A Supervised Neural Network Control for Magnetorheological Damper in an Aircraft Landing Gear

This paper adopts an intelligent controller based on supervised neural network control for a magnetorheological (MR) damper in an aircraft landing gear. An MR damper is a device capable of adjusting the damping force by changing the magnetic field generated in electric coils. Applying an MR damper to the landing gears of an aircraft could minimize the impact at landing and increase the impact absorption efficiency. Various techniques proposed for controlling the MR damper in aircraft landing gears require information on the damper force or the mass of the aircraft to determine optimal parameters and control commands. This information is obtained by estimation with a model in a practical operating environment, and the accompanying inaccuracies cause performance degradation. Machine learning-based controllers have also been proposed to address model dependency but require a large number of drop test data. Unlike simulations, which can conduct a large number of virtual drop tests, the cost and time are limited in the actual experimental environment. Therefore, a neural network controller with supervised learning is proposed in this paper to simulate the behavior of a proven controller only with system states. The experimental data generated by applying the hybrid controller with the exact mass and force information, which has demonstrated high performance among the existing techniques, are set as the target for supervised learning. To verify the effectiveness of the proposed controller, drop test experiments using the intelligent controller and the hybrid controller with and without exact information about aircraft mass and force are executed. The experimental results from the drop tests of a landing gear show that the proposed controller maintains superior performance to the hybrid controller without using explicit damper models or any information on the aircraft mass or strut force.

Methodology for the Automated Visual Detection of Bird and Bat Collision Fatalities at Onshore Wind Turbines

The number of collision fatalities is one of the main quantification measures for research concerning wind power impacts on birds and bats. Despite being integral in ongoing investigations as well as regulatory approvals, the state-of-the-art method for the detection of fatalities remains a manual search by humans or dogs. This is expensive, time consuming and the efficiency varies greatly among different studies. Therefore, we developed a methodology for the automatic detection using visual/near-infrared cameras for daytime and thermal cameras for nighttime. The cameras can be installed in the nacelle of wind turbines and monitor the area below. The methodology is centered around software that analyzes the images in real time using pixel-wise and region-based methods. We found that the structural similarity is the most important measure for the decision about a detection. Phantom drop tests in the actual wind test field with the system installed on 75 m above the ground resulted in a sensitivity of 75.6% for the nighttime detection and 84.3% for the daylight detection. The night camera detected 2.47 false positives per hour using a time window designed for our phantom drop tests. However, in real applications this time window can be extended to eliminate false positives caused by nightly active animals. Excluding these from our data reduced the false positive rate to 0.05. The daylight camera detected 0.20 false positives per hour. Our proposed method has the advantages of being more consistent, more objective, less time consuming, and less expensive than manual search methods.

Experimental Validation for the Performance of MR Damper Aircraft Landing Gear

The landing gear of an aircraft serves to mitigate the vibration and impact forces transmitted from the ground to the fuselage. This paper addresses magneto-rheological (MR) damper landing gear, which provides high shock absorption efficiency and excellent stability in various landing conditions by adjusting the damping force using external magnetic field intensity. The performance and stability of an MR damper was verified through numerical simulations and drop tests that satisfied aviation regulations for aircraft landing gear. In this study, a prototype MR damper landing gear, a drop test jig, and a two-degree-of-freedom model were developed to verify the performance of the MR damper, with real-time control, for light aircraft landing gear. Two semi-active control algorithms, skyhook control and hybrid control, were applied to the MR damper landing gear. The drop tests were carried out under multiple conditions, and the results were compared with numerical simulations based on the mathematical model. It was experimentally verified that as the shock absorption efficiency increased, the landing gear’s cushioning performance significantly improved by 17.9% over the efficiency achieved with existing passive damping.

Drop tower tests of Taiji-1 inertial sensor substitute

Taiji-1, which is the first technical verification satellite of China’s Space Gravitational Wave Detection Program, was successfully launched on August 31, 2019. The mission aimed to investigate the key technologies used in space gravitational wave detection. The inertial sensor, which was one of the main payloads, measured the residual acceleration of the satellite, and verified the drag-free control technology. Its performance was crucial to the success of the Taiji-1 mission. To ensure its performance in orbit, the inertial sensor was fully evaluated prior to launch. Owing to the gravitational acceleration on the ground, it is impossible to verify all the properties of the inertial sensor in a routine laboratory. A feasible method to conduct such tests is to use a drop tower. To guarantee the safety of the inertial sensor, a substitute was used with similar structure and circuit design. A total of 20 falls in three groups were completed, a set of research methods was established, and the importance of conducting simulations before the drop tests was verified. For the first time, the switch of different circuit gains in a drop tower test has been achieved and the National Microgravity Laboratory of China (NMLC) drop tower’s residual accelerations in three dimensions were measured. The results demonstrated that the microgravity level of the drop tower can reach about 58 μg0 in the fall direction and 13 μg0 along the horizontal axes.

A Parametric Analysis of Embedded Tissue Marker Properties and Their Effect on the Accuracy of Displacement Measurements

Datasets obtained from cadaveric experimentation are broadly used in validating finite element models of head injury. Due to the complexity of such measurements in soft tissues, experimentalists have relied on tissue-embedded radiographic or sonomicrometry tracking markers to resolve tissue motion caused by impulsive loads. Dynamic coupling of markers with the surrounding tissue has been a previous concern, yet a thorough sensitivity investigation of marker influences on tissue deformation has not been broadly discussed. Technological improvements to measurement precision have bolstered confidence in acquired data, however precision is often conflated with accuracy; the inclusion of markers in the tissue may alter its natural response, resulting in a loss of accuracy associated with an altered displacement field. To gain an understanding of how marker properties may influence the measured response to impact, we prepared a set of nine marker designs using a Taguchi L9 array to investigate marker design choice sensitivity. Each of these designs was cast into a block of tissue simulant and subjected to repeated drop tests. Vertical displacement was measured and compared to the response of the neat material, which contained massless tracking markers. Medium density and medium stiffness markers yielded the least deviation from the neat material response. The results provide some design guidelines indicating the importance of maintaining marker matrix density ratio below 1.75 and marker stiffness below 1.0 MPa. These properties may minimize marker interference in tissue deformation. Overall, embedded marker properties must be considered when measuring the dynamic response of tissue.

Numerical Model Study of Prototype Drop Tests on Cube and Cubipod® Concrete Armor Units Using the Combined Finite–Discrete Element Method

This paper aims to evaluate the structural strength of unreinforced concrete armor units (CAU), named Cubipod®, used on rubble-mound breakwaters and coastal structures, through a numerical methodology using the combined finite–discrete element method (FDEM). A numerical modeling methodology is developed to reproduce the results of an experimental examination published by Medina et al. (2011) of a free-fall drop test performed on a 15 t conventional Cubic block and a 16 t Cubipod® unit. The field results of the Cube drop tests were used to calibrate the model. The numerically simulated response to the Cubipod® test is then discussed in the context of a validation study. The calibration process and validation study provide insights into the sensitivity of breakage to tensile strength and collision angle, as well as a better understanding of the crushing and cracking damage of this unit under drop test impact conditions.

Development of Removable Visual Impact Indicator or Polymer Composite Materials

The prototype of removable visual impact indicator for thermoset polymer composite materials is developed, and its characteristics are experimentally determined. The indicator is a fabric tape glued by epoxy to the surface of the polymer composite. The tape is impregnated with a composition that provides a visual response at the place of an impact on the composite surface. Ball-drop tests demonstrated the increase of the magnitude of the visual response with the impact energy at different substrate hardnesses. The shelf-life and mode of the tape storage until commissioning are determined. Peel tests showed the ability to remove a used indicator without damaging the surface of the composite.