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Mavris,
Dimitri N.
Mavris,
Dimitri N.
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ItemIdentification of Instantaneous Anomalies in General Aviation Operations using Energy Metrics(Georgia Institute of Technology, 2019-12) Puranik, Tejas G. ; Mavris, Dimitri N.Quantification and improvement of safety is one of the most important objectives among the General Aviation community. In recent years, machine learning techniques have emerged as an important enabler in the data-driven safety enhancement of aviation operations with a number of techniques being applied to flight data to identify and isolate anomalous (and potentially unsafe) operations. Energy-based metrics provide measurable indications of the energy state of the aircraft and can be viewed as an objective currency to evaluate various safety-critical conditions across a heterogeneous fleet of aircraft and operations. In this paper, a novel method of identifying instantaneous anomalies for retrospective safety analysis in General Aviation using energy-based metrics is proposed. Each flight data record is processed by a sliding window across the multi-variate time series of evaluated metrics. A Gaussian Mixture Model using energy metrics and their variability within each window is fit in order to predict the probability of any instant during the flight being nominal. Instances during flights that deviate from the nominal are isolated to identify potential increased levels of risk. The identified anomalies are compared with traditional methods of safety assessment such as exceedance detection to highlight the benefits of the developed method. The methodology is demonstrated using flight data records from two representative aircraft for critical phases of flight.
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ItemA Framework for Electrified Propulsion Architecture and Operation Analysis(Georgia Institute of Technology, 2019-07) Cinar, Gokcin ; Garcia, Elena ; Mavris, Dimitri N.Purpose – The purpose of this paper was to create a generic and flexible framework for the exploration, evaluation and side-by-side comparison of novel propulsion architectures. The intent for these evaluations was to account for varying operation strategies and to support architectural design space decisions, at the conceptual design stages, rather than single-point design solutions. Design/methodology/approach – To this end, main propulsion subsystems were categorized into energy, power and thrust sources. Two types of matrices, namely, the property and interdependency matrices, were created to describe the relationships and power flows among these sources. These matrices were used to define various electrified propulsion architectures, including, but not limited to, turboelectric, series-parallel and distributed electric propulsion configurations. Findings – As a case study, the matrices were used to generate and operate the distributed electric propulsion architecture of NASA’s X-57 Mod IV aircraft concept. The mission performance results were acceptably close to the data obtained from the literature. Finally, the matrices were used to simulate the changes in the operation strategy under two motor failure scenarios to demonstrate the ease of use, rapidness and automation. Originality/value – It was seen that this new framework enables rapid and analysis-based comparisons among unconventional propulsion architectures where solutions are driven by requirements.
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ItemMulti-UAV Trajectory Optimization Utilizing a NURBS-Based Terrain Model for an Aerial Imaging Mission(Georgia Institute of Technology, 2019-05) Choi, Youngjun ; Chen, Mengzhen ; Choi, Younghoon ; Briceno, Simon ; Mavris, Dimitri N.Trajectory optimization precisely scanning an irregular terrain is a challenging problem since the trajectory optimizer needs to handle complex geometry topology, vehicle performance, and a sensor specification. To address these problems, this paper introduces a novel framework of a multi-UAV trajectory optimization method for an aerial imaging mission in an irregular terrain environment. The proposed framework consists of terrain modeling and multi-UAV trajectory optimization. The terrain modeling process employs a Non-Uniform Rational B-Spline (NURBS) surface fitting method based on point cloud information resulting from an airborne LiDAR sensor or other sensor systems. The NURBS-based surface model represents a computationally efficient terrain topology. In the trajectory optimization method, the framework introduces a multi-UAV vehicle routing problem enabling UAV to scan an entire area of interest, and obtains feasible trajectories based on given vehicle performance characteristics, and sensor specifications, and the approximated terrain model. The proposed multi-UAV trajectory optimization algorithm is tested by representative numerical simulations in a realistic aerial imaging environment, namely, San Diego and Death Valley, California.
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ItemEnergy-Constrained Multi-UAV Coverage Path Planning for an Aerial Imagery Mission Using Column Generation(Georgia Institute of Technology, 2019-03) Choi, Younghoon ; Choi, Youngjun ; Briceno, Simon ; Mavris, Dimitri N.This paper presents a new Coverage Path Planning (CPP) method for an aerial imaging mission with multiple Unmanned Aerial Vehicles (UAVs). In order to solve a CPP problem with multicopters, a typical mission profile can be defined with five mission segments: takeoff, cruise, hovering, turning, and landing. The traditional arc-based optimization approaches for the CPP problem cannot accurately estimate actual energy consumption to complete a given mission because they cannot account for turning phases in their model, which may cause non-feasible routes. To solve the limitation of the traditional approaches, this paper introduces a new route-based optimization model with column generation that can trace the amount of energy required for all different mission phases. This paper executes numerical simulations to demonstrate the effectiveness of the proposed method for both a single UAV and multiple UAV scenarios for CPP problems.