Richard Beblo

Aerodynamic Parameter Prediction on a Airfoil with Flap via Artificial Hair Sensors and Feedforward Neural Network

Gust alleviation and flutter suppression are essential elements of an effective fly-by-feel system. Knowledge of real-time forces and moments can have huge effect on designing an effective controller for flutter suppression and gust rejection. One unique method of predicting forces and moments is to use distributed arrays of artificial hair sensors that are capable of sensing the environment and therefore capturing important flow features. In this paper, the local flow measurement from the artificial hair sensor is used with feed-forward neural network to predict the aerodynamic parameters (angle of attack, freestream velocity, lifte coefficient and moment coefficient per unit span, and flap angle) on an airfoil containing control surface. These aerodynamic parameters can be combined with the airfoil’s physical parameters to predict the real time lift and moment. Also, the effect of artificial hair sensor integration location on prediction of aerodynamic parameters is studied.

Aerodynamic Characteristics Prediction via Artificial Hair Sensor and Feedforward Neural Network

Fly by feel is a concept in which distributed sensors and actuators are integrated on an aerial system for state awareness or sensation of the environment, and make use of distributed control to increase the system maneuverability, stability and safety. Artificial hair sensors are good candidates as sensors for the fly by feel concept because they are lightweight, have low manufacturing costs and can easily be integrated on the surface of air-vehicle without affecting the flow. We investigate an application of artificial hair sensors considering its capability of measuring the local flow velocity combined with a Feedforward Artificial Neural Network to predict the aerodynamic quantities such as lift coefficient, moment coefficient, angle of attack and free-stream velocity in real-time. These quantities, when combined with the physical and unsteady aerodynamics parameters, will make a framework for designing and implementing an active controller for gust alleviation in a pitch and plunge airfoil system.Copyright

Thermal Properties of Magnetite Nanoparticle and Carbon Fiber Doped Epoxy Shape Memory Polymer

Presented are the results of an experimental investigation into the effects of particle and carbon fiber (CF) doping in epoxy shape memory polymer (SMP). Motivation for the work originates from the need to increase the thermal performance, and thus decrease the time required to transition the polymer given a finite amount of thermal energy, of a SMP link in a bi-stable linkage. Such a multi-functional link is responsible for structural support, mechanism reconfigurability, as well as system damping. Thus any improvement in thermal properties must be weighed against increases in brittleness and weight as well as altered mechanical properties as a result of the chosen method. Two part epoxy SMP by CRG Industries is doped with Fe3 O4 (magnetite) nanoparticles (20–30nm spheres) at a weight fraction of 10% as well as 3mm and 10mm carbon fibers at a weight fraction of 5.4%; resulting in all dopants having a volume fraction of approximately 2.5%. The thermal conductivity, specific heat, and diffusivity are experimentally measured by a Hot Disk Thermal Constants Analyser from ambient through transition and the results compared with several thermal composite models. Changes in the thermal properties of the composites and neat polymers with respect to temperature are presented and the effects these changes have on the predictions of thermal models discussed, specifically the effect of changes in thermal properties near the transition temperature and the resulting change in predicted energy required for transition. The effects of adhesion between the particles and the matrix and particle dispersion on conductive paths and material thermal properties are also discussed.Copyright

Design, modeling, and optimization of a thermally activated reconfigurable wing system

Reconfigurable structures such as morphing aircraft generally require an on-board energy source to function. At high speeds, however, frictional heating generated at the nose of a morphing aircraft can provide a large amount of thermal energy during a short period of time. This thermal energy can be collected, transferred, and utilized to reconfigure the aircraft. Direct utilization of thermal energy has the ability to significantly decrease or eliminate the losses associated with converting thermal energy to other forms, such as electric. The following work describes possible system designs and components that can be utilized to transfer the thermal energy harvested at the nose of the aircraft to internal components for direct thermal actuation of a reconfigurable wing structure. Previously reported topology optimized heat collectors, vehicle trajectories, and the deployment mechanism are combined with the presented analytical model of a heat pipe for a system level model used to optimize the system based on weight and the desired wing deployment time.

System Design and Modeling of a Thermally Activated Reconfigurable Wing

Abstract : Reconfigurable structures such as morphing aircraft generally require an on board energy source to function. Frictional heating during the high speed deployment of a blunt nosed low speed reconnaissance air vehicle can provide a large amount of thermal energy during a short period of time. This thermal energy can be collected, transferred, and utilized to reconfigure the deployable aircraft. Direct utilization of thermal energy has the ability to significantly decrease or eliminate the losses associated with converting thermal energy to other forms, such as electric. The following work attempts to describe possible system designs and components that can be utilized to transfer the thermal energy harvested at the nose of the aircraft during deployment to internal components for direct thermal actuation of a reconfigurable wing structure. A model of a loop heat pipe is presented and used to predict the time-dependant transfer of energy. Previously reported thermal profiles of the nose of the aircraft, calculated based on trajectory and mechanical analysis of the actuation mechanism, are reviewed and combined with the model of the thermal transport system providing a system level feasibility investigation and design tool. The efficiency, implementation, benefits, and limitations of the direct use thermal system are discussed and compared with currently utilized systems.

Gust prediction via artificial hair sensor array and neural network

Gust Load Alleviation (GLA) is an important aspect of flight dynamics and control that reduces structural loadings and enhances ride quality. In conventional GLA systems, the structural response to aerodynamic excitation informs the control scheme. A phase lag, imposed by inertia, between the excitation and the measurement inherently limits the effectiveness of these systems. Hence, direct measurement of the aerodynamic loading can eliminate this lag, providing valuable information for effective GLA system design. Distributed arrays of Artificial Hair Sensors (AHS) are ideal for surface flow measurements that can be used to predict other necessary parameters such as aerodynamic forces, moments, and turbulence. In previous work, the spatially distributed surface flow velocities obtained from an array of artificial hair sensors using a Single-State (or feedforward) Neural Network were found to be effective in estimating the steady aerodynamic parameters such as air speed, angle of attack, lift and moment coefficient. This paper extends the investigation of the same configuration to unsteady force and moment estimation, which is important for active GLA control design. Implementing a Recurrent Neural Network that includes previous-timestep sensor information, the hair sensor array is shown to be capable of capturing gust disturbances with a wide range of periods, reducing predictive error in lift and moment by 68% and 52% respectively. The L2 norms of the first layer of the weight matrices were compared showing a 23% emphasis on prior versus current information. The Recurrent architecture also improves robustness, exhibiting only a 30% increase in predictive error when undertrained as compared to a 170% increase by the Single-State NN. This diverse, localized information can thus be directly implemented into a control scheme that alleviates the gusts without waiting for a structural response or requiring user-intensive sensor calibration.

Aligning nickel particles for joule heating in epoxy shape memory polymer using a magnetic field and linear vibration

One of the major remaining barriers to the widespread adoption of thermally activated shape memory polymer is the method used to heat them. Presented is an investigation into using 5 μm nickel particles aligned into chains as embedded joule heaters for epoxy shape memory polymer. The high density of particle chain heaters reduces the time and energy required to reach transition by minimizing excess heat required due to the low thermal conductivity of the polymer by heating the material more uniformly. The chains are formed by curing the polymer in a uniform magnetic field generated by two sets of N42SH neodymium magnets above and below the sample approximately 57 mm apart. Modeling of the induced magnetic field within and between particles during curing and an analytical model predicting particle mobility in a fluid with respect to vibration frequency and amplitude are presented and discussed in context to this work. Since epoxy resin has a high viscosity, particle mobility is encouraged by sonicating the sample at 300 Hz at an amplitude of approximately 50 μm prior to polymerization using an industrial shaker and Teflon guides. Copper mesh electrodes are attached to the resulting samples using 10% by volume nickel particle shape memory polymer epoxy. Significant particle alignment is confirmed via optical microscope images. Electrical resistivity is measured as low as 57 Ω mm at nickel volume concentrations of 1.0%. Infrared images of the samples during heating are presented, and electrical energy required with respect to sample thermal capacity is estimated.

Shape memory polymer filled honeycomb model and experimental validation

An analytical model predicting the in-plane Youngs and shear moduli of a shape memory polymer filled honeycomb composite is presented. By modeling the composite as a series of rigidly attached beams, the mechanical advantage of the load distributed on each beam by the infill is accounted for. The model is compared to currently available analytical models as well as experimental data. The model correlates extremely well with experimental data for empty honeycomb and when the polymer is above its glass transition temperature. Below the glass transition temperature, rule of mixtures is shown to be more accurate as bending is no longer the dominant mode of deformation. The model is also derived for directions other than the typical x and y allowing interpolation of the stiffness of the composite in any direction.

Design of a Morphing Skin by Optimizing a Honeycomb Structure With a Two-Phase Material Infill

For morphing wing skin applications, low in-plane stiffness is advantageous to reduce the cost of actuation and high out-of-plane stiffness is required to withstand the aerodynamic loads. A proposed solution is to engineer a composite material made of a honeycomb support combined with a multi-state infill that can reduce the Young’s modulus for a low in-plane stiffness. Assuming thin beam theory and using the potential energy formulation, equivalent in-plane Young’s moduli can be calculated for a range of honeycomb cell geometries. The out-of-plane deflection of a representative plate fixed on all edges is calculated using flat plate theory and used to assess the performance of the skin system. To optimize the cell geometry for a given application, the out-of-plane deflection is constrained and the honeycomb cell geometry varied to investigate the design space. Results show that a skin can be designed to have in-plane Young’s moduli similar to the polymer infill and still have a low out-of-plane deflection. However, these results come at the expense of increased skin weight. Further analysis to obtain a more realistic design is done by imposing weight and geometric constraints.Copyright