Fuel Burn Cost Research Articles

Analyzing daily sorties at NAS Kingsville utilizing alternative refueling methods

Training Air Wing TWO (TW-2) is responsible for the intermediate and advanced phases of Undergraduate Jet Pilot Training and provides the US Navy and Marine Corps with newly winged aviators. The objective of this study is to improve daily operations at TW-2 using sortie output and aircraft refuel waiting time as measures of performance. We define a sortie as any flight event attempted on the daily flight schedule to facilitate student training. We create a discrete-event simulation to model daily jet flow and operations at TW-2. We compare current operations with several alternative refueling strategies that incorporate hot pit refueling to minimize the time jets spend on the ground between consecutive sorties. We consider different factors and run a variety of experiments to determine the impact of various fueling strategies on resource utilization rates in an effort to generate more sorties. Our analysis finds that TW-2 can increase daily sortie throughput by an average of 60 sorties by incorporating both hot pit and cold refueling. We recommend using two hot pits to decrease the yearly idle fuel-burn cost by over $342,000 and reclaim a value of $98,422,500 from the annual maintenance contract at TW-2.

RETRACTED: A new dynamic pushback control method for reducing fuel-burn costs: Using predicted taxi-out time

Abstract Long departure-taxi-out time leads to significant airport surface congestion, fuel-burn costs, and excessive emissions of greenhouse gases. To reduce these undesirable effects, a Predicted taxi-out time-based Dynamic Pushback Control (PDPC) method is proposed. The implementation of this method requires two steps: first, the taxi-out times for aircraft are predicted by the least-squares support-vector regression approach of which the parameters are optimized by an introduced improved Firefly algorithm. Then, a dynamic pushback control model equipped with a linear gate-hold penalty function is built, along with a proposed iterative taxiway queue-threshold optimization algorithm for solving the model. A case study with data obtained from Beijing International airport (PEK) is presented. The taxi-out time prediction model achieves predictive accuracy within 3 min and 5 min by 84.71% and 95.66%, respectively. The results of the proposed pushback method show that total operation cost and fuel-burn cost achieve a 14.0% and 21.1% reduction, respectively, as compared to the traditional K-control policy. (3) From the perspective of implementation, using PDPC policy can significantly reduce the queue length in taxiway and taxi-out time. The total operation cost and fuel-burn cost can be curtailed by 37.2% and 52.1%, respectively, as compared to the non-enforcement of any pushback control mechanism. These results show that the proposed pushback control model can reduce fuel-burn costs and airport surface congestion effectively.

Aircraft Vertical Route Optimization by Beam Search and Initial Search Space Reduction

This paper describes an optimization algorithm that provides an economical vertical navigation profile by finding the combinations of climb, cruise, and descent speeds, as well as altitudes, for an aircraft to minimize flight costs. The computational algorithm takes advantage of a space search reduction methodology to reduce the initial number of available speed and altitude combinations. The optimal solution was found by implementing the beam search algorithm. A bounding function that correctly estimates the flight cost by considering step climbs was developed to reduce the number of calculations required by the beam search algorithm. The full-flight fuel burn cost was obtained using a performance database-based method. The algorithm uses a numerical performance model instead of equations of motion to compute fuel burn. The database was developed by using flight experimental data. To validate the algorithm, its results were compared to those of three other algorithms: an exhaustive search, beam search, and search space reduction. The solution provided by the algorithm was also compared to the solution provided by a flight management system. Following this comparison, the algorithm systematically found the optimal solutions, which were better in terms of flight cost than those provided by the flight management system.

Multi-commodity flow network model of the flight gate assignment problem

The flight gate assignment problem is encountered by gate managers at an airport on a periodic basis. This assignment should be made so as to balance carrier efficiency and passenger comfort, while providing buffers for unexpected events that cause assignment disruptions. In this paper, a binary integer multi-commodity gate flow network model is presented with the objective of minimizing the fuel burn cost of aircraft taxi by type and expected passenger discomfort for “tight” connections as a function of inter-gate distance and connection time. This approach is shown to be computationally efficient within a decomposition approach for large problem instances. A numerical application of this approach is given for the gating of Continental Airlines at George W. Bush Intercontinental Airport in Houston (IAH).

Uncertainty and Sensitivity Analysis in Aircraft Operating Cost in Structural Design Optimization

The paper focuses on the development of an aircraft design optimization methodology that models uncertainty and sensitivity analysis in the tradeoff between manufacturing cost, structural requirements, and aircraft direct operating cost. Specifically, rather than only looking at manufacturing cost, direct operating cost is also considered in terms of the impact of weight on fuel burn, in addition to the acquisition cost to be borne by the operator. Ultimately, there is a tradeoff between driving design according to minimal weight and driving it according to reduced manufacturing cost. The analysis of cost is facilitated with a genetic-causal cost-modeling methodology, and the structural analysis is driven by numerical expressions of appropriate failure modes that use ESDU International reference data. However, a key contribution of the paper is to investigate the modeling of uncertainty and to perform a sensitivity analysis to investigate the robustness of the optimization methodology. Stochastic distributions are used to characterize manufacturing cost distributions, and Monte Carlo analysis is performed in modeling the impact of uncertainty on the cost modeling. The results are then used in a sensitivity analysis that incorporates the optimization methodology. In addition to investigating manufacturing cost variance, the sensitivity of the optimization to fuel burn cost and structural loading are also investigated. It is found that the consideration of manufacturing cost does make an impact and results in a different optimal design configuration from that delivered by the minimal-weight method. However, it was shown that at lower applied loads there is a threshold fuel burn cost at which the optimization process needs to reduce weight, and this threshold decreases with increasing load. The new optimal solution results in lower direct operating cost with a predicted savings of 640/m 2 of fuselage skin over the life, relating to a rough order-of-magnitude direct operating cost savings of $500,000 for the fuselage alone of a small regional jet. Moreover, it was found through the uncertainty analysis that the principle was not sensitive to cost variance, although the margins do change.

A model for the airlines’ fuel management strategies

In this paper, a model for the airlines’ optimal fuel management strategies is presented. The model determines the optimal amount of ferry fuel to be loaded at each airport for a given aircraft route. The problem is formulated in the form of a mathematical program with an objective function that captures the trade-off between cost saving associated with loading excess fuel at airports with lower fuel prices, and extra fuel burn cost and extra maintenance cost associated with flying the aircraft with heavier fuel weights. A set of experiments is performed using the model to examine the potential benefits and limitations of the proposed fuel ferrying strategies. The experiments consider different fuel price scenarios and various operational conditions for the flights. The results of these experiments are presented along with a case study that uses real aircraft routing data.