Atmospheric CO₂ enrichment is employed by greenhouse tomato growers to increase fruit yields, and CO₂ applications are managed according to atmospheric set points or CO₂ injection rates. These methods do not immediately focus on the targets of CO₂ applications: plant performance and the regulation of plant carbon status. This thesis explores several plant-based approaches that may have potential for use in the management of CO₂ in greenhouse tomato production. Three plant-based approaches to CO₂ management were explored in commercial and experimental tomato greenhouses. These were: (1) simulation modeling, (2) non-destructive analysis of growth and (3) the status of plant carbon reserves. A cost and benefit analysis (c/b) using simulation modeling was carried out using grower-collected greenhouse environment and yield data. Simulation modeling was useful for retrospectively determining c/b of several CO₂ scenarios. The model was effective in predicting long term yields, but not short term yield variations, which limits its application for CO₂ management. Non-destructive measures of growth: stem length and diameter, leaf area and fruit load were found to be too sluggish for daily CO₂ dosing decision-making. Finally, plants growing under CO₂ enrichment can deposit substantial carbon as starch in their leaves. Plant carbon status was evaluated by determining the spatial distribution of leaf starch in the shoot and by following its variation diurnally and after the onset of CO₂ enrichment. As starch is difficult to measure by a grower, leaf mass per unit area (LMA) was also monitored for assessment as a surrogate measure for starch. Leaves in positions 7 to 9 were identified as the most meaningful in the shoot to sample. Diurnal profiles indicated these leaves carryover substantial starch from one day to the next. Monitoring starch at its peak time of accumulation (14 h to 16 h), at sunset and sunrise will indicate how much the peak starch reserves are used overnight. If starch remains high between peak and sunrise the following day, then the plants are in a carbon-surplus state and CO₂ enrichment could be postponed. For upper canopy leaves LMA is substantially influenced by starch and thus is a promising surrogate.

Orientador: Rubens Maciel Filho / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica / Made available in DSpace on 2018-08-11T05:06:17Z (GMT). No. of bitstreams: 1 DiazMateus_FabianAndrey_M.pdf: 2380896 bytes, checksum: be3b7c2cb01810009ddbc674d0b696e6 (MD5) Previous issue date: 2008 / Resumo: Neste trabalho é desenvolvida a modelagem matemática e a simulação computacional de um forno para processos de conversão térmica de frações pesadas de petróleo. O modelo cinético das reações de conversão é tomada de Sugaya (1993) a qual consta de uma reação irreversível de primeira ordem com 9 lumps reacionais e 24 pseudocomponentes. Os 24 pseudocomponentes são caracterizados e suas propriedades são calculadas mediante diferentes correlações e métodos encontrados na literatura. À medida que a carga avança pela tubulação do forno, a reação ocorre gerando quantidades maiores de componentes leves alterando as condições de fluxo como decorrência de alterações físico-químicas. Estes efeitos são levados em consideração na modelagem desenvolvida. O estado da mistura é verificado para cada passo de integração mediante a equação Soave Redlich Kwong. No caso de escoamento bifásico, as propriedades do líquido e do vapor são calculadas para determinar o regime de escoamento e calcular o Holdup. Este parâmetro permite estimar as propriedades de transporte, os coeficientes de transferência e a perda de carga. Inicialmente é simulada uma unidade piloto de craqueamento térmico. Esta unidade consta de uma serpentina aquecida isotermicamente, fato pelo qual só balanço de massa é integrado. O programa encontra as constantes cinéticas mediante um algoritmo Newton ¿ Raphson, cuja função objetivo é a diferença entre a conversão calculada e a conversão medida. Finalmente o forno industrial é simulado. Balanços de massa, momento, energia e temperatura de parede são integrados. Os resultados obtidos apresentam boa concordância com os dados do forno 23H ¿ 1 (Refinaria Presidente Bernardes, Cubatão) para craqueamento térmico. Deposição de coque na tubulação é avaliada para analisar o comportamento do processo. O programa desenvolvido permite o estudo do processo de craqueamento térmico para processos de conversão térmica como o coqueamento retardado e visco-redução. Novos parâmetros operacionais podem ser estudados, diferentes cargas e estratégias de controle podem ser simuladas e avaliadas com o software desenvolvido / Abstract: The mathematical modeling and the computational simulation of a process furnace for thermal conversion of heavy oil fractions is developed in this work. Kinetics of conversion reactions is from Sugaya (1993). It is based in a first order irreversible reaction with 9 lumps and 24 pseudocomponents. The 24 pseudocomponents are characterized and their properties calculated by different correlations and methods available in the literature. As walks through the furnace tubes, the feed, initially liquid, reacts generating light fractions and gas. The state of the mixture is checked for each integration step by a subroutine based on the Soave Redlich Kwong equation. When two phases are flowing, properties of the liquid and vapor are calculated to determine the flow regime and the holdup. This parameter allows to calculate the transport properties and the heat transfer and pressure drop coefficients. Initially, a thermal cracking pilot plant is simulated. This unit is formed by a reactor coil that is isothermally quenched; consequently, only mass balance is integrated. The program finds the kinetic constants by a Newton ¿ Raphson algorithm whose objective function is the difference between the calculated and measured conversion. Finally, an industrial furnace is simulated. Mass, momentum, wall temperature and energy balances are integrated. Results show good agreement whit the data reported from the industrial furnace 23-H-1 (Refinery Presidente Bernardes, Cubatão) for thermal cracking. Coke deposition in tubes is tested to analyze the performance of the process. The program developed in this work allows an insight study of thermal cracking processes such as delayed coking and visbreaking. New operational parameters, different feeds, control strategies and many other parameters can be studied. / Mestrado / Desenvolvimento de Processos Químicos / Mestre em Engenharia Química

A viticultura no Brasil e no Estado de São Paulo encontra-se em expansão nos últimos 10 anos e a cv. Niagara Rosada (Vitis labrusca) se destaca como principal cultivar para produção de uvas para mesa. Essa cultivar é suscetível à várias doenças foliares, como a ferrugem (Phakopsora euvitis) e o míldio (Plasmopara viticola). Não existem estimativas quantitativas dos danos causados por essas doenças na cv. Niagara Rosada. Diante do exposto os objetivos desse trabalho foram quantificar os efeitos da ferrugem e do míldio nas trocas gasosas, nas limitações da fotossíntese, no acúmulo de biomassa, no acúmulo de carboidratos, e na produção da cv. Niagara Rosada e desenvolver um modelo de simulação para V. labrusca acoplado com os mecanismos de danos da ferrugem e míldio. Experimentos foram conduzidos, separadamente para cada doença, em condições controladas, em mudas inoculadas com diferentes concentrações de P. euvitis e P. viticola e em campo experimental. Medidas de trocas gasosas e curvas de resposta da taxa líquida de assimilação de CO2 ao aumento da concentração intercelular de CO2 (Ci) foram realizadas em mudas sadias e infectadas com P. euvitis e P. viticola. Teores de açúcares solúveis totais, sacarose e amido foram determinados em plantas sadias e inoculadas com os patógenos. P. euvitis e P. viticola reduziram a taxa fotossintética em plantas infectadas tanto na área da lesão como no tecido verde adjacente a lesão (lesão virtual). Valores do parâmetro β, indicativo da lesão virtual, foram de 5,7 e 2,9, respectivamente para P. euvitis e P. viticola. P. euvitis reduziu em 48%, 36% e 67% a atividade da Rubisco (Vcmax), a taxa máxima de transporte de elétrons usados para a regeneraração da RuBP (Jmax) e a condutância do mesofilo (gm), respectivamente, em folhas infectadas. A área foliar e biomassa de raízes em mudas inoculadas com P. euvitis foram reduzidas. Através de análises histopatológicas e da quantificação de amido nas folhas sadias e doentes foi possível observar o acúmulo de amido em regiões adjacentes às pústulas de P. euvitis. Mesmo em baixas severidades da ferrugem já se observam reduções no acúmulo de carboidratos em raízes. P. viticola reduziu Vcmax em 23,5 % em folhas infectadas comparadas às folhas sadias. P. viticola reduziu a biomassa de raízes e quantidade de carboidratos nas raízes de mudas doentes e de plantas no campo em ano de alta severidade da doença. Plantas no campo com sintomas míldio produziram em média 0,5 kg a menos do que plantas sadias e a principal causa da redução na produção foi a queda de bagas causada pela infecção de P. viticola nos cachos. Um modelo de simulação para Vitis labrusca foi desenvolvido, utilizando o software Stella®. A produção, partição e dinâmica da biomassa da videira foi simulada ao longo de 20 anos e os efeitos de P. euvitis e P. viticola na redução do tecido verde sadio da planta, na redução da eficiência fotossintética, no desvio de assimilados, na aceleração da senescência foliar e na queda de frutos foram inseridos no modelo. / Viticulture in Brazil and in the state of São Paulo has increased in the last 10 years and cv. Niagara Rosada (Vitis labrusca) is the main cultivar for the production of table grapes. This cultivar is susceptible to several foliar diseases, such as rust (Phakopsora euvitis) and downy mildew (Plasmopara viticola). There are no quantitative estimates of the damage caused by these pathogens in cv. Niagara Rosada. The objectives of this work were to quantify the effects of rust and downy mildew on gas exchange, photosynthesis limitations, biomass accumulation, carbohydrate accumulation and production of cv. Niagara Rosada and to develop a simulation model for V. labrusca coupled with damage mechanisms caused by rust and mildew. Experiments were conducted, independently for each disease, under controlled conditions in potted plants inoculated with different concentrations of P. euvitis and P. viticola and in experimental field, with natural occurrence of diseases. Measurements of gas exchange and response curves of photosynthetic rate to the increase of the intercellular CO2 concentration (Ci) were carried out in healthy plants and infected plants with P. euvitis and P. viticola. Total soluble sugars, sucrose and starch contents were determined in healthy plants and inoculated plants with the pathogens and kept under controlled conditions. P. euvitis and P. viticola reduced the photosynthetic rate in infected plants both in the area of the lesion and in the green tissue adjacent to the lesion (virtual lesion). Values of parameter β, indicative of the virtual lesion, were 5.8 and 2.9, respectively for P. euvitis and P. viticola. P. euvitis reduced the activity of Rubisco (Vcmax), rate of electrons transport contributing for the RuBP-regeneration (Jmax) and the conductance of mesophyll (gm), respectively, on infected leaves by 48%, 36% and 67%. The severity of P. euvitis reduced leaf area and biomass of plant roots. The histopathological analysis and starch quantification in the leaves allowed to observe starch accumulation in regions adjacent to the pustules of P. euvitis. Even in low disease severities, reductions in carbohydrates accumulation of in roots are already observed. P. viticola reduced Vcmax by 23.5% in infected leaves compared to healthy leaves. P. viticola reduced the root biomass and carbohydrate amounts in the roots of potted plants and plants in the field in the year of high disease severity. Field plants with mildew symptoms produced on average 0.5 kg less than healthy plantsand the main cause of reduction in production was the drop of berries caused by infection of P. viticola in the clusters. A simulation model for Vitis labrusca was developed using Stella ® software. The production, partitioning and dynamics of grapevine biomass was simulated over 20 years and the effects of P. euvitis and P. viticola on the reduction of healthy green plant tissue and photosynthetic efficiency, the assimilative sapper, leaf senescence acceleration and fruit drop were coupled in the model.

Atmospheric CO₂ enrichment is employed by greenhouse tomato growers to increase fruit yields, and CO₂ applications are managed according to atmospheric set points or CO₂ injection rates. These methods do not immediately focus on the targets of CO₂ applications: plant performance and the regulation of plant carbon status. This thesis explores several plant-based approaches that may have potential for use in the management of CO₂ in greenhouse tomato production. Three plant-based approaches to CO₂ management were explored in commercial and experimental tomato greenhouses. These were: (1) simulation modeling, (2) non-destructive analysis of growth and (3) the status of plant carbon reserves. A cost and benefit analysis (c/b) using simulation modeling was carried out using grower-collected greenhouse environment and yield data. Simulation modeling was useful for retrospectively determining c/b of several CO₂ scenarios. The model was effective in predicting long term yields, but not short term yield variations, which limits its application for CO₂ management. Non-destructive measures of growth: stem length and diameter, leaf area and fruit load were found to be too sluggish for daily CO₂ dosing decision-making. Finally, plants growing under CO₂ enrichment can deposit substantial carbon as starch in their leaves. Plant carbon status was evaluated by determining the spatial distribution of leaf starch in the shoot and by following its variation diurnally and after the onset of CO₂ enrichment. As starch is difficult to measure by a grower, leaf mass per unit area (LMA) was also monitored for assessment as a surrogate measure for starch. Leaves in positions 7 to 9 were identified as the most meaningful in the shoot to sample. Diurnal profiles indicated these leaves carryover substantial starch from one day to the next. Monitoring starch at its peak time of accumulation (14 h to 16 h), at sunset and sunrise will indicate how much the peak starch reserves are used overnight. If starch remains high between peak and sunrise the following day, then the plants are in a carbon-surplus state and CO₂ enrichment could be postponed. For upper canopy leaves LMA is substantially influenced by starch and thus is a promising surrogate. / Land and Food Systems, Faculty of / Graduate

In this paper we present an approach to the analysis of the contribution of a small subregion in a dataset to the global flow. To this purpose, we subtract the potential flow that is induced by the boundary of the sub-domain from the original flow. Since the potential flow is free of both divergence and rotation, the localized flow field retains the original features. In contrast to similar approaches, by making explicit use of the boundary flow of the subregion, we manage to isolate the region-specific flow that contains exactly the local contribution of the considered subdomain to the global flow. In the remainder of the paper, we describe an implementation on unstructured grids in both two and three dimensions. We discuss the application of several widely used feature extraction methods on the localized flow, with an emphasis on topological schemes.

Counter Unmanned Aerial System (CUAS) security systems have unrealistic performance expectations hyped on marketing and idealistic testing environments. By developing an agent-based model to simulate these systems, an average performance metric can be obtained, thereby providing better representative values of true system performance.<br><br>Due to high cost, excessive risk, and exponentially large parameter possibilities, it is unrealistic to test a CUAS system for optimal performance in the real world. Agent-based simulation can provide the necessary variability at a low cost point and allow for numerous parametric possibilities to provide actionable output from the CUAS system. <br><br>This study describes and documents the Simulation of CUAS Networks and Sensors (SCANS) Framework in a novel attempt at developing a flexible modeling framework for CUAS systems based on device parameters. The core of the framework rests on sensor and communication device agents. These sensors, including Acoustic, Radar, Passive Radio Frequency (RF), and Camera, use input parameters, sensor specifications, and UAS specifications to calculate such values as the sound pressure level, received signal strength, and maximum viewable distance. The communication devices employ a nearest-neighbor routing protocol to pass messages from the system which are then logged by a command and control agent. <br><br>This framework allows for the flexibility of modeling nearly any CUAS system and is designed to be easily adjusted. The framework is capable of reporting true positives, true negatives, and false negatives in terms of UAS detection. For testing purposes, the SCANS Framework was deployed in AnyLogic and models were developed based on existing, published, empirical studies of sensors and detection UAS.<br>

<p>The research effort addressed important gaps in the modeling to simulate Urban Air Mobility (UAM) operations and couple optimization analyses for vehicle design, fleet allocations, and operational choices for next generation urban travel. Urban Air Mobility is expected to be a \$1 trillion dollar industry by 2040, but operators and designers have limited models and tools to estimate fleet performance, cost metrics, emissions performance, and profit for a given concept under future concepts of operations. A review of the literature reveals 14 modeling gaps related to infrastructure, operations, airspace, vehicles, and customers. In addition, the UAM industry requires better understanding of how operational choices may impact vehicle design and fleet allocations in a market with significant economic barriers and infrastructure needs. To address those needs, this effort proposed alternatives to address modeling challenges and develop studies to evaluate UAM vehicle concepts and concepts of operations in ways once not possible using the enhanced modeling tools. The research findings revealed that modeling coupled design/fleet and operational choices can affect daily profitability potential by 2-4\times\, for piloted and autonomous operations and affect the fleet size from between 12-50 vehicles across small, medium, and large metropolitan areas. The modeling capability provided by the improvements in UAM operations simulations and accessing vehicle and fleet metrics enables future studies to address UAM in a holistic manner. The increased capability could benefit the UAM community and inform future operations and concepts of operations in preparation for ubiquitous operations.</p>

No description available.

I utilized forest growth model (FVS-FFE) and fire simulation software (FlamMap, Randig), integrated through GIS software (ArcMap9.3), to quantify the impacts varied landscape-scale fuel treatments have on short-term onsite carbon loss, long-term onsite carbon storage, burn probability, conditional flame length, and mean fire size. Thirteen fuel treatment scenarios were simulated on a 42,000 hectare landscape in northern California: one untreated, three proposed by the US Forest Service, and nine that were spatially-optimized and developed with the Treatment Optimization Model in FlamMap. The nine scenarios developed in FlamMap varied by treatment intensity (10%, 20%, and 30% of the landscape treated) and treatment type (prescribed fire, mastication and thin + burn). Each scenario was subjected to 10,000 simulated wildfires with random ignition locations in order to develop burn probability and average flame length values for each scenario. I also recorded mean fire size for each scenario. I used the burn probability values to represent the likelihood of future wildfire occurrence, which I incorporated into our long-term onsite carbon storage projections. Our results suggest that the influence landscape-scale fuel treatments have on carbon dynamics and fire behavior metrics (mean burn probability, flame length and mean fire size) are highly dependent upon the treatment arrangement, type, and intensity. The results suggest that treating 20% of the landscape maximizes long-term carbon storage and that prescribed fire minimizes short-term carbon loss and maximizes onsite long-term carbon storage. Treating 20% of the landscape also appears to be the optimal treatment intensity for reducing fire behavior metrics, and treating beyond this level produces diminishing returns in reduction of fire behavior. When treating 20% of the landscape, site-specific treatments appear to perform well in comparison to spatially-optimized treatments.

Several studies in the field of outdoor recreation management and planning have used computer simulation modeling to demonstrate its utility as a tool to help managers monitor encounters and similar visitor use-related indicators of quality. However, previous applications of computer simulation modeling to outdoor recreation planning and management have generally done little to assess the reliability, or precision, of model estimates. The purpose of this research is to explore several questions concerning the reliability of computer simulation model estimates for monitoring wilderness solitude-related indicators of quality. In particular, can reliable estimates of solitude-related indicators be generated for low use recreation environments, such as backcountry and wilderness areas? Is there a spatial component to questions about the reliability of computer simulation estimates for low use visitor landscapes? The research presented in this thesis examines the reliability of computer simulation estimates of wilderness solitude indicators that account for the timing and location of hiking and camping encounters in the backcountry of Great Smoky Mountains National Park. This study was designed to model visitor use and inter-group encounters in the Cosby and Big Creek areas of Great Smoky Mountains National Park, which are located within the park's proposed wilderness area. Two primary types of information about visitor use in the study area were collected to construct the computer simulation model in this study. First, information was gathered about the amount of visitation to the study area; second, information was collected about visitors' travel routes within the study area. Three alternative methods were used to estimate the number of replications needed to obtain desired levels of precision for the visitor-based and spatially based computer simulation model outputs. The results suggest that computer simulation models of visitor use can generate precise estimates for a small to moderate number of visitor-based and spatially-based outputs. However, there are constraints to generating precise estimates of use-related outputs as the number of outputs estimated simultaneously becomes large. This challenge is particularly pronounced in cases where at least some of the outputs are derived for low use attractions, trails, or camping locations. / Master of Science