U.S. Air Force Research Laboratory Aerospace Systems Directorate

An all-diode-pumped, multistage Nd:YAG amplifier is investigated as a means of extending the duration of high-power, burst-mode laser pulse sequences to an unprecedented 30 ms or more. The laser generates 120 mJ per pulse at 1064.3 nm with a repetition rate of 10 kHz, which is sufficient for a wide range of planar laser diagnostics based on fluorescence, Raman scattering, and Rayleigh scattering, among others. The utility of the technique is evaluated for image sequences of formaldehyde fluorescence in a lifted methane-air diffusion flame. The advantages and limitations of diode pumping are discussed, along with long-pulse diode-bar performance characteristics to guide future designs.

jet to capture the spatiotemporal evolution of the temperature field.

Hybrid femtosecond/picosecond coherent anti‐Stokes Raman scattering (fs/ps CARS) of N 2 has recently been demonstrated for gas‐phase thermometry in reacting flows, enabling frequency‐domain detection at high repetition rates with excellent chemical specificity and independence from the effects of collisions and nonresonant background. In this work, we overcome the limited sensitivity of vibrational fs/ps CARS thermometry of N 2 below 1200 K by spectrally resolving J ‐dependent rovibrational coherence revivals that occur 32 ps after initial excitation. The N 2 rovibrational coherence is excited using broadband, 100‐fs pump and Stokes pulses and probed as a function of time using a narrowband, 5.8‐ps probe pulse (bandwidth of 2.5 cm −1 ). The rovibrational features exhibit sufficient temperature sensitivity below 1200 K for accurate thermometry using a simple, time‐dependent phenomenological model. Specifically, three distinct spectral features at a single probe delay of 32.5 ps are analyzed, corresponding to rovibrational revivals with mean rotational quantum numbers of < J > = 3.5, 14, and 28. Good agreement is found between simulated and measured fs/ps CARS spectra in an adiabatic flat‐flame burner from 298 to 2400 K. Copyright © 2015 John Wiley & Sons, Ltd.

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Recent interest in fly-by-feel approaches for aircraft control has motivated the development of novel sensors for use in aerial systems. Artificial hair sensors (AHSs) are one type of device that promise to fill a unique niche in the sensory suite for aerial systems. In this work, we investigate the capability of an AHS based on structural glass fibers to directly identify flow stagnation and separation points on a cylindrical domain in a steady flow. The glass fibers are functionalized with a radially aligned carbon nanotube (CNT) forest and elicit a piezoresistive response as the CNT forest impinges on electrodes in a micropore when the hair is deflected due to viscous drag forces. Particle image velocimetry is used to measure the flow field allowing for the resulting moment and force acting on the hair to be correlated with the electrical response. It is demonstrated that the AHS provides estimates for the locations of both the stagnation and separation in steady flow. From this, a simulation of a heading estimation is presented to demonstrate a potential application for hair sensors. These results motivate the construction of large arrays of hair sensors for imaging and resolving flow structures in real time.

In the design and implementation of networked multiagent systems, it is essential not only to guarantee closed-loop system stability but also to schedule interagent information exchange in order to prevent potential network overload and decrease wireless communication costs. For stably scheduling information exchange in networked multiagent systems, the contribution of this article is threefold. We first present a new event-triggered distributed control architecture predicated on a dynamic threshold, which involves an error signal between the state of an agent and the state of its reference model as well as an exponentially decaying term, to schedule interagent information exchange. Building upon the first contribution and in contrast to the standard sampled data exchange viewpoint when an event occurs, second, we propose a method entitled solution-predictor curve. In particular, this method approximates the solution trajectory related to information exchange, where every agent stores this curve and distributively exchanges its parameters when an event occurs. Its key feature is that each agent utilizes the resulting solution trajectory over the time interval until the next event occurs, where it has the capability to further reduce interagent information exchange compared with the sampled data case. A system-theoretical stability analysis of the proposed event-triggered distributed control architecture is given, which captures both sampled data and solution-predictor curve cases, and practical guidelines on the selection of parameter tuning parameters are also stated. As the third contribution, we demonstrate the efficacy of our theoretical results in laboratory-level experiments.

Abstract The repeatability of an additive manufacturing (AM) process that fabricates a unique specimen with inherent damping capability is explored. A laser powder bed fusion (LPBF) technique is used to additively manufacture nickel alloy components with the same geometry/dimensions. Key aspects to the manufacturing process such as scan strategy and build orientation are observed alongside damping performance. The results from forced-response testing show repeatable correlation between damping performance and modal response information. Furthermore, despite different scan strategies and build sequences, the results demonstrate that inherent damping repeatability is driven by the unique component geometry and has minimal sensitivity to manufacturing.

This paper studies distributed adaptive architectures for controlling uncertain multiagent systems with unmeasurable coupled dynamics. Specifically, we first analyze a standard distributed adaptive control method with system uncertainties and coupled dynamics in a leader-follower setting, where we present local stability conditions. We second propose an additional feedback term within the control signal of each agent in order to relax the aforementioned local stability conditions. An illustrative numerical example is then given in order to demonstrate our contributions.

Distributed adaptive control is a powerful framework to preserve stability of networked multiagent systems in the presence of uncertainties resulting from, for example, modeling errors, unknown control effectiveness, and perturbed information exchange. However, considering multiagent systems that consist of agents with heterogeneous actuator capabilities, implementation of distributed adaptive control approaches is not a trivial task. This is due to the fact that each agent in this case cannot identically execute given local control laws and this can lead to a poor networked multiagent system performance or even overall instability. To make the first attempt to this challenging problem, we consider a class of uncertain networked multiagent systems with single integrator dynamics in the context of a leader-follower problem and propose a novel distributed adaptive control design procedure for guaranteeing overall stability in the presence of agents having different actuator bandwidths. Specifically, a distributed adaptive control architecture is implemented for agent uncertainties and a hedging method, which modifies ideal reference models of each agent, is utilized to allow for correct adaptation that does not get affected due to the presence of actuator bandwidths. We then analyze the stability of the networked multiagent system and compute the actuator bandwidth limits of each agent using tools from Lyapunov stability and linear matrix inequalities.

Coherent anti‐Stokes Raman scattering (CARS)‐spectroscopy‐based thermometry techniques developed for laboratory flames face a stiff challenge when implemented in practical combustion environments such as engine test facilities. In addition to limited optical access, the harsh environments associated with these test facilities (i.e. uncontrolled humidity, vibration, and large thermal gradients) often restrict the operation of sensitive laser systems. To circumvent this problem, we have developed a fiber‐based, picosecond (ps) CARS system employing long‐length (up to 6 m), multimode silica fibers that permits the laser system to be isolated from the high heat and vibration of the test hardware. Proof‐of‐principle, single‐laser‐shot temperature measurements using a 3‐m‐long fiber system are demonstrated in atmospheric pressure, near‐adiabatic, laboratory H 2 –air flames. Limitations that are imposed by long‐length multimode‐fiber beam delivery for CARS thermometry are identified as nonlinear effects during beam propagation along the fiber, depolarization of the laser beam, and degradation of the beam quality at the output of the fiber. These effects are investigated in detail, and potential improvements are suggested. The current study shows promise for implementation of fiber‐based ps‐CARS spectroscopy in harsh environments such as those encountered in combustors and afterburners in practical gas‐turbine‐engine test facilities. Copyright © 2013 John Wiley & Sons, Ltd.

Abstract Two new trifunctional alkene monomers based on the highly modular perfluoropyridine scaffold are synthesized with an aliphatic and an aromatic moiety, 4‐penten‐1‐ol and eugenol, respectively. The monomers are the basis for thiol‐ene thermoset materials, formulated against a difunctional or trifunctional thiol. Systems based on these novel monomers have a wide range of thermal properties, with glass transition temperatures ( T g s) spanning from −42 to 21 °C. Mixed systems obey the Fox equation, and T g s of the mixtures can be tuned to specific values in that range. Thermal degradation temperatures follow a similar trend, with decomposition temperatures ranging from 274 to 348 °C in nitrogen with varying compositions having tailorability therein. This new class of semifluorinated thermoset materials with tunable thermal properties has several potential applications within the aerospace industry, such as sealants and coatings, where stability and survivability at high temperatures in harsh environmental conditions are imperative.

ABSTRACT We report the thermal, mechanical, and diffusion properties of bisphenol E based polycyanurate nanocomposites with three forms of graphene derived from sequential processing of the same carbon nanostructure. Edge‐functionalized graphene nanoplatelets (GNP) were converted to graphene oxide (GO), then heated to produce thermally reduced graphene oxide (TRGO). All three reinforcements were individually mixed with the dicyanate ester of bisphenol E (LECy) at low loading levels and cured to form polycyanurate nanocomposites. GNP, with very low oxygen functionality, was incompatible with the cyanate ester, while the highly oxidized GO formed well‐dispersed (though not exfoliated) nanocomposites, with the TRGO forming a good dispersion on mixing but phase separating during cure. The addition of GO, and, to a lesser extent, TRGO, resulted in improved mechanical properties, particularly fracture toughness, with the addition of TRGO having a modestly negative effect on the glass transition temperature. Surprisingly, neither GO nor TRGO addition was effective at slowing down the diffusion of water in the polycyanurate, with the addition of both resulting in increased equilibrium moisture uptake. It thus appears that the trade‐off between dispersion and the required level of oxygen functionality acts in a manner to frustrate attempts at minimizing the permeation of water by addition of graphene‐based reinforcements. © 2014 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2014 , 52 , 1061–1070

View Video Presentation: https://doi.org/10.2514/6.2023-4253.vid Simultaneous density-fluctuation measurements were made using a linear array focused laser differential interferometer (LA-FLDI) over a 7-deg sharp cone in Mach-6 flow. Second-mode fluctuations were measured and showed to vary in amplitude with height above the surface and a Reynolds number sweep captured transition onset. As Reynolds number increased, the peak fluctuation height decreased due to the thinning of the boundary layer. The computed density eigenfunction was compared to the integrated FLDI measurements for one case. FLDI measurements were also compared to surface pressure fluctuation measurements made by a PCB sensor at the same axial position with excellent agreement. In particular, the second-mode peak frequency agreed within 10% between the two measurement techniques, and the second-mode amplitude peaked at the same freestream Reynolds for the most amplified FLDI height.

Abstract A new class of power generation devices that experiences increased losses due to bulk flow separation in segments of their expected in-flight regime is emerging. As such, active flow control becomes increasingly relevant to mitigate these losses and reclaim the entire flight envelope. This study explores the effect of flow injection on transonic flows experiencing bulk separation. Reynolds-averaged Navier–Stokes simulations of a 3D wall-mounted hump at low Reynolds numbers are conducted to assess the response of transonic bulk separation to flow injection. Unsteady simulations are performed to understand the differences between slot and discrete port injection and determine optimum forcing frequencies. Discrete ports require higher pressures to overcome the momentum deficit associated with the smaller injection area relative to the width of the domain. Steady and unsteady injections are found viable strategies for mitigating the extent (or appearance) of bulk separation. Experiments are conducted with discrete injection for a range of Mach and Reynolds numbers. The response of the bulk separation to said injection is evaluated by analyzing both local pressure measurements and schlieren imaging. The study shows that the required pressure of injection is strongly correlated to the length scale of the uncontrolled separation. With large-eddy simulations, the flow separation and frequency content within the separated region can be reasonably predicted. This study aims to take further steps to establish guidelines for applying flow control to the emerging class of power generation devices experiencing losses from bulk separation.

In the previous work, a distributed adaptive control method was considered for uncertain multiagent systems with unmeasurable coupled dynamics, where overall closed-loop stability was established when local stability conditions for each agent were held. However, it was shown that these conditions could yield high-gain parameters in the resulting control signals, where this is not desired in practice. The contribution of this paper is a new distributed adaptive control architecture predicated on adaptive robustifying terms to remove the aforementioned high-gain requirement. An illustrative numerical example is included to demonstrate our theoretical contribution.

In this paper, we propose a model reference adaptive control approach for uncertain dynamical systems in the presence of both actuator dynamics and actuator amplitude saturation limits. Specifically, we use a new expanded reference model including a deficit term between the ideal control signal and its saturated version. Closed-loop system stability of the proposed approach utilizing this expanded reference model is analyzed using linear matrix inequalities (LMIs) and Lyapunov theory, where the resulting stability conditions capture the interplay between the allowable actuator dynamics, actuator amplitude saturation limits, initial conditions, and the system uncertainties. An illustrative numerical example is further provided to demonstrate the efficacy of the proposed approach.

For reducing information exchange in distributed control of multiagent systems, we propose a norm-free and adaptive event-triggering rule, which is decentralized and predicated on the solution-predictor curve method. Here, the decentralized feature implies that the proposed event-triggering rule depends on own error signals of an agent. Moreover, the norm-free feature implies that the left side of the proposed event-triggering rule inequality does not depend on distances such as absolute values of error signals to yield better agent-to-agent information exchange reduction. To achieve decentralized and norm-free features at the same time, an adaptive term is also utilized in the event-triggering rule for each agent in order to estimate unknown variable unavailable to an agent. The proposed event-triggering rule works both for the sampled data exchange case as well as for the data exchange case predicated on the solution-predictor curve method. In contrast to standard sampled data exchange, the solution-predictor curve method has the ability to further reduce agent-to-agent information exchange, where each agent stores this curve and exchanges its parameters when an event occurs in a distributed manner for approximating the solution trajectory of each agent.

In this paper, we propose a new event-triggering approach to schedule control data transmissions in state feedback control of linear time-invariant dynamical systems. Specifically, an energy function-based and norm-free event-triggering condition is presented, where the embedded processor broadcasts a sampled data of its control signal value through a zero-order-hold operator to the dynamical system when the left side of the event-triggering condition equals to its right side. Here, the energy function-based feature implies that the right side of this event-triggering condition involves an energy function as well as its time-derivative for making the selection of its right side user-adjustable. Moreover, the norm-free feature implies that the left side of this event-triggering condition does not depend on signal norms to yield better control data transmission reduction. We also present illustrative numerical examples in order to demonstrate the efficacy of the proposed event-triggering approach in scheduling state feedback control data transmissions.

Summary While adaptive control methods have the capability to suppress the effect of system uncertainties without excessive reliance on dynamical system models, their stability can be adversely affected in the presence of coupled dynamics. Motivated by this standpoint, the contribution of this article is a decoupling approach for model reference adaptive control algorithms. The key feature of the proposed framework is that it guarantees asymptotic convergence between the trajectories of an uncertain dynamical system and a given reference model without relying on any measurements from the coupled dynamics under a tight sufficient stability condition. We also provide a generalization to address the uncertainty in the control effectiveness matrix, where the resulting sufficient stability condition in this case relies on linear matrix inequalities. Finally, numerical examples are provided to illustrate the efficacy of the presented theoretical results.

View Video Presentation: https://doi.org/10.2514/6.2023-0946.vid The evolution of a Mach 1.92 turbulent boundary layer downstream of a compliant panel undergoing post-flutter oscillations is examined using particle image velocimetry (PIV) and Reynolds-Averaged Navier-Stokes (RANS) modeling. Five data sets are investigated, including two large-amplitude deformation cases, two baseline rigid (flat) test articles, and a fifth case during panel failure at the trailing edge. The RANS simulations include only the mean panel deformation, whereas PIV was collected during the dynamic post-flutter oscillations. The two flutter cases without local failure consist of a dynamically active panel response with snap-through events, and a large-amplitude deformation consistent with a thermally buckled panel. Both PIV and RANS capture the same general trends for the mean-velocity response of the intact panel, including a locally reduced wall shear stress for the large-amplitude flutter case. Analysis of the turbulence stresses suggests a more complex response, with near-wall behavior possibly attributable to curvature-induced pressure gradient effects. For the case of panel failure, the PIV results reveal a more pronounced boundary layer response due to the formation of a surface discontinuity, with perturbations to the mean velocity and turbulence statistics persisting approximately two boundary layer thicknesses downstream.