Optimal planning software platform development with cloud computing technology

The paper describes research and development of software platform for optimal operation planning of pulp-and-paper and forestry enterprises using cloud computing technology. This work is a part of long-term activity carried out by Petrozavodsk State University (PetrSU) in the field of scientific research, software development and customer projects for enterprises of pulp-and-paper and forestry industry of Russia. The Platform uses advanced mathematical models and optimization algorithms developed by IT-park of PetrSU to create services for solving a series of planning tasks for different industries: production of corrugated packaging, sawmill, plywood production, timber enterprise

Ensuring Energy Efficiency and Safety of the Cyclic Operation of the Mining Dump Truck

It’s known that the use of the automobile vehicles in a quarry for transporting the rock mass is characterized by a cyclic nature and the ability to overcome the slopes of up to 8-12% along the road as well as curves with the radii of at least 20-24 m. However, the disadvantage of this way of transportation of quarry loads is relatively high costs [1]. One of the ways to reduce costs is to implement the software-based operation of the mining dump truck while ensuring energy efficiency and safety. This way implies following the route “mine face – concentrator” when driving with the rock mass and the route “concentrator – mine face” when driving without a cargo along the specified trajectory and at a given driving speed using the information management systems in a quarry and on the board of the mining dump truck controlled by the driver as well as in an unmanned version in case of autonomous driving. The article describes the method to optimize the function “way – speed” and as a result the way to optimize the control of the traction electric motors in a mining dump truck during cyclic movement along the specified trajectory with a fixed time to pass the route in order to ensure energy efficiency and safety when using the method of dynamic programming developed by Richard Bellman

Russian forest sequesters substantially more carbon than previously reported

Abstract Since the collapse of the Soviet Union and transition to a new forest inventory system, Russia has reported almost no change in growing stock (+ 1.8%) and biomass (+ 0.6%). Yet remote sensing products indicate increased vegetation productivity, tree cover and above-ground biomass. Here, we challenge these statistics with a combination of recent National Forest Inventory and remote sensing data to provide an alternative estimate of the growing stock of Russian forests and to assess the relative changes in post-Soviet Russia. Our estimate for the year 2014 is 111 ± 1.3 × 109 m3, or 39% higher than the value in the State Forest Register. Using the last Soviet Union report as a reference, Russian forests have accumulated 1163 × 106 m3 yr-1 of growing stock between 1988–2014, which balances the net forest stock losses in tropical countries. Our estimate of the growing stock of managed forests is 94.2 × 109 m3, which corresponds to sequestration of 354 Tg C yr-1 in live biomass over 1988–2014, or 47% higher than reported in the National Greenhouse Gases Inventory