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Sampling Plans01:23

Sampling Plans

Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
Typical Model Studies01:30

Typical Model Studies

Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.

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Related Experiment Video

Updated: Jun 26, 2026

Lab-Scale Model to Evaluate Odor and Gas Concentrations Emitted by Deep Bedded Pack Manure
06:52

Lab-Scale Model to Evaluate Odor and Gas Concentrations Emitted by Deep Bedded Pack Manure

Published on: July 19, 2018

Scaled tests and modeling of effluent stack sampling location mixing.

Kurtis P Recknagle1, Satoru T Yokuda, Marcel Y Ballinger

  • 1Pacific Northwest National Laboratory, PO Box 999, Richland, WA 99352, USA.

Health Physics
|January 10, 2009
PubMed
Summary
This summary is machine-generated.

Computational fluid dynamics (CFD) modeling effectively predicts mixing in radioactive air emission sampling systems. This approach aids in designing compliant sampling locations for nuclear facilities, meeting American National Standards Institute standards.

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Area of Science:

  • Nuclear Engineering
  • Environmental Monitoring
  • Computational Science

Background:

  • Nuclear facilities require precise monitoring of radioactive air emissions.
  • Compliance with American National Standards Institute (ANSI) standards is crucial for sampling systems.
  • Ensuring uniform air velocity and contaminant concentration is key to accurate monitoring.

Purpose of the Study:

  • To evaluate the mixing efficiency of a radioactive air emission sampling system using computational fluid dynamics (CFD).
  • To determine if the sampling location meets ANSI/HPS N13.1-1999 criteria for uniformity.
  • To assess the cost-effectiveness of CFD modeling in designing or retrofitting sampling systems.

Main Methods:

  • A three-dimensional computational fluid dynamics (CFD) computer model was developed.
  • The model simulated airflow and contaminant mixing in the exhaust system of the Radiochemical Processing Laboratory.
  • CFD predictions were compared with measurements from a scale-model stack and the full-scale facility stack.

Main Results:

  • CFD modeling provided reasonable predictions for velocity, cyclonic flow, and gas/aerosol uniformity.
  • The model indicated greater mixing improvement with increased distance from the injection point than observed in measurements.
  • Modeled full-scale uniformity values were similar to those of the scale model.

Conclusions:

  • CFD is a valuable tool for assessing and optimizing radioactive air emission sampling locations.
  • The CFD model can predict performance and aid in meeting regulatory standards like ANSI/HPS N13.1-1999.
  • CFD offers a cost-effective method for designing and retrofitting nuclear facility sampling systems.