Model predictions of wind and turbulence profiles associated with an ensemble of aircraft accidents

The feasibility of predicting conditions under which wind/turbulence environments hazardous to aviation operations exist is studied by examining a number of different accidents in detail. A model of turbulent flow in the atmospheric boundary layer is used to reconstruct wind and turbulence profiles which may have existed at low altitudes at the time of the accidents. The predictions are consistent with available flight recorder data, but neither the input boundary conditions nor the flight recorder observations are sufficiently precise for these studies to be interpreted as verification tests of the model predictions

1.5 °C pathways for the Global Industry Classification (GICS) sectors chemicals, aluminium, and steel.

To achieve the goals of the Paris Climate Agreement, decarbonization targets and benchmarks for specific industry sectors are required. This opens up a whole new research area for energy modelling because although decarbonization pathways have been developed for countries, regions, or communities, few have been developed for industry sectors. In this research, we document the development of energy scenarios for industry sectors classified under the Global Industry Classification Standard (GICS). A bottom-up energy demand analysis based on market projections for the chemical, aluminium, and steel industries forms the basis for scenario development, with the aim of completely decarbonizing the electricity and process heat supplies for these industries by 2050. We document the individual steps in the energy demand analyses based on industry-specific market projections and energy intensities. In the last step, the carbon budget is calculated. The complete decarbonization of the industries analysed seems possible based on the available technology. Supplementary Information: The online version contains supplementary material available at 10.1007/s42452-022-05004-0

Measuring Organic Molecular Emission in Disks with Low Resolution Spitzer Spectroscopy

We explore the extent to which Spitzer IRS spectra taken at low spectral resolution can be used in quantitative studies of organic molecular emission from disks surrounding low mass young stars. We use Spitzer IRS spectra taken in both the high and low resolution modules for the same sources to investigate whether it is possible to define line indices that can measure trends in the strength of the molecular features in low resolution data. We find that trends in HCN emission strength seen in the high resolution data can be recovered in low resolution data. In examining the factors that influence the HCN emission strength, we find that the low resolution HCN flux is modestly correlated with stellar accretion rate and X-ray luminosity. Correlations of this kind are perhaps expected based on recent observational and theoretical studies of inner disk atmospheres. Our results demonstrate the potential of using the large number of low resolution disk spectra that reside in the Spitzer archive to study the factors that influence the strength of molecular emission from disks. Such studies would complement results for the much smaller number of circumstellar disks that have been observed at high resolution with IRS

Baby-Step Giant-Step Algorithms for the Symmetric Group

We study discrete logarithms in the setting of group actions. Suppose that $G$ is a group that acts on a set $S$. When $r,s \in S$, a solution $g \in G$ to $r^g = s$ can be thought of as a kind of logarithm. In this paper, we study the case where $G = S_n$, and develop analogs to the Shanks baby-step / giant-step procedure for ordinary discrete logarithms. Specifically, we compute two sets $A, B \subseteq S_n$ such that every permutation of $S_n$ can be written as a product $ab$ of elements $a \in A$ and $b \in B$. Our deterministic procedure is optimal up to constant factors, in the sense that $A$ and $B$ can be computed in optimal asymptotic complexity, and $|A|$ and $|B|$ are a small constant from $\sqrt{n!}$ in size. We also analyze randomized "collision" algorithms for the same problem

Just transition: Employment projections for the 2.0 °c and 1.5 °c scenarios

© The Author(s) 2019. This section provides the input data for two different employment development calculation methods: The quantitative analysis, which looks into the overall number of jobs in renewable and fossil fuel industries and the occupational analysis which looks into specific job categories required for the solar and wind sector as well as the oil, gas, and coal industry. Results are given with various figures and tables