mass

Mass measurements for 9 batch anaerobic reactors.

datasets

Functions for calculating biochemical methane potential (BMP) from laboratory measurements and other types of data processing and prediction useful for biogas research. Raw laboratory measurements for diverse methods (volumetric, manometric, gravimetric, gas density) can be processed to calculate BMP. Theoretical maximum BMP or methane or biogas yield can be predicted from various measures of substrate composition. Molar mass and calculated oxygen demand (COD') can be determined from a chemical formula. Measured gas volume can be corrected for water vapor and to standard (or user-defined) temperature and pressure. Gas quantity can be converted between volume, mass, and moles. A function for planning BMP experiments can consider multiple constraints in suggesting substrate or inoculum quantities, and check for problems. Inoculum and substrate mass can be determined for planning BMP experiments. Finally, a set of first-order models can be fit to measured methane production rate or cumulative yield in order to extract estimates of ultimate yield and kinetic constants. See Hafner et al. (2018) <doi:10.1016/j.softx.2018.06.005> for details. OBA is a web application that provides access to some of the package functionality: <https://biotransformers.shinyapps.io/oba1/>. The Standard BMP Methods website documents the calculations in detail: <https://www.dbfz.de/en/BMP>.

Sasha D. Hafner

biogas

Process Biogas Data and Predict Biogas Production

Charlotte Rennuit

Camilla Justesen

Nanna Lojborg

Jacob Mortensen

Jonas Ohlsson

Sergi Astals

Konrad Koch

Soeren Weinrich

Jin Mi Triolo

Ali Heidarzadeh Vazifehkhoran

mass function

A data frame with 18 observations on the following 4 variables.<dl>
 <dt><code>id</code></dt>
<dd>identification code, a unique value for each reactor in the dataset. A factor with levels <code>2_1</code>, <code>2_2</code>, <code>2_3</code>, <code>2_4</code>, <code>2_5</code>, <code>2_6</code>, <code>2_10</code>, <code>2_11</code>, and <code>2_12</code></dd> <dt><code>date.time</code></dt>
<dd>date and time of mass measurement, a POSIXct object.</dd> <dt><code>days</code></dt>
<dd>elapsed time of mass measurements (from reactor setup) in days, a numeric vector.</dd> <dt><code>mass</code></dt>
<dd>total reactor mass in g, a numeric vector.</dd> <dt><code>when</code></dt>
<dd>when was measurement taken? A character vector with two values.</dd> 
</dl>

Format

Mass Change of Batch Reactors — mass

A data frame with 18 observations on the following 4 variables.<dl>
 <dt><code>id</code></dt>
<dd>identification code, a unique value for each reactor in the dataset. A factor with levels <code>2_1</code>, <code>2_2</code>, <code>2_3</code>, <code>2_4</code>, <code>2_5</code>, <code>2_6</code>, <code>2_10</code>, <code>2_11</code>, and <code>2_12</code></dd>

 <dt><code>date.time</code></dt>
<dd>date and time of mass measurement, a POSIXct object.</dd>

 <dt><code>days</code></dt>
<dd>elapsed time of mass measurements (from reactor setup) in days, a numeric vector.</dd>

 <dt><code>mass</code></dt>
<dd>total reactor mass in g, a numeric vector.</dd>

 <dt><code>when</code></dt>
<dd>when was measurement taken? A character vector with two values.</dd>

 
</dl>

Mass Change of Batch Reactors

mass: Mass Change of Batch Reactors

Description

Usage

Arguments

Format

Details

Examples