Simulation of a real-time process adaptation in the manufacture of high-density fibreboards using multivariate regression analysis and feedforward control

The industrial manufacturing of wood-based panels has become a highly technological process, where all parameters have to be perfectly adjusted to manufacture products of high quality. However, variations caused by differing wood characteristics as well as variations of single process parameters can cause out-of-control events. These undesirable events can be diminished by monitoring and controlling the entire manufacturing process using multivariate statistical techniques. Hence, a real-time process adaptation of an industrial scale fibreboard manufacturing process was simulated. Regression results revealed a mean normalised root mean squared error of prediction of 4.6 %, when predicting the internal bond strength of fibreboards. The regression model is regularly validated and, if necessary, recalibrated using the offline determined board properties (feedback control). Consequently, the process can immediately be adapted as soon as the board is produced (feedforward control). The investigations resulted in reliable models and revealed high potential for permanent industrial implementation.     

Producing softwood of different quality: does this provide risk compensation?

This study analysed whether the production of high-quality assortments, saw timber and pulpwood in Norway spruce (Picea abies) and Scots pine (Pinus sylvestris) stands leads to effects of risk compensation. Mixtures of conventionally treated pruned and non-pruned stands, as well as mixtures of stands which had been optimized concerning the occurrence of assortments and financial criteria were considered. The price simulation was done by bootstrapping to avoid the assumption of a certain distribution of timber prices, and to preserve the correlations of the timber prices from different assortments. The financial valuation was carried out with annuities within a Monte Carlo simulation with 10,000 repetitions. To quantify the effect of natural hazards, the calculations were repeated with and without this factor. Minimum risk portfolios were determined and optimization performed using both a utility function as well as the value-at-risk approach. The mixtures with minimum risk were dominated by pine stands, as they are less affected by natural hazards and prices for pine timber have a lower volatility, although pine timber prices are generally lower compared to that of spruce timber. These pine dominated portfolios showed risk reductions up to 92% compared to the riskiest single stand, but the annuities were reduced even more. In contrast to this, the portfolios optimized with the utility function and the value-at-risk approach consisted of spruce stands. These spruce portfolios showed an efficient risk reduction of up to 60%. Additionally, higher annuities and larger diversification effects occurred in the portfolios containing the optimized stands. Integrating the risk of natural hazards, the annuities decreased, as did the correlation of the annuities of the different stands, while risk increased. Altogether these effects led to higher relative risk reductions when forming optimal portfolios. These results indicate that producing different assortments of spruce and pine leads to risk compensation, especially when considering portfolios consisting of optimized stands.     

Spatial interpolation of in situ data by self-organizing map algorithms (neural networks) for the assessment of carbon stocks in European forests

Self-organizing maps (SOMs) are an advanced neural networks application. SOMs were applied for the spatially explicit estimation of forest carbon stocks for a test region in Thuringia (Germany). The approach utilizes in situ national forest inventory data and satellite remote sensing data (Landsat 7 ETM+) and provides maps showing a high-resolution spatial distribution of forest carbon stocks. The generated maps are compared to alternative estimates obtained by the k-nearest neighbour (kNN) method—a remote sensing based carbon assessment. Beside maps the SOM- and kNN-approaches were utilized to calculate statistical estimates of carbon stock and growing stock. The statistical estimates were validated by calculating bias and mean square errors with reference to in situ assessments.     

Environment and tree size controlling stem sap flux in a perhumid tropical forest of Central Sulawesi,Indonesia

• Introduction   

We studied stem sap flux density in seven common tree species in a perhumid tropical rainforest at pre-montane elevation in Sulawesi with the aims (1) to analyse the among-species variation in flow patterns, (2) to search for an assumed convergence in the response to controlling environmental factors, and (3) to investigate the effect of tree size on xylem flux.     

Dynamic crushing characteristics of spruce wood under large deformations

An extensive series of large deformation crushing tests with spruce wood specimens was conducted. Material orientation, lateral constraint and loading rate were varied. Regarding material orientation, a reduction in the softening effect and the general force level was observed with a higher fiber-load angle. A comparison with characteristics gained by application of Hankinson’s formula showed discrepancies in compression strength and the beginning of the hardening effect. Lateral constraint of the specimens caused a multiaxial stress state in the specimens, which was quantified with the applied measuring method. Further, a higher force level compared to specimens without lateral constraint and significant hardening effect at large deformations resulted. Thus, the influence of a multiaxial stress state on the force level could be determined. An increase in the loading rate led to higher force levels at any displacement value and material orientation.     

Humus balances of different farm production systems in main production areas in Austria

The importance of the soil humus content is indisputable. Soil humus plays an important role in preserving soil fertility and exerts great influence on plant production and yield potential. However, proofing that management‐related changes in the stock of soil organic matter (SOM) have taken place against the background of spatial and temporal variation is a difficult task. In most cases, sampling over a long period of time is needed to verify these changes. Alternatively, potential changes in the SOM stock can be estimated using humus balancing models, which help to identify the need for humus reproduction on a farm. In general, a humus balance is the difference between the humus demand of cultivated crops and humus supply through crops and organic fertilizers. In this study, the ‘Dynamic Humus Unit Method' within the modelling program REPRO was applied to calculate the humus balance for 29 model‐farms that are representative of most of the agricultural production in Austria. Each model‐farm represents a specific production type (PT) and farming system in a defined region or main production area (MPA). This approach gives an overview of the humus balances at a large scale and allows a general trend in Austria to be estimated. Besides differing between conventional and organic farming systems, specific site conditions can also be selected in the model. The constructed model‐farms belong to different PTs such as “forage production”, “cash crops”, “refinement”, and “permanent crops”. The PT “permanent crops” refers to the cultivation of wine. The cropping system of each PT was analyzed in detail, while livestock keeping was considered only when applicable. Positive humus balances were found for all PTs except for permanent crops. The results ranged from –122 to 890 kg C ha^?1 y^?1. Regions and farm structure, e.g., forage production compared to cash crop, were found to have a greater influence than the kind of farming system (i.e., organic vs. conventional farming). Comparing the different PTs, forage production had the highest positive humus balances (219 to 890 kg C ha^?1 y^?1), followed by cash crop (24 to 239 kg C ha^?1 y^?1), refinement (–64 to 402 kg C ha^?1 y^?1) and permanent crops (–122 to –38 kg C ha^?1 y^?1). Regarding the farming system, organic farming led to more humus accumulation than conventional farming due to a higher share of fodder legumes and catch crops and more diverse crop rotations. The results were within the range of available empirical data on SOM change, and it was therefore concluded that the results are reasonable. In general, humus reproduction can be regarded as sufficient for agricultural production.     

Sediment Dynamics and Pollutant Mobility in Rivers (SEDYMO): Assessing Catchment-Wide Emission-Immission Relationships from Sediment Studies. BMBF Coordinated Research Project SEDYMO (2002–2006)

-  DOI: http://dx.doi.org/10.1065/jss2005.11.002 Background and Scope. Apart from their function as indicator or memory for local pollutant inputs, sediments, and especially sediment cores, can be used as a tool for assessing emissionimmission relationships of contaminants on a river-basin scale. Methods. In the framework of the SEDYMO program, source effects, i.e. intensity of sediment erosion under different shear stress, were investigated using a combination of core profile or sampling box studies in laboratory flumes and a mobile in-situ testing device for sediment stability. Results. Calculations of immission risks on downstream areas, e.g., from a three-step approach (substances of concern, areas of concern, areas of risk; Heise et al. 2004), may be directly confirmed from sediment core data, specifically from flood layers, at the target site.     

Modelling the interaction between powdery mildew epidemics and host dynamics of tomato

European Journal of Plant Pathology - A model simulating the progress of powdery mildew coupled to the growth dynamics of tomato, with a time step of 1&;nbsp;day, is developed. The model is...