Modelling spatio-temporal environmental data

A conceptual model for environmental data is presented with special emphasis on the ability to store spatio-temporal references of the data. Other aspects of the model are the ability to handle hierarchical data and semantics of the measurements. The model was tested with an implementation on an object-relational database management system. As a part of the test implementation, a forestry data set covering 75 years and 4900 hectares was loaded onto the database.     

Antenna phase pattern measurements at millimeter wave frequencies using the differential phase method with only one power meter

The differential phase measurement method has been improved to need the use of only one power meter instead of three power meters. This enables accurate antenna phase pattern measurements with a simplified set-up, accompanied by the reduction in cost. All advantages of the differential phase measurement method are still also available, e.g. there is no need to phase lock oscillators or to use rotary joints. The measurement results for an antenna at 110 GHz are presented. A good agreement with earlier data was obtained.     

Reaction engineering studies in a polytropic fixed-bed reactor over a highly active and selective catalyst for oxidative methane coupling

The oxidative coupling of methane (OCM) was carried out in a polytropic fixed-bed reactor applying a Zr/La/Sr catalyst developed by the Neste company. Over this catalyst the OCM reaction follows a complex reaction scheme which includes primary parallel reaction steps to CO, CO₂ and C₂H₆ and consecutive reactions of ethane to ethylene or CO_x. Yield of higher hydrocarbons C₂₊ obtained with this catalyst strongly depended on reaction conditions, i.e. low partial pressures of methane and oxygen obtained by diluting the feed gas with nitrogen and high reaction temperatures promoted C₂₊ selectivity and yield. The maximum yield amounted to 21.4% (20 Vol.-% CH₄, 9 Vol.-% O₂, 71 Vol.-% N₂, T = 860°C; X_CH4 = 41.8%, S = 52.5%). This result belongs to the highest yields reported in the open literature.     

Predicting the health risks related to whole-body vibration and shock: a comparison of alternative assessment methods for high-acceleration events in vehicles

In this paper, alternative assessment methods for whole-body vibration and shocks are compared by means of 70 vibration samples measured from 13 work vehicles, deliberately selected to represent periods containing shocks. Five methodologies (ISO 2631-1:1997, BS 6841:1987, ISO 2631-5:2004, DIN SPEC 45697:2012 and one specified by Gunston [2011], ‘G-method’) were applied to the vibration samples. In order to compare different evaluation metrics, limiting exposures were determined by calculating times to reach the upper limit thresholds given in the methods. Over 10-fold shorter times to exposure thresholds were obtained for the tri-axial VDV (BS 6841) than for the dominant r.m.s. (ISO 2631-1) when exposures were of high magnitude or contained substantial shocks. Under these exposure conditions, the sixth power approaches (ISO 2631-5, DIN SPEC, G-method) are more stringent than a fourth power VDV method. The r.m.s. method may lead to misleading outcomes especially if a lengthy measurement includes a small number of severe impacts. In conclusion, methodologies produce different evaluations of the vibration severity depending on the exposure characteristics, and the correct method must be selected.     

Neural networks in process life cycle profit modelling

Changes in operational environment of the process industry such as decreasing selling prices, increased competition between companies and new legislation, set requirements for performance and effectiveness of the industrial production lines and processes. For the basis of this study, a life cycle profit (LCP) model of a pulp process was constructed using different kind of process information including chemical consumptions and production levels of material and energy flows in unit processes. However, all the information needed in the creation of relevant LCP model was not directly provided by information systems of the plant. In this study, neural networks was used to model pulp bleaching process and fill out missing information and furthermore to create estimators for the alkaline chemical consumption. A data-based modelling approach was applied using an example, where factors affecting the sodium hydroxide consumption in the bleaching stage were solved. The results showed that raw process data can be refined into new valuable information using computational methods and moreover to improve the accuracy of life cycle profit models.