Plastic trees

Pirk, Sören; Stava, Ondrej; Kratt, Julian; Said, Michel Abdul Massih; Neubert, Boris; Mĕch, Radomír; Beneš, Bedřich; Deußen, Oliver

doi:10.1145/2185520.2185546

Cited by 86 publications

(6 citation statements)

References 42 publications

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“…Examples of SSM are LIGNUM [ 13 ], a functional-structural plant model based on the physiological principles of growth of pine trees, but also applicable to other tree forms [ 32 ]; self-organizing tree model [ 3 ] based on the heuristic principles of growth, capable of producing various tree shapes and used in computer graphics; plastic trees [ 4 ], procedural growth models used in computer graphics; AMAP/GreenLab (see e.g., [ 33 , 34 ]), a modeling approach to generate FSPM based upon empirical rules of growth with some physiological processes taken into account.…”

Section: Resultsmentioning

confidence: 99%

Bayes Forest: a data-intensive generator of morphological tree clones

et al. 2017

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Detailed and realistic tree form generators have numerous applications in ecology and forestry. For example, the varying morphology of trees contributes differently to formation of landscapes, natural habitats of species, and eco-physiological characteristics of the biosphere. Here, we present an algorithm for generating morphological tree “clones” based on the detailed reconstruction of the laser scanning data, statistical measure of similarity, and a plant growth model with simple stochastic rules. The algorithm is designed to produce tree forms, i.e., morphological clones, similar (and not identical) in respect to tree-level structure, but varying in fine-scale structural detail. Although we opted for certain choices in our algorithm, individual parts may vary depending on the application, making it a general adaptable pipeline. Namely, we showed that a specific multipurpose procedural stochastic growth model can be algorithmically adjusted to produce the morphological clones replicated from the target experimentally measured tree. For this, we developed a statistical measure of similarity (structural distance) between any given pair of trees, which allows for the comprehensive comparing of the tree morphologies by means of empirical distributions describing the geometrical and topological features of a tree. Finally, we developed a programmable interface to manipulate data required by the algorithm. Our algorithm can be used in a variety of applications for exploration of the morphological potential of the growth models (both theoretical and experimental), arising in all sectors of plant science research.

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Section: Resultsmentioning

confidence: 99%

Bayes Forest: a data-intensive generator of morphological tree clones

et al. 2017

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“…Similarly, the tree is affected by local properties of the environment, such as the presence of obstacles, which control the spread of grass and direct the growth of the roots of tree. The result of this interaction is adaptation to the environment and efficiency in the use of the available resources [33,34].…”

Section: Introduction and Motivation Of The Workmentioning

confidence: 99%

Exergy As a Measure of Sustainable Retrofitting of Buildings

Bandera

Mardones

et al. 2018

Energies

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This study presents a novel optimization methodology for choosing optimal building retrofitting strategies based on the concept of exergy analysis. The study demonstrates that the building exergy analysis may open new opportunities in the design of an optimal retrofit solution despite being a theoretical approach based on the high performance of a Carnot reverse cycle. This exergy-based solution is different from the one selected through traditional efficient retrofits where minimizing energy consumption is the primary selection criteria. The new solution connects the building with the reference environment, which acts as "an unlimited sink or unlimited sources of energy", and it adapts the building to maximize the intake of energy resources from the reference environment. The building hosting the School of Architecture at the University of Navarra has been chosen as the case study building. The unique architectural appearance and bespoke architectural characteristics of the building limit the choices of retrofitting solutions; therefore, retrofitting solutions on the façade, roof, roof skylight and windows are considered in multi-objective optimization using the jEPlus package. It is remarkable that different retrofitting solutions have been obtained for energy-driven and exergy-driven optimization, respectively. Considering the local contexts and all possible reference environments for the building, three "unlimited sinks or unlimited sources of energy" are selected for the case study building to explore exergy-driven optimization: the external air, the ground in the surrounding area and the nearby river. The evidence shows that no matter which reference environment is chosen, an identical envelope retrofitting solution has been obtained.

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“…Light distribution and proximity to solid objects and other trees realistically influence the growth simulation of trees in Pirk et al (2012). Following on from this work, Pirk et al (2014) presents a novel method for simulating tree growth with turbulent wind fields.…”

Section: Geometric Simulation Of Biological Creaturesmentioning

confidence: 99%

Simulating the Geometric Growth of the Marine Sponge Crella incrustans

O'Hagan

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<p>Understanding how marine sponges grow is an important field of study for marine biologists, as it helps them predict how a marine sponge will grow under certain environmental conditions. Simulating the growth is one of the most powerful ways to help marine biologists understand sponge growth, as many scenarios can be simulated with different simulation parameters using few resources. This thesis describes a way to simulate and grow geometric models of the marine sponge Crella incrustans. The simulation improves upon state-of-the-art procedural modelling work by simulating fluid flow and nutrient dispersion in the ocean, simulating sponge growth, and changing the skeletal architecture of the sponge in the growth model. The change in skeletal architecture and other simulation parameters are then evaluated qualitatively against photos of a real-life Crella incrustans sponge and state-of-the-art work, and the performance of the simulation is qualitatively evaluated by comparing simulation times for different parameters. The results support the hypothesis that changing the skeletal architecture from radiate accretive to Halichondrid produces a sponge model which is closer in resemblance to the photos than the prior work's sponge model.</p>

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Plastic trees

Cited by 86 publications

References 42 publications

Bayes Forest: a data-intensive generator of morphological tree clones

Bayes Forest: a data-intensive generator of morphological tree clones

Exergy As a Measure of Sustainable Retrofitting of Buildings

Simulating the Geometric Growth of the Marine Sponge Crella incrustans

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