MATHEMATICAL Models | Academic Articles

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Posts Tagged ‘MATHEMATICAL models’

Sensitivity analysis of the magflow cellular automaton model for lava flow simulation

Abstract: MAGFLOW is a physics-based numerical model for lava flow simulations based on the Cellular Automaton approach that has been successfully used to predict the lava flow paths during the recent eruptions on Mt Etna. We carried out an extensive sensitivity analysis of the physical and rheological parameters that control the evolution function of the automaton and which are measured during eruptive events, in an effort to verify the reliability of the model and improve its applicability to scenario forecasting. The results obtained, which include Sobol” sensitivity indices computed using polynomial chaos expansion, confirm the consistency of MAGFLOW with the underlying physical model and identify water content and solidus temperature as critical parameters for the automaton. Additional tests also indicate that flux rates can have a strong influence on the emplacement of lava flows, and that to obtain more accurate simulations it is better to have continuous monitoring of the effusion rates, even if with moderate errors, rather than sparse accurate measurements. [Copyright &y& Elsevier]

July 6, 2012 Tags: CELLULAR automata, CHAOTIC behavior in systems, COMPUTER simulation, LAVA flows, MATHEMATICAL models, PARAMETER estimation, SENSITIVITY analysis, TEMPERATURE effect
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Rigorous evaluation of a soil heat transfer model for mesoscale climate change impact studies

Abstract: The influence of Climate Change on plant development as well as on carbon and nitrogen cycling in soils is an important research topic for Global Change impact assessment at the regional scale. These changes affect the availability and quality of ground and surface waters and accordingly the future productivity of agriculturally used landscapes. The integrated assessment of these changes requires a robust prediction of the potential future characteristics of soil temperature and moisture based on scale-appropriate, process-oriented models. Hence, we present the Soil Heat Transfer Module (SHTM) used as a component of the mesoscale decision support system DANUBIA, which is developed by the multi-disciplinary research project GLOWA-Danube (www.glowa-danube.de). DANUBIA is applied on the Upper Danube catchment to assess the future changes in water availability, quality and use based on Global Change scenarios. In order to cover the temporal and spatial resolution (1h, 1×1km) of the main model as well as the desired investigation period of 50 years, SHTM combines a variable time step conductive heat transfer algorithm with an analytical lower boundary condition to react to long-term climate change with minimal model drift. Changes in soil moisture and soil freezing are explicitly taken into account. The ground heat flux at the soil surface is computed by iterative closure of the energy balance including radiative, latent and sensible energy fluxes. Validation of the heat transfer scheme shows that the variable time step solution improves computational efficiency while imposing only minimal RMSE and phase shift errors. Furthermore, the analytical lower boundary stabilizes the long term heat balance and induces a rather small potential model drift in the order of 0.001Wm−2. Then the results of the full land surface model including SHTM are compared to measurements at 25 agrometeorological sites. Without site-specific parameterisation other than land cover type, we show that the model performs well (RMSE about 2K) in reproducing daily and annual top soil temperature dynamics over long simulation periods. The analysis of systematic model errors reveals that about 75% of the RMSE is attributable to uncertainties in meteorological input, canopy parameters and snow processes. [Copyright &y& Elsevier]

July 5, 2012 Tags: Agricultural, CARBON cycle (Biogeochemistry), CLIMATIC changes, ENVIRONMENTAL impact analysis, HEAT -- Transmission, MATHEMATICAL models, METEOROLOGY, NITROGEN cycle, PLANTS -- Development, SOIL heating
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Phosphorus dynamics in an ephemeral wetland ecosystem after re-flooding

Abstract: To test whether large amounts of phosphorus (P) are accumulated in the floodplain during dry antecedent conditions, and whether they would be released as the predominant source of P in the overlaying floodwater, in accord with the Flood Pulse Concept, we calculated the mass balance of P in an intermittent floodplain wetland after environmental water application. The P mass balance was calculated by combining a wetland water balance model and P releasing dynamics that were estimated from glasshouse sediment inundation experiments. Upon receiving environmental water, which inundated 412 ha of swamps and river red gum (Eucalyptus camaldulensis) woodlands, our results showed that 394.5 kg of P was mobilised in the system (342.0 kg from 368.4 ha of woodland and 52.5 kg from 43.6 ha of swamp and channels). In addition, the mass of P in incoming water was 74.0 kg, giving a peak in situ mass of 468.5 kg P in the water column. The estimation was verified using the water column P calculated from field samples. Our results indicated that the majority of P (84.2%) was internal loading, and the floodplain may be a source of P enrichment for adjacent water bodies or groundwater if floodwater is discharged rapidly. However, our modelling results also suggested that the high concentration of P in the water column was not sustained most probably because soils re-adsorbed the dissolved P. Approximately 110 days for the woodland and 39 days for the swamp were needed to reduce the P levels to 20% of their peak values respectively. Environmental water managers must decide how to manage P-enriched floodwater; retaining floodwater in the floodplain for a long time could reduce the risk of P enrichment downstream receiving water bodies; or, keeping internal P loading in the wetland could cause eutrophication in the system that was initially targeted for restoration. Best management practices, such as staged flooding and flooding timing are discussed. [Copyright &y& Elsevier]

June 24, 2012 Tags: BIOTIC communities, ENVIRONMENTAL impact analysis, FLOODPLAIN ecology, MASS budget (Geophysics), MATHEMATICAL models, PHOSPHORUS, VERNAL pools
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On calibration data selection: the case of stormwater quality regression models

Abstract: A stormwater quality model should be calibrated and verified against available data before it can be confidently used. This paper mainly examines two questions: how do the size and selection of calibration data sets affect model performances and how should the calibration data sets be selected. Regression models are used to simulate stormwater quality (TSS and COD) with variables characterizing rainfall and flow characteristics. Based on large databases of three catchments in France, several models are calibrated and verified with different data subsets. It is confirmed that the selection of calibration data sets leads to significant uncertainty in model performance. The information content in the calibration data sets is also important in addition to their size. Generally model performances can be improved by using a large size of calibration data sets and by selecting calibration data that are representative of all data. Three methods endeavoring to improve model performance by selecting calibration data either according to model outputs or model inputs are developed based on the principle of choosing calibration data that are representative of the whole data set. The effectiveness of the three selection methods is demonstrated by their application on databases of the three catchments. Model performances can be generally improved by selection methods. The selection methods based on model inputs that consider multi-dimension information perform better than the method with one-dimension information consideration. [Copyright &y& Elsevier]

June 24, 2012 Tags: CALIBRATION, DATABASE selection, MATHEMATICAL models, PERFORMANCE evaluation, RAIN & rainfall, RAINWATER -- Analysis, WATER quality, WATERSHEDS
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Magnetic characteristics analysis of permanent magnet motor by using complex approximation taking account of two-dimensional magnetic properties

This paper presents a complex E&S modeling approach, which is developed with a complex approximation for conventional E&S modeling. Complex E&S modeling is used to analyze a permanent magnet motor and the validity of complex E&S modeling is demonstrated. The computation time of complex E&S modeling can be considerably reduced in comparison with conventional E&S modeling. © 2012 Wiley Periodicals, Inc. Electr Eng Jpn, 180(2): 9-16, 2012; Published online in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/eej.21268 [ABSTRACT FROM AUTHOR]

June 23, 2012 Tags: APPROXIMATION theory, COMPARATIVE studies, COMPUTATIONAL complexity, MAGNETIC properties, MATHEMATICAL models, PERMANENT magnet motors
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How to compute variance-based sensitivity indicators with your spreadsheet software

Abstract: The use of sensitivity indicators is explicitly recommended by authorities like the EC, the US EPA and others in model valuation and audit. In this note, we want to draw the attention to a numerically efficient algorithm that computes first order global sensitivity effects from given data using a discrete cosine transformation. [Copyright &y& Elsevier]

June 22, 2012 Tags: ALGORITHMS, ANALYSIS of variance, COMPUTER software, DATA analysis, DISCRETE cosine transforms, ELECTRONIC spreadsheets, MATHEMATICAL models, SENSITIVITY analysis
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Effects of traffic signal coordination on noise and air pollutant emissions

Abstract: Traffic management solutions are increasingly called for to address problems of transport and mobility. In particular, coordinated traffic lights that create green waves along major arterials are an increasingly used strategy to reduce travel times. Although it is usually assumed that an improved traffic flow will result in lower vehicle emissions, little scientific research has been spent on the effects of synchronized traffic lights on emissions. Moreover, because changes in traffic flow do not necessarily influence travel times, noise and air quality in the same way, there is a clear need for a combined approach. This paper reports on a computational study in which a microscopic traffic simulation model (Paramics) is combined with submodels for the emission of noise (Imagine) and air pollutants (VERSIT+). Through the simulation of a range of scenarios, the model is used to investigate the influence of traffic intensity, signal coordination schemes and signal parameters on the noise, carbon dioxide, nitrogen oxides and particulate matter emissions along an arterial road equiped with a series of traffic lights. It was found that the introduction of a green wave could potentially lower the emissions of the considered air pollutants by 10%–40% in the most favorable conditions, depending on traffic flow and signal timing settings. Sound pressure levels were found to decrease by up to 1 dB(A) near the traffic signals, but to increase by up to 1.5 dB(A) in between intersections. Traffic intensity and green split were found to have the largest influence on emissions, while the cycle time did not have a significant influence on emissions. [Copyright &y& Elsevier]

June 19, 2012 Tags: AIR pollution, COMPUTER simulation, EMISSION control, MATHEMATICAL models, NOISE pollution, PARAMETER estimation, TRAFFIC signs & signals, TRANSPORTATION -- Management, TRAVEL time (Traffic engineering)
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Bayesian networks for the management of greenhouse gas emissions in the british agricultural sector

Abstract: Recent years have witnessed a rapid rise in the development of deterministic and non-deterministic models to estimate human impacts on the environment. An important failing of these models is the difficulty that most people have understanding the results generated by them, the implications to their way of life and also that of future generations. Within the field, the measurement of greenhouse gas emissions (GHG) is one such result. The research described in this paper evaluates the potential of Bayesian Network (BN) models for the task of managing GHG emissions in the British agricultural sector. Case study farms typifying the British agricultural sector were inputted into both, the BN model and CALM, a Carbon accounting tool used by the Country Land and Business Association (CLA) in the UK for the same purpose. Preliminary results show that the BN model provides a better understanding of how the tasks carried out on a farm impact the environment through the generation of GHG emissions. This understanding is achieved by translating the emissions information into their cost in monetary terms using the Shadow Price of Carbon (SPC), something that is not possible using the CALM tool. In this manner, the farming sector should be more inclined to deploy measures for reducing its impact. At the same time, the output of the analysis can be used to generate a business plan that will not have a negative effect on a farm”s capital income. [Copyright &y& Elsevier]

June 17, 2012 Tags: AGRICULTURAL industries, BAYESIAN statistical decision theory, BUSINESS enterprises, EMISSIONS trading, ENVIRONMENTAL impact analysis, GREENHOUSE gas mitigation, MATHEMATICAL models, SHADOW prices
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Actors and factors in land-use simulation: the challenge of urban shrinkage

Abstract: Both modelers and social scientists attempt to find better explanations of complex urban systems. They include development paths, underlying driving forces and their expected impacts. So far, land-use research has predominantly focused on urban growth. However, new challenges have arisen since urban shrinkage entered the research agenda of the social and land-use sciences. Therefore, the focus of this paper is a twofold one: Using the example of urban shrinkage, we first discuss the capacity of existing land-use modeling approaches to integrate new social science knowledge in terms of land-use, demography and governance because social science models are indispensable for accurately explaining the processes behind shrinkage. Second, we discuss the combination of system dynamics (SD), cellular automata (CA) and agent-based model (ABM) approaches to cover the main characteristics, processes and patterns of urban shrinkage. Using Leipzig, Germany, as a case study, we provide the initial results of a joint SD-CA model and an ABM that both operationalize social science knowledge regarding urban shrinkage. [Copyright &y& Elsevier]

June 16, 2012 Tags: CELLULAR automata, COMPUTER simulation, DEMOGRAPHY, LAND use, MATHEMATICAL models, SOCIAL scientists, URBAN decline, URBAN growth
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A multi-model comparison of soil carbon assessment of a coniferous forest stand

Abstract: We simulated soil carbon stock dynamics of an Austrian coniferous forest stand with five soil-only models (Q, ROMUL, RothC, SoilCO2/RothC and Yasso07) and three plant–soil models (CENTURY, CoupModel and Forest-DNDC) for an 18-year period and the decomposition of a litter pulse over a 100-year period. The objectives of the study were to assess the consistency in soil carbon estimates applying a multi-model comparison and to present and discuss the sources of uncertainties that create the differences in model results. Additionally, we discuss the applicability of different modelling approaches from the view point of large-scale carbon assessments. Our simulation results showed a wide range in soil carbon stocks and stock change estimates reflecting substantial uncertainties in model estimates. The measured stock change estimate decreased much more than the model predictions. Model results varied not only due to the model structure and applied parameters, but also due to different input information and assumptions applied during the modelling processes. Initialization procedures applied with the models induced large differences among the modelled soil carbon stocks and stock change estimates. Decomposition estimates of the litter pulse driven by model structures and parameters also varied considerably. Our results support the use of relatively simple soil-only models with low data requirements in inventory type of large-scale carbon assessments. It is important that the modelling processes within the national inventories are transparently reported and special emphasis is put on how the models are used, which assumptions are applied and what is the quality of data used both as input and to calibrate the models. [Copyright &y& Elsevier]

June 16, 2012 Tags: COMPARATIVE studies, COMPUTER simulation, FOREST litter -- Biodegradation, MATHEMATICAL models, PARAMETER estimation, SOILS -- Carbon content, TAIGAS, UNCERTAINTY (Information theory)
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