Creating moisture prediction models for seasoned fuelwood

Jyrki Raitila; Veli-Pekka Heiskanen; Marja Kolström; Johanna Routa

doi:10.5071/IBSCE2015-2AV.1.21

Creating moisture prediction models for seasoned fuelwood

Jyrki Raitila, Veli-Pekka Heiskanen, Marja Kolström, Johanna Routa

Research output: Contribution to conference › Conference Poster › Scientific

Abstract

Moisture of fuelwood affects both, profitability of supplying wood chips and the economy of running an energy plant. Most fuel wood is seasoned outdoors, therefore drying depends on the weather. Moisture changes of stored wood in different drying environments can be estimated with multivarite models. The objective of this study was to develop and validate model prototypes for estimating optimal storage times for stacked fuelwood. In addition to taking moisture samples manually, load cell based automated data recording for moisture content alteration was used successfully. The main factors considered in this study for predicting moisture changes of fuelwood were the fuelwood type, precipitation and evaporation; actual or cumulative. In practice, multivariate drying models can help optimize deliveries of fuelwood and therefore increase the efficiency of the whole bioenergy supply chain.

Original language	English
DOIs	https://doi.org/10.5071/IBSCE2015-2AV.1.21
Publication status	Published - 2015
Event	International Bioenergy (Shanghai) Exhibition and Asian Bioenergy Conference, IBSCE 2015 - Shanghai, China Duration: 21 Oct 2015 → 23 Oct 2015

Conference

Conference	International Bioenergy (Shanghai) Exhibition and Asian Bioenergy Conference, IBSCE 2015
Abbreviated title	IBSCE 2015
Country/Territory	China
City	Shanghai
Period	21/10/15 → 23/10/15

Keywords

moisture content
fuelwood
natural drying
drying model
predicting moisture

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.5071/IBSCE2015-2AV.1.21

Cite this

@conference{7ae3665bf2e44eb9a4516a9dc430e302,

title = "Creating moisture prediction models for seasoned fuelwood",

abstract = "Moisture of fuelwood affects both, profitability of supplying wood chips and the economy of running an energy plant. Most fuel wood is seasoned outdoors, therefore drying depends on the weather. Moisture changes of stored wood in different drying environments can be estimated with multivarite models. The objective of this study was to develop and validate model prototypes for estimating optimal storage times for stacked fuelwood. In addition to taking moisture samples manually, load cell based automated data recording for moisture content alteration was used successfully. The main factors considered in this study for predicting moisture changes of fuelwood were the fuelwood type, precipitation and evaporation; actual or cumulative. In practice, multivariate drying models can help optimize deliveries of fuelwood and therefore increase the efficiency of the whole bioenergy supply chain.",

keywords = "moisture content, fuelwood, natural drying, drying model, predicting moisture",

author = "Jyrki Raitila and Veli-Pekka Heiskanen and Marja Kolstr{\"o}m and Johanna Routa",

note = "HUO: Poster presentation LIS: Abstract reviewed Project code: 104790 ; International Bioenergy (Shanghai) Exhibition and Asian Bioenergy Conference, IBSCE 2015, IBSCE 2015 ; Conference date: 21-10-2015 Through 23-10-2015",

year = "2015",

doi = "10.5071/IBSCE2015-2AV.1.21",

language = "English",

}

TY - CONF

T1 - Creating moisture prediction models for seasoned fuelwood

AU - Raitila, Jyrki

AU - Heiskanen, Veli-Pekka

AU - Kolström, Marja

AU - Routa, Johanna

N1 - HUO: Poster presentation LIS: Abstract reviewed Project code: 104790

PY - 2015

Y1 - 2015

N2 - Moisture of fuelwood affects both, profitability of supplying wood chips and the economy of running an energy plant. Most fuel wood is seasoned outdoors, therefore drying depends on the weather. Moisture changes of stored wood in different drying environments can be estimated with multivarite models. The objective of this study was to develop and validate model prototypes for estimating optimal storage times for stacked fuelwood. In addition to taking moisture samples manually, load cell based automated data recording for moisture content alteration was used successfully. The main factors considered in this study for predicting moisture changes of fuelwood were the fuelwood type, precipitation and evaporation; actual or cumulative. In practice, multivariate drying models can help optimize deliveries of fuelwood and therefore increase the efficiency of the whole bioenergy supply chain.

AB - Moisture of fuelwood affects both, profitability of supplying wood chips and the economy of running an energy plant. Most fuel wood is seasoned outdoors, therefore drying depends on the weather. Moisture changes of stored wood in different drying environments can be estimated with multivarite models. The objective of this study was to develop and validate model prototypes for estimating optimal storage times for stacked fuelwood. In addition to taking moisture samples manually, load cell based automated data recording for moisture content alteration was used successfully. The main factors considered in this study for predicting moisture changes of fuelwood were the fuelwood type, precipitation and evaporation; actual or cumulative. In practice, multivariate drying models can help optimize deliveries of fuelwood and therefore increase the efficiency of the whole bioenergy supply chain.

KW - moisture content

KW - fuelwood

KW - natural drying

KW - drying model

KW - predicting moisture

U2 - 10.5071/IBSCE2015-2AV.1.21

DO - 10.5071/IBSCE2015-2AV.1.21

M3 - Conference Poster

T2 - International Bioenergy (Shanghai) Exhibition and Asian Bioenergy Conference, IBSCE 2015

Y2 - 21 October 2015 through 23 October 2015

ER -

Creating moisture prediction models for seasoned fuelwood

Abstract

Conference

Keywords

UN SDGs

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