دورية أكاديمية
Evaluating the Impact of Meteorological Data Sources on Moisture Prediction Accuracy of Eucalyptus Nitens Log Pile Natural Drying Models
العنوان: | Evaluating the Impact of Meteorological Data Sources on Moisture Prediction Accuracy of Eucalyptus Nitens Log Pile Natural Drying Models |
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المؤلفون: | Strandgard, Martin, Taskhiri, Mohammad Sadegh, Turner, Paul |
المصدر: | Croatian Journal of Forest Engineering : Journal for Theory and Application of Forestry Engineering ; ISSN 1845-5719 (Print) ; ISSN 1848-9672 (Online) ; Volume 44 ; Issue 2 |
بيانات النشر: | Faculty of Forestry and Wood Technology, University of Zagreb |
سنة النشر: | 2023 |
المجموعة: | Hrčak - Portal of scientific journals of Croatia / Portal znanstvenih časopisa Republike Hrvatske |
مصطلحات موضوعية: | Forest biomass, supply chain, sensor network, natural drying model, cost saving |
الوصف: | Drying forest biomass at roadside can reduce transport costs and greenhouse gas emissions by reducing its weight and increasing its net calorific value. Drying models are required for forest supply chain analysis to determine optimum storage times considering storage costs and returns. The study purpose was to evaluate the impact of the source of meteorological data on the goodness of fit and practical application of Eucalyptus nitens log pile drying models. The study was conducted in Long Reach, NE Tasmania, Australia from the 6th of February to 6th of August 2020. Four data sources were compared: the nearest meteorological station, interpolated meteorological data, a portable weather station, and digital temperature/RH sensors. Predicted moisture content (MC) values from the only previously published E. nitens log pile drying model were also evaluated using the current study data sources as inputs. Log pile MC changes were determined from weight changes measured by placing the study logs on a steel frame bolted to load cells at each corner. As the study was based on debarked logs, dry matter losses were assumed to be negligible. Initial MC of the logs was determined by extracting samples using an electric drill and drying them until constant weight was achieved. Initial log pile drying rates were high with several daily MC losses >2%. Portable weather station data produced the best goodness of fit drying model. The second-best goodness of fit model was based on meteorological station data. From a user acceptability perspective (highest proportion of results within ±5% of measured values), the best model was based on temperature/RH sensor data. Goodness of fit measures for the temperature/RH sensor data model were poorer than for the other data sources, but still acceptable. The published E. nitens log drying model had the poorest results for goodness of fit and user acceptability. In conclusion, portable weather stations are best suited to research trials due to the expense of placing a weather station at ... |
نوع الوثيقة: | article in journal/newspaper |
وصف الملف: | application/pdf |
اللغة: | English |
العلاقة: | https://hrcak.srce.hr/310150Test |
الإتاحة: | https://doi.org/10.5552/crojfe.2023.1757Test https://hrcak.srce.hr/310150Test https://hrcak.srce.hr/file/447675Test |
حقوق: | info:eu-repo/semantics/openAccess |
رقم الانضمام: | edsbas.4CE21FAA |
قاعدة البيانات: | BASE |
الوصف غير متاح. |