47,285 research outputs found
Multi-aircraft environmentally-scored weather-resilient optimised 4D-trajectories
Weather phenomena are one of the biggest causes for significant delays and unpredictable disruptions within air traffic management (ATM) network operations. The changing global climate increases the future severity and frequency of these air traffic disturbing weather phenomena. This deteriorates the predictability of 4D trajectory ATM network planning and potentially increases the delays within air traffic operations. Furthermore, aviation itself has a responsibility to mitigate its climate impact to improve the long-term sustainability of the ATM operations and to contribute to the global effort towards the reduction of anthropogenic climate change. The SESAR2020 exploratory research project CREATE (Grant 890898) aims to find answers on how to improve the weather-resilience of ATM-operations and to reduce its climate impact. A concept of operations (ConOps) has been developed which describes an integrated trajectory optimisation framework to tactically define environmentally-scored optimised 4D trajectories, for a multi-aircraft airspace configuration, using advanced numerical weather prediction models, combined with air traffic control (ATC) driven demand-capacity balancing methods. The framework will be applied to an en-route use-case focusing on the unorganised traffic over the North Atlantic, and a Terminal Manoevring Area (TMA) use-case focusing on the Naples Capodichino airspace. The optimised trajectories aim to evade thunderstorms and contrail formation regions, whilst minimising CO2, non-CO2 and local air quality (LAQ) impacts.This project has received funding within the framework of the SESAR Joint Undertaking
project “Innovative Operations and Climate and Weather Models to Improve ATM Resilience
and Reduce Impacts” (SESARH2020-ER4 CREATE) within the European Union's Horizon
2020 research and innovation programme under grant agreement No 890898. The CREATE
consortium is formed by ATM/Meteo/Environmental specialists from the Royal Netherlands
Aerospace Centre (NLR), Universitat Politècnica de Catalunya (UPC), Centro Italiano
Ricerche Aerospaziali (CIRA), Università degli Studi di Napoli Parthenope (UNIPARTH,
project coordinator), ARIANET, Ilmatieteen Laitos (Finnish Meteorological Institute, FMI),
and Institute for Sustainable Society and Innovation (ISSNOVA).Peer ReviewedPostprint (published version
Formulation and optimization of the energy-based blended quasicontinuum method
We formulate an energy-based atomistic-to-continuum coupling method based on
blending the quasicontinuum method for the simulation of crystal defects. We
utilize theoretical results from Ortner and Van Koten (manuscript) to derive
optimal choices of approximation parameters (blending function and finite
element grid) for microcrack and di-vacancy test problems and confirm our
analytical predictions in numerical tests
Recommended from our members
Climate models miss most of the coarse dust in the atmosphere.
Coarse mineral dust (diameter, ≥5 μm) is an important component of the Earth system that affects clouds, ocean ecosystems, and climate. Despite their significance, climate models consistently underestimate the amount of coarse dust in the atmosphere when compared to measurements. Here, we estimate the global load of coarse dust using a framework that leverages dozens of measurements of atmospheric dust size distributions. We find that the atmosphere contains 17 Tg of coarse dust, which is four times more than current climate models simulate. Our findings indicate that models deposit coarse dust out of the atmosphere too quickly. Accounting for this missing coarse dust adds a warming effect of 0.15 W·m-2 and increases the likelihood that dust net warms the climate system. We conclude that to properly represent the impact of dust on the Earth system, climate models must include an accurate treatment of coarse dust in the atmosphere
Fast calibration of the Libor Market Model with Stochastic Volatility and Displaced Diffusion
This paper demonstrates the efficiency of using Edgeworth and Gram-Charlier
expansions in the calibration of the Libor Market Model with Stochastic
Volatility and Displaced Diffusion (DD-SV-LMM). Our approach brings together
two research areas; first, the results regarding the SV-LMM since the work of
Wu and Zhang (2006), especially on the moment generating function, and second
the approximation of density distributions based on Edgeworth or Gram-Charlier
expansions. By exploring the analytical tractability of moments up to fourth
order, we are able to perform an adjustment of the reference Bachelier model
with normal volatilities for skewness and kurtosis, and as a by-product to
derive a smile formula relating the volatility to the moneyness with
interpretable parameters. As a main conclusion, our numerical results show a
98% reduction in computational time for the DD-SV-LMM calibration process
compared to the classical numerical integration method developed by Heston
(1993)
- …