A physiological Plant Growth Simulation Engine Based on Accurate Radiant Energy Transfer

We present a new model for plant growth simulation, taking into account the eco-physiological processes driving plant development with unprecedented fidelity. The growth model, based on a physiological analysis, essentially simulates the internal function of the plant, and has been validated against measured biological data with excellent results. We show how to account for the influence of light through photosynthesis, and thereby incorporate the effects of a given plant's immediate environment on its architecture, shape and size. Since biological matter is controlled by water transpiration and received radiant enery, the model requires efficient and accurate simulation of radiant energy exchanges. We describe a complete lighting simulation system tailored for the difficult case of plants, by adapting state-of-the-art techniques such as hierarchical instanciation for radiosity and general BRDF modeling. Our results show that (a) our lighting simulation system efficiently provides the required information at the desired level of accuracy, and (b) the plant growth model is extremely well calibrated against real plants and (c) the combined system can simulate many interesting growth situations with direct feedback from the environment on the plant's characteristics. Applications range from landscape simulation to agronomical and agricultural studies, and to the design of virtual plants responding to their environment

Integrated model concept for district energy management optimisation platforms

District heating systems play a key role in reducing the aggregated heating and domestic hot water production energy consumption of European building stock. However, the operational strategies of these systems present further optimisation potential, as most of them are still operated according to reactive control strategies. To fully exploit the optimisation potential of these systems, their operations should instead be based on model predictive control strategies implemented through dedicated district energy management platforms. This paper describes a multiscale and multidomain integrated district model concept conceived to serve as the basis of an energy prediction engine for the district energy management platform developed in the framework of the MOEEBIUS project. The integrated district model is produced by taking advantage of co-simulation techniques to couple building (EnergyPlus) and district heating system (Modelica) physics-based models, while exploiting the potential provided by the functional mock-up interface standard. The district demand side is modelled through the combined use of physical building models and data-driven models developed through supervised machine learning techniques. Additionally, district production-side infrastructure modelling is simplified through a new Modelica library designed to allow a subsystem-based district model composition, reducing the time required for model development. The integrated district model and new Modelica library are successfully tested in the Stepa Stepanovic subnetwork of the city of Belgrade, demonstrating their capacity for evaluating the energy savings potential available in existing district heating systems, with a reduction of up to 21% of the aggregated subnetwork energy input and peak load reduction of 24.6%.The research activities leading to the described developments and results, were funded by the European Uniońs Horizon 2020 MOEEBIUS project, under grant agreement No 680517. Authors would like to ex-press their gratitude to the operator of the Vozdovac district heating system (Beogradske elektrane) for the specifications used to develop and calibrate the models, and to Solintel M&P, SL for developing the initial versions of the EnergyPlus models (including only the geometrical and constructive definition of the buildings), in the framework of the MOEEBIUS project

AN EFFICIENT SEGMENTATION ALGORITHM FOR ENTITY INTERACTION

The inventorying of biological diversity and studies in biocomplexity require the management of large electronic datasets of organisms. While species inventory has adopted structured electronic databases for some time, the computer modelling of the functional interactions between biological entities at all levels of life is still in the stage of development. One of the challenges for this type of modelling is the biotic interactions that occur between large datasets of entities represented as computer algorithms. In real-time simulation that models the biotic interactions of large population datasets, the use of computational processing time could be extensive. One way of increasing the efficiency of such simulation is to partition the landscape so that entities need only traverse its local space for entities that falls within the interaction proximity. This article presents an efficient segmentation algorithm for biotic interactions for research related to the modelling and simulation of biological systems

Interactive Visualization of Virtual Orchard

Colloque avec actes et comité de lecture. internationale.International audienceIn the application in agriculture and forestry of modeling and simulation of three-dimensional plant growth, interactive visualization of virtual plant community using recently developed model processing and model simplification technology in computer graphics and virtual reality becomes a new focus. The new methods in this paper are the simplifications of models with special shapes: Progressive Leaves Union and View-Dependent Branch Mesh Reorganization, where the originalities include: (1) topological structure modifying progressive simplification with error analysis for sparse parts of a plant, i.e., leaves, flowers and fruits; (2) multi-resolution remeshing for continuous parts, mainly branches; (3) simplification degree determined by viewpoint position, permitted errors, display resolution, and different positions of plants. Therefore, plant models with high proportional simplification are obtained keeping original visual effect within permission scope. Plant modeling and the growth simulation methods in AMAP team are used and plant-positioning data are generated from software AMAP-OrchestraTM as data source. An interactive navigation in virtual orchard is accomplished, and a virtual apple orchard is presented as an example. All of this work is taken in the organization and environment of the high performance computation and visualization in ISA and SILVES projects of INRIA

Adaptation of the GreenLab model for analyzing sink-source relationships in Chinese Pine saplings

International audienceSince the 1990s, a new generation of models has emerged to simulate tree growth with consideration of both tree structure and functional processes. However, calibration of these functional-structural models (FSMs) often remains an open problem due to the topological complexity of trees and to the heavy measurements required. In this paper, we explore a possible way for dealing with the fitting problem, based on the GreenLab model approach. Detailed organ-level data including topological and geometrical measurements were collected on eight Chinese Pine saplings (Pinus tabulaeformis carr.) grown near Beijing. Adaptation of GreenLab to introduce a flexible modeling for biomass allocation to ring growth is presented. The main assumptions, such as allometry rules and sink relationships, were investigated. The problem of calibration of a complex branching structure was solved by defining an average tree. The results were interpreted with particular focus on the ones concerning the hidden mechanisms of secondary growth

Mathematical and computational methods for functional-structural plant modelling using L-systems and their applications to modelling the kiwifruit vine

Mathematical and computational modelling provides a framework within which the understanding of plant growth and development can be further advanced. By abstracting from reality, it provides a way to test our hypotheses of the behaviour of real plants, offers simple explanations of observed phenomenon, and allows us to make quantitative predictions under new conditions. In particular, functional-structural plant models are well suited for these types of studies, because they capture the complex interactions between plant architecture and physiological processes as governed by the environment. The aim of this research was to investigate and develop mathematical and computational methods for use in functional-structural plant modelling, and, in particular, to allow easy incorporation of various aspects of plant growth and development at different spatial and temporal scales into one complex dynamical system. To this end, a functional-structural kiwifruit vine model was constructed using an L-system based plant modelling platform. The model was used to integrate the kiwifruit vine's architectural development with mechanistic modelling of carbon transport and allocation. The branching pattern was captured at the individual shoot level by modelling axillary shoot development using a discrete-time Markov chain. An existing carbon transport-resistance model was extended to account for several source/sink components of individual plant elements. The model was then interfaced with the light simulation program QuasiMC, and used to estimate the absorbed irradiance of each leaf during the course of the vine's development. Furthermore, the operation of QuasiMC was illustrated and analysed using an abstract virtual canopy (a triangle mix) and the kiwifruit vine model as examples. Several simulations, inspired by biological experiments, were performed to illustrate the capabilities of the kiwifruit model, including the plastic response of shoot growth to local carbon supply, the branching patterns of two Actinidia species, the effect of carbon limitation and topological distance on fruit size, and the complex behaviour of sink competition for carbon. The model was able to represent the major features of kiwifruit growth and function, and provided a solid foundation for investigating plant modelling methodology. A major challenge in functional-structural plant modelling is the integration of several previously modelled aspects of plant function into one model. To meet this challenge, the kiwifruit model provided the inspiration for extending L-systems with a new modules of modules approach, which combines pseudo-L-systems with sets of productions and lists of modules to consider within those sets. Using the new approach, a model of a kiwifruit shoot was constructed that integrates previously modelled aspects of the shoot's architecture with carbon dynamics, apical dominance and biomechanics. In the short term, the kiwifruit model will be used to help explore the vine's physiology and genetic control. For example, it will help give a physiological interpretation of experimental results on competition for carbon between vegetative and reproductive components of the vine. In the long term, it will serve as the basis for development of decision support systems to help improve kiwifruit production

Progressive Polygon Foliage Simplification

Colloque avec actes et comité de lecture. nationale.National audienceA leaf polygon decimation method, Progressive Leaves Union (PLU), is presented to gradually diminish the number of sparse polygons while approximately keeping the spatial occupation and color distribution of the foliage. In each step of decimation, a new leaf is constructed to represent other two leaves close in position and similar in united. All steps of simplification are recorded in preprocessing, and appropriate simplified models are chosen for different viewing positions and for different resolutions in vizualisation. Experiments have shown that PLU keeps visual effect of original foliage, and when combined with branch polygon simplification, is efficient for multi-resolution representation and view-dependent plant community visualization