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System uncertainty remains a challenge for effective control of lower extremity exoskeletons, particularly in clinical populations. Adaptive control offers a potential solution by accounting for unknown system characteristics in real time. Here, we introduce the use of Gaussian-based adaptive control (GBAC) in a two-degree-of-freedom (DOF) exoskeleton for an angular position tracking task in the presence of system uncertainty. The mathematical derivation of the implicitly non-Lyapunov adaptation law is presented using Lagrangian mechanics, including a Gaussian kernel regressor and its stable convergence. We then evaluate GBAC performance in a 2-DOF simulation compared with a previously developed robust adaptive backstepping algorithm, Lyapunov-stable Slotine–Li control, and a proportional-integral-derivative (PID) controller. We additionally complete 1-DOF simulations to evaluate the effects of external disturbance and parameter uncertainty on controller performance. Finally, we evaluate GBAC experimentally in our existing 1-DOF knee exoskeleton along with Slotine–Li and PID controllers. The simulation results demonstrate the improved tracking performance and faster convergence of GBAC, especially in the presence of an external disturbance and uncertainty introduced by extra segment length and mass. The experimental results demonstrate similar performance, wherein GBAC and Slotine–Li provide stable tracking in the presence of unmodeled system dynamics; however, convergence time was faster and tracking error was lower for GBAC. Collectively, these results demonstrate that GBAC is an effective adaptive controller in the presence of system uncertainty and therefore warrants further development and investigation for use in flexible joint exoskeleton systems, particularly those designed for pediatric and/or clinical populations that have inherently high uncertainty.
This paper presents a comprehensive approach for mitigating noise pollution from unmanned aerial vehicles (UAVs) in urban environment through path planning using reinforcement learning (RL). The study focuses on Turin, Italy, leveraging its diverse urban architecture to develop a comprehensive model. A detailed 3D occupancy grid map, based on OpenStreetMap data, was created to represent buildings’ locations and heights while a population density map was developed to account for demographic variances. The research develops a dynamic noise source model that adjusts noise emission levels based on UAV velocity, ensuring realistic noise impact predictions. Acoustic ray tracing techniques are utilised to simulate noise propagation, accounting for atmospheric absorption and reflections from urban structures, providing a detailed analysis of noise distribution. The core of this work is the application of the deep deterministic policy gradient (DDPG) algorithm within the RL framework. The algorithm is tailored to optimise flight paths by minimising noise impact while balancing other factors like path length and energy efficiency. The RL agent learns to navigate complex urban landscapes, integrating penalties for idling, excessive path length and abrupt manoeuvers to refine its path planning strategy. Simulation results with several maps unseen during training reveal that the RL-based approach effectively reduces noise impact in urban settings, making it a viable solution for better integrating UAVs into urban air mobility (UAM) systems. The methodology is scalable and adaptable, with potential applications in various urban environments globally. This research contributes to the development of sustainable drone operations in UAM context by addressing the critical issue of noise pollution, enhancing public acceptance and regulatory compliance.
Vibration is defined as oscillation away from equilibrium and is a significant problem in aviation. Vibration is transmitted to the flight crew through all contact surfaces, including flight controls, floor and seats. Various effects are known to occur on flight crew exposed to vibration, with fatigue and low back pain being the most common vibration-related health complaints. Studies have shown that prolonged exposure to vibration or accumulated vibration can increase the risk of chronic low back pain and injury by increasing the exposure dose. In particular, there is data that helicopter pilots have more low back pain than fixed wing pilots. This is due to the fact that helicopters have much more vibration-generating factors due to the working principle of helicopters and the posture of helicopter pilots is slightly forward-leaning. In this study, an isolator cushion with a quasi-zero stiffness mechanism was developed, manufactured and tested to reduce the transmission of vibration to the pilot and flight crew during the operation of the Sikorsky UH-60 helicopter. The use of the specially designed cushion led to a noticeable reduction in vibration exposure under various flight conditions.
In conventional hypersonic wind tunnels, tunnel noise is dominated by acoustic radiation from turbulent nozzle-wall boundary layers, which can directly influence the boundary-layer transition (BLT) over the model in the test section. To offer new insights into BLT in conventional ground facilities, direct numerical simulations (DNS) were performed to simulate the receptivity and transition processes of a Mach 8 boundary layer over a nearly sharp $7^\circ$ half-angle cone, with transition triggered by tunnel-like broadband free-stream acoustic disturbances radiated from the nozzle wall of the Sandia hypersonic wind tunnel at Mach 8 (Sandia HWT-8). The DNS captured all the stages of the transition to turbulence caused by tunnel noise, including the passage of broadband free-stream noise through the shock wave, the receptivity process leading to the generation of Mack’s second-mode waves, their nonlinear growth to saturation, the laminar breakdown to turbulence and the post-transitional, fully turbulent flow. The transition location predicted by DNS compared well with that of Pate’s theory and was also consistent with the locations of peak pressure fluctuations as measured in the Sandia HWT-8 facility. The computed skin friction and Stanton number distributions in the initial breakdown region showed an overshoot compared with the turbulent predictions by the van Driest II theory. The wall-pressure spectra in both the transitional and turbulent regions of the cone compared well with those measured in the Sandia HWT-8. The second-mode breakdown amplitude $A_{max}$ predicted by the DNS was also consistent with sharp-cone measurements from multiple conventional wind tunnels.
We present a proof-of-principle study of active beam-pointing control for the Zettawatt-Equivalent Ultrashort pulse laser System (ZEUS) using a piezo-actuated 16-inch mirror. To the best of our knowledge, this is the largest actively controlled mirror reported in a high-power laser system. A simple proportional feedback control was implemented based on a field-programmable gate array, which reduced the standard deviation of beam-pointing fluctuations by 91% to 0.075 μrad in the horizontal direction and by 78% to 0.25 μrad in the vertical direction. We also demonstrated the elimination of long-term pointing jitter caused by temperature drift using the same apparatus.
The influence of compressibility on shear flow turbulence is investigated within a self-preservation framework. This study focuses on the axisymmetric jet to examine compressibility effects in a slowly spatially evolving flow, unlike mixing layers, where the convective Mach number remains constant. Revisiting self-preservation, an a priori description of the compressible scaling for Reynolds stresses and higher-order velocity moments is developed. Turbulence moments are found to scale with powers of the spreading rate, suggesting Reynolds stress anisotropy results from compressibility effects consistent with self-preservation of the governing equations. Particle image velocimetry measurements for Mach 0.3 and perfectly expanded Mach 1.25 jets confirm the scaling predictions. The attenuation function, $\varPhi (M_c)$, describing the relationship between the convective Mach number, $M_c$, and the spreading rate, follows a similar trend in jets and mixing layers, where a higher $M_c$ results in reduced spreading rates. In the jet where $M_c$ decays, the relationship between the local $M_c$ and turbulence attenuation remains captured through $\varPhi (M_c)$, which scales proportionally with the spreading rate. A new scale is introduced, where the pressure in the mean momentum equation is substituted. The difference between the streamwise and radial-Reynolds-normal stresses was found to be a scale which is independent of Mach number and spreading rate. Further analysis of the Reynolds-stress-transport budget shows that internal redistribution of energy occurs within the Reynolds-normal stresses, and the role of pressure modification in turbulence attenuation supports previous observations. These findings confirm that the compressible axisymmetric jet exhibits self-preservation, with scaling extending into supersonic regimes.
Flame–flame interactions in continuous combustion systems can induce a range of nonlinear dynamical behaviours, particularly in the thermoacoustic context. This study examines the mutual coupling and synchronisation dynamics of two thermoacoustic oscillators in a model gas-turbine combustor operating within a stochastic environment and subjected to external sinusoidal forcing. Experimental observations from two flames in an annular combustor reveal the emergence of dissimilar limit cycles, indicating localised lock-in of thermoacoustic oscillators. To interpret these dynamics, we introduce a coupled stochastic oscillator model with sinusoidal forcing terms, which highlights the critical role of individual synchronisation in enabling local lock-in. Furthermore, through stochastic system identification using this phenomenological low-order model, we mathematically demonstrate that a transition towards self-sustained oscillations can be driven solely by enhanced mutual coupling under external forcing. This combined experimental and modelling effort offers a novel framework for characterising complex coupled flame dynamics in practical combustion systems.
This paper presents a detailed technical overview of the femtosecond precision timing and synchronization systems implemented at the Shanghai high repetition rate XFEL and extreme light facility (SHINE). These systems are designed to deliver stabilized optical references to multiple receiver clients, ensuring high-precision synchronization between the optical master oscillator (OMO) and optical/RF subsystems. The core components include an OMO, fiber length stabilizers and laser-to-laser synchronization modules that achieve femtosecond-level accuracy. Our discussion extends to the various subsystems that comprise the synchronization infrastructure, including the OMO, fiber length stabilizer and advanced phase detection techniques. Finally, we highlight ongoing research and development efforts aimed at enhancing the functionality and efficiency of these systems, thereby contributing to the advancement of X-ray free-electron laser technology and its applications in scientific research.
This study investigates the incorporation of advanced heating, ventilation, and air conditioning (HVAC) systems with reinforcement learning (RL) control to enhance energy efficiency in low-energy buildings amid the extreme seasonal temperatures of Tehran. We conducted comprehensive simulation assessments using the EnergyPlus and HoneybeeGym platforms to evaluate two distinct reinforcement learning models: traditional Q-learning (Model A) and deep reinforcement learning (DRL) with neural networks (Model B). Model B consisted of a deep convolutional network architecture with 256 neurons in each hidden layer, employing rectified linear units as activation functions and the Adam optimizer at a learning rate of 0.001. The results demonstrated that the RL-managed systems resulted in a statistically significant reduction in energy-use intensity of 25 percent (p < 0.001), decreasing from 250 to 200 kWh/m² annually in comparison to the baseline scenario. The thermal comfort showed notable improvements, with the expected mean vote adjusting to 0.25, which falls within the ASHRAE Standard 55 comfort range, and the percentage of anticipated dissatisfaction reduced to 10%. Model B (DRL) demonstrated a 50 percent improvement in prediction accuracy over Model A, with a mean absolute error of 0.579366 compared to 1.140008 and a root mean square error of 0.689770 versus 1.408069. This indicates enhanced adaptability to consistent daily trends and irregular periodicities, such as weather patterns. The proposed reinforcement learning method achieved energy savings of 10–15 percent compared to both rule-based and model predictive control and approximately 10 percent improvement over rule-based control, while employing fewer building features than existing state-of-the-art control systems.
A wall-modelled large eddy simulation approach is proposed in a discontinuous Galerkin (DG) setting, building on the slip-wall concept of Bae et al. (J. Fluid Mech., vol. 859, 2019, pp. 400–432) and the universal scaling relationship by Pradhan and Duraisamy (J. Fluid Mech., vol. 955, 2023, A6). The effect of the order of the DG approximation is introduced via the length scales in the formulation. The level of under-resolution is represented by a slip Reynolds number and the model attempts to incorporate the effects of the numerical discretization and the subgrid-scale model. The dynamic part of the new model is based on a modified form of the Germano identity -- performed on the universal scaling parameter -- and is coupled with the dynamic Smagorinsky model. A sharp modal cutoff filter is used as the test filter for the dynamic procedure, and the dynamic model can be easily integrated into any DG solver. Numerical experiments on channel flows show that grid independence of the statistics is achievable and predictions for the mean velocity and Reynolds stress profiles agree well with the direct numerical simulation, even with significant under-resolution. When applied to flows with separation and reattachment, the model also consistently predicts one-point statistics in the reverse flow and post-reattachment regions in good agreement with experiments. The performance of the model in accurately predicting equilibrium and separated flows using significantly under-resolved meshes can be attributed to several aspects that work synergistically: the optimal finite-element projection framework, the interplay of the scale separation and numerical discretization within the DG framework, and the consistent dynamic procedures for subgrid and wall modelling.
Despite their commonalities, the Arab Gulf States have started economic diversification from different settings and against different political backgrounds. This book applies a multi-method approach including Qualitative Comparative Analysis (QCA) to highlight their heterogeneous economic development trajectories and to compare them to other major oil exporters. From a political economy perspective, it demonstrates how neoclassical economic theory fails to grasp the underlying mechanisms of their development. The research design of this study is tailored to small and medium-sized samples with special characteristics. As such, it offers new opportunities for comparative studies not only of this region but also of other specific samples of countries from a wider perspective of heterodox economics.
Turbulence–chemistry interaction in a Mach-7 hypersonic boundary layer with significant production of radical species is characterised using direct numerical simulation. Overriding a non-catalytic surface maintained as isothermal at 3000 K, the boundary layer is subject to finite-rate chemical effects, comprising both dissociation/recombination processes as well as the production of nitric oxide as mediated by the Zel’dovich mechanism. With kinetic-energy dissipation giving rise to temperatures exceeding 5300 K, molecular oxygen is almost entirely depleted within the aerodynamic heating layer, producing significant densities of atomic oxygen and nitric oxide. Owing to the coupling between turbulence-induced thermodynamic fluctuations and the chemical-kinetic processes, the Reynolds-averaged production rates ultimately depart significantly from their mean-field approximations. To better characterise this turbulence–chemistry interaction, which arises primarily from the exchange reactions in the Zel’dovich mechanism, a decomposition for the mean distortion of finite-rate chemical processes with respect to thermodynamic fluctuations is presented. Both thermal and partial-density fluctuations, as well as the impact of their statistical co-moments, are shown to contribute significantly to the net chemical production rate of each species. Dissociation/recombination processes are confirmed to be primarily affected by temperature fluctuations alone, which yield an augmentation of the molecular dissociation rates and reduction of the recombination layer’s off-wall extent. While the effect of pressure perturbations proves largely negligible for the mean chemical production rates, fluctuations in the species mass fractions are shown to be the primary source of turbulence–chemistry interaction for the second Zel’dovich reaction, significantly modulating the production of all major species apart from molecular nitrogen.
We derive the scale-by-scale uncertainty energy budget equation and demonstrate theoretically and computationally the presence of a self-similar equilibrium cascade of decorrelation in an inertial range of scales during the time range of power-law growth of uncertainty in statistically stationary homogeneous turbulence. This cascade is predominantly inverse and driven by compressions of the reference field’s relative deformation tensor and their alignments with the uncertainty velocity field. Three other subdominant cascade mechanisms are also present, two of which are forward and also dominated by compressions and one of which, the weakest and the only nonlinear one of the four, is inverse. The uncertainty production and dissipation scalings which may follow from the self-similar equilibrium cascade of decorrelation lead to power-law growths of the uncertainty integral scale and the average uncertainty energy which are also investigated. Compressions are key not only to chaoticity, as previously shown, but also to stochasticity.
We study experimentally, numerically and theoretically the gravitational instability induced by dissolution of carbon dioxide with a forced lateral flow. The study is restricted to the model case of a vertical Hele-Shaw cell filled with water. While a transverse (horizontal) flow is continuously forced through the whole cell, the carbon dioxide is introduced above the liquid–gas interface so that a $\textrm {CO}_2$-enriched diffusive layer gradually forms on top of the liquid phase. The diffusive layer destabilises through a convective process which entrains the $\textrm {CO}_2$–water mixture towards the bottom of the cell. The concentration fields are measured quantitatively by means of a pH-sensitive dye (bromocresol green) that reveals a classic fingering pattern. We observe that the transverse background flow has a stabilising effect on the gravitational instability. At low velocity (i.e. for small thickness-based Péclet numbers), the behaviour of the system is hardly altered by the background flow. Beyond a threshold value of the Péclet number ($\textit{Pe} \sim 15$), the emergence of the fingering instability is delayed (i.e. the growth rate becomes smaller), while the most unstable wavelength is increased. These trends can be explained by the stabilising role of the Taylor–Aris dispersion in the horizontal direction and a model is proposed, based on previous works, which justifies the scalings observed in the limit of large Péclet number for the growth rate ($\sigma ^\star \sim \textit{Pe}^{-4}$) and the most unstable wavelength ($\lambda ^\star \sim \textit{Pe}^{\,5/2}$). The flux (rate mass transfer) of $\textrm {CO}_2$ in the nonlinear regime is also weakly decreased by the background transverse flow.
In the present study, we investigate the relation between temperature ($T^{\prime}$) and streamwise velocity ($u^{\prime}$) fluctuations by assessing the state-of-the-art Reynolds analogy models. These analyses are conducted on three levels: in the statistical sense, in spectral space and via the distribution characteristics of temperature fluctuations. It is observed that the model proposed by Huang et al. (HSRA) (1995 J. Fluid Mech.305, 185–218), is the only model that works well for both channel flows and turbulent boundary layers in the statistical sense. In spectral space, the intensities of $T^{\prime}$ at small scales are discovered to be larger than the predictions of these models, whereas those at scales corresponding to the energy-containing eddies and the large-scale motions are approximately equal to and smaller than the predictions of the HSRA, respectively. The success of the HSRA arises from this combined effect. In compressible turbulent boundary layers, the relationship between the intensities of positive temperature and negative velocity fluctuations is found to be well described by a model proposed by Gaviglio (1987 IntlJ. Heat Mass Transfer, 30, 911–926), whereas that between negative temperature and positive velocity fluctuations is accurately depicted by the HSRA. The streamwise length scale, rather than the spanwise length scale, is found to be more suitable for characterising the scale characteristics of the $u^{\prime}-T^{\prime}$ relation in spectral space. Combining these observations and a newly proposed modified generalised Reynolds analogy (Cheng & Fu 2024 J. Fluid Mech.999, A20), models regarding the relations in spectral space for both compressible channel flows and turbulent boundary layers are developed, and a strategy for generating more reliable temperature fluctuations as the inlet boundary condition for simulations of compressible boundary layers is also suggested.
The momentum dispersion model for flows in isotropic porous media has been validated and successfully applied by Rao & Jin (2022, J. Fluid Mech., vol. 937, A17). However, the anisotropic coupled models concerning heat–fluid–solid interactions in turbulent forced convection requires further development. This research proposes various anisotropic physical coefficient tensors to model the total drag ${R}_{i}$, interphase energy resistance $H$, momentum dispersion and thermal dispersion accounting for both anisotropic and isotropic scenarios. The effective physical coefficients of the Darcy–Forchheimer equation regarding ${R}_{i}$ are adapted to accommodate anisotropy. The heat transfer coefficient $h$ between the solid and fluid, despite being a scalar, is also required to depend on the local flow direction in anisotropic cases. Two scaling laws of $h$ with respect to a local Reynolds number ${\textit{Re}_{K}}$ are found: $h\sim \textit{Re}_K^2$ for the Darcy regime, and $h\sim \textit{Re}_{K}^{1/2}$ for the Forchheimer regime, with a transition at ${\textit{Re}_{K}}\sim 1$. The influence of momentum and thermal dispersions, along with the modelling errors of ${R}_{i}$ and $H$ originating from heterogeneity, are approximated using a second-order pseudo-stress tensor and a pseudo-flux vector, respectively. The effective viscosity and thermal diffusivity tensors are simplified into longitudinal and transverse components using tensor symmetries, and are assumed to rely mainly on another local Reynolds number ${\textit{Re}_{d}}$. Both components of the effective viscosity are positive in isotropic cases, whereas the longitudinal component may be negative in anisotropic cases, mainly serving as a compensation of overestimated drag. The coupled models are applied to simulate turbulent forced thermal convection in porous media with one or two length scales across a wide range of Reynolds numbers. The comparisons with direct numerical simulations results imply that the coupled macroscopic models can accurately predict not only statistically stationary distributions but also real-time changes in velocity and temperature.
Standing acoustic waves in a channel generate time-mean Eulerian flows. In homogeneous fluids, these streaming flows have been shown by Rayleigh to result from viscous attenuation of the waves in oscillatory boundary (i.e. Stokes) layers. However, the strength and structure of the mean flow significantly depart from the predictions of Rayleigh when inhomogeneities in fluid compressibility or density are present. This change in mean flow behaviour is of particular interest in thermal management, as streaming flows can be used to enhance cooling. In this work, we consider standing acoustic wave oscillations of an ideal gas in a differentially heated channel with hot- and cold-wall temperatures respectively set to $T_* + \Delta \varTheta _*$ and $T_*$. An asymptotic analysis for a normalised temperature differential $\Delta \varTheta _*/T_*$ comparable to the small acoustic Mach number is performed to capture the transition between the two documented regimes of Rayleigh streaming ($\Delta \varTheta _*\,{=}\,0$) and baroclinic streaming ($\Delta \varTheta _* =O(T_*)$). Our analytical solution accounts for existing experimental and numerical results and elucidates the separate contributions of viscous torques in Stokes layers and baroclinic forcing in the interior to driving the streaming flow. The analysis yields a scaling estimate for the temperature difference $\Delta \varTheta _{c_*}$ at which baroclinic driving is comparable to viscous forcing, signalling the smooth transition from Rayleigh to baroclinic acoustic streaming.
This practically-oriented, all-inclusive guide covers the essential concepts of power electronics through MATLAB® examples and simulations. In-depth explanation of important topics including digital control, power electronic applications, and electrical drives make it a valuable reference for readers. The experiments and applications based on MATLAB® models using fuzzy logic and neural networks are included for better understanding. Engrossing discussion of concepts such as diac, light-emitting diode, thyristors, power MOSFET and static induction transistor, offers an enlightening experience to readers. With numerous solved examples, exercises, review questions, and GATE questions, the undergraduate and graduate students of electrical and electronics engineering will find this text useful.
When a liquid film on a horizontal plate is driven in motion by a shear stress, surface waves are easily generated. This paper studies such flow at moderate Reynolds numbers, where the surface tension and inertial force are equally important. The governing equations for two-dimensional flows are derived using the long-wave approximation along with the integral boundary-layer theory. For small disturbances, the dispersion relation and neutral curves are determined by the linear stability analysis. For finite-amplitude perturbations, the numerical simulation suggests that the oscillations generated by the perturbation in a certain place continuously spread to the surrounding areas. When the effects of surface tension and gravity reach equilibrium, steady-state solutions will emerge, which include two cases: solitary waves and periodic waves. The former have heteroclinic trajectories between two stationary points, while the latter include five patterns at different parameters. In addition, there are also periodic waves that do not converge after a long period of time. During these evolution processes, strange attractors appear in the phase space. By examining the Poincaré section and the sensitivity to initial values, we demonstrate that these waves can be divided into two types: quasi-periodic and chaotic solutions. The specific type depends on parameters and initial conditions.