Novel phenomena-based dynamic model of carbon black/composite vapour sensors

2006 ◽  
Vol 463 (2078) ◽  
pp. 551-568 ◽  
Author(s):  
James W.T Yates ◽  
Michael J Chappell ◽  
Julian W Gardner
Keyword(s):  
Mathematical Model ◽  
Carbon Black ◽  
Ambient Air ◽  
Model Parameters ◽  
World Systems ◽  
Computational Power ◽  
Ethanol Vapour ◽  
Physically Based ◽  
Poly Caprolactone ◽  
Modelling Approach

A novel physically based mathematical model of carbon black/polymer vapour sensors is described, which incorporates parameters that have physical meaning. This model has an analytical solution and so requires negligible computational power to analyse a sensor's response to a particular form of input. Another advantage of this modelling approach is that the environmental dependencies of sensor responses may be compensated for and so help in the design of better pattern-recognition algorithms for electronic nose systems. This also means that the underlying chemistry of the sensors may be decoupled from their physical non-analyte specific properties. Experimentally, three different conducting nanocomposite polymers, poly(styrene- co -butadine), poly(ethyl- co -vinyl acetate) and poly(caprolactone), were tested. Each experiment consisted of separate exposures of the sensors to acetone and ethanol vapour in ambient air. A total of 336 such experiments were performed over a two-week period. The model was validated with respect to these data and was then fitted to the two vapour responses simultaneously, demonstrating its applicability to ‘real world’ systems. The temperature dependence of the model parameters was judged to be the most important factor and it needs to be compensated for when applying this type of sensor in practice.

scholarly journals Testing the Efficiency of Parameter Disaggregation for Distributed Rainfall-Runoff Modelling

Water ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 972
Author(s):  
Sotirios Moustakas ◽  
Patrick Willems
Keyword(s):  
Spatial Data ◽  
Distributed Model ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Natural Processes ◽  
Reliable Model ◽  
Physically Based ◽  
Lumped Models ◽  
Uniform Model ◽  
Modelling Approach

A variety of hydrological models is currently available. Many of those employ physically based formulations to account for the complexity and spatial heterogeneity of natural processes. In turn, they require a substantial amount of spatial data, which may not always be available at sufficient quality. Recently, a top-down approach for distributed rainfall-runoff modelling has been developed, which aims at combining accuracy and simplicity. Essentially, a distributed model with uniform model parameters (base model) is derived from a calibrated lumped conceptual model. Subsequently, selected parameters are disaggregated based on links with the available spatially variable catchment properties. The disaggregation concept is now adjusted to better account for non-linearities and extended to incorporate more model parameters (and, thus, larger catchment heterogeneity). The modelling approach is tested for a catchment including several flow gauging stations. The disaggregated model is shown to outperform the base model with respect to internal catchment dynamics, while performing similarly at the catchment outlet. Moreover, it manages to bridge on average 44% of the Nash–Sutcliffe efficiency difference between the base model and the lumped models calibrated for the internal gauging stations. Nevertheless, the aforementioned improvement is not necessarily sufficient for reliable model results.

A complementary modelling approach to manage uncertainty of computationally expensive models

2007 ◽  
Vol 56 (8) ◽  
pp. 1-9 ◽  
Author(s):  
Z. Vojinovic
Keyword(s):  
Support Vector ◽  
Model Parameters ◽  
Machine Model ◽  
Systematic Analysis ◽  
Physically Based Model ◽  
Physically Based ◽  
Computationally Expensive ◽  
Estimation Of Model Parameters ◽  
Insight Into ◽  
Modelling Approach

The fact that the models applied in the ‘water domain’ are far from reality can be attributed to many reasons. In this context, a systematic analysis of uncertainties reflected by the model error can provide insight into the level of confidence in the model results and how to approach estimation of optimal model parameters. This paper discusses the four commonly used approaches for estimation of model parameters and suggests that an alternative complementary modelling approach should be considered in cases where the traditional model calibration gives limited results and particularly in cases where the computationally expensive models are concerned. It treats uncertainty as modelling the total discrepancy between the model and physical process. The proposed approach combines the results from a physically-based model and Support Vector Machine model into the final solution.

scholarly journals Sequential modelling of the Earth’s core magnetic field

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Guillaume Ropp ◽  
Vincent Lesur ◽  
Julien Baerenzung ◽  
Matthias Holschneider
Keyword(s):  
Magnetic Field ◽  
Prior Information ◽  
Spatial Scales ◽  
Model Parameters ◽  
International Geomagnetic Reference Field ◽  
The Earth ◽  
Temporal And Spatial ◽  
Different Sources ◽  
Original Approach ◽  
Modelling Approach

Abstract We describe a new, original approach to the modelling of the Earth’s magnetic field. The overall objective of this study is to reliably render fast variations of the core field and its secular variation. This method combines a sequential modelling approach, a Kalman filter, and a correlation-based modelling step. Sources that most significantly contribute to the field measured at the surface of the Earth are modelled. Their separation is based on strong prior information on their spatial and temporal behaviours. We obtain a time series of model distributions which display behaviours similar to those of recent models based on more classic approaches, particularly at large temporal and spatial scales. Interesting new features and periodicities are visible in our models at smaller time and spatial scales. An important aspect of our method is to yield reliable error bars for all model parameters. These errors, however, are only as reliable as the description of the different sources and the prior information used are realistic. Finally, we used a slightly different version of our method to produce candidate models for the thirteenth edition of the International Geomagnetic Reference Field.

On the spread of ultrafine particulate matter: A mathematical model for motor vehicle emissions and their effects as an asthma trigger

2021 ◽  
Author(s):  
Michelle N. Rosado-Pérez ◽  
Karen Ríos-Soto
Keyword(s):  
Mathematical Model ◽  
Ultrafine Particles ◽  
Motor Vehicle ◽  
Traveling Wave Solutions ◽  
Reaction Diffusion ◽  
Ambient Air ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Motor Vehicles ◽  
Diffusion Type

Asthma is a respiratory disease that affects the lungs, with a prevalence of 339.4 million people worldwide [G. Marks, N. Pearce, D. Strachan, I. Asher and P. Ellwood, The Global Asthma Report 2018, globalasthmareport.org (2018)]. Many factors contribute to the high prevalence of asthma, but with the rise of the industrial age, air pollutants have become one of the main Ultrafine particles (UFPs), which are a type of air pollutant that can affect asthmatics the most. These UFPs originate primarily from the combustion of motor vehicles [P. Solomon, Ultrafine particles in ambient air. EM: Air and Waste Management Association’s Magazine for Environmental Managers (2012)] and although in certain places some regulations to control their emission have been implemented they might not be enough. In this work, a mathematical model of reaction–diffusion type is constructed to study how UFPs grow and disperse in the environment and in turn how they affect an asthmatic population. Part of our focus is on the existence of traveling wave solutions and their minimum asymptotic speed of pollutant propagation [Formula: see text]. Through the analysis of the model it was possible to identify the necessary threshold conditions to control the pollutant emissions and consequently reduce the asthma episodes in the population. Analytical and numerical results from this work prove how harmful the UFEs are for the asthmatic population and how they can exacerbate their asthma episodes.

A sewer ventilation model applying conservation of momentum

2011 ◽  
Vol 64 (6) ◽  
pp. 1374-1382 ◽  
Author(s):  
M. Ward ◽  
G. Hamer ◽  
A. McDonald ◽  
J. Witherspoon ◽  
E. Loh ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Treatment Plant ◽  
Ambient Air ◽  
Momentum Equation ◽  
Ventilation Rate ◽  
Water Interface ◽  
Model Accuracy ◽  
Air Water Interface ◽  
Conservation Of Momentum ◽  
Gravity Sewer

The work presented herein was completed in an effort to characterize the forces influencing ventilation in gravity sewers and to develop a mathematical model, based on conservation of momentum, capable of accounting for friction at the headspace/pipe interface, drag at the air/water interface, and buoyancy caused by air density differences between a sewer headspace and ambient. Experiments were completed on two full scale sewer reaches in Australia. A carbon monoxide-based tracer technique was used to measure the ventilation rate within the sewer headspaces. Additionally, measurements of pressure, relative humidity, and temperature were measured in the ambient air and sewer headspace. The first location was a five kilometre long sewer outfall beginning at a wastewater treatment plant and terminating at the ocean. The second location was a large gravity sewer reach fitted with ventilation fans. At the first location the headspace was entirely sealed except for openings that were controlled during the experiments. In this situation forces acting on the headspace air manifested mostly as a pressure distribution within the reach, effectively eliminating friction at the pipe wall. At the second location, air was forced to move near the same velocity as the wastewater, effectively eliminating drag at the air/water interface. These experiments allowed individual terms of the momentum equation to be evaluated. Experimental results were compared to the proposed mathematical model. Conclusions regarding model accuracy are provided along with model application guidance and assumptions.

scholarly journals Evaluating performances of simplified physically based models for landslide susceptibility

2015 ◽  
Vol 12 (12) ◽  
pp. 13217-13256 ◽  
Author(s):  
G. Formetta ◽  
G. Capparelli ◽  
P. Versace
Keyword(s):  
Landslide Susceptibility ◽  
Goodness Of Fit ◽  
Shallow Landslides ◽  
Model Parameters ◽  
Test Case ◽  
Susceptibility Analysis ◽  
Physically Based ◽  
Private And Public ◽  
Physically Based Models

Abstract. Rainfall induced shallow landslides cause loss of life and significant damages involving private and public properties, transportation system, etc. Prediction of shallow landslides susceptible locations is a complex task that involves many disciplines: hydrology, geotechnical science, geomorphology, and statistics. Usually to accomplish this task two main approaches are used: statistical or physically based model. Reliable models' applications involve: automatic parameters calibration, objective quantification of the quality of susceptibility maps, model sensitivity analysis. This paper presents a methodology to systemically and objectively calibrate, verify and compare different models and different models performances indicators in order to individuate and eventually select the models whose behaviors are more reliable for a certain case study. The procedure was implemented in package of models for landslide susceptibility analysis and integrated in the NewAge-JGrass hydrological model. The package includes three simplified physically based models for landslides susceptibility analysis (M1, M2, and M3) and a component for models verifications. It computes eight goodness of fit indices by comparing pixel-by-pixel model results and measurements data. Moreover, the package integration in NewAge-JGrass allows the use of other components such as geographic information system tools to manage inputs-output processes, and automatic calibration algorithms to estimate model parameters. The system was applied for a case study in Calabria (Italy) along the Salerno-Reggio Calabria highway, between Cosenza and Altilia municipality. The analysis provided that among all the optimized indices and all the three models, the optimization of the index distance to perfect classification in the receiver operating characteristic plane (D2PC) coupled with model M3 is the best modeling solution for our test case.

scholarly journals Hydrologic responses of the Zwalm catchment using the REW model: incorporating uncertainty of soil properties

2006 ◽  
Vol 3 (1) ◽  
pp. 69-114 ◽  
Author(s):  
A. El Ouazzani Taibi ◽  
G. P. Zhang ◽  
A. Elfeki
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Hydraulic Conductivity ◽  
Model Parameters ◽  
Watershed Model ◽  
The Monte Carlo Method ◽  
Physically Based ◽  
Hydrologic Responses ◽  
High Influence ◽  
Model Approach

Abstract. The research presented in this paper focuses on an application of a newly developed physically-based watershed model approach, which is called Representative Elementary Watershed (REW) approach. The study stressed the effects of uncertainty of input parameters on the watershed responses (i.e. simulated discharges). The approach was applied to the Zwalm catchment, which is an agriculture dominated watershed with a drainage area of 114.3 km2 located in East-Flanders, Belgium. Uncertainty analysis of the model parameters is limited to the saturated hydraulic conductivity because of its high influence on the watershed hydrologic behavior. The assessment of outputs uncertainty is performed using the Monte Carlo method. The ensemble statistical watershed responses and their uncertainties are calculated and compared with the measurements. The results show that the measured discharges are falling within the 95% confidence interval of the modeled discharge.

scholarly journals A Population Modelling Approach to Studying Age-Related Effects on Excitation-Contraction Coupling in Human Cardiomyocytes

2019 ◽  
Author(s):  
Arsenii Dokuchaev ◽  
Svyatoslav Khamzin ◽  
Olga Solovyova
Keyword(s):  
Experimental Data ◽  
Transient Outward Current ◽  
Model Parameters ◽  
Maximal Velocity ◽  
Population Modelling ◽  
Individual Parameter ◽  
Human Cardiomyocytes ◽  
Age Related ◽  
Age Related Changes ◽  
Modelling Approach

AbstractAgeing is the dominant risk factor for cardiovascular diseases. A great body of experimental data has been gathered on cellular remodelling in the Ageing myocardium from animals. Very few experimental data are available on age-related changes in the human cardiomyocyte. We have used our combined electromechanical model of the human cardiomyocyte and the population modelling approach to investigate the variability in the response of cardiomyocytes to age-related changes in the model parameters. To generate the model population, we varied nine model parameters and excluded model samples with biomarkers falling outside of the physiological ranges. We evaluated the response to age-related changes in four electrophysiological model parameters reported in the literature: reduction in the density of the K+ transient outward current, maximal velocity of SERCA, and an increase in the density of NaCa exchange current and CaL-type current. The sensitivity of the action potential biomarkers to individual parameter variations was assessed. Each parameter modulation caused an increase in APD, while the sensitivity of the model to changes in GCaL and Vmax_up was much higher than to those in the effects of Gto and KNaCa. Then 60 age-related sets of the four parameters were randomly generated and each set was applied to every model in the control population. We calculated the frequency of model samples with repolarisation anomalies (RA) and the shortening of the electro-mechanical window in the ageing model populations as an arrhythmogenic ageing score. The linear dependence of the score on the deviation of the parameters showed a high determination coefficient with the most significant impact due to the age-related change in the CaL current. The population-based approach allowed us to classify models with low and high risk of age-related RA and to predict risks based on the control biomarkers.

scholarly journals The identification of a device based on a Peltier element by the least squares method

2020 ◽  
pp. 17-27
Author(s):  
Vladimir Grinkevich ◽  
Keyword(s):  
Mathematical Model ◽  
Least Squares ◽  
Least Squares Method ◽  
Control Object ◽  
Object Identification ◽  
Model Parameters ◽  
Peltier Element ◽  
Transport Delay ◽  
Non Linear ◽  
The Mathematical Model

The evaluation of the mathematical model parameters of a non-linear object with a transport delay is considered in this paper. A temperature controlled stage based on a Peltier element is an identification object in the paper. Several input signal implementations are applied to the input of the identification object. The least squares method is applied for the calculation of the non-linear differential equitation parameters which describe the identification object. The least squares method is used due to its simplicity and the possibility of identification non-linear objects. The parameters values obtained in the process of identification are provided. The plots of temperature changes in the temperature control system with a controller designed based on the mathematical model of the control object obtained as a result of identification are shown. It is found that the mathematical model obtained in the process of identification may be applied to design controllers for non-linear systems, in particular for a temperature stage based on a Peltier element, and for self-tuning controllers. However, the least square method proposed in the paper cannot estimate the transport delay time. Therefore it is required to evaluate the time delay by temperature transient processes. Dynamic object identification is applied when it is required to obtain a mathematical model structure and evaluate the parameters by an input and output control object signal. Also, identification is applied for auto tuning of controllers. A mathematical model of a control object is required to design the controller which is used to provide the required accuracy and stability of control systems. Peltier elements are applied to design low-power and small- size temperature stage . Hot benches based on a Peltier element can provide the desired temperature above and below ambient temperature.

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