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Data‐driven urban modelling: the case of explainable detection of Urban Heat Island (UHI)
No full text<p>Nasim Eslamirad Doctoral Thesis completed draft.</p>
Virtual Green Planner 2021 Unity project
No full text<p>Virtual Green Planner is an interactive 3d software for concept-level collaborative urban and green space planning and analysis developed in the GreenTwins project. This is the Unity project of the 2021 version of the software.</p>
Green twins - urban tempo source code
No full text<p>This is the latest source code package for urban tempo pilot app for Finest Twins internal use.</p><p><strong>Important: </strong>in order to reuse the code, the software components licensed by the author will have to be removed or bought a new license for! Please open Unity package manager upon opening the project to list the the assets.</p>
GreenTwins individual plant and plant cover type data
No full text<p>This dataset contains materials for visualizing GreenTwins pilot area individual plants and plant cover types for 3D city models and digital twins. The data follow the structure defined in <a href="https://data.taltech.ee/records/m543b-6a059?token=eyJhbGciOiJIUzUxMiJ9.eyJpZCI6IjI2YTczY2I4LWZlODMtNGI0ZS1iN2YyLWI2NWNjMGM3ZjJkMyIsImRhdGEiOnt9LCJyYW5kb20iOiIxYWIwNjhmZmRhYWNjY2Q5ZWExZTQ0MDk5OWQ5MzBmNCJ9.ZYRmCRcWQAEBlZkFb1CGUf0RgtX63qWdX-V5jg0tsDZfVDhuVJrNzjQN9iEGtBBtR4E-bChQbVeSZgZ2B09IfA">GreenTwins information model on individual plants and plant cover types</a>, which is a draft of a vegetation model extension based on the CityGML 2.0 standard. The modelled species have been selected in order to be able to visualise (the growth of) vegetation of the <a href="https://data.taltech.ee/records/297eg-k0050?token=eyJhbGciOiJIUzUxMiJ9.eyJpZCI6ImY5NDNkN2NkLWZjMjctNGJlYS05ZmJkLTcxYmNiM2U2NTg2MyIsImRhdGEiOnt9LCJyYW5kb20iOiI5MmZjMjUzNDhlZDUzYmIyYmU3ODM2MGZhMjI3YTY4YyJ9.38GKEw2cZUdSPCu2Q6IYLXNqRPpE2jVYuINXMuCdDh8968pN6Bi6eABNc8bGy--RpdgjOaWnOia_fN9HX0Uq6Q">GreenTwins pilot areas in Tallinn, Estonia, and Helsinki, Finland</a>.</p><p>The GreenTwins vegetation data is defined in terms of Individual plants (point data) and larger Plant cover polygons. Individual plants can be either trees or shrubs, whereas each Plant cover polygons can be defined to contain a species composition consisting of trees, shrubs and Herbaceous plants. Trees and shrubs can be visualised in 3D visualisation applications as 3D models, with plant expert-defined growth curves and seasonality information. Herbaceous plants are visualised as billboards, the outlook of which may vary from short-cut (due to modelled maintenance) to full-grown and to seasonal versions.</p><p>This package contains materials for the construction of Tree and Shrub growth-series 3D models, from photography instructions to photographs (trees, shrubs and a selection of herbaceous plants), hand-modelled textures and 3D twigs (trees and shrubs), algorithmically modelled 3D branch structures in various Levels-of-Detail (trees and shrubs), example 3D models of a selection of example species (trees) in various ages and Levels-of-Detail, and an example herbaceous plant photograph and billboard. The 3D modelling algorithm used to produce the growth-series of branch 3D models for trees and shrubs) in various Levels-of-Detail is published separately (Fabritius <i>et al. </i>manuscript). The algorithmically created tree branches were connected to hand-made twigs using the GreenTwins web application available at <a href="http://zircon-coal-mechanic.glitch.me/">zircon-coal-mechanic.glitch.me</a>. Tree and shrub dimensions were projected into the future using a projection algorithm (not published).</p>
Virtual Green Planner 2023 Windows 64-bit standalone build
No full text<p>Virtual Green Planner is an interactive 3d software for concept-level collaborative urban and green space planning and analysis. This is the Windows 64-bit standalone build of the project.</p>
Genome-scale modelling-based discovery of metabolic strategies in oleaginous yeast Rhodotorula toruloides
No full text<p>Oral presentation was delivered at the 8th Conference on Physiology of Yeasts and Filamentous Fungi on June 7, 2023, in Cork, Ireland.</p>
Ultimate strength assessment of stiffened panel using non-linear mechanical behavior of an equivalent single layer: grillage FE model used for analysis
No full text<p>This example shows how the ESL can be applied in the ultimate strength structural analysis in Abaqus finite element software. In other words, ESL methodology is applied only in some parts of the structure while larger structural supporting components like girders and webframes are still modeled explicitly. FIles include also the Full_3D_FEM model used for validating the ESL model.</p><p>Dataset includes following files:</p><p>1. ESL_nonlinear_grillage.inp - this is Abaqus input file for running the ESL nonlinear grillage model.</p><p>2. ugensFINALv_master.for - this defines the nonlinear stiffness or ABD matrix. This is called by input file (ESL_nonlinear_grillage.inp ).</p><p>3. Full_3D_FEM.inp - Full_3D_FEM model used for validating the ESL model.</p>
Swell hindcast data for the Baltic Sea
No full text<p>Swell hindcast data from 1999 to 2018. These data are based on the simulation made by The Baltic Monitoring Forecasting Centres(BAL MFC) Production Unit at Finnish Meteorological Institute (FMI) for the Copernicus Marine Environment Monitoring Service (CMEMS) for the product BALTICSEA_REANALYSIS_WAV_003_015. However, it contains variables not available in the CMEMS products.</p><p>These data are documented in the publication Björkqvist, J.-V., Pärt, S., Alari, V., Rikka, S., Lindgren, E., and Tuomi, L.: Swell hindcast statistics for the Baltic Sea, Ocean Sci. Discuss. [preprint], https://doi.org/10.5194/os-2021-62, in review, 2021. The figures in the publication can be reproduced using these data.</p><p>Swell dominates the global sea state and therefore significantly contributes to processes at the air and seabed interfaces. Nonetheless, smaller enclosed seas are detached from the global swell climate. We present swell statistics for the Baltic Sea using 20 years of swell partitioned model data. The swell significant wave height was mostly under 2 m, and in the winter (DJF) the mean significant swell height was typically less than 0.4 m; higher swell was found at limited nearshore areas. Swell waves were typically short (under 5 s), with mean periods over 8 s being rare. In open-sea areas the average ratio of swell energy (to total energy) was below 0.4 – significantly less than in World Ocean. Certain coastal areas were swell dominated over half the times, mostly because of weak winds (U < 5 ms−1 ) rather than high swell heights. Swell dominated events with a swell height over 1 m typically lasted under 10 h. A cross-correlation analysis indicates that swell in the open sea is mostly generated from local wind-sea when wind decays (dominant time lag roughly 15 h). Near the coast, however, the results suggests that the swell is partially detached from the local wind-waves, although not necessarily from the weather system that generates them</p>