2 resultados para Different sizes
em Dalarna University College Electronic Archive
Resumo:
The objective with this study has been to build general models of the mechanics in tree felling with chain-saw and to compare felling torque for different tools. The theoretical models are completed and validated with a comparative study. The study includes a great number of felling tools of which some are used with different methods. Felling torque was measured using a naturally like measuring arrangement where a tree is cut at about 3.7 m height and then anchored with a dynamometer to a tree opposite to the felling direction. Notch and felling cut was made as ordinary with exception that the hinge was made extra thin to reduce bending resistance. The tree was consequently not felled during the trials and several combinations of felling tools and individuals could be used on the same tree.The results show big differences between tools, methods and persons. The differences were, however, not general, but could vary depending on conditions (first of all tree diameters). Tools and methods that push or pull on the stem are little affected by the size of the tree, while tools that press on the stump are very much dependent of a large stump-diameter. Hand force asserted on a simple pole is consequently a powerful tool on small trees. For trees of medium size there are several alternative methods with different sizes and brands of felling levers and wedges. Larger and more ungainly tools and methods like tree pusher, winch, etc. develop very high felling torque on all tree sizes. On large trees also the felling wedge and especially the use of several wedges together develop very high felling torque.
Resumo:
To have good data quality with high complexity is often seen to be important. Intuition says that the higher accuracy and complexity the data have the better the analytic solutions becomes if it is possible to handle the increasing computing time. However, for most of the practical computational problems, high complexity data means that computational times become too long or that heuristics used to solve the problem have difficulties to reach good solutions. This is even further stressed when the size of the combinatorial problem increases. Consequently, we often need a simplified data to deal with complex combinatorial problems. In this study we stress the question of how the complexity and accuracy in a network affect the quality of the heuristic solutions for different sizes of the combinatorial problem. We evaluate this question by applying the commonly used p-median model, which is used to find optimal locations in a network of p supply points that serve n demand points. To evaluate this, we vary both the accuracy (the number of nodes) of the network and the size of the combinatorial problem (p). The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 supply points we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000 (which is aggregated from the 1.5 million nodes). To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when the accuracy in the road network increase and the combinatorial problem (low p) is simple. When the combinatorial problem is complex (large p) the improvements of increasing the accuracy in the road network are much larger. The results also show that choice of the best accuracy of the network depends on the complexity of the combinatorial (varying p) problem.