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Related Concept Videos

Regression Analysis01:11

Regression Analysis

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Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
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Carbon Dioxide Transport in the Blood01:19

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Carbon dioxide (CO2) transport in the blood is critical to human physiology. On average, our body cells produce around 200 mL of CO2 per minute, precisely the quantity expelled by the lungs. This process involves the transportation of CO2 from the tissue cells to the lungs in three primary forms.
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1. Dissolved in plasma: A small percentage (7-10%) of CO2 is transported and dissolved directly in the plasma.
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Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
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Model Approaches for Pharmacokinetic Data: Physiological Models01:15

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Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
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Estimation of the Physical Quantities01:05

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On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
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Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

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Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
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Measurements of CO2 Fluxes at Non-Ideal Eddy Covariance Sites
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A predictive estimation method for carbon dioxide transport by data-driven modeling with a physically-based data

Jina Jeong1, Eungyu Park2, Weon Shik Han3

  • 1Korea Institute of Geoscience and Mineral Resources, Daejeon, Republic of Korea.

Journal of Contaminant Hydrology
|October 4, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a data-driven method to predict carbon dioxide (CO2) leaks and concentrations from geological sequestration sites. The method, using the Ogata-Banks solution, accurately forecasts future CO2 levels and quantifies uncertainty.

Keywords:
CO(2) concentrationCyber-physical system (CPS)Data modelData-driven modelEarly warning system (EWS)Process-based model

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Area of Science:

  • Geological Engineering
  • Environmental Science
  • Data Science

Background:

  • Geological CO2 sequestration requires accurate monitoring for potential leaks.
  • Predicting CO2 concentrations is crucial for environmental safety and operational management.

Purpose of the Study:

  • To develop and validate a data-driven method for predicting CO2 leaks and concentrations.
  • To enhance prediction accuracy by integrating a physically-based data model.

Main Methods:

  • Comparative analysis of candidate models using CO2 concentration data from the EIT site.
  • Adoption of the Ogata-Banks solution as the representative data model.
  • Ensemble forecasting using a training dataset for validation.

Main Results:

  • The Ogata-Banks solution demonstrated superior representativeness for the test data.
  • The developed data-driven method, incorporating the Ogata-Banks model, achieved high prediction accuracy.
  • The method effectively captured uncertainty through quantile intervals.

Conclusions:

  • Integrating physically-based models significantly improves data-driven predictions for CO2 sequestration monitoring.
  • The proposed method offers a robust tool for real-time monitoring and decision-making in subsurface applications.