A Comparison of the Neal-Smith and ω\u3csub\u3esp\u3c/sub\u3eΤ\u3csub\u3eθ2\u3c/sub\u3e, ς\u3csub\u3esp\u3c/sub\u3e, τ\u3csub\u3eθ\u3c/sub\u3e Flying Qualities Criteria

Aircraft pitch response is a vital element of piloted vehicle flying qualities. There has been controversy over both the form and the substance of the requirements for short-term pitch response. Currently, MIL-STD- 1797A offers six different methods for evaluating short-term pitch response. These six methods often give conflicting results. Two methods are analyzed in this thesis - the Neal-Smith criteria and the ωspΤθ2, ςsp, τθ criteria. Domains from both criteria are mapped into each other identifying regions of conflict and regions of agreement. Parametric studies are performed and evaluated for trends. Further, a real-time analysis tool for evaluating these methods is developed

Hard Hat Ambient Liability Observer (HALO)

Capturing workplace incident information is a growing area of concern for most companies. To assist with this, the design team proposed the H.A.L.O. This design uses time-of-flight sensors connected to LEDs to create a proximity-based hazard warning system. It also records incident data using an accelerometer and micro-SD card. This helps workers avoid some of the most common workplace injuries, slips, trips, and falls and accidental collisions. Students have created a design with engineering, and marketing requirements that accomplish this task. The proposed design allows for this monitoring and mitigation systems to be attached to hard hats. Team members developed software and hardware subsystems to fit on any hardhat without hindering worker safety. The completed design uses the systems listed above register hazardous objects within 1.5m and color shifts depending on distance. Within the 150-degree FOV, any objects approaching the device are registered. In case of a possible concussive event, collision data writes to a SD card for use during an incident investigation. After a semester of development and integration, the H.A.L.O. system met the engineering requirements to assist with preventing workplace injury in a cost-effective manner

Airplane Pitch Response to Rapid Configuration Change: Flight Test and Safety Assessment

This paper examines airplane response to rapid flap extension on seven general aviation airplanes. The scenario involves a pilot flying in the traffic pattern becoming distracted, abruptly extending flaps while looking outside the airplane, and failing to notice airspeed and pitch-attitude changes. The airplanes tested reached pitch forces of up to 36 lbf, meeting FAA requirements but exceeding the capability of 55% of the population. Flight data showed a pitch-up to more than 30˚ in 5 s after flap extension, causing airspeed to drop below stall speed for four of the airplanes. At traffic pattern altitudes, stalling an airplane can be fatal. The NTSB lists over 1000 accidents caused by loss of control in the traffic pattern between 1982 and 2017. As general aviation airplanes do not carry flight data recorders, it is unknown how many of those accidents may have involved stalls caused by uncommanded response after flap extension. From the data gathered in flight, it seems possible some were. To improve safety, flight training should prepare students to anticipate rapid pitch changes during flap extension and retraction. In addition, airplane developers could interconnect flaps with the elevator, reduce horizontal tail size, or use a T-tail. The FAA should consider reducing the maximum pitch stick and wheel forces in 14 CFR §23.143 to 20 lbf or less

Real-Time Satellite Component Recognition with YOLO-V5

With the increasing risk of collisions with space debris and the growing interest in on-orbit servicing, the ability to autonomously capture non-cooperative, tumbling target objects remains an unresolved challenge. To accomplish this task, characterizing and classifying satellite components is critical to the success of the mission. This paper focuses on using machine vision by a small satellite to perform image classification based on locating and identifying satellite components such as satellite bodies, solar panels or antennas. The classification and component detection approach is based on “You Only Look Once” (YOLO) V5, which uses Neural Networks to identify the satellite components. The training dataset includes images of real and virtual satellites and additional preprocessed images to increase the effectiveness of the algorithm. The weights obtained from the algorithm are then used in a spacecraft motion dynamics and orbital lighting simulator to test classification and detection performance. Each test case entails a different approach path of the chaser satellite to the target satellite, a different attitude motion of the target satellite, and different lighting conditions to mimic that of the Sun. Initial results indicate that once trained, the YOLO V5 approach is able to effectively process an input camera feed to solve satellite classification and component detection problems in real-time within the limitations of flight computers

Performance Study of YOLOv5 and Faster R-CNN for Autonomous Navigation around Non-Cooperative Targets

Autonomous navigation and path-planning around non-cooperative space objects is an enabling technology for on-orbit servicing and space debris removal systems. The navigation task includes the determination of target object motion, the identification of target object features suitable for grasping, and the identification of collision hazards and other keep-out zones. Given this knowledge, chaser spacecraft can be guided towards capture locations without damaging the target object or without unduly the operations of a servicing target by covering up solar arrays or communication antennas. One way to autonomously achieve target identification, characterization and feature recognition is by use of artificial intelligence algorithms. This paper discusses how the combination of cameras and machine learning algorithms can achieve the relative navigation task. The performance of two deep learning-based object detection algorithms, Faster Region-based Convolutional Neural Networks (R-CNN) and You Only Look Once (YOLOv5), is tested using experimental data obtained in formation flight simulations in the ORION Lab at Florida Institute of Technology. The simulation scenarios vary the yaw motion of the target object, the chaser approach trajectory, and the lighting conditions in order to test the algorithms in a wide range of realistic and performance limiting situations. The data analyzed include the mean average precision metrics in order to compare the performance of the object detectors. The paper discusses the path to implementing the feature recognition algorithms and towards integrating them into the spacecraft Guidance Navigation and Control system.Comment: 12 pages, 10 figures, 9 tables, IEEE Aerospace Conference 202

Cervicovaginal Safety of the Formulated, Biguanide-Based Human Immunodeficiency Virus Type 1 (HIV-1) Inhibitor NB325 in a Murine Model

Vaginal microbicides that reduce or eliminate the risk of HIV-1 sexual transmission must do so safely without adversely affecting the integrity of the cervicovaginal epithelium. The present studies were performed to assess the safety of the biguanide-based antiviral compound NB325 in a formulation suitable for topical application. Experiments were performed using a mouse model of cervicovaginal microbicide application, which was previously shown to be predictive of topical agent toxicity revealed in microbicide clinical trials. Mice were exposed vaginally to unformulated NB325 or NB325 formulated in the hydroxyethyl cellulose “universal placebo.” Following exposures to formulated 1% NB325 for 10 min to 24 h, the vaginal and cervical epithelia were generally intact, although some areas of minimal vaginal epithelial damage were noted. Although formulated NB325 appeared generally safe for application in these studies, the low but observable level of toxicity suggests the need for improvements in the compound and/or formulation

The role of community-based Hubs in reef restoration: Collaborative monitoring at Moore Reef

The Cairns-Port Douglas region is home to multiple coral rehabilitation and stewardship projects supported by scientists, Traditional Owners, and a range of local stakeholders. The Cairns-Port Douglas Reef Hub has been a platform for collaboration across Traditional Owners, tourism operators, not-for-profits and scientists from the Reef Restoration and Adaptation Program (AIMS and CSIRO) to design and deliver a project at Moore Reef that assesses how new techniques for assisted coral recovery can be applied in rubble habitats. The collaborative project evaluates the viability of newly engineered coral seeding devices developed by AIMS, for deploying coral recruits that were spawned in the National Sea Simulator in December 2022 to sites at Moore Reef close to tourist pontoons. This project provides important data to inform future scaling up of restoration activities and provides a model for active involvement of a range of partners. Through this work, the project builds understanding around key ingredients for best-practice, place-based engagement opportunities for Reef communities and the general public

Magnetic Resonance Imaging of Ethyl-nitrosourea-induced Rat Gliomas: A Model for Experimental Therapeutics of Low-grade Gliomas

Human low-grade gliomas represent a population of brain tumors that remain a therapeutic challenge. Preclinical evaluation of agents, to test their preventive or therapeutic efficacy in these tumors, requires the use of animal nobreak models. Spontaneous gliomas develop in models of chemically induced carcinogenesis, such as in the transplacental N-ethyl-N-nitrosourea (ENU) rat model. However, without the ability to detect initial tumor formation, multiplicity or to measure growth rates, it is difficult to test compounds for their interventional or preventional capabilities. In this study Fisher-334 rats, treated transplacentally with ENU, underwent magnetic resonance imaging (MRI) examination in order to evaluate this approach for detection of tumor formation and growth. ENU-induced intracranial cerebral tumors were first observable in T2-weighted images beginning at 4 months of age and grew with a mean doubling time of 0.487 ± 0.112 months. These tumors were found histologically to be predominately mixed gliomas. Two therapeutic interventions were evaluated using MRI, vitamin A (all-trans retinol palmitate, RP), as a chemopreventative agent and the anti-angiogenic drug SU-5416. RP was found to significantly delay the time to first tumor observation by one month ( P = 0.05). No differences in rates of tumor formation or growth rates were observed between control and RP-treated groups. MRI studies of rats treated with SU-5416 resulted in reduction in tumor growth rates compared to matched controls. These results show that MRI can be used to provide novel information relating to the therapeutic efficacy of agents against the ENU-induced tumor model.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45391/1/11060_2004_Article_352248.pd

Trajectory Energy Management Systems for eVTOL Vehicles: Modeling, Simulation and Testing

Presented at AIAA AVIATION Forum 2022The rise of electric aircraft propulsion methods, the increased use of automated and integrated flight control systems, and the envisioned use of personal Vertical Takeoff and Landing (VTOL) vehicles in urban environments lead to novel technical and regulatory challenges for aircraft manufacturers, certification authorities and operators. The combination of electric propulsion, where energy reserves and powertrain performance are highly sensitive to the environment, and VTOL, where the aircraft cannot simply glide to an emergency landing, generates the need for Trajectory Energy Management (TEM). The TEM task involves the manipulation of flight and propulsion controls to achieve a planned flight profile. The TEM system must provide the pilot or automated control system with guidance cues to achieve a planned flight profile, to maintain an energy-optimal trajectory, to avoid deviations from the flight plan causing increases in energy and power consumption, and to mitigate the risk of energy completion. As the pilot must manage both the energy source and flight dynamics energy state, the TEM system must provide sufficient information to the pilot, so that the pilot can perform the mission. This research is intended to define some requirements for energy management such that the pilot can safely accomplish an intended profile and land with enough energy reserves. These requirements must be defined based on prototype algorithm development, simulation results, and flight test data