Multibody Simulation Model of the Roller Test Rig

Multibody simulation model of the roller test rig is presented in this work. The roller test rig consists of a paper machine’s tube roll supported with a hard bearing type balancing machine. The simulation model includes non-idealities that are measured from the physical structure. These non-idealities are the shell thickness variation of the roll and roundness errors of the shafts of the roll. These kinds of non-idealities are harmful since they can cause subharmonic resonances of the rotor system. In this case, the natural vibration mode of the rotor is excited when the rotation speed is a fraction of the natural frequency of the system. With the simulation model, the half critical resonance is studied in detail and a sensitivity analysis is performed by simulating several analyses with slightly different input parameters. The model is verified by comparing the simulation results with those obtained by measuring the real structure. Comparison shows that good accuracy is achieved, since equivalent responses are achieved within the error limit of the input parameters.

A simulation model of the optimal maintenance strategy: conceptual agent-based approach

In this Master’s thesis agent-based modeling has been used to analyze maintenance strategy related phenomena. The main research question that has been answered was: what does the agent-based model made for this study tell us about how different maintenance strategy decisions affect profitability of equipment owners and maintenance service providers? Thus, the main outcome of this study is an analysis of how profitability can be increased in industrial maintenance context. To answer that question, first, a literature review of maintenance strategy, agent-based modeling and maintenance modeling and optimization was conducted. This review provided the basis for making the agent-based model. Making the model followed a standard simulation modeling procedure. With the simulation results from the agent-based model the research question was answered. Specifically, the results of the modeling and this study are: (1) optimizing the point in which a machine is maintained increases profitability for the owner of the machine and also the maintainer with certain conditions; (2) time-based pricing of maintenance services leads to a zero-sum game between the parties; (3) value-based pricing of maintenance services leads to a win-win game between the parties, if the owners of the machines share a substantial amount of their value to the maintainers; and (4) error in machine condition measurement is a critical parameter to optimizing maintenance strategy, and there is real systemic value in having more accurate machine condition measurement systems.

Development of Generic Simulation Model for Mobile Working Machines

This master’s thesis has been done for Drive! –project in which a new electric motor solution for mobile working machines is developed. Generic simulation model will be used as marketing and development tool. It can be used to model a wide variety of different vehicles with and without electric motor and to show customer the difference between traditionally build vehicles and those with new electric motor solution. Customers can also use simulation model to research different solutions for their own vehicles. At the start of the project it was decided that MeVEA software would be used as main simulation program and Simulink will only be used to simulate the operation of electrical components. Development of the generic model started with the research of these two software applications, simulation models which are made with them and how these simulation models can be build faster. Best results were used for building of generic simulation model. Finished generic model can be used to produce new tractor models for real-time simulations in short notice. All information about model is collected to one datasheet which can be easily filled by the user. After datasheet is filled a script will automatically build new simulation model in seconds. At the moment generic model is capable of building simulation models for wide variety of different tractors but it can be easily altered for other vehicle types too which would also benefit greatly from electric drive solution. Those could be for example wheel loaders and harvesters.

Simulation model of wind turbine gearbox and lubrication system

As increasing efficiency of a wind turbine gearbox, more power can be transferred from rotor blades to generator and less power is used to cause wear and heating in the gearbox. By using a simulation model, behavior of the gearbox can be studied before creating expensive prototypes. The objective of the thesis is to model a wind turbine gearbox and its lubrication system to study power losses and heat transfer inside the gearbox and to study the simulation methods of the used software. Software used to create the simulation model is Siemens LMS Imagine.Lab AMESim, which can be used to create one-dimensional mechatronic system simulation models from different fields of engineering. When combining components from different libraries it is possible to create a simulation model, which includes mechanical, thermal and hydraulic models of the gearbox. Results for mechanical, thermal, and hydraulic simulations are presented in the thesis. Due to the large scale of the wind turbine gearbox and the amount of power transmitted, power loss calculations from AMESim software are inaccurate and power losses are modelled as constant efficiency for each gear mesh. Starting values for simulation in thermal and hydraulic simulations were chosen from test measurements and from empirical study as compact and complex design of gearbox prevents accurate test measurements. In further studies to increase the accuracy of the simulation model, components used for power loss calculations needs to be modified and values for unknown variables are needed to be solved through accurate test measurements.

Uncertainty assessment of a process-based integrated catchment model of phosphorus

Despite the many models developed for phosphorus concentration prediction at differing spatial and temporal scales, there has been little effort to quantify uncertainty in their predictions. Model prediction uncertainty quantification is desirable, for informed decision-making in river-systems management. An uncertainty analysis of the process-based model, integrated catchment model of phosphorus (INCA-P), within the generalised likelihood uncertainty estimation (GLUE) framework is presented. The framework is applied to the Lugg catchment (1,077 km2), a River Wye tributary, on the England–Wales border. Daily discharge and monthly phosphorus (total reactive and total), for a limited number of reaches, are used to initially assess uncertainty and sensitivity of 44 model parameters, identified as being most important for discharge and phosphorus predictions. This study demonstrates that parameter homogeneity assumptions (spatial heterogeneity is treated as land use type fractional areas) can achieve higher model fits, than a previous expertly calibrated parameter set. The model is capable of reproducing the hydrology, but a threshold Nash-Sutcliffe co-efficient of determination (E or R 2) of 0.3 is not achieved when simulating observed total phosphorus (TP) data in the upland reaches or total reactive phosphorus (TRP) in any reach. Despite this, the model reproduces the general dynamics of TP and TRP, in point source dominated lower reaches. This paper discusses why this application of INCA-P fails to find any parameter sets, which simultaneously describe all observed data acceptably. The discussion focuses on uncertainty of readily available input data, and whether such process-based models should be used when there isn’t sufficient data to support the many parameters.

Simulating metals and mine discharges in river basins using a new integrated catchment model for metals: pollution impacts and restoration strategies in the Aries-Mures river system in Transylvania, Romania

The INtegrated CAtchment (INCA) model has been developed to simulate the impact of mine discharges on river systems. The model accounts for the key kinetic chemical processes operating as well as the dilution, mixing and redistribution of pollutants in rivers downstream of mine discharges or acid rock drainage sites. The model is dynamic and simulates the day-to-day behaviour of hydrology and eight metals (cadmium, mercury, copper, zinc, lead, arsenic, manganese and chromium) as well as cyanide and ammonia. The model is semi-distributed and can simulate catchments, sub-catchment and in-stream river behaviour. The model has been applied to the Roia Montan Mine in Transylvania, Romania, and used to assess the impacts of old mine adits on the local catchments as well as on the downstream Aries and Mures river system. The question of mine restoration is investigated and a set of clean-up scenarios investigated. It is shown that the planned restoration will generate a much improved water quality from the mine and also alleviate the metal pollution of the river system.

A simulation model of self-organising evolvability in software systems

The evolvability of a software artifact is its capacity for producing heritable or reusable variants; the inverse quality is the artifact's inertia or resistance to evolutionary change. Evolvability in software systems may arise from engineering and/or self-organising processes. We describe our 'Conditional Growth' simulation model of software evolution and show how, it can be used to investigate evolvability from a self-organisation perspective. The model is derived from the Bak-Sneppen family of 'self-organised criticality' simulations. It shows good qualitative agreement with Lehman's 'laws of software evolution' and reproduces phenomena that have been observed empirically. The model suggests interesting predictions about the dynamics of evolvability and implies that much of the observed variability in software evolution can be accounted for by comparatively simple self-organising processes.

Equipping Simulation Model (BIOSIM)’s Actors With Multi-agent Intelligence on Cross platforms

Thesis is to Introduce an Intelligent cross platform architecture with Multi-agent system in order to equip the simulation Models with agents, having intelligent behavior, reactive and pro-active nature and rational in decision making.

Simulation model using meta heuristic algorithms for achieving optimal arrangement of storage bins in a sawmill yard

Bin planning (arrangements) is a key factor in the timber industry. Improper planning of the storage bins may lead to inefficient transportation of resources, which threaten the overall efficiency and thereby limit the profit margins of sawmills. To address this challenge, a simulation model has been developed. However, as numerous alternatives are available for arranging bins, simulating all possibilities will take an enormous amount of time and it is computationally infeasible. A discrete-event simulation model incorporating meta-heuristic algorithms has therefore been investigated in this study. Preliminary investigations indicate that the results achieved by GA based simulation model are promising and better than the other meta-heuristic algorithm. Further, a sensitivity analysis has been done on the GA based optimal arrangement which contributes to gaining insights and knowledge about the real system that ultimately leads to improved and enhanced efficiency in sawmill yards. It is expected that the results achieved in the work will support timber industries in making optimal decisions with respect to arrangement of storage bins in a sawmill yard.

Statistics and kinetics of single-molecule electron transfer dynamics in complex environments: A simulation model study

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Assessment of aquatic plants in the reservoirs of AES-Tiete and development of an integrated control model for the most important species

The general objective of this work was to develop a monitoring and management model for aquatic plants that could be used in reservoir cascades in Brazil, using the reservoirs of AES-Tiete as a study case. The investigations were carried out at the reservoirs of Barra-Bonita, Bariri, Ibitinga, Promissao, and Nova-Avanhandava, located in the Tiete River Basin; Agua Vermelha, located in the Grande River Basin; Caconde, Limoeiro, and Euclides da Cunha, which are part of the Pardo River Basin; and the Mogi-Guacu reservoir, which belongs to the Mogi-Guacu River basin. The main products of this work were: development of techniques using satellite-generated images for monitoring and planning aquatic plant control; planning and construction of a boat to move floating plant masses and an airboat equipped with a DGPS navigation and application flow control system. Results allowed to conclude that the occurrence of all types of aquatic plants is directly associated with sedimentation process and, consequently, with nutrient and light availability. Reservoirs placed at the beginning of cascades are more subject to sedimentation and occurrence of marginal, floating and emerged plants, and are the priority when it comes to controlling these plants, since they provide a supply of weeds for the other reservoirs. Reservoirs placed downstream show smaller amounts of water-suspended solids, with greater transmission of light and occurrence of submerged plants.