United States Air Force Research Laboratory

The services provided by ground handling companies at airports play an important role in ensuring that flight operations are carried out safely and securely on the airside of the airport and supporting airport authorities and airlines with services for passengers on the land side.These services have very effective role in reducing turnaround times of aircraft by ensuring uninterrupted and smooth operations, optimizing aircraft utilization, improving passenger experiences with effective and uninterrupted check-in, boarding and baggage procedures, and also play an active role in the attractiveness by the customers and determining sustainable strategies of the airlines for the future. At the same time, as the effective, efficient, and uninterrupted provision of ground handling services has an impact on the optimum capacity utilization of airport infrastructure elements, the performance of ground handling companies also makes significant contributions to airport infrastructure management. This study aims to develop a model to evaluate the performance of ground handling companies. For the model, MCDM approach was applied in performance evaluation. The model employs a hybrid model composed of Fuzzy Analytical Hierarchy Process (AHP) and Fuzzy TOPSIS Methods in the weighting of the criteria, and ranking of the companies successively. Model application was made at Antalya Airport.

Linear programming is a fundamental tool in a wide range of decision systems. However, without privacy protections, sharing the solution to a linear program may reveal information about the underlying data used to formulate it, which may be sensitive. Therefore, in this paper we introduce an approach for protecting sensitive data while formulating and solving a linear program. First, we prove that this method perturbs objectives and constraints in a way that makes them differentially private. Then, we show that (i) privatized problems always have solutions, and (ii) their solutions satisfy the constraints in their corresponding original, non-private problems. The latter result solves an open problem in the literature. Next, we analytically bound the expected sub-optimality of solutions that is induced by privacy. Numerical simulations show that, under a typical privacy setup, the solution produced by our method yields a 65% reduction in sub-optimality compared to the state of the art.

CdGeP 2 is a non-centrosymmetric uniaxial crystal whose birefringence is too low for phase-matching in its transparency range; however, it has been successfully applied in THz generation using near-IR laser pump sources. We present measurements of the linear thermal expansion of CdGeP 2 in the 12-820 K temperature range by X-ray diffraction using powdered samples. The results indicate strong anisotropy with negligible compression along the optical axis.

Understanding and controlling the dynamic interactions between fluid flows and solid materials and structures-a field known as fluid-structure interaction-is central not only to established disciplines such as aerospace and naval engineering, but also to emerging technologies such as energy harvesting, soft robotics, and biomedical devices. In recent years, the advent of metamaterials has provided exciting opportunities to rethink and redesign fluid-structure interactions. The idea of engineering the internal structure of materials that interface with fluid flows opens a new horizon for the precise and effective manipulation and control of coupled fluidic, acoustic, and elastodynamic responses. This review focuses on this relatively unexplored interdisciplinary theme with broad technological significance. Salient potential applications, such as reduction of fuel consumption in transport systems, efficiency of renewable energy extraction, noise mitigation, and resilience against structural fatigue, depend on controlling interactions among flow, acoustic, and vibration mechanisms. Flow control, for example, which spans a wealth of regimes such as laminar, transitional, turbulent, and unsteady separated flows, is strongly influenced by fluid-structure interaction. This review surveys and discusses conceptual frameworks that describe the interplay between fluids and elastic solids, with a focus on contemporary and emerging concepts. The paper is organised into three main sections: fluid-structure and flow-phonon interactions, flow-induced acoustic interactions with metamaterials, and exotic metamaterial concepts with potential impact on fluid-structure interaction. It concludes with perspectives on current challenges and future directions in this rapidly expanding area of research.

Controlling the absorption and emission of circularly polarized light (CPL) in free-standing polymer thin films is central to next-generation chiral photonic and optoelectronic technologies. Still, it remains hindered by limited optical activity, weak mechanical robustness, and poor scalability. Here, we present vitrimer-based chiral self-standing films (P*VFs), synthesized in situ with a fluorene-thiophene chiral polymer additive, that combine mechanical stability, reprocessability, self-repairing properties, and tunable chiroptical responses. The vitrimer matrix confines hierarchically ordered helical domains, enhancing circular dichroism (CD) while suppressing linear anisotropy, as confirmed by CD spectroscopy and Mueller matrix ellipsometry. These films exhibit reversible strain-dependent CD switching, with ellipticity decreasing under stretching (5% strain) and recovering upon stress release across multiple cycles. In parallel, the dynamic vitrimer network enables mechanochromic self-healing, restoring both optical functionality and mechanical integrity. These materials are not simple blends; even a ∼ 1 wt % chiral polymer dopant in a hard-soft polymer/vitrimer triples the CD response, surpassing that of the pure polymer and thereby boosting the macroscopic chiral properties. This synergy of chirality, vitrimer dynamics, and hierarchical self-assembly yields multifunctional films that outperform spin-coated chiral polymers, offering a versatile platform for adaptive optics, stress-sensing devices, reconfigurable photonics, and resilient coatings in extreme environments.

The focus of this study is to experimentally quantify the impact of gusts on the performance of a NACA-0012 airfoil and provide a load estimation strategy from modal decomposition coefficients. Experiments are performed in a water tunnel facility at chord-based Reynolds number $Re\approx4\times10^4$ for a range of angles of attack $-6^\circ\le\alpha\le12^\circ$. The gust generator functioned as a bluff body with a controlled shedding phase, producing a von K\'{a}rm\'{a}n vortex street. The generator was tested at two different locations; in the first configuration, the gust generator was positioned inline 1.5 chords upstream of the airfoil leading edge (referred to as the centered-gust case), and, in the second configuration, the gust generator was positioned upstream of the airfoil with a 0.5 chord transverse offset (referred to as the offset-gust case). Aerodynamic load experiments were performed for both configurations, $\alpha$ from $-6^\circ$ to $12^\circ$ with an increment of $1^\circ$. Synchronized load-cell and time-resolved PIV measurements were performed for selected $\alpha$ (i.e., $0^\circ$, $6^\circ$, and $12^\circ$) for both configurations. Proper Orthogonal Decomposition (POD) of the velocity field was used to extract coherent structures and identify dominant modes across different scenarios. Cross-correlation between the time-varying POD coefficients of the dominant modes and $c_l$, together with magnitude-squared coherence, was used to quantify the impact of the flow field on $c_l$. The centered-gust preserved a near-linear $c_l(\alpha)$ but reduced lift-curve slope and significantly increased variance; the offset-gust induced earlier deviation from a linear slope and higher drag values. Time-resolved PIV showed the rise/fall of $c_l$ associated with leading-edge upwash/downwash due to vortical structures convecting over the airfoil. The gust footprint is shown to be captured by a pair of POD modes; coherence between lift-curve and time-varying coefficient approached peak value at the gust frequency ($\sim$2.1~Hz) and the dominant mode led $c_l$ by $t^*\sim$0.12 and 0.18, with correlation peaks of 0.92 and 0.83, for centered and offset-gust configurations, respectively, at $\alpha = 12^\circ$. These findings showed a phase-accurate linkage between a coherent gust and lift response. This enabled the use of multi-time-delay Linear-Stochastic-Estimation to predict $c_l$ from the time-varying POD coefficient. The estimated $c_l$ values using this approach had a Root Mean Square Error (RMSE) of 0.135. The resulting low-order model description enables estimation of $c_l$ from select dominant modes.

Spacecraft operate under limited on-board resources resulting from size, weight and power (SWap) requirements. These on-board limitations include limited data processing capability. As spacecraft operations complexity grows so does the reliance in system to accurately provide the internal state of these systems from sensor data. Estimators used to reconstruct the internal state of a system rely in sensor data assimilation to produce accurate state reconstruction. We explore estimators for linear systems that reduce the amount of data they need to assimilate while keeping a desired level of performance in the reconstruction of the internal state of a system. As a measure of estimator performance, we employ the state covariance. We use the discrete algebraic Riccati equation to predict the steady state covariance of a Kalman Filter implementation of a linear system. To perform data assimilation reduction, we implement a measurement update decimation that depends on the desired level of estimator performance. To test this approach, we implement a Kalman Filter to an arbitrarily large linear system that implements the maximum allowable measurement update decimation while maintaining the estimator covariance within a maximum desired level.

This study demonstrates the application of an internal schlieren imaging technique to visualize flow and combustion phenomena within a rotating detonation engine (RDE). Leveraging a self-aligned, single-sided optical setup inspired by focusing schlieren methods, the system enables high-speed (100 kHz) imaging through sapphire windows in the combustor annulus. The technique provides full-field visualization of key processes including fuel-air mixing, ignition onset, and detonation wave propagation—all without requiring through-optical access. All three regimes of the RDE process are investigated: (1) cold flow fuel-air mixing, (2) the ignition process, and (3) quasi-steady detonation operation. The internal schlieren will be applied to the first process to demonstrate cold flow mixing conditions by assessing hydrogen jet penetration and asymmetries in air-fuel mixing. Next, the technique will be applied to combustor initiation to quantify induction length as a function of mass flow rate. Results show clear correlations between mass flow rate and induction length. Lastly, the quasi-steady detonation wave propagation is assessed by providing imaging of the detonation wave where qualitative dynamic detonation features such as wave tilt and some quantitative features such as wave thickness are demonstrated. This work establishes a robust internal schlieren methodology capable of capturing key stages of RDE operation. The technique provides an integrated diagnostic framework for assessing injector designs, ignition behavior, and detonation structure under varying operating conditions and fuels.

Robots operating in space are subject to lower mechanical loads than those on Earth due to the absence of gravity and atmospheric pressure. Reduced force allows for the use of lighter and larger link structures for robots, which, in turn, tend to be more flexible. Modeling and simulation of flexible structures incur high computational demands that are sometimes prohibitive to inform an autonomous control or decision-making algorithm in a timely manner. Therefore, efficient model order reduction (MOR) techniques that accelerate simulation and execution times while maintaining their fidelity to provide a suitable output are required. This paper introduces the energy-based MOR for Flexible In-Space (eMORFIS) Robotic Systems method. The proposed eMORFIS is based on Euler–Bernoulli beam theory and finite element discretization, seamlessly incorporates both internal and external forces while supporting revolute and prismatic joints. The resulting structural dynamics are projected into modal space, where MOR techniques generate reduced models that preserve essential dynamic behavior while enhancing computational performance. The eMORFIS methodology is demonstrated with one- and two-degree-of-freedom planar manipulators, and its extension to multi-link systems is straightforward. This proposed approach is validated in a simulation environment using flexible and rigid links in robotic systems. The results show a significant reduction in the model’s order, while maintaining millimetric differences in tip position and orientation between the full and reduced model