scholarly journals Reference equations for impulse oscillometric and respiratory system model parameters in anglo and hispanic children

2016 ◽  
Vol 37 (1) ◽  
Author(s):  
EG Meraz
Keyword(s):  
Respiratory System ◽  
System Model ◽  
Model Parameters ◽  
Hispanic Children ◽  
Reference Equations

Multi-day flow forecasting using the Kalman filter

1991 ◽  
Vol 18 (2) ◽  
pp. 320-327 ◽  
Author(s):  
Murray A. Fitch ◽  
Edward A. McBean
Keyword(s):  
Kalman Filter ◽  
Prediction Model ◽  
Linear Prediction ◽  
Measured Data ◽  
System Model ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Forecasting Performance ◽  
Optimal Forecasting ◽  
Linear Prediction Model

A model is developed for the prediction of river flows resulting from combined snowmelt and precipitation. The model employs a Kalman filter to reflect uncertainty both in the measured data and in the system model parameters. The forecasting algorithm is used to develop multi-day forecasts for the Sturgeon River, Ontario. The algorithm is shown to develop good 1-day and 2-day ahead forecasts, but the linear prediction model is found inadequate for longer-term forecasts. Good initial parameter estimates are shown to be essential for optimal forecasting performance. Key words: Kalman filter, streamflow forecast, multi-day, streamflow, Sturgeon River, MISP algorithm.

Simulation and Simulation Software Development of the Braking Process of a Subway Train

2014 ◽  
Vol 556-562 ◽  
pp. 294-301 ◽  
Author(s):  
Long Han ◽  
Chun Tian ◽  
Yan Wang ◽  
Meng Ling Wu ◽  
Zhuo Jun Luo
Keyword(s):  
Computational Effort ◽  
Simulation Software ◽  
System Model ◽  
Brake System ◽  
Railway Vehicle ◽  
Model Parameters ◽  
Modeling Process ◽  
Time Simulation ◽  
Subway Train ◽  
Braking Process

This paper deals with the problem of braking process modeling. A subway train braking process simulation software is built, which composes of a GUI and a underlying model. The underlying model consists of a train model and a brake system model. The train model is simplified and built by assembling subcomponent element models of a railway vehicle. The brake system model is simplified and built based on experimental data in order to reduce computational effort. The GUI of the software can be use to input model parameters, display simulation results, and store simulation data. As a result of the simplifications of the modeling process, the developed software can perform real time simulation.

scholarly journals Experimental Evaluation of Dry Powder Inhalers During In- and Exhalation Using a Model of the Human Respiratory System (xPULM™)

2021 ◽  
Author(s):  
Richard Pasteka ◽  
Joao Pedro Santos da Costa ◽  
Mathias Forjan
Keyword(s):  
Respiratory Tract ◽  
Respiratory System ◽  
Particle Number ◽  
Particle Diameter ◽  
Upper Airway ◽  
System Model ◽  
Dry Powder Inhalers ◽  
Dry Powder ◽  
Pharmaceutical Aerosols ◽  
Airway Model

Dry powder inhalers are used by a large number of patients worldwide to treat respiratory diseases. The objective of this work is to experimentally investigate changes in aerosol particle diameter and particle number concentration of pharmaceutical aerosols generated by five dry powder inhalers under realistic inhalation and exhalation conditions. The active respiratory system model (xPULM™) was used as a model of the human respiratory system and to simulate a patient undergoing inhalation therapy. A mechanical upper airway model was developed, manufactured and introduced as a part of the xPULM™ to represent the human upper respiratory tract with high fidelity. Integration of optical aerosol spectrometry technique into the setup allowed for evaluation of pharmaceutical aerosols. The results show that the upper airway model increases the resistance of the overall system and act as a filter for bigger particles (>3 µm). Furthermore, there is a significant difference (p < 0.05) in mean particle diameter between inhaled and exhaled particles with the majority of the particles depositing in the lung. The minimum deposition is reached for particle size of 0.5 µm. The mean particle number concentrations exhaled are 2.94% (BreezHaler®), 2.66% (Diskus®), 10.24% (Ellipta®) 2.13% (HandiHaler®) and 6.22% (Turbohaler®). In conclusion, the xPULM™ active respiratory system model is a viable option for studying interactions of pharmaceutical aerosols and the respiratory tract in terms of applicable deposition mechanisms. The model can support the reduction of animal experimentation in aerosol research and provide an alternative to experiments with human subjects.

scholarly journals Oceanic and atmospheric methane cycling in the cGENIE Earth system model

2020 ◽  
Author(s):  
Christopher T. Reinhard ◽  
Stephanie Olson ◽  
Sandra Kirtland Turner ◽  
Cecily Pälike ◽  
Yoshiki Kanzaki ◽  
...  
Keyword(s):  
Climate Impacts ◽  
Earth System Model ◽  
System Model ◽  
Comprehensive Treatment ◽  
Model Parameters ◽  
Anaerobic Oxidation Of Methane ◽  
Earth System ◽  
Atmospheric Methane ◽  
Model Framework ◽  
Oxidation Of Methane

Abstract. The methane (CH4) cycle is a key component of the Earth system that links planetary climate, biological metabolism, and the global biogeochemical cycles of carbon, oxygen, sulfur, and hydrogen. However, currently lacking is a numerical model capable of simulating a diversity of environments in the ocean where CH4 can be produced and destroyed, and with the flexibility to be able to explore not only relatively recent perturbations to Earth’s CH4 cycle but also to probe CH4 cycling and associated climate impacts under the very low-O2 conditions characteristic of most of Earth history and likely widespread on other Earth-like planets. Here, we present a refinement and expansion of the ocean-atmosphere CH4 cycle in the intermediate-complexity Earth system model cGENIE, including parameterized atmospheric O2-O3-CH4 photochemistry and schemes for microbial methanogenesis, aerobic methanotrophy, and anaerobic oxidation of methane (AOM). We describe the model framework, compare model parameterizations against modern observations, and illustrate the flexibility of the model through a series of example simulations. Though we make no attempt to rigorously tune default model parameters, we find that simulated atmospheric CH4 levels and marine dissolved CH4 distributions are generally in good agreement with empirical constraints for the modern and recent Earth. Finally, we illustrate the model’s utility in understanding the time-dependent behavior of the CH4 cycle resulting from transient carbon injection into the atmosphere, and present model ensembles that examine the effects of atmospheric pO2, oceanic dissolved SO42− and the thermodynamics of microbial metabolism on steady-state atmospheric CH4 abundance. Future model developments will address the sources and sinks of CH4 associated with the terrestrial biosphere and marine CH4 gas hydrates, both of which will be essential for comprehensive treatment of Earth’s CH4 cycle during geologically recent time periods.

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