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Title: Sequential Design of Experiments

Abstract

A sequential design of experiments strategy is being developed and implemented that allows for adaptive learning based on incoming results as the experiment is being run. The plan is to incorporate these strategies for the NCCC and TCM experimental campaigns to be run in the coming months. This strategy for experimentation has the advantages of allowing new data collected during the experiment to inform future experimental runs based on their projected utility for a particular goal. For example, the current effort for the MEA capture system at NCCC plans to focus on maximally improving the quality of prediction of CO 2 capture efficiency as measured by the width of the confidence interval for the underlying response surface that is modeled as a function of 1) Flue Gas Flowrate [1000-3000] kg/hr; 2) CO 2 weight fraction [0.125-0.175]; 3) Lean solvent loading [0.1-0.3], and; 4) Lean solvent flowrate [3000-12000] kg/hr.

Authors:
 [1]
  1. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Research Org.:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1367830
Report Number(s):
LA-UR-17-25281
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS; Energy Sciences

Citation Formats

Anderson-Cook, Christine Michaela. Sequential Design of Experiments. United States: N. p., 2017. Web. doi:10.2172/1367830.
Anderson-Cook, Christine Michaela. Sequential Design of Experiments. United States. doi:10.2172/1367830.
Anderson-Cook, Christine Michaela. Fri . "Sequential Design of Experiments". United States. doi:10.2172/1367830. https://www.osti.gov/servlets/purl/1367830.
@article{osti_1367830,
title = {Sequential Design of Experiments},
author = {Anderson-Cook, Christine Michaela},
abstractNote = {A sequential design of experiments strategy is being developed and implemented that allows for adaptive learning based on incoming results as the experiment is being run. The plan is to incorporate these strategies for the NCCC and TCM experimental campaigns to be run in the coming months. This strategy for experimentation has the advantages of allowing new data collected during the experiment to inform future experimental runs based on their projected utility for a particular goal. For example, the current effort for the MEA capture system at NCCC plans to focus on maximally improving the quality of prediction of CO2 capture efficiency as measured by the width of the confidence interval for the underlying response surface that is modeled as a function of 1) Flue Gas Flowrate [1000-3000] kg/hr; 2) CO2 weight fraction [0.125-0.175]; 3) Lean solvent loading [0.1-0.3], and; 4) Lean solvent flowrate [3000-12000] kg/hr.},
doi = {10.2172/1367830},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Jun 30 00:00:00 EDT 2017},
month = {Fri Jun 30 00:00:00 EDT 2017}
}

Technical Report:

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