scholarly journals DEVELOPMENT AND ANALYSIS OF 2D FLIGHT PLANNING SEARCH ENGINE CONSIDERING FUSION OF SWIM DATA

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Michael Hius Sentoso ◽  
Neno Ruseno
Keyword(s):  
Search Engine ◽  
Economic Value ◽  
Weather Condition ◽  
Weather Data ◽  
Flight Planning ◽  
Navigation Data ◽  
Flight Plan ◽  
Optimum Route ◽  
Python Programming ◽  
Alternate Routes

Flight planning is one of the essential factors of the airline operation. The selection of routes will determine the economic value of the flight. However, some conditions may prevent the flight to use the most optimum route due to airspace restriction or weather condition. The research aims to develop a search engine program that uses dynamic flight parameters that considers fusion of System Wide Information Management (SWIM) data including weather data and NOTAM to produce the most optimum route in 2D flight planning. The Dijkstra’s pathfinding is implemented in Python programming language to produce the flight plan. The navigation data used is enroute airway in Indonesian FIR regions. The scenario used is a flight from Jakarta to Makassar with duration of 2 hours flight with considering the effect of restricted airspace and weather blockage during in-flight. The study also uses the optimum route produced by the algorithm to be compared with the possible alternate routes to define how optimum the route is. Adding a restricted airspace parameter will result in a new optimum flight plan that able avoids the airspace and the most minimum distance. The effect of external wind parameter could influence the optimum route which may vary depends on the speed of the wind.

scholarly journals Aircraft Trajectory Prediction using LSTM Neural Network with Embedded Convolutional Layer

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Yutian Pang ◽  
Nan Xu ◽  
Yongming Liu
Keyword(s):  
Los Angeles ◽  
Network Architecture ◽  
Mean Squared Error ◽  
Weather Condition ◽  
Weather Data ◽  
Flight Data ◽  
The Real ◽  
International Airport ◽  
Flight Plan ◽  
Convective Weather

The development of convective weather avoidance algorithm is crucial for aviation operations and it is also a key objective of the next generation air traffic management system. This paper proposes a novel network architecture that embeds convolutional layers into long short-time memory (LSTM) cells to predict the trajectory, based on the convective weather condition along the flight plan before the aircraft takeoff. The data used in the experiments are history flight track data, the last on-file flight plan, and the time-dependent convective weather map. The history flight data are taken from NASA Sherlock database and the weather data used in this paper is the Echo Top (ET) convective weather product from Corridor Integrated Weather System (CIWS). The experiment is conducted using three months history data over the period from Nov 1, 2018 through Feb 5, 2019 with the flights from John F. Kennedy International Airport (JFK) to Los Angeles International Airport (LAX) but the methodology can be applied to the flights between any arbitrary two airports. Interpolation is performed on flight plans and real history tracks to fix the fold number of LSTM cell and also reduce computation complexity. The training loss is defined as the standard Mean Squared Error (MSE) of the predicted tracks and the real history tracks. Adam optimizer is used for backpropagation. Learning from the real historical flight data, the out-of-sample test shows that 47.0\% of the predicted flight tracks are able to reduce the deviation compared to the last on-file flight plan. The overall variance is reduced by 12.3\%.

scholarly journals Examining the Impact of Adverse Weather on Travel Time Reliability of Urban Corridors in Shanghai

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yajie Zou ◽  
Ting Zhu ◽  
Yifan Xie ◽  
Linbo Li ◽  
Ying Chen
Keyword(s):  
Travel Time ◽  
Weather Condition ◽  
Time Of Day ◽  
Weather Data ◽  
Time Variability ◽  
Travel Time Reliability ◽  
Time Data ◽  
Adverse Weather Condition ◽  
Adverse Weather ◽  
The Impact

Travel time reliability (TTR) is widely used to evaluate transportation system performance. Adverse weather condition is an important factor for affecting TTR, which can cause traffic congestions and crashes. Considering the traffic characteristics under different traffic conditions, it is necessary to explore the impact of adverse weather on TTR under different conditions. This study conducted an empirical travel time analysis using traffic data and weather data collected on Yanan corridor in Shanghai. The travel time distributions were analysed under different roadway types, weather, and time of day. Four typical scenarios (i.e., peak hours and off-peak hours on elevated expressway, peak hours and off-peak hours on arterial road) were considered in the TTR analysis. Four measures were calculated to evaluate the impact of adverse weather on TTR. The results indicated that the lognormal distribution is preferred for describing the travel time data. Compared with off-peak hours, the impact of adverse weather is more significant for peak hours. The travel time variability, buffer time index, misery index, and frequency of congestion increased by an average of 29%, 19%, 22%, and 63%, respectively, under the adverse weather condition. The findings in this study are useful for transportation management agencies to design traffic control strategies when adverse weather occurs.

scholarly journals Weather Prediction using Advanced Machine Learning Techniques

2021 ◽  
Vol 2089 (1) ◽  
pp. 012059
Author(s):  
G. Hemalatha ◽  
K. Srinivasa Rao ◽  
D. Arun Kumar
Keyword(s):  
Linear Relationship ◽  
Weather Prediction ◽  
Weather Condition ◽  
Weather Conditions ◽  
Machine Learning Techniques ◽  
Weather Data ◽  
Learning Techniques ◽  
Proposed Model ◽  
Non Linear ◽  
The Relationship

Abstract Prediction of weather condition is important to take efficient decisions. In general, the relationship between the input weather parameters and the output weather condition is non linear and predicting the weather conditions in non linear relationship posses challenging task. The traditional methods of weather prediction sometimes deviate in predicting the weather conditions due to non linear relationship between the input features and output condition. Motivated with this factor, we propose a neural networks based model for weather prediction. The superiority of the proposed model is tested with the weather data collected from Indian metrological Department (IMD). The performance of model is tested with various metrics..

scholarly journals In-Flight Aircraft Trajectory Optimization within Corridors Defined by Ensemble Weather Forecasts

Aerospace ◽  
2020 ◽  
Vol 7 (10) ◽  
pp. 144 ◽  
Author(s):  
Martin Lindner ◽  
Judith Rosenow ◽  
Thomas Zeh ◽  
Hartmut Fricke
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Trajectory Optimization ◽  
Air Traffic ◽  
Weather Data ◽  
Parameter Uncertainties ◽  
Weather Forecasts ◽  
Fuel Savings ◽  
Flight Plan ◽  
Aircraft Trajectory

Today, each flight is filed as a static route not later than one hour before departure. From there on, changes of the lateral route initiated by the pilot are only possible with air traffic control clearance and in the minority. Thus, the initially optimized trajectory of the flight plan is flown, although the optimization may already be based upon outdated weather data at take-off. Global weather data as those modeled by the Global Forecast System do, however, contain hints on forecast uncertainties itself, which is quantified by considering so-called ensemble forecast data. In this study, the variability in these weather parameter uncertainties is analyzed, before the trajectory optimization model TOMATO is applied to single trajectories considering the previously quantified uncertainties. TOMATO generates, based on the set of input data as provided by the ensembles, a 3D corridor encasing all resulting optimized trajectories. Assuming that this corridor is filed in addition to the initial flight plan, the optimum trajectory can be updated even during flight, as soon as updated weather forecasts are available. In return and as a compromise, flights would have to stay within the corridor to provide planning stability for Air Traffic Management compared to full free in-flight optimization. Although the corridor restricts the re-optimized trajectory, fuel savings of up to 1.1%, compared to the initially filed flight, could be shown.

Flight Planning with a Digital Computer

1963 ◽  
Vol 44 (6) ◽  
pp. 355-363
Author(s):  
Peter E. Kraght
Keyword(s):  
Digital Computer ◽  
Operating Cost ◽  
Cost Savings ◽  
Flight Crew ◽  
Planning Program ◽  
Flight Planning ◽  
Commercial Airline ◽  
Manual Selection ◽  
Optimum Route ◽  
Selection Of

Safety, passenger comfort, and operating economy require that commercial airline flights be preflight planned. There are many route and altitude combinations between origination and destination. Manual selection of the best is tedious, costly in man-hours, and never perfect. A digital computer can do the job quickly, using few man-hours, with a higher order of perfection. American Airlines contracted with IBM to develop jointly a flight planning program for a 60,000 digit IBM 1620 computer. The program was placed into operation on 4 February 1962 and quickly expanded to produce 5000 lines of flight plans for over 200 trips daily. Operating cost savings are on the order of several million dollars annually. The program continuously surrounds an aircraft with a set of prognostic temperatures and winds valid by the craft's clocks at the plane's altitude. The program also selects the optimum route and the optimum altitude profile on the selected route. Flight plans on the optimum route at the optimum altitude are automatically delivered to the flight crew and the controlling dispatchers.

Review of Passive Downdraught Evaporative Cooling Technique and its Application

2013 ◽  
Vol 390 ◽  
pp. 691-695 ◽  
Author(s):  
Jing Qiu ◽  
Bao Feng Li ◽  
Yu Qiu
Keyword(s):  
Global Climate ◽  
Low Cost ◽  
Evaporative Cooling ◽  
Weather Condition ◽  
Cost Effective ◽  
Weather Data ◽  
North West ◽  
Direct Evaporative Cooling ◽  
Key Factor ◽  
Cooling Technique

Direct evaporative cooling has long been demonstrated as an energy efficient ,cost effective and no CFCs emission means for space cooling in hot dry regions .With the aggravating of the global climate warming and energy crisis, using passive cooling technique will be a good solution . In this paper, the theory of passive downdraught evaporative cooling techniques is analyzed. It is an environmental friendly technique in that it can provide more fresh air than the conventional air-conditionings, and also low cost on operation and no CFCs emission compared with conventional air-conditionings. In this paper, some cases will be introduced .The successful PDEC cases in hot dry areas show weather condition is the key factor for the feasibility using PDEC technique. From the analysis on the weather data in Turpan, which presents a typical climatic character in North-west China , predicts a great feasibility of using PDEC technique in public architectures.

scholarly journals DroneTank: Planning UAVs’ Flights and Sensors’ Data Transmission under Energy Constraints

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2913 ◽  
Author(s):  
Runqun Xiong ◽  
Feng Shan
Keyword(s):  
Dynamic Programming ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm ◽  
Energy Budgets ◽  
Water Tank ◽  
Transmission Scheduling ◽  
Flight Planning ◽  
Flight Plan ◽  
Joint Problem ◽  
Transmission Schedule

We consider an Unmanned Aerial Vehicle (UAV, also known as drone) as an aerial sink to travel along a natural landscape or rural industrial linear infrastructure to collect data from deployed sensors. We study a joint schedule problem that involves flight planning for the drone and transmission scheduling for sensors, such that the maximum amount of data can be collected with a limited individual energy budget for the UAV and the sensors, respectively. On one hand, the flight planning decides the flight speed and flight path based on sensor locations, energy budgets, and the transmission schedule. On the other hand, the transmission schedule decides for each sensor when to deliver data and what transmission power to use based on the energy budgets and flight plan. By observing three import optimality properties, we decouple the joint problem into two subproblems: drone flight planning and sensor transmission scheduling. For the first problem, we propose a dynamic programming algorithm to produce the optimal flight planning. For the second problem, with a flight plan as input, we introduce a novel technique (water-tank), which together with dynamic programming, is the key to achieve an optimal transmission schedule that maximizes data collection. Simulations show that the separately determined flight plan and transmission schedule are near-optimal for the original joint problem.

Simplified Flight Planning

1951 ◽  
Vol 4 (3) ◽  
pp. 248-259
Author(s):  
W. G. Hamer
Keyword(s):  
Rapid Method ◽  
Weather Conditions ◽  
Direct Approach ◽  
Flight Planning ◽  
Flight Plan ◽  
Fuel Loads ◽  
The Future ◽  
The One

The basic procedures used by most airlines to compile their flight plans are very similar, and are by no means as simple as they could be. When a choice of routes exists it is the normal practice to compile a series of flight plans from which the one giving the most advantageous route in the prevailing weather conditions is selected. In the absence of a direct approach to the problem of selecting the best route, the method of comparing different flight plans is improved by increasing the number of plans; it is therefore desirable that a method of speeding up the process of compilation should be evolved so that a greater number of plans can be prepared. Also the increased aircraft speeds which are to be expected in the future, and the requirement to reduce fuel loads, especially fuel reserves, to a minimum call for some rapid method of modifying the flight plan on receipt of in-flight forecasts and observations.

In-Flight Planning and Intelligent Pilot Aids for Emergencies and Non-Nominal Flight Conditions Using Automatically Generated Flight Plans

2007 ◽  
Vol 51 (2) ◽  
pp. 55-59 ◽  
Author(s):  
Vittesh V. Kalambi ◽  
Amy R. Pritchett ◽  
Daniel P. J. Bruneau ◽  
Mica R. Endsley ◽  
David B. Kaber
Keyword(s):  
Real Time ◽  
Performance Measures ◽  
Time Of Flight ◽  
Environmental Information ◽  
Flight Path ◽  
Path Generation ◽  
Flight Planning ◽  
Flight Plan ◽  
Direct Route

The following study examined pilots' performance on in-flight planning tasks in non-nominal and emergency conditions using autoflight systems capable of automatically generating a flight plan. The findings revealed that autoflight systems did not significantly impact replanning, while the scenarios did significantly affect the primary performance measures of distance flown and time of flight. Additionally, pilots selected the most direct route when possible and did not distinguish between emergency and non-nominal flight conditions. Pilots also favored use of the automatically generated flight plans. We conclude that: 1) automatic flight path generation benefits in-flight replanning primarily by reducing workload in emergencies; and 2) such a system will require real time access to environmental information, including traffic, weather and terrain, be considered simultaneously.

scholarly journals Evaluating the Relationship between Rainfall, Maximum Temperature and Convective Systems over Selected Cities in Nigeria

2019 ◽  
pp. 1-18
Author(s):  
B. M. Dada
Keyword(s):  
Negative Correlation ◽  
Positive Impact ◽  
Weather Condition ◽  
Weather Data ◽  
Maximum Temperature ◽  
Convective Systems ◽  
Annual Variations ◽  
Mapping Techniques ◽  
June July ◽  
The Relationship

The convective systems and maximum temperature are key weather parameters that affect various sectors of the Nigerian economy, especially Agriculture, health and transportation. Agriculture which is the mainstay of the economy of Nigeria is weather driven. A balanced weather condition brings about good crop yield which in turn have a positive impact on the economy. The aim of this study was to evaluate the relationship between rainfall, maximum temperature and convective activities over Ikeja, Abuja and Kano cities in Nigeria. Monthly weather data of squall, thunderstorms, maximum temperature and rainfall were obtained from the archives of the Nigeria Meteorological Agency for the period between 1985 and 2015 (30 years). Seasonal and inter-annual variations and relationships between the parameters were analyzed. Over Ikeja the result highlighted a gradual increase in these parameters from January to May/June, while the decrease began from October through to December. Further analysis revealed two separate peak periods for these parameters, with rainfall having its peaks in the months of June and September; Thunderstorm, June and October, and squall attaining its maxima in May and October. Over Kano, March, April and May (MAM) and September, October and November (SON) period indicated that the rain that fell during that period had positive correlation while December, January and February (DJF) and June, July and August (JJA) has a negative correlation. Over Abuja, DJF, MAM and SON showed positive while JJA shows a negative correlation. There will be a need for further studies which will consider the role(s) being played by the various triggering mechanisms and the extent to which the influence of the occurrence of these convective activities rainfall and maximum temperature. The utilization of modelling and mapping techniques may also give further insight into the variation of these systems and a clue to issuing more accurate forecasts and predictions.

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