Improving Object Detectors by Exploiting Bounding Boxes for Augmentation Design
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The challenging requirements that are evolving for future aircraft demand that each design be optimally integrated, for the penalties imposed by nonoptimal performance are significant. Classic numerical optimization algorithms have been and will continue to be important tools for aircraft designers. These methods are, however, limited to certain categories of aircraft design variables, leaving the remainder to be determined by the user. A method that makes use of knowledge-based expert systems offers the potential for aiding the conceptual design process in a way that is similar to that of numerical optimization, except that it would address discrete, discontinuous, abstract, or any other unoptimized aspect of vehicle design and integration. Other unique capabilities such as automatic discovery and learning in design may also be achievable in the near term. This paper discusses current practice in conceptual aircraft design and knowledge-based systems, and how knowledge-based systems can be used in conceptual design.
A methodology is presented for a modal suppression control law design using flight test data instead of mathematical models to obtain the required gain and phase information about the flexible airplane. This approach is referred to as BODEDIRECT. The purpose of the BODEDIRECT program is to provide a method of analyzing the modal phase relationships measured directly from the airplane. These measurements can be achieved with a frequency sweep at the control surface input while measuring the outputs of interest. The measured Bode-models can be used directly for analysis in the frequency domain, and for control law design. Besides providing a more accurate representation for the system inputs and outputs of interest, this method is quick and relatively inexpensive. To date, the BODEDIRECT program has been tested and verified for computational integrity. Its capabilities include calculation of series, parallel and loop closure connections between Bode-model representations. System PSD, together with gain and phase margins of stability may be calculated for successive loop closures of multi-input/multi-output systems. Current plans include extensive flight testing to obtain a Bode-model representation of a commercial aircraft for design of a structural stability augmentation system.
Major challenges for astronauts in future long-duration exploration missions (LDEMs) will be that crewmembers are not expected to be medical professionals, may be under high workload and stress, are facing physiological challenges caused by spaceflight, and will have limited, delayed voice communications with medical support from Earth. An autonomous medical response agent (AMRA) is envisioned to help astronauts address medical complaints, develop a differential diagnosis, and guide self-treatment until a healthy state is restored. AMRA develops a process of personalized diagnosis and treatment through a Bayesian predictive control system that recommends therapeutic control actions including diagnostic tests and treatments to crewmembers (Menon, 2020). The Human Computer Interaction (HCI) lab from NASA Ames Research Center’s Human Systems Integration Division (Code TH) has collaborated with Nahlia Inc in human-centered design augmentation research for AMRA. The project, titled Design of ‘Autonomous Medical Response Agent Interface Prototype for Long Duration Spaceflight, has been funded by the Translational Research Institute for Space Health (TRISH) and introduces an interactive user-interface prototype that guides astronauts through self-diagnosis, treatment, and rehabilitation while communicating with remote specialists in ground support (most notably a patient’s flight surgeon). Our project develops the interaction design for the crewmember using AMRA through user research, iterative design, and usability testing to evaluate the user interface and workflow designed. The interface design deliverable for this project, titled AMRA Aggregate Information Display (AMRA AID) is an integrated information display system for comprehensive autonomous medical guidance, diagnosis, and treatment of in-flight medical conditions experienced by crewmembers. AMRA AID demonstrates how we might ensure crew autonomy, increase the crew’s medical capabilities, and decrease cognitive burden within a front-end user interface. AMRA AID refrains from relying on input from ground or mission control for self-treatment of medical issues—though ground awareness and communication with ground is maintained as a means of ensuring trust between mission control and crew. AMRA AID demonstrates how the crew’s on-board medical system might integrate with information from vehicle monitoring and crew schedule, without assuming causal relationships. AMRA AID’s comprehensive view enables efficient information access for both crew and ground support, reducing cognitive burden in the event of an unplanned or emergency medical incident and enabling informed analytical decisions to be made based on both crew and vehicle health. Human-centered design augmentation advanced within the prototype included: enhanced workflow and treatment guidance for two medical scenarios for a non-specialist user base with various levels of medical training, interaction design which considered speech (conversational user interface) elements and on-screen interactions to be developed in future iterations of the project, communication design and functional requirements relevant to self-care versus caring for another astronaut, as well as user testing of the prototype with an international space medical community. This project arrives at critical findings regarding usability needs, communication requirements, and integrated information requirements for a future technology interface functioning to increase confidence between ground support and LDEM crewmembers.
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Within conceptual design changes occur rapidly due to a combination of uncertainty and shifting requirements. To stay relevant in this fluid time, trade studies must also be performed rapidly. In order to drive down analysis time while improving the information gained by these studies, surrogate models can be created to represent the complex output of a tool or tools within a specified tradespace. In order to create this model however, a large amount of data must be collected in a short amount of time. By this method, the historical approach of relying on subject matter experts to generate the data required is schedule infeasible. However, by implementing automation and distributed analysis the required data can be generated in a fraction of the time. Previous work focused on setting up a tool called multiPOST capable of orchestrating many simultaneous runs of an analysis tool assessing these automated analyses utilizing heuristics gleaned from the best practices of current subject matter experts. In this update to the previous work, elements of graph theory are included to further drive down analysis time by leveraging data previously gathered. It is shown to outperform the previous method in both time required, and the quantity and quality of data produced.
Within conceptual design changes occur rapidly due to a combination of uncertainty and shifting requirements. To stay relevant in this fluid time, trade studies must also be performed rapidly. In order to drive down analysis time while improving the information gained by these studies, surrogate models can be created to represent the complex output of a tool or tools within a specified tradespace. In order to create this model however, a large amount of data must be collected in a short amount of time. By this method, the historical approach of relying on subject matter experts to generate the data required is schedule infeasible. However, by implementing automation and distributed analysis the required data can be generated in a fraction of the time. Previous work focused on setting up a tool called multiPOST capable of orchestrating many simultaneous runs of an analysis tool assessing these automated analyses utilizing heuristics gleaned from the best practices of current subject matter experts. In this update to the previous work, elements of graph theory are included to further drive down analysis time by leveraging data previously gathered. It is shown to outperform the previous method in both time required, and the quantity and quality of data produced.
Analyses of design variations on a pitch axis stabilization and command augmentation system (SCAS) for a STOVL fighter aircraft are performed in a moving base simulation experiment. The primary goal of this study is to determine if turbulence-induced control activity could be reduced by modifying SCAS parameters while keeping the response-to-command characteristics of the baseline system that provide Level 1 flying qualities. Pilot ratings and control utilization statistics for the baseline system are in agreement with similar data gathered in a prior simulation test involving the same aircraft and control system.
Nonlinear digital programming techniques for airplane stability augmentation systems design
A no-risk approach for developing an Improved Waste Collection Subsystem (WCS) for the shuttle orbiter is described. The GE Improved WCS Concept builds on the experience of 14 Shuttle missions with over 400 man-days of service. This concept employs the methods of the existing flight-proven mature design, augmenting them to eliminate foreseen difficulties and to fully comply with the design requirements. The GE Improved WCS Concept includes separate storage for used wipes. Compaction of the wipes provides a solution to the capacity problem, fully satisfying the 210 man-day storage requirement. The added feature of in-flight serviceable storage space for the wipes creates a variable capacity feature which affords redundancy in the event of wipes compaction system failure. Addition of features permitting in-flight servicing of the feces storage tank creates a variable capacity WCS with easier post-flight servicing to support rapid turnaround of the Shuttle orbiter. When these features are combined with a vacuum pump to evacuate wipes and fecal storage tanks through replaceable odor/bacteria filters to the cabin, the GE Improved WCS satisfies the known requirements for Space Station use, including no venting to space.
A piloted simulation study assessed various levels of stability and control augmentation designed to improve the handling qualities of several helicopters in nap-of-the-earth (NOE) flight. Five basic single rotor helicopters - one teetering, two articulated, and two hingeless - which were found to have a variety of major deficiencies in a previous fixed-based simulator study were selected as baseline configurations. The stability and control augmentation systems (SCAS) include simple control augmentation systems (CAS) to decouple pitch and yaw responses due to collective input and to quicken the pitch and roll control responses; SCAS of rate command type designed to optimize the sensitivity and damping and to decouple the pitch-roll due to aircraft angular rate; and attitude command type SCAS. Pilot ratings and commentary are presented as well as performance data related to the task. SCAS control usage and their gain levels associated with specific rotor type are also discussed.
Of all large space structural systems, space stations present a unique challenge and requirement to advanced control technology. Their operations require control system stability over an extremely broad range of parameter changes and high level of disturbances. During shuttle docking the system mass may suddenly increase by more than 100% and during station assembly the mass may vary even more drastically. These coupled with the inherent dynamic model uncertainties associated with large space structural systems require highly sophisticated control systems that can grow as the stations evolve and cope with the uncertainties and time-varying elements to maintain the stability and pointing of the space stations. The aspects of space station operational properties are first examined, including configurations, dynamic models, shuttle docking contact dynamics, solar panel interaction, and load reduction to yield a set of system models and conditions. A model reference adaptive control algorithm along with the inner-loop plant augmentation design for controlling the space stations under severe operational conditions of shuttle docking, excessive model parameter errors, and model truncation are then investigated. The instability problem caused by the zero-frequency rigid body modes and a proposed solution using plant augmentation are addressed. Two sets of sufficient conditions which guarantee the globablly asymptotic stability for the space station systems are obtained.
Several night nap-of-the-earth mission tasks were evaluated using a helmet-mounted display which provided a limited field-of-view image with superimposed flight control symbology. A wide range of stability and control augmentation designs was investigated. Variations in controller force-deflection characteristics and the number of axes controlled through an integrated side-stick controller were studied. In general, a small displacement controller is preferred over a stiffstick controller particularly for maneuvering flight. Higher levels of stability augmentation were required for IMC tasks to provide handling qualities comparable to those achieved for the same tasks conducted under simulated visual flight conditions.
Several night nap-of-the-earth mission tasks were evaluated using a helmet-mounted display which provided a limited field-of-view image with superimposed flight control symbology. A wide range of stability and control augmentation designs was investigated. Variations in controller force-deflection characteristics and the number of axes controlled through an integrated side-stick controller were studied. In general, a small displacement controller is preferred over a stiffstick controller particularly for maneuvering flight. Higher levels of stability augmentation were required for IMC tasks to provide handling qualities comparable to those achieved for the same tasks conducted under simulated visual flight conditions. Previously announced in STAR as N82-23216
A sensitivity analysis is presented that can be used to judge the impact of vehicle dynamic model variations on the relative stability of multivariable continuous closed-loop control systems. The sensitivity analysis uses and extends the singular-value concept by developing expressions for the gradients of the singular value with respect to variations in the vehicle dynamic model and the controller design. Combined with a priori estimates of the accuracy of the model, the gradients are used to identify the elements in the vehicle dynamic model and controller that could severely impact the system's relative stability. The technique is demonstrated for a yaw/roll damper stability augmentation designed for a business jet.
A ground simulator experiment was conducted on the Flight Simulator for Advanced Aircraft at Ames Research Center to investigate the influence of several static stability and stability/control augmentation design parameters on helicopter flying qualities during terminal area operations in instrument conditions. Effects of light turbulence were included. Two levels of static stability in each rotational axis (pitch, roll, yaw) were examined for a hingeless rotor configuration. The variations in pitch and roll were: (1) stable and (2) neutral static stability; in yaw there were two stable levels. Four types of stability/control augmentation were also examined for the lower level of static stability in each axis. This latter investigation covered three helicopter rotor types: hingeless, articulated, and teetering. Four pilots performed a total of 105 evaluations of these parameters for a representative VOR instrument approach task. Pilot rating results indicate the acceptability of neutral static stability longitudinally and laterally and the need for pitch-roll attitude augmentation to achieve a satisfactory system.
Diagnosis of endoleak following endovascular aortic repair (EVAR) relies on manual review of multi-slice CT angiography (CTA) by physicians which is a tedious and time-consuming process that is susceptible to error. We evaluate the use of a deep neural network for the detection of endoleak on CTA for post-EVAR patients using a novel data efficient training approach. 50 CTAs and 20 CTAs with and without endoleak respectively were identified based on gold standard interpretation by a cardiovascular subspecialty radiologist. The Endoleak Augmentor, a custom designed augmentation method, provided robust training for the machine learning (ML) model. Predicted segmentation maps underwent post-processing to determine the presence of endoleak. The model was tested against 3 blinded general radiologists and 1 blinded subspecialist using a held-out subset (10 positive endoleak CTAs, 10 control CTAs). Model accuracy, precision and recall for endoleak diagnosis were 95%, 90% and 100% relative to reference subspecialist interpretation (AUC = 0.99). Accuracy, precision and recall was 70/70/70% for generalist1, 50/50/90% for generalist2, and 90/83/100% for generalist3. The blinded subspecialist had concordant interpretations for all test cases compared with the reference. In conclusion, our ML-based approach has similar performance for endoleak diagnosis relative to subspecialists and superior performance compared with generalists.