Understanding advances in the simulation of the Madden-Julian Oscillation in a numerical weather prediction model.

The Madden-Julian Oscillation (MJO) is the dominant mode of intraseasonal variability in the Trop- ics. It can be characterised as a planetary-scale coupling between the atmospheric circulation and organised deep convection that propagates east through the equatorial Indo-Pacific region. The MJO interacts with weather and climate systems on a near-global scale and is a crucial source of predictability for weather forecasts on medium to seasonal timescales. Despite its global signifi- cance, accurately representing the MJO in numerical weather prediction (NWP) and climate models remains a challenge. This thesis focuses on the representation of the MJO in the Integrated Forecasting System (IFS) at the European Centre for Medium-Range Weather Forecasting (ECMWF), a state-of-the-art NWP model. Recent modifications to the model physics in Cycle 32r3 (Cy32r3) of the IFS led to ad- vances in the simulation of the MJO; for the first time the observed amplitude of the MJO was maintained throughout the integration period. A set of hindcast experiments, which differ only in their formulation of convection, have been performed between May 2008 and April 2009 to asses the sensitivity of MJO simulation in the IFS to the Cy32r3 convective parameterization. Unique to this thesis is the attribution of the advances in MJO simulation in Cy32r3 to the mod- ified convective parameterization, specifically, the relative-humidity-dependent formulation for or- ganised deep entrainment. Increasing the sensitivity of the deep convection scheme to environmen- tal moisture is shown to modify the relationship between precipitation and moisture in the model. Through dry-air entrainment, convective plumes ascending in low-humidity environments terminate lower in the atmosphere. As a result, there is an increase in the occurrence of cumulus congestus, which acts to moisten the mid-troposphere. Due to the modified precipitation-moisture relationship more moisture is able to build up which effectively preconditions the tropical atmosphere for the transition to deep convection. Results from this thesis suggest that a tropospheric moisture control on convection is key to simulating the interaction between the physics and large-scale circulation associated with the MJO.

System Integration of PV/T Collectors in Solar Cooling Systems

The demand for cooling and air-conditioning of building is increasingly ever growing. This increase is mostly due to population and economic growth in developing countries, and also desire for a higher quality of thermal comfort. Increase in the use of conventional cooling systems results in larger carbon footprint and more greenhouse gases considering their higher electricity consumption, and it occasionally creates peaks in electricity demand from power supply grid. Solar energy as a renewable energy source is an alternative to drive the cooling machines since the cooling load is generally high when solar radiation is high. This thesis examines the performance of PV/T solar collector manufactured by Solarus company in a solar cooling system for an office building in Dubai, New Delhi, Los Angeles and Cape Town. The study is carried out by analyzing climate data and the requirements for thermal comfort in office buildings. Cooling systems strongly depend on weather conditions and local climate. Cooling load of buildings depend on many parameters such as ambient temperature, indoor comfort temperature, solar gain to the building and internal gains including; number of occupant and electrical devices. The simulations were carried out by selecting a suitable thermally driven chiller and modeling it with PV/T solar collector in Polysun software. Fractional primary energy saving and solar fraction were introduced as key figures of the project to evaluate the performance of cooling system. Several parametric studies and simulations were determined according to PV/T aperture area and hot water storage tank volume. The fractional primary energy saving analysis revealed that thermally driven chillers, particularly adsorption chillers are not suitable to be utilizing in small size of solar cooling systems in hot and tropic climates such as Dubai and New Delhi. Adsorption chillers require more thermal energy to meet the cooling load in hot and dry climates. The adsorption chillers operate in their full capacity and in higher coefficient of performance when they run in a moderate climate since they can properly reject the exhaust heat. The simulation results also indicated that PV/T solar collector have higher efficiency in warmer climates, however it requires a larger size of PV/T collectors to supply the thermally driven chillers for providing cooling in hot climates. Therefore using an electrical chiller as backup gives much better results in terms of primary energy savings, since PV/T electrical production also can be used for backup electrical chiller in a net metering mechanism.

Evaluation Of Reservoir Model Integration With Deterministic And Probabilistic Streamflow Forecasts

Due to the increase in water demand and hydropower energy, it is getting more important to operate hydraulic structures in an efficient manner while sustaining multiple demands. Especially, companies, governmental agencies, consultant offices require effective, practical integrated tools and decision support frameworks to operate reservoirs, cascades of run-of-river plants and related elements such as canals by merging hydrological and reservoir simulation/optimization models with various numerical weather predictions, radar and satellite data. The model performance is highly related with the streamflow forecast, related uncertainty and its consideration in the decision making. While deterministic weather predictions and its corresponding streamflow forecasts directly restrict the manager to single deterministic trajectories, probabilistic forecasts can be a key solution by including uncertainty in flow forecast scenarios for dam operation. The objective of this study is to compare deterministic and probabilistic streamflow forecasts on an earlier developed basin/reservoir model for short term reservoir management. The study is applied to the Yuvacık Reservoir and its upstream basin which is the main water supply of Kocaeli City located in the northwestern part of Turkey. The reservoir represents a typical example by its limited capacity, downstream channel restrictions and high snowmelt potential. Mesoscale Model 5 and Ensemble Prediction System data are used as a main input and the flow forecasts are done for 2012 year using HEC-HMS. Hydrometeorological rule-based reservoir simulation model is accomplished with HEC-ResSim and integrated with forecasts. Since EPS based hydrological model produce a large number of equal probable scenarios, it will indicate how uncertainty spreads in the future. Thus, it will provide risk ranges in terms of spillway discharges and reservoir level for operator when it is compared with deterministic approach. The framework is fully data driven, applicable, useful to the profession and the knowledge can be transferred to other similar reservoir systems.

A Higher order and stable method for the numerical integration of Random Differential Equations

Trabalho apresentado no Congresso Nacional de Matemática Aplicada à Indústria, 18 a 21 de novembro de 2014, Caldas Novas - Goiás

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Simulation of the energy performance of maize production integrated to pig farming

Foi avaliado o desempenho energético da suinocultura integrada à produção de milho em grão em sistema de plantio direto mecanizado. Nesta concepção de integração proposta, os dejetos suínos são utilizados como fertilizantes na produção de milho. O sistema foi delimitado envolvendo as atividades associadas ao manejo dos suínos e de produção do milho (manejo do solo, cultivo e colheita). O período de análise considerado foi de um ano, o que possibilita a produção de três lotes de suínos e duas safras de milho. Para avaliar o desempenho energético, foram criados três indicadores: eficiência energética, eficiência de uso de fontes não renováveis e o custo de energia não renovável para a produção de proteína. As entradas energéticas são compostas pelos insumos e pela infraestrutura, utilizados na criação dos suínos e na produção de milho, e pela radiação solar incidente no agrossistema. Já as saídas são representadas pelos seus produtos (suínos terminados e o milho). Os resultados obtidos nas simulações apontam que a integração melhora o desempenho energético das granjas suinícolas, aumentando a eficiência energética (186%) e a eficiência não renovável (352%), além de reduzir o custo de energia não renovável para a produção de proteína (‑58%).

Simulation of dynamic pinion course using Runge-Kutta's method and impact modeling

Once defined the relationship between the Starter Motor components and their functions, it is possible to develop a mathematical model capable to predict the Starter behavior during operation. One important aspect is the engagement system behavior. The development of a mathematical tool capable of predicting it is a valuable step in order to reduce the design time, cost and engineering efforts. A mathematical model, represented by differential equations, can be developed using physics laws, evaluating force balance and energy flow through the systems degrees of freedom. Another important physical aspect to be considered in this modeling is the impact conditions (particularly on the pinion and ring-gear contact). This work is a report of those equations application on available mathematical software and the resolution of those equations by Runge-Kutta's numerical integration method, in order to build an accessible engineering tool. Copyright © 2011 SAE International.

A NS-2 simulation model for DNP3 protocol over IEEE 802.15.4 wireless protocol toward low cost simulation of Smart Grid applications

Faced with an imminent restructuring of the electric power system, over the past few years many countries have invested in a new paradigm known as Smart Grid. This paradigm targets optimization and automation of electric power network, using advanced information and communication technologies. Among the main communication protocols for Smart Grids we have the DNP3 protocol, which provides secure data transmission with moderate rates. The IEEE 802.15.4 is another communication protocol also widely used in Smart Grid, especially in the so-called Home Area Network (HAN). Thus, many applications of Smart Grid depends on the interaction of these two protocols. This paper proposes modeling, in the traditional network simulator NS-2, the integration of DNP3 protocol and the IEEE 802.15.4 wireless standard for low cost simulations of Smart Grid applications.

Stochastic simulation of time-series models combined with geostatistics to predict water-table scenarios in a Guarani Aquifer System outcrop area, Brazil

Stochastic methods based on time-series modeling combined with geostatistics can be useful tools to describe the variability of water-table levels in time and space and to account for uncertainty. Monitoring water-level networks can give information about the dynamic of the aquifer domain in both dimensions. Time-series modeling is an elegant way to treat monitoring data without the complexity of physical mechanistic models. Time-series model predictions can be interpolated spatially, with the spatial differences in water-table dynamics determined by the spatial variation in the system properties and the temporal variation driven by the dynamics of the inputs into the system. An integration of stochastic methods is presented, based on time-series modeling and geostatistics as a framework to predict water levels for decision making in groundwater management and land-use planning. The methodology is applied in a case study in a Guarani Aquifer System (GAS) outcrop area located in the southeastern part of Brazil. Communication of results in a clear and understandable form, via simulated scenarios, is discussed as an alternative, when translating scientific knowledge into applications of stochastic hydrogeology in large aquifers with limited monitoring network coverage like the GAS.

Computational simulation of the flow-induced vibration of a circular cylinder subjected to wake interference

In this work, we considered the flow around two circular cylinders of equal diameter placed in tandem with respect to the incident uniform flow. The upstream cylinder was fixed and the downstream cylinder was completely free to move in the cross-stream direction, with no spring or damper attached to it. The centre-to-centre distance between the cylinders was four diameters, and the Reynolds number was varied from 100 to 645. We performed two- and three-dimensional simulations of this flow using a Spectral/hp element method to discretise the flow equations, coupled to a simple Newmark integration routine that solves the equation of the dynamics of the cylinder. The differences of the behaviours observed in the two- and three-dimensional simulations are highlighted and the data is analysed under the light of previously published experimental results obtained for higher Reynolds numbers.

Study of a wind-wave numerical model and its integration with ocean and oil-spill numerical models

The ability to represent the transport and fate of an oil slick at the sea surface is a formidable task. By using an accurate numerical representation of oil evolution and movement in seawater, the possibility to asses and reduce the oil-spill pollution risk can be greatly improved. The blowing of the wind on the sea surface generates ocean waves, which give rise to transport of pollutants by wave-induced velocities that are known as Stokes’ Drift velocities. The Stokes’ Drift transport associated to a random gravity wave field is a function of the wave Energy Spectra that statistically fully describe it and that can be provided by a wave numerical model. Therefore, in order to perform an accurate numerical simulation of the oil motion in seawater, a coupling of the oil-spill model with a wave forecasting model is needed. In this Thesis work, the coupling of the MEDSLIK-II oil-spill numerical model with the SWAN wind-wave numerical model has been performed and tested. In order to improve the knowledge of the wind-wave model and its numerical performances, a preliminary sensitivity study to different SWAN model configuration has been carried out. The SWAN model results have been compared with the ISPRA directional buoys located at Venezia, Ancona and Monopoli and the best model settings have been detected. Then, high resolution currents provided by a relocatable model (SURF) have been used to force both the wave and the oil-spill models and its coupling with the SWAN model has been tested. The trajectories of four drifters have been simulated by using JONSWAP parametric spectra or SWAN directional-frequency energy output spectra and results have been compared with the real paths traveled by the drifters.

Numerische Integration, angewandt bei der Inferenz in Zustandsraummodellen

In dieser Arbeit werden neuere methodische Entwicklungen aus dem Bereich der Numerischen Integration für die näherungsweise Berechnung von Zustandraummodellen erprobt. Die resultierenden Algorithmen werden bzgl. ihrer Approximationsgüte mit den populären simulationsbasierten Näherungsverfahren verglichen.

Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20\% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.

Integration of computational models and experimental characterization to study internal frost damage in cementitious materials

The objective of this doctoral research is to investigate the internal frost damage due to crystallization pore pressure in porous cement-based materials by developing computational and experimental characterization tools. As an essential component of the U.S. infrastructure system, the durability of concrete has significant impact on maintenance costs. In cold climates, freeze-thaw damage is a major issue affecting the durability of concrete. The deleterious effects of the freeze-thaw cycle depend on the microscale characteristics of concrete such as the pore sizes and the pore distribution, as well as the environmental conditions. Recent theories attribute internal frost damage of concrete is caused by crystallization pore pressure in the cold environment. The pore structures have significant impact on freeze-thaw durability of cement/concrete samples. The scanning electron microscope (SEM) and transmission X-ray microscopy (TXM) techniques were applied to characterize freeze-thaw damage within pore structure. In the microscale pore system, the crystallization pressures at sub-cooling temperatures were calculated using interface energy balance with thermodynamic analysis. The multi-phase Extended Finite Element Modeling (XFEM) and bilinear Cohesive Zone Modeling (CZM) were developed to simulate the internal frost damage of heterogeneous cement-based material samples. The fracture simulation with these two techniques were validated by comparing the predicted fracture behavior with the captured damage from compact tension (CT) and single-edge notched beam (SEB) bending tests. The study applied the developed computational tools to simulate the internal frost damage caused by ice crystallization with the two dimensional (2-D) SEM and three dimensional (3-D) reconstructed SEM and TXM digital samples. The pore pressure calculated from thermodynamic analysis was input for model simulation. The 2-D and 3-D bilinear CZM predicted the crack initiation and propagation within cement paste microstructure. The favorably predicted crack paths in concrete/cement samples indicate the developed bilinear CZM techniques have the ability to capture crack nucleation and propagation in cement-based material samples with multiphase and associated interface. By comparing the computational prediction with the actual damaged samples, it also indicates that the ice crystallization pressure is the main mechanism for the internal frost damage in cementitious materials.

Curricular Integration of Simulations in Neuroscience - Instructional and Technical Perspectives

In recent years interactive media and tools, like scientific simulations and simulation environments or dynamic data visualizations, became established methods in the neural and cognitive sciences. Hence, university teachers of neural and cognitive sciences are faced with the challenge to integrate these media into the neuroscientific curriculum. Especially simulations and dynamic visualizations offer great opportunities for teachers and learners, since they are both illustrative and explorable. However, simulations bear instructional problems: they are abstract, demand some computer skills and conceptual knowledge about what simulations intend to explain. By following two central questions this article provides an overview on possible approaches to be applied in neuroscience education and opens perspectives for their curricular integration: (i) How can complex scientific media be transformed for educational use in an efficient and (for students on all levels) comprehensible manner and (ii) by what technical infrastructure can this transformation be supported? Exemplified by educational simulations for the neurosciences and their application in courses, answers to these questions are proposed a) by introducing a specific educational simulation approach for the neurosciences b) by introducing an e-learning environment for simulations, and c) by providing examples of curricular integration on different levels which might help academic teachers to integrate newly created or existing interactive educational resources in their courses.