Browse Topic: Identification
This specification covers the requirements for a hard anodic coating on magnesium alloys.
This specification covers an aircraft-quality, low-alloy steel in the form of bars, forgings, mechanical tubing, and forging stock.
This specification covers a premium aircraft-quality, low-alloy steel in the form of bars, forgings, mechanical tubing, and forging stock.
This specification covers a carbon steel in the form of bars up through 3.000 inches (76.2 mm), forgings, and forging stock.
This specification covers a dilute aluminum/TiB2 metal matrix composite in the form of investment castings.
This specification covers bonded honeycomb core made of aluminum alloy and supplied in the form of blocks, slices, or other configurations as ordered.
This specification covers an aluminum alloy in the form of centrifugal castings.
This specification covers the requirements for producing a continuous white layer with controlled extent of porosity by means of a gaseous process, automatically controlled to maintain set values of the nitriding and carburizing potentials that determine properties of the nitrocarburized surface. Automatic control is intended to ensure repeatability of nitrogen and carbon content of the white layer which influences properties such as wear and corrosion resistance, ductility and fatigue strength.
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This paper deals with the uncertainty estimation of identified frequency and damping trends of whirl flutter modes, obtained by applying system identification methods on experimental data. In particular, two different identification approaches are considered, namely the free-decay analysis by using Matrix Pencil algorithm and the Data-Driven Stochastic Subspace Identification method (SSI), applied to system response to stochastic input. The two approaches lead to as many uncertainty estimation methodologies, both leveraging the bootstrapping statistical process. A full validation procedure is then set up to assess the accuracy of such methods in correctly quantifying the uncertainty of the estimated statistics. To do so, a wing-rotor state-space linear numerical model is used to simulate system response to both dwell and stochastic inputs. The state space numerical system aims to replicate the ATTILA wing-rotor wind-tunnel model, which falls in the framework of Clean Sky 2 European
This paper presents the experimental results of a bare-aircraft model identification of a small-medium sized helicopter. The experimental data were collected using two different approaches, i.e. with manual inputs in open-loop and with automatic inputs in closed-loop. This work demonstrates experimentally that, using a suitable algorithm, the two different experimental approaches converge on equivalent models. The proposed algorithm, i.e., a continuous-time variant of the Predictor Based Subspace Identification Algorithm (PBSID) algorithm, prove to deal properly with data acquired in closed-loop where the correlation between the inputs is very high.
Generalized Predictive Control (GPC) is an advanced form of an adaptive control algorithm that uses experimentally acquired data to determine the input-output relationship of complex systems through a process called system identification. GPC has historically been employed for stability augmentation and vibration reduction of dynamically-scaled tiltrotor aircraft wind-tunnel models since the complex nature of these dynamic systems does not lend itself well to traditional control approaches. The present research expands upon previous analytical and experimental work with wind-tunnel experiments that utilize improved GPC techniques. These techniques improved controller robustness such that a working controller was stable across a multitude of model configurations and wind-tunnel conditions and successfully suppressed vibration and vehicle flutter. Advanced GPC (AGPC) enables self-adaptation of a traditional GPC control law. AGPC was also investigated during the present research but was
This investigation reveals many DoD contractors do not treat integration as a stand-alone activity. Instead, integration is an inherent part of the development process. The contractors did not have a specific documented process for integration beyond calling out integration as an activity in the development process. Integration is an integrator unique step within the development process to meet functional and performance requirements. Identification of the interfaces and engineering to match the interfaces requires substantial individual expertise and heuristics for each integration effort resulting in inconsistent non-repeatable integrations. This increases risk, and limits third party integration effectiveness and utility. This paper identifies steps that can be taken to increase the speed and effectiveness of integration while decreasing the effort and dependency on individual expertise.
Dynamic rollovers represent a major hazard for helicopters during near-ground operations, often resulting in significant aircraft damage and passenger injuries. To improve safety in operations, recent studies have focused on developing a Helicopter Flight Data Monitoring framework to provide data-driven insights on operational safety. This work contributes to that effort by proposing an approach to identify precursors to dynamic rollovers. According to NTSB reports, approximately 60% of such incidents occur during in-flight phases like hover, hover-taxi, or landing. To capture the complex non-linear dynamics of helicopters, physics-based simulations were conducted to estimate a first hitting time metric, defined as the time until blade-ground contact, across a wide range of initial conditions for an inflight initial state of the helicopter. Eight parameters were identified as driving the first hitting time, and a probabilistic model was created to predict the distribution of that
Dynamic stall continues to be a limiting factor for rotorcraft performance in forward flight. The complex flow physics, resulting from blade kinematics, aeroelastic deformations, and blade-vortex interactions, makes this problem challenging. The availability of results from recent high-fidelity coupled computational aerodynamics-structural dynamics simulations provides an opportunity to gain new insights into the physics of dynamic stall on rotor blades in realistic operating conditions. Recent research efforts have also resulted in the identification of a leading-edge suction parameter (LESP), whose critical value has been shown to correlate with the flow events leading to dynamic stall. Critical LESP is largely independent of motion parameters, and is dependent mostly on the airfoil shape, Reynolds number, and Mach number. In this work, LESP variation along the blades of a UH-60A rotor in forward flight is extracted from high-fidelity computational results. The objective is to
The Human Readiness Level (HRL) scale was applied to a high criticality, disruptive, prototype laser-based aviation sensor to evaluate its readiness for human use. Applying HRL to the laser-based aviation sensor accelerated risk identification and provided enough lead time to influence design. Specifically, a protective sensor cover prototype was implemented to address key safety issues. This success demonstrated that the HRL scale is invaluable and should be applied to other technologies.
Aerodynamic interactions impact multirotor vehicle performance throughout its entire flight envelope and change with vehicle orientation, attitude, and forward flight speed. This paper presents efforts in incorporating these interaction effects into a reduced-order numerical quadrotor model informed by experimental flight test data. The interaction model employed system identification tools to compensate for discrepancies between actual rotor performance data and a Blade Element Theory (BET) based baseline model. Incorporation of the interaction model derived from system identification techniques improved the accuracy of model predicted rotor performance. The interaction model also provided insight into interaction effects predominantly influencing rotor performance for multiple flight conditions. The results demonstrate the utility of system identification techniques for accurate multirotor modeling capabilities.
The Autoclave processing is commonly used in manufacturing high-performance fibre-reinforced thermoset composite components in the aerospace industry. Variations in the cure cycle, sometimes even apparently minor deviations from the prescribed cure cycle, can harm the laminate properties. Given the costly and time-consuming autoclave manufacturing process, there is a strong need to cure the maximum number of parts in the shortest possible time without compromising quality. In order to achieve high-rate automated manufacturing with the optimized autoclave process, it is important to construct a digital twin modelling approach to mirror the physical composite curing process in the virtual domain based on the integration of high-fidelity multi-physics models. The resulting digital twin includes a thermal CFD model, a thermo-chemo-mechanical module, and an efficient and accurate block coupling between these two modules. The customized Abaqus driven by local and spatial variation of the
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