Hok K. Ng

Aircraft Trajectory Optimization and Contrails Avoidance in the Presence of Winds

There are indications that persistent contrails can lead to adverse climate change, although the complete effect on climate forcing is still uncertain. A flight trajectory optimization algorithm with fuel and contrails models, which develops alternative flight paths, provides policy makers the necessary data to make tradeoffs between persistent contrails mitigation and aircraft fuel consumption. This study develops an algorithm that calculates wind-optimal trajectories for cruising aircraft while avoiding the regions of airspace prone to persistent contrails formation. The optimal trajectories are developed by solving a non-linear optimal control problem with path constraints. The regions of airspace favorable to persistent contrails formation are modeled as penalty areas that aircraft should avoid and are adjustable. The tradeoff between persistent contrails formation and additional fuel consumption is investigated, with and without altitude optimization, for 12 city-pairs in the continental United States. Without altitude optimization, the reduction in contrail travel times is gradual with increase in total fuel consumption. When altitude is optimized, a two percent increase in total fuel consumption can reduce the total travel times through contrail regions by more than six times. Allowing further increase in fuel consumption does not seem to result in proportionate decrease in contrail travel times.

Health monitoring of a satellite system

A health monitoring system based on analytical redundancy is developed for satellites on elliptical orbits. Analytical redundancy, which reduces the need for hardware redundancy, uses the modeled dynamic relationship between system inputs and measured system outputs to form a residual process that is used for detecting and identifying faults. First, the dynamics of the satellite including orbital mechanics and attitude dynamics is modeled as a periodic system. Then, periodic fault detection filters are designed to detect and identify the satellite’s actuator and sensor faults. In addition, parity equations are constructed using the algebraic redundant relationship among actuators and sensors. Furthermore, a residual processor is designed to generate the probability of each fault by using a sequential probability test. Finally, the health monitoring system, consisting of periodic fault detection filters, parity equations, and residual processor, is evaluated in the simulation in the presence of disturbances and uncertainty.

A vehicle health monitoring system evaluated experimentally on a passenger vehicle

A vehicle health monitoring system based on analytical redundancy, is developed for automated passenger vehicles. A residual generator and a residual processor are designed together to detect and identify actuator and sensor faults of the Buick LeSabre rapidly. The residual generator includes fault detection filters and parity equations. It uses the control commands and sensor measurements to generate the residuals, which have a unique static pattern in response to each fault. Then, the residual processor interrogates the residuals by matching them to one of several known patterns. It computes the probability of each hypothesis conditioned on the history of residuals. The fault detection latency is reduced by integrating the design of the residual generator and the residual processor. The vehicle health monitoring system is evaluated in real-time on a Buick LeSabre. The vehicle sensor and actuator faults are simulated artificially by the computer or created manually by the driver. In one experiment, a real intermittent sensor fault occurred and was immediately detected and identified. The real-time evaluation demonstrates that the vehicle health monitoring system can detect and identify actuator and sensor faults under various disturbances and uncertainties with almost minimal detection latency

Optimizing Aircraft Trajectories with Multiple Cruise Altitudes in the Presence of Winds

This study develops a trajectory-optimization algorithm for approximately minimizing aircraft travel time and fuel burn by combining a method for computing minimum-time routes in winds on multiple horizontal planes and an aircraft fuel burn model for generating fuel-optimal vertical profiles. It is applied to assess the potential benefits of flying user-preferred routes for commercial cargo flights operating between Anchorage, Alaska and major airports in Asia and the contiguous United States. Flying wind-optimal trajectories with a fuel-optimal vertical profile reduces average fuel burn of international flights cruising at a single altitude by 1–3%. The potential fuel savings of performing en route step climbs are not significant for many shorter domestic cargo flights that have only one step climb. Wind-optimal trajectories reduce fuel burn and travel time relative to the flight-plan route by up to 3% for the domestic cargo flights. However, for transoceanic traffic, the fuel burn savings could be as mu...

Design and Evaluation of a Dynamic Programming Flight Routing Algorithm Using the Convective Weather Avoidance Model

The optimization of tra! c flows in congested airspace with varying convective weather is a challenging problem. One approach is to generate shortest routes between origins and destinations while meeting airspace capacity constraint in the presence of uncertainties, such as weather and airspace demand. This study focuses on development of an optimal flight path search algorithm that optimizes national airspace system throughput and e! ciency in the presence of uncertainties. The algorithm is based on dynamic programming and utilizes the predicted probability that an aircraft will deviate around convective weather. It is shown that the running time of the algorithm increases linearly with the total number of links between all stages. The optimal routes minimize a combination of fuel cost and expected cost of route deviation due to convective weather. They are considered as alternatives to the set of coded departure routes which are predefined by FAA to reroute pre-departure flights around weather or air tra! c constraints. A formula, which calculates predicted probability of deviation from a given flight path, is also derived. The predicted probability of deviation is calculated for all path candidates. Routes with the best probability are selected as optimal. The predicted probability of deviation serves as a computable measure of reliability in pre-departure rerouting. The algorithm can also be extended to automatically adjust its design parameters to satisfy the desired level of reliability.

Tradeoff Between Contrail Reduction and Emissions in United States National Airspace

This paper describes a class of strategies for reducing persistent contrail formation with the capability of trading o between contrails and aircraft induced emissions. The concept of contrail frequency index is dened and used to quantify the contrail activities. The contrail reduction strategies reduce the contrail frequency index by altering aircraft’s cruising altitude with consideration to extra emissions. The strategies use a user-dened factor to trade o between contrail reduction and extra emissions. The analysis shows that contrails can be reduced with extra emissions and without adding congestion to airspace. For a day with high contrail activities, the results show that the maximal contrail reduction strategy can achieve a contrail reduction of 88%. When a trade-o factor is used, the strategy can achieve less contrail reduction while emitting less emissions compared to the maximal contrail reduction strategy. The user-dened trade-o factor provides a exible way to trade o between contrail reduction and extra emissions. Better understanding of the trade-os between contrails and emissions and their impact on the climate need to be developed to fully utilize this class of contrail reduction strategies. The strategies provide a starting point for developing operational policies to reduce the impact of aviation on climate.

Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA’s Aviation Environmental Portfolio Management Tool for Impacts.

Benefits Analysis of Wind-Optimal Operations For Trans- Atlantic Flights

North Atlantic Tracks are trans-Atlantic routes across the busiest oceanic airspace in the world. This study analyzes and compares current flight-plan routes to wind-optimal routes for trans-Atlantic flights. The historical flight track data recorded by EUROCONTROL’s Central Flow Management Unit is merged with data from FAA’s Enhanced Traffic Management System to provide an accurate flight movement database containing the highest available flight path resolution in both systems. The combined database is adopted for airspace simulation integrated with aircraft fuel burn to simulate traffic within the Organized Track System (OTS). The fuel burn for the tracks in the OTS are compared with the corresponding quantities for the wind-optimized routes for a month to evaluate the potential benefits of flying wind-optimal routes in North Atlantic Airspace. The potential fuel savings depend on existing inefficiencies in current flight plans, atmospheric conditions and location of the city-pairs. The potential benefits are compared with actual flight tests that have been conducted since 2010 between a few city-pairs in the trans-Atlantic region to improve fuel consumption.

Prediction and Use of Contrail Frequency Index for Contrail Reduction Strategies

Methods have been proposed to reduce aircraft-induced contrails by on-board sensing and strategic planning. This paper describes a class of indices that predict potential aircraft-induced contrail formations one to six hours in advance. The indices can be used to identify air traffic control centers and altitudes with high potential for contrail formation. The results show that the index is affected more by the changing atmospheric conditions than by small daily variations in the nominal traffic. The analysis shows that the one-hour predicted contrail frequency index is highly correlated with the actual contrail frequency, with an average correlation coefficient of 0.85. The correlation coefficient is lower with longer prediction time, down to 0.52 for six-hour prediction. The average success rates for identifying air traffic control centers and altitudes with high contrail frequency are as high as 83.47% for one-hour prediction.

Fault detection, identification and reconstruction for ground vehicles

A fault detection filter and a fault reconstruction process are designed to monitor the sensors and actuators on ground vehicles. The fault can be detected because the residual generated by the fault detection filter is zero when there is no fault and the residual becomes nonzero when a fault occurs. Furthermore, the faulty component can be identified because the residual is nonzero in a unique and a priori known direction for each fault. Finally, the fault can be reconstructed from the residual by the fault reconstruction process. The performance of the fault detection filter and fault reconstruction process are evaluated using empirical data.