998 resultados para virtual plant


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This project constructed virtual plant leaf surfaces from digitised data sets for use in droplet spray models. Digitisation techniques for obtaining data sets for cotton, chenopodium and wheat leaves are discussed and novel algorithms for the reconstruction of the leaves from these three plant species are developed. The reconstructed leaf surfaces are included into agricultural droplet spray models to investigate the effect of the nozzle and spray formulation combination on the proportion of spray retained by the plant. A numerical study of the post-impaction motion of large droplets that have formed on the leaf surface is also considered.

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Light interception is a major factor influencing plant development and biomass production. Several methods have been proposed to determine this variable, but its calculation remains difficult in artificial environments with heterogeneous light. We propose a method that uses 3D virtual plant modelling and directional light characterisation to estimate light interception in highly heterogeneous light environments such as growth chambers and glasshouses. Intercepted light was estimated by coupling an architectural model and a light model for different genotypes of the rosette species Arabidopsis thaliana (L.) Heynh and a sunflower crop. The model was applied to plants of contrasting architectures, cultivated in isolation or in canopy, in natural or artificial environments, and under contrasting light conditions. The model gave satisfactory results when compared with observed data and enabled calculation of light interception in situations where direct measurements or classical methods were inefficient, such as young crops, isolated plants or artificial conditions. Furthermore, the model revealed that A. thaliana increased its light interception efficiency when shaded. To conclude, the method can be used to calculate intercepted light at organ, plant and plot levels, in natural and artificial environments, and should be useful in the investigation of genotype-environment interactions for plant architecture and light interception efficiency. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

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Plant performance is significantly influenced by prevailing light and temperature conditions during plant growth and development. For plants exposed to natural fluctuations in abiotic environmental conditions it is however laborious and cumbersome to experimentally assign any contribution of individual environmental factors to plant responses. This study aimed at analyzing the interplay between light, temperature and internode growth based on model approaches. We extended the light-sensitive virtual plant model L-Cucumber by implementing a common Arrhenius function for appearance rates, growth rates, and growth durations. For two greenhouse experiments, the temperature-sensitive model approach resulted in a precise prediction of cucumber mean internode lengths and number of internodes, as well as in accurately predicted patterns of individual internode lengths along the main stem. In addition, a system's analysis revealed that environmental data averaged over the experimental period were not necessarily related to internode performance. Finally, the need for a species-specific parameterization of the temperature response function and related aspects in modeling temperature effects on plant development and growth is discussed.

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Pesticides used in agricultural systems must be applied in economically viable and environmentally sensitive ways, and this often requires expensive field trials on spray deposition and retention by plant foliage. Computational models to describe whether a spray droplet sticks (adheres), bounces or shatters on impact, and if any rebounding parent or shatter daughter droplets are recaptured, would provide an estimate of spray retention and thereby act as a useful guide prior to any field trials. Parameter-driven interactive software has been implemented to enable the end-user to study and visualise droplet interception and impaction on a single, horizontal leaf. Living chenopodium, wheat and cotton leaves have been scanned to capture the surface topography and realistic virtual leaf surface models have been generated. Individual leaf models have then been subjected to virtual spray droplets and predictions made of droplet interception with the virtual plant leaf. Thereafter, the impaction behaviour of the droplets and the subsequent behaviour of any daughter droplets, up until re-capture, are simulated to give the predicted total spray retention by the leaf. A series of critical thresholds for the stick, bounce, and shatter elements in the impaction process have been developed for different combinations of formulation, droplet size and velocity, and leaf surface characteristics to provide this output. The results show that droplet properties, spray formulations and leaf surface characteristics all influence the predicted amount of spray retained on a horizontal leaf surface. Overall the predicted spray retention increases as formulation surface tension, static contact angle, droplet size and velocity decreases. Predicted retention on cotton is much higher than on chenopodium. The average predicted retention on a single horizontal leaf across all droplet size, velocity and formulations scenarios tested, is 18, 30 and 85% for chenopodium, wheat and cotton, respectively.

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This paper presents a motion control system for guidance of an underactuated Unmanned Underwater Vehicle (UUV) on a helical trajectory. The control strategy is developed using Port-Hamiltonian theory and interconnection and damping assignment passivity-based control. Using energy routing, the trajectory of a virtual fully actuated plant is guided onto a vector field. A tracking controller is then used that commands the underactuated plant to follow the velocity of the virtual plant. An integral control is inserted between the two control layers, which adds robustness and disturbance rejection to the design.

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This paper presents a novel power control strategy that decouples the active and reactive power for a synchronous generator connected to a power network. The proposed control paradigm considers the capacitance of the transmission line along with its resistance and reactance as-well. Moreover the proposed controller takes into account all cases of R-X relationships, thus allowing it to function in Virtual Power Plant (VPP) structures which operate at both medium voltage (MV) and low voltage (LV) levels. The independent control of active and reactive power is achieved through rotational transformations of the terminal voltages and currents at the synchronous generator's output. This paper details the control technique by first presenting the mathematical and electrical network analysis of the methodology and then successfully implementing the control using MATLAB-SIMULINK simulation.

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Utilization of renewable energy sources and energy storage systems is increasing with fostering new policies on energy industries. However, the increase of distributed generation hinders the reliability of power systems. In order to stabilize them, a virtual power plant emerges as a novel power grid management system. The VPP has a role to make a participation of different distributed energy resources and energy storage systems. This paper defines core technology of the VPP which are demand response and ancillary service concerning about Korea, America and Europe cases. It also suggests application solutions of the VPP to V2G market for restructuring national power industries in Korea.

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Many accidents occur world-wide in the use of construction plant and equipment, and safety training is considered by many to be one of the best approaches to their prevention. However, current safety training methods/tools are unable to provide trainees with the hands-on practice needed. Game technology-based safety training platforms have the potential to overcome this problem in a virtual environment. One such platform is described in this paper - its characteristics are analysed and its possible contribution to safety training identified. This is developed and tested by means of a case study involving three major pieces of construction plant, which successfully demonstrates that the platform can improve the process and performance of the safety training involved in their operation. This research not only presents a new and useful solution to the safety training of construction operations, but illustrates the potential use of advanced technologies in solving construction industry problems in general.

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4D simulation, building information modeling, virtual construction, computer simulation and virtual prototyping are emerging topics in the building construction industry. These techniques not only relate to the buildings themselves, but can also be applied to other forms of construction, including bridges. Since bridge construction is a complex process involving multiple types of plant and equipment, applying such virtual methods benefits the understanding of all parties in construction practice. This paper describes the relationship between temporary platforms, plant and equipment resources and a proposed-built model in the construction planning and use of Virtual Prototyping Simulation (VPS) to implement different construction scenarios in order to help planners identify an optimal construction plan. A case study demonstrates the use of VPS integrated with temporary platform design and plant and equipment-resource allocation to generate different construction scenarios.

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The control paradigms of the distributed generation (DG) sources in the smart grid are realised by either utilising virtual power plant (VPP) or by employing MicroGrid structures. Both VPP and MicroGrid are presented with the problem of control of power flow between their comprising DG sources. This study depicts this issue for VPP and proposes a novel and improved universal active and reactive power flow controllers for three-phase pulse width modulated voltage source inverters (PWM-VSI) operating in the VPP environment. The proposed controller takes into account all cases of R-X relationship, thus allowing it to function in systems operating at high, medium (MV) and low-voltage (LV) levels. Also proposed control scheme for the first time in an inverter control takes into account the capacitance of the transmission line which is an important factor to accurately represent medium length transmission lines. This allows the proposed control scheme to be applied in VPP structures, where DG sources can operate at MV LV levels over a short/medium length transmission line. The authors also conducted small signal stability analysis of the proposed controller and compared it against the small signal study of the existing controllers.

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The use of maize simulation models to determine the optimum plant population for rainfed environments allows the evaluation of plant populations over multiple years and locations at a lower cost than traditional field experimentation. However the APSIM maize model that has been used to conduct some of these 'virtual' experiments assumes that the maximum rate of soil water extraction by the crop root system is constant across plant populations. This untested assumption may cause grain yield to be overestimated in lower plant populations. A field experiment was conducted to determine whether maximum rates of water extraction vary with plant population, and the maximum rate of soil water extraction was estimated for three plant populations (2.4, 3.5 and 5.5 plants m(-2)) under water limited conditions. Maximum soil water extraction rates in the field experiment decreased linearly with plant population, and no difference was detected between plant populations for the crop lower limit of soil water extraction. Re-analysis of previous maize simulation experiments demonstrated that the use of inappropriately high extraction-rate parameters at low plant populations inflated predictions of grain yield, and could cause erroneous recommendations to be made for plant population. The results demonstrate the importance of validating crop simulation models across the range of intended treatments. (C) 2013 Elsevier E.V. All rights reserved.

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Esta dissertação apresenta o projeto, desenvolvimento e implementação de um software para criação de animações, simulações e treinamentos de processos e instruções técnicas industriais, destacando também a arquitetura utilizada para sua implementação. O software apresentado permite a geração de animações, textos, sons e interações, fornecendo ferramentas de criação, visualização e supervisão da simulação com o uso de Realidade Virtual em três dimensões. A dissertação trata ainda do uso prático do software através de um estudo de caso com simulações 3D de processos industriais reais de uma usina de geração de energia elétrica. Este estudo também contribui para as áreas de treinamento em realidade virtual e sistemas de autoria 3D ao apresentar conceitos inovadores na área de supervisão automática, mostrando também uma possível estrutura de componentes de software para uso nas áreas citadas. Pode-se destacar ainda a revisão de tecnologias semelhantes à proposta neste trabalho, visando à identificação de influências, melhorias e inovações nas áreas de autoria 3D e treinamento.

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As indústrias têm buscado constantemente reduzir gastos operacionais, visando o aumento do lucro e da competitividade. Para alcançar essa meta, são necessários, dentre outros fatores, o projeto e a implantação de novas ferramentas que permitam o acesso às informações relevantes do processo de forma precisa, eficiente e barata. Os sensores virtuais têm sido aplicados cada vez mais nas indústrias. Por ser flexível, ele pode ser adaptado a qualquer tipo de medição, promovendo uma redução de custos operacionais sem comprometer, e em alguns casos até melhorar, a qualidade da informação gerada. Como estão totalmente baseados em software, não estão sujeitos a danos físicos como os sensores reais, além de permitirem uma melhor adaptação a ambientes hostis e de difícil acesso. A razão do sucesso destes tipos de sensores é a utilização de técnicas de inteligência computacional, as quais têm sido usadas na modelagem de vários processos não lineares altamente complexos. Este trabalho tem como objetivo estimar a qualidade da alumina fluoretada proveniente de uma Planta de Tratamento de Gases (PTG), a qual é resultado da adsorção de gases poluentes em alumina virgem, via sensor virtual. O modelo que emula o comportamento de um sensor de qualidade de alumina foi criado através da técnica de inteligência computacional conhecida como Rede Neural Artificial. As motivações deste trabalho consistem em: realizar simulações virtuais, sem comprometer o funcionamento da PTG; tomar decisões mais precisas e não baseada somente na experiência do operador; diagnosticar potenciais problemas, antes que esses interfiram na qualidade da alumina fluoretada; manter o funcionamento do forno de redução de alumínio dentro da normalidade, pois a produção de alumina de baixa qualidade afeta a reação de quebra da molécula que contém este metal. Os benefícios que este projeto trará consistem em: aumentar a eficiência da PTG, produzindo alumina fluoretada de alta qualidade e emitindo menos gases poluentes na atmosfera, além de aumentar o tempo de vida útil do forno de redução.

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This paper investigates the use of virtual reality (VR) technologies to facilitate the analysis of plant biological data in distinctive steps in the application pipeline. Reconstructed three-dimensional biological models (primary polygonal models) transferred to a virtual environment support scientists' collaborative exploration of biological datasets so that they obtain accurate analysis results and uncover information hidden in the data. Examples of the use of virtual reality in practice are provided and a complementary user study was performed.