mutually synchronized mode at L = 2700 mm, where GHI and thermoacoustic modes are locked into each other. Temporal analysis reveals the coexistence of various dynamical states during mutual synchronization, including a simultaneous increase in the amplitudes of flame HRR and acoustic pressure oscillations. Similarly, spatial analysis reveals strong HRR fluctuations occurring at the recirculation zone due to large-scale vortex roll-up. Lastly, two distinct mechanisms causing flame blowoff are identified: (i) a few cycles of flame pinch-off followed by global flame blowoff when ϕ falls below the lean flammability limit and (ii) flame pinch-off and flame-wall quenching together cause global flame blowoff.

In this study, how the coating of polydopamine (PDA) and polyvinylidene fluoride (PVDF) on boron particles affects the ignition and combustion characteristics of kerosene droplets was investigated. In this work, PVDF was first coated onto boron nanoparticles using PDA as a binder to form double-coated composite particles (denoted as B@PF), and then the B@PF particles were blended into kerosene to produce nanofluidic fuels. Various characterization techniques were used to evaluate the ignition and combustion performance of the B@PF composites and the nanofuel droplets, including scanning electron microscopy (SEM), thermogravimetric-differential scanning calorimetry (TG-DSC), laser ignition testing, and single droplet combustion experiments. The results showed that the PDA coating could effectively prevent the moisture absorption of the particles in ambient air and increase the heat release by 42.97 %, while the PVDF coating would have a negative impact on the energy properties of the particles. Pure B particles have the lowest spectral intensity under laser light, which is consistent with the DSC results. The addition of pure B particles to kerosene reduced the ignition delay time by nearly 86 %, while the PVDF coating could enhance the droplet heat transfer to further reduce the ignition delay time. However, the increase in PVDF content negatively affects the combustion rate of the droplets by decreasing the energy properties of the particles. In the final residue combustion stage, the reaction between PVDF and B2O3 increases the burning intensity of the B particles and reduces the size of the combustion residue. Based on the experimental results, a comprehensive model for the ignition, combustion and residue burning of droplets coated with both PDA and PVDF is proposed.

We present an improved dynamic model to predict the time-varying characteristics of the far-wake flow behind a wind turbine. Our model, based on the FAST.Farm engineering model, is novel in that it estimates the turbulence generated by convective instabilities, which selectively amplifies the inflow velocity fluctuations. Our model also incorporates scale dependence when calculating the wake meandering induced by the passive wake meandering mechanism. For validation, our model is compared with FAST.Farm and large-eddy simulation (LES). For the mean flow, our model agrees well with LES in terms of the wake deficit and wake width, but the FAST.Farm model underestimates the former and overestimates the latter. For the instantaneous flow, our model predicts well the wake-center deflection and turbulent kinetic energy, reducing the discrepancies in the spectral characteristics by more than a factor of two relative to LES, depending on the Strouhal number. By incorporating two key mechanisms governing the far-wake dynamics, our model can predict more accurately the dynamic wake evolution, making it suitable for real-time calculations of wind farm performance.

We experimentally investigate the forced synchronization of a self-excited chaotic thermoacoustic oscillator with two natural frequencies, $f_1$ and $f_2$ . On increasing the forcing amplitude, $\epsilon _f$ , at a fixed forcing frequency, $f_f$ , we find two different types of synchronization: (i) $f_f/f_1 = 1:1$ or $2:1$ chaos-destroying synchronization (CDS), and (ii) phase synchronization of chaos (PSC). En route to $1:1$ CDS, the system transitions from an unforced chaotic state ( ${\rm {CH}}_{1,2}$ ) to a forced chaotic state ( ${\rm {CH}}_{1,2,f}$ ), then to a two-frequency quasiperiodic state where chaos is destroyed ( $\mathbb {T}^2_{2,f}$ ), and finally to a phase-locked period-1 state ( ${\rm {P1}}_f$ ). The route to $2:1$ CDS is similar, but the quasiperiodic state hosts a doubled torus $(2\mathbb {T}^2_{2,f})$ that transforms into a phase-locked period-2 orbit $({\rm {P2}}_f)$ when CDS occurs. En route to PSC, the system transitions to a forced chaotic state ( ${\rm {CH}}_{1,2,f}$ ) followed by a phase-locked chaotic state, where $f_1$ , $f_2$ and $f_f$ still coexist but their phase difference remains bounded. We find that the maximum reduction in thermoacoustic amplitude occurs near the onset of CDS, and that the critical $\epsilon _f$ required for the onset of CDS does not vary significantly with $f_f$ . We then use two unidirectionally coupled Anishchenko–Astakhov oscillators to phenomenologically model the experimental synchronization dynamics, including (i) the route to $1:1$ CDS, (ii) various phase dynamics, such as phase drifting, slipping and locking, and (iii) the thermoacoustic amplitude variations in the $f_f/f_1$ – $\epsilon _f$ plane. This study extends the applicability of open-loop control further to a chaotic thermoacoustic system, demonstrating (i) the feasibility of using an existing actuation strategy to weaken aperiodic thermoacoustic oscillations, and (ii) the possibility of developing new active suppression strategies based on both established and emerging methods of chaos control.

The ignition delay of aluminum particles can be profoundly influenced by the agglomeration and combustion characteristics of solid propellants. In this experimental study, the ignition of individual aluminum particles in nitrate ester plasticized polyether (NEPE) and hydroxyl-terminated polybutadiene (HTPB) propellant atmospheres was examined using laser ignition tests and high-speed photography. Focus was directed at the effects of the atmospheric composition, pressure, and aluminum particle size (500, 800 and 1000 mu m). It was observed that the non-homogeneous reaction heat generation and convective heat exchange rates during particle ignition could be increased by increasing the CO2 content or ambient temperature, resulting in a shorter ignition delay time. This explains why aluminum particles tended to burn more efficiently in nitrate ester plasticized polyether than in hydroxyl-terminated polybutadiene. In addition, it was found that the ignition delay time decreased with increasing pressure and was inversely proportional to the particle size squared. An ignition model for aluminum particle ignition in a multi-component atmosphere was developed and validated to describe the temperature change and energy transfer during ignition. The calculated ignition delay times were found to be within 5% of the experimental values. The model also showed that increasing the ambient temperature was more effective than increasing the CO2 content at enhancing ignition, and that CO2 was more effective than O2, which was itself more effective than H2O. Overall, this study provides useful insight into the ignition characteristics of aluminum particles in different propellant environments. The results could be used to develop more effective propellant formulations, optimize combustion processes, and improve safety in the handling and use of aluminum-based propellants.

The amount of energy delivered to a solid-fueled rocket motor is its most crucial performance indicator. Metallic fuels, such as aluminum, is commonly added to propellants for obtaining high energy densities. In this study, the agglomeration of four distinct types of composite solid propellants, comprising different adhesives, oxidants, and Al particles, during gradual heating was experimentally investigated using a microscopic heating device. Thermogravimetry, quenching analysis, microscopic observations, and the collection of condensed combustion products were used to examine the microscale processes of agglomeration in the propellants during their combustion. Melting of the binder was found to enable the aluminum particles to travel and relative motion between the particles and the melting layer will act liquid drag forces on the particles, while oxidiser recession in the binder led to unbalanced surface tension forces acting on the aluminum particles, both these two forces pulling them closer together. Some particles were ejected into the gas under the action of aerodynamic drag. The addition of 10% RDX to the HTPB propellant increased the agglomerate size from 200 to 224 μm. Reducing the diameter of the aluminum particles in the NEPE propellant from 29 to 13 μm increased the agglomerate size from 200 to 632 μm. Moreover, RDX reacted exothermically at low temperatures in the HTPB propellant, enhancing the capillary forces and increasing the agglomerate size. The agglomeration process was dominated by a balance between the aerodynamic, adhesive, and capillary forces.

We use complex network analysis to investigate the vortical interactions in a bluffbody stabilized combustion system containing a turbulent lean premixed swirling flame. Using time-resolved vorticity measurements, we construct time-varying weighted spatial networks whose node strength distribution is derived from the Biot-Savart law. We find widespread evidence of scale-free topology in the vortical networks, with the most coherent flow structures acting as the primary network hubs. Crucially, we find that even after the onset of thermoacoustic instability, the scale-free topology can persist continuously in time, contrary to some suggestions from the literature. This discovery could have important implications for the design of flow controllers that rely on destroying the primary hubs of vortical networks.

We numerically explore the two-dimensional, incompressible, isothermal flow through a wavy channel, with a focus on how the channel geometry affects the routes to chaos at Reynolds numbers between 150 and 1000. We find that (i) the period-doubling route arises in a symmetric channel, (ii) the Ruelle-Takens-Newhouse route arises in an asymmetric channel, and (iii) the type-II intermittency route arises in both asymmetric and semiwavy channels. We also find that the flow through the semiwavy channel evolves from a quasiperiodic torus to an unstable invariant set (chaotic saddle), before eventually settling on a period-1 limit-cycle attractor. This study reveals that laminar channel flow at elevated Reynolds numbers can exhibit a variety of nonlinear dynamics. Specifically, it highlights how breaking the symmetry of a wavy channel can not only influence the critical Reynolds number at which chaos emerges, but also diversify the types of bifurcation encountered en route to chaos itself.

We present probabilistic solutions to a pair of mutually coupled Van der Pol oscillators subjected to stochastic forcing. We consider three different types of coupling: reactive, dissipative, and nonlinear coupling. Using stochastic averaging, we derive the stationary Fokker-Planck equation for each oscillator, yielding a probability density function for the fluctuation amplitude. For each coupling type, we numerically validate the Fokker-Planck solutions for different noise levels and coupling strengths, with a focus on the stochastic and bifurcation characteristics. The validated analytical expressions derived in this study could serve to improve the prediction and control of a generic class of coupled oscillator systems operating near the Hopf point in the presence of noise.

Owing to its hydrogen storage capacity, aluminum hydride (AlH3) has been proposed as a potential fuel additive in solid rocket propellants to achieve a higher specific impulse and cooler combustion. In this experimental investigation, we examine the effects of AlH3 loading and particle size on the thermal decomposition, ignition, agglomeration and combustion of high-energy solid propellants at pressures up to 9.1 MPa. We use a variety of diagnostics, including thermogravimetry, differential scanning calorimetry, energy dispersive X-ray spectroscopy, scanning electron microscopy and so on. The results show that adding AlH3 can enhance the thermal decomposition of the propellants. As the loading of fine-grained AlH3 increases, the combustion intensity drops, but the ignition delay time drops as well (by 60 %). When the AlH3 particle size increases, the ignition delay time rises, but it remains shorter than that of a baseline propellant containing Al instead of AlH3. Although AlH3 is found to lower the gas-phase flame temperature and temperature gradient, it enhances the burning rate and lowers the pressure exponent from 0.58 to 0.50. Fine-grained AlH3 is also found to shrink the near-burning surface agglomerates and condensed combustion products, increasing the combustion efficiency from 81.9 % to 94.7 %. However, coarse-grained AlH3 shows the opposite effect, decreasing the combustion efficiency to 63.3 %. Overall, this study sheds new light on the influence of AlH3 addition on high-energy propellants, facilitating the application of this promising fuel additive in solid rocket motors.

Nader Karimi, Larry K. B. Li, Manosh C. Paul, Mohammad Hossein Doranehgard and Freshteh Sotoudeh introduce the RSC Advances themed issue on Advances in Sustainable Hydrogen Energy.