Comparison of moisture prediction models for stacked fuelwood

Jyrki Raitila (Corresponding Author), Veli-Pekka Heiskanen, Johanna Routa, Marja Kolström, Lauri Sikanen

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)

Abstract

The objective of this study was to develop, compare and validate model prototypes for estimating the optimal storage time of fuelwood stacks stored outdoors based on average moisture changes. Multivariate models for estimating moisture changes in different drying environments were created for this purpose. Experimental data were gathered during 7 to 14 months for most common wood fuel raw materials. In addition to taking moisture samples manually, load cell-based automated data recording for fuelwood moisture content change estimation proved a feasible option to obtain data for fuelwood drying models. The major factors considered in this study for predicting woody biomass moisture content change were precipitation, cumulative precipitation, evaporation, cumulative reference evaporation and fuelwood type. Multivariate drying models can help optimize deliveries of fuelwood and therefore increase the efficiency of the whole fuelwood supply chain.
Original languageEnglish
Pages (from-to)1896-1905
JournalBioenergy Research
Volume8
Issue number4
DOIs
Publication statusPublished - 2015
MoE publication typeA1 Journal article-refereed

Fingerprint

fuelwood
Moisture
prediction
Drying
Evaporation
drying
Wood fuels
Data recording
evaporation
water content
Supply chains
Raw materials
Biomass
supply chain
prototypes
raw materials
storage time
biomass

Keywords

  • Moisture content
  • Fuelwood
  • Natural drying
  • Drying model
  • Predicting moisture

Cite this

Raitila, Jyrki ; Heiskanen, Veli-Pekka ; Routa, Johanna ; Kolström, Marja ; Sikanen, Lauri. / Comparison of moisture prediction models for stacked fuelwood. In: Bioenergy Research. 2015 ; Vol. 8, No. 4. pp. 1896-1905.
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Comparison of moisture prediction models for stacked fuelwood. / Raitila, Jyrki (Corresponding Author); Heiskanen, Veli-Pekka; Routa, Johanna; Kolström, Marja; Sikanen, Lauri.

In: Bioenergy Research, Vol. 8, No. 4, 2015, p. 1896-1905.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

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AU - Raitila, Jyrki

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AU - Routa, Johanna

AU - Kolström, Marja

AU - Sikanen, Lauri

PY - 2015

Y1 - 2015

N2 - The objective of this study was to develop, compare and validate model prototypes for estimating the optimal storage time of fuelwood stacks stored outdoors based on average moisture changes. Multivariate models for estimating moisture changes in different drying environments were created for this purpose. Experimental data were gathered during 7 to 14 months for most common wood fuel raw materials. In addition to taking moisture samples manually, load cell-based automated data recording for fuelwood moisture content change estimation proved a feasible option to obtain data for fuelwood drying models. The major factors considered in this study for predicting woody biomass moisture content change were precipitation, cumulative precipitation, evaporation, cumulative reference evaporation and fuelwood type. Multivariate drying models can help optimize deliveries of fuelwood and therefore increase the efficiency of the whole fuelwood supply chain.

AB - The objective of this study was to develop, compare and validate model prototypes for estimating the optimal storage time of fuelwood stacks stored outdoors based on average moisture changes. Multivariate models for estimating moisture changes in different drying environments were created for this purpose. Experimental data were gathered during 7 to 14 months for most common wood fuel raw materials. In addition to taking moisture samples manually, load cell-based automated data recording for fuelwood moisture content change estimation proved a feasible option to obtain data for fuelwood drying models. The major factors considered in this study for predicting woody biomass moisture content change were precipitation, cumulative precipitation, evaporation, cumulative reference evaporation and fuelwood type. Multivariate drying models can help optimize deliveries of fuelwood and therefore increase the efficiency of the whole fuelwood supply chain.

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