Models in country scale carbon accounting of forest soils

Selective papers of the workshop on "Development of models and forest soil surveys for monitoring of soil carbon", Koli, Finland, April 5-9 2006.

Improving inventory management

Having inventory to cover from all possible problems would increase the inventory level indefinitely in accordance with the standard deviation. If the materials in stock are not used, but kept just to be on the safe side, they are waste. The main objective of this study was to find out, how much inventory is required to cover the requirements, without causing delivery problems towards the end-customers, and how the inventory could be controlled efficiently. Several improvements were made in the controlling principles, and the inventory level was quickly decreased by more than 30 %, and kept on the reached level. The suitability of kanban control was investigated, and it was eventually taken into some use. A great advantage was found in the new procedures in securing the supply. The requests for quotations were diversified, and the faulty basis was corrected. Thus, the inventory surplus would later be avoided, and at the same time, a lot of valuable time was saved from daily routines to further improvement projects.

A comparison of electricity spot prices simulation using ARMA-GARCH and mean-reverting models

The aim of this work is to compare two families of mathematical models for their respective capability to capture the statistical properties of real electricity spot market time series. The first model family is ARMA-GARCH models and the second model family is mean-reverting Ornstein-Uhlenbeck models. These two models have been applied to two price series of Nordic Nord Pool spot market for electricity namely to the System prices and to the DenmarkW prices. The parameters of both models were calibrated from the real time series. After carrying out simulation with optimal models from both families we conclude that neither ARMA-GARCH models, nor conventional mean-reverting Ornstein-Uhlenbeck models, even when calibrated optimally with real electricity spot market price or return series, capture the statistical characteristics of the real series. But in the case of less spiky behavior (System prices), the mean-reverting Ornstein-Uhlenbeck model could be seen to partially succeeded in this task.

Utilization of a Time Domain Simulator in the Technical and Economic Analysis of a Wind Turbine Electric Drive Train

The amount of installed wind power has been growing exponentially during the past ten years. As wind turbines have become a significant source of electrical energy, the interactions between the turbines and the electric power network need to be studied more thoroughly than before. Especially, the behavior of the turbines in fault situations is of prime importance; simply disconnecting all wind turbines from the network during a voltage drop is no longer acceptable, since this would contribute to a total network collapse. These requirements have been a contributor to the increased role of simulations in the study and design of the electric drive train of a wind turbine. When planning a wind power investment, the selection of the site and the turbine are crucial for the economic feasibility of the installation. Economic feasibility, on the other hand, is the factor that determines whether or not investment in wind power will continue, contributing to green electricity production and reduction of emissions. In the selection of the installation site and the turbine (siting and site matching), the properties of the electric drive train of the planned turbine have so far been generally not been taken into account. Additionally, although the loss minimization of some of the individual components of the drive train has been studied, the drive train as a whole has received less attention. Furthermore, as a wind turbine will typically operate at a power level lower than the nominal most of the time, efficiency analysis in the nominal operating point is not sufficient. This doctoral dissertation attempts to combine the two aforementioned areas of interest by studying the applicability of time domain simulations in the analysis of the economicfeasibility of a wind turbine. The utilization of a general-purpose time domain simulator, otherwise applied to the study of network interactions and control systems, in the economic analysis of the wind energy conversion system is studied. The main benefits of the simulation-based method over traditional methods based on analytic calculation of losses include the ability to reuse and recombine existing models, the ability to analyze interactions between the components and subsystems in the electric drive train (something which is impossible when considering different subsystems as independent blocks, as is commonly done in theanalytical calculation of efficiencies), the ability to analyze in a rather straightforward manner the effect of selections other than physical components, for example control algorithms, and the ability to verify assumptions of the effects of a particular design change on the efficiency of the whole system. Based on the work, it can be concluded that differences between two configurations can be seen in the economic performance with only minor modifications to the simulation models used in the network interaction and control method study. This eliminates the need ofdeveloping analytic expressions for losses and enables the study of the system as a whole instead of modeling it as series connection of independent blocks with no lossinterdependencies. Three example cases (site matching, component selection, control principle selection) are provided to illustrate the usage of the approach and analyze its performance.

Numerical Investigation of Flow Past a Circular Cylinder and in a Staggered Tube Bundle Using Various Turbulence Models

Transitional flow past a three-dimensional circular cylinder is a widely studied phenomenon since this problem is of interest with respect to many technical applications. In the present work, the numerical simulation of flow past a circular cylinder, performed by using a commercial CFD code (ANSYS Fluent 12.1) with large eddy simulation (LES) and RANS (κ - ε and Shear-Stress Transport (SST) κ - ω! model) approaches. The turbulent flow for ReD = 1000 & 3900 is simulated to investigate the force coefficient, Strouhal number, flow separation angle, pressure distribution on cylinder and the complex three dimensional vortex shedding of the cylinder wake region. The numerical results extracted from these simulations have good agreement with the experimental data (Zdravkovich, 1997). Moreover, grid refinement and time-step influence have been examined. Numerical calculations of turbulent cross-flow in a staggered tube bundle continues to attract interest due to its importance in the engineering application as well as the fact that this complex flow represents a challenging problem for CFD. In the present work a time dependent simulation using κ – ε, κ - ω! and SST models are performed in two dimensional for a subcritical flow through a staggered tube bundle. The predicted turbulence statistics (mean and r.m.s velocities) have good agreement with the experimental data (S. Balabani, 1996). Turbulent quantities such as turbulent kinetic energy and dissipation rate are predicted using RANS models and compared with each other. The sensitivity of grid and time-step size have been analyzed. Model constants sensitivity study have been carried out by adopting κ – ε model. It has been observed that model constants are very sensitive to turbulence statistics and turbulent quantities.

Automated, adaptive methods for forest inventory

Forest inventories are used to estimate forest characteristics and the condition of forest for many different applications: operational tree logging for forest industry, forest health state estimation, carbon balance estimation, land-cover and land use analysis in order to avoid forest degradation etc. Recent inventory methods are strongly based on remote sensing data combined with field sample measurements, which are used to define estimates covering the whole area of interest. Remote sensing data from satellites, aerial photographs or aerial laser scannings are used, depending on the scale of inventory. To be applicable in operational use, forest inventory methods need to be easily adjusted to local conditions of the study area at hand. All the data handling and parameter tuning should be objective and automated as much as possible. The methods also need to be robust when applied to different forest types. Since there generally are no extensive direct physical models connecting the remote sensing data from different sources to the forest parameters that are estimated, mathematical estimation models are of "black-box" type, connecting the independent auxiliary data to dependent response data with linear or nonlinear arbitrary models. To avoid redundant complexity and over-fitting of the model, which is based on up to hundreds of possibly collinear variables extracted from the auxiliary data, variable selection is needed. To connect the auxiliary data to the inventory parameters that are estimated, field work must be performed. In larger study areas with dense forests, field work is expensive, and should therefore be minimized. To get cost-efficient inventories, field work could partly be replaced with information from formerly measured sites, databases. The work in this thesis is devoted to the development of automated, adaptive computation methods for aerial forest inventory. The mathematical model parameter definition steps are automated, and the cost-efficiency is improved by setting up a procedure that utilizes databases in the estimation of new area characteristics.

Methods and Models for Accelerating Dynamic Simulation of Fluid Power Circuits

The objective of this dissertation is to improve the dynamic simulation of fluid power circuits. A fluid power circuit is a typical way to implement power transmission in mobile working machines, e.g. cranes, excavators etc. Dynamic simulation is an essential tool in developing controllability and energy-efficient solutions for mobile machines. Efficient dynamic simulation is the basic requirement for the real-time simulation. In the real-time simulation of fluid power circuits there exist numerical problems due to the software and methods used for modelling and integration. A simulation model of a fluid power circuit is typically created using differential and algebraic equations. Efficient numerical methods are required since differential equations must be solved in real time. Unfortunately, simulation software packages offer only a limited selection of numerical solvers. Numerical problems cause noise to the results, which in many cases leads the simulation run to fail. Mathematically the fluid power circuit models are stiff systems of ordinary differential equations. Numerical solution of the stiff systems can be improved by two alternative approaches. The first is to develop numerical solvers suitable for solving stiff systems. The second is to decrease the model stiffness itself by introducing models and algorithms that either decrease the highest eigenvalues or neglect them by introducing steady-state solutions of the stiff parts of the models. The thesis proposes novel methods using the latter approach. The study aims to develop practical methods usable in dynamic simulation of fluid power circuits using explicit fixed-step integration algorithms. In this thesis, twomechanisms whichmake the systemstiff are studied. These are the pressure drop approaching zero in the turbulent orifice model and the volume approaching zero in the equation of pressure build-up. These are the critical areas to which alternative methods for modelling and numerical simulation are proposed. Generally, in hydraulic power transmission systems the orifice flow is clearly in the turbulent area. The flow becomes laminar as the pressure drop over the orifice approaches zero only in rare situations. These are e.g. when a valve is closed, or an actuator is driven against an end stopper, or external force makes actuator to switch its direction during operation. This means that in terms of accuracy, the description of laminar flow is not necessary. But, unfortunately, when a purely turbulent description of the orifice is used, numerical problems occur when the pressure drop comes close to zero since the first derivative of flow with respect to the pressure drop approaches infinity when the pressure drop approaches zero. Furthermore, the second derivative becomes discontinuous, which causes numerical noise and an infinitely small integration step when a variable step integrator is used. A numerically efficient model for the orifice flow is proposed using a cubic spline function to describe the flow in the laminar and transition areas. Parameters for the cubic spline function are selected such that its first derivative is equal to the first derivative of the pure turbulent orifice flow model in the boundary condition. In the dynamic simulation of fluid power circuits, a tradeoff exists between accuracy and calculation speed. This investigation is made for the two-regime flow orifice model. Especially inside of many types of valves, as well as between them, there exist very small volumes. The integration of pressures in small fluid volumes causes numerical problems in fluid power circuit simulation. Particularly in realtime simulation, these numerical problems are a great weakness. The system stiffness approaches infinity as the fluid volume approaches zero. If fixed step explicit algorithms for solving ordinary differential equations (ODE) are used, the system stability would easily be lost when integrating pressures in small volumes. To solve the problem caused by small fluid volumes, a pseudo-dynamic solver is proposed. Instead of integration of the pressure in a small volume, the pressure is solved as a steady-state pressure created in a separate cascade loop by numerical integration. The hydraulic capacitance V/Be of the parts of the circuit whose pressures are solved by the pseudo-dynamic method should be orders of magnitude smaller than that of those partswhose pressures are integrated. The key advantage of this novel method is that the numerical problems caused by the small volumes are completely avoided. Also, the method is freely applicable regardless of the integration routine applied. The superiority of both above-mentioned methods is that they are suited for use together with the semi-empirical modelling method which necessarily does not require any geometrical data of the valves and actuators to be modelled. In this modelling method, most of the needed component information can be taken from the manufacturer’s nominal graphs. This thesis introduces the methods and shows several numerical examples to demonstrate how the proposed methods improve the dynamic simulation of various hydraulic circuits.

Hipsometric relationship modeling using data sampled in tree scaling and inventory plots

This work evaluated eight hypsometric models to represent tree height-diameter relationship, using data obtained from the scaling of 118 trees and 25 inventory plots. Residue graphic analysis and percent deviation mean criteria, qui-square test precision, residual standard error between real and estimated heights and the graybill f test were adopted. The identity of the hypsometric models was also verified by applying the F(Ho) test on the plot data grouped to the scaling data. It was concluded that better accuracy can be obtained by using the model prodan, with h and d1,3 data measured in 10 trees by plots grouped into these scaling data measurements of even-aged forest stands.

MCMC Analysis for Optimization of Stochastic Models

In any decision making under uncertainties, the goal is mostly to minimize the expected cost. The minimization of cost under uncertainties is usually done by optimization. For simple models, the optimization can easily be done using deterministic methods.However, many models practically contain some complex and varying parameters that can not easily be taken into account using usual deterministic methods of optimization. Thus, it is very important to look for other methods that can be used to get insight into such models. MCMC method is one of the practical methods that can be used for optimization of stochastic models under uncertainty. This method is based on simulation that provides a general methodology which can be applied in nonlinear and non-Gaussian state models. MCMC method is very important for practical applications because it is a uni ed estimation procedure which simultaneously estimates both parameters and state variables. MCMC computes the distribution of the state variables and parameters of the given data measurements. MCMC method is faster in terms of computing time when compared to other optimization methods. This thesis discusses the use of Markov chain Monte Carlo (MCMC) methods for optimization of Stochastic models under uncertainties .The thesis begins with a short discussion about Bayesian Inference, MCMC and Stochastic optimization methods. Then an example is given of how MCMC can be applied for maximizing production at a minimum cost in a chemical reaction process. It is observed that this method performs better in optimizing the given cost function with a very high certainty.

Thermal comfort in reduced models of broilers' houses, under different types of roofing materials

The research was developed to evaluate the use of different types of roofing materials regularly used in poultry houses. Measurements of thermal comfort were made through the use of techniques such as the Black Globe and Humidity Index (BGHI), the Thermal Heat Load (THL) and Enthalpy (H). Conducted in the State University of Goiás, during the months of April and May, 2011, the experiment was composed of five different treatments: AC - Asbestos cement tiles, BA -Bamboo tiles, BAP - Bamboo tiles painted in white, FB -Vegetable fiber tiles and bitumen, FBP -Vegetable fiber tiles and bitumen painted in white. The experiment consisted in 15 repetitions, which were considered the different days of measurements taken. Throughout the studied period, the time of the day considered the least comfortable was the one observed at 2:00pm, and the coverage of vegetable fiber and bitumen showed the highest value of BGHI (84.1) when compared to other types of coverage, characterizing a situation of lower thermal comfort, and no difference was found for THL and H on treatments in the studied region.

Comparison of diffusion models for description of osmotic dehydration of radish slices dipped in brine

ABSTRACT This paper aims at describing the osmotic dehydration of radish cut into cylindrical pieces, using one- and two-dimensional analytical solutions of diffusion equation with boundary conditions of the first and third kind. These solutions were coupled with an optimizer to determine the process parameters, using experimental data. Three models were proposed to describe the osmotic dehydration of radish slices in brine at low temperature. The two-dimensional model with boundary condition of the third kind well described the kinetics of mass transfers, and it enabled prediction of moisture and solid distributions at any given time.

Towards Inter-organizational Working Capital Management

Working capital is an investment which is tied up into the inventories and accounts receivable and which is released with accounts payable. Due to the current business landscape with tightened financial conditions and finance markets, organizations emphasize efficient working capital management. With efficient working capital management, a company can reduce the need of finance, free up cash, increase profitability, improve liquidity, increase the efficiency of operations, and decrease (financing) costs. From the perspective of an individual company, efficient working capital management means decreasing inventory levels by shortening the cycle time of inventories, decreasing accounts receivable by shortening the trade credit terms and effective collection procedures, and increasing the level of accounts payable by paying the suppliers later. From an inter-organizational perspective, however, working capital should not be sub-optimized by a single company but holistic view to working capital management through the supply chain should be adopted to create value and improve performance together. The purpose of this research is to take academic research as well as practical management towards inter-organizational working capital management. The thesis discusses the benefits as well as mechanisms of working capital management in the inter-organizational context and has two main objectives: (1) to examine the effect of inter-organizational working capital management on performance in the value chain context and (2) to develop models of working capital management for internal as well as inter-organizational value chains. The results of the archival research conducted in the value chain of the pulp and paper industry and the value chain of the automotive industry indicate that companies can increase relative profitability by managing working capital comprehensively by taking into account all three components, and holistically though the value chain. Companies in the value chain benefit from different strategies in working capital management depending on the position of the company in the value chain. This can be taken into account in inter-organizational working capital management. The effects of inter-organizational working capital management actions on the financing costs of working capital were studied via simulations. Simulations also show that the value chain and individual companies benefit from an inter-organizational view to working capital management. Inter-organizational working capital management actions include for example: shortening the cycle time of inventories, reducing product costs, shifting inventories, shortening payment terms, and considering the cost of capital. The thesis also provides solutions for the practical requirements for tools to control working capital. The design science part of the research introduces the adjusted cash conversion cycle (ACCC) model for internal value chains, as well as models for working capital management in the inter-organizational value chain context: the working capital management model (WCMM) and the financial cycle time model (FCTM) designed in corporation and product levels respectively. This research contributes to literature on working capital management and interorganizational accounting. The research gives a holistic, inter-organizational view to the management of working capital. It advances the knowledge in working capital management on operational level, increases knowledge in the recently risen theme of supply chainoriented, collaborative working capital management, combines management accounting research with supply chain management research, and contributes to the demand of practical inter-organizational accounting methods. In addition, the research has strong practical focus as new managerial methods are introduced.

Antinociceptive effect of intrathecal neostigmine evaluated in rats by two different pain models

The analgesic efficacy of cholinergic agonists and anticholinesterase agents has been widely recognized. The analgesic effect obtained by activating cholinergic mechanisms, however, seems to depend on the experimental pain model utilized for its evaluation. The antinociceptive effect of intraspinal neostigmine was examined in rats submitted concurrently to the tail flick and formalin tests. Neostigmine (8.25 and 16.5 nmol) produced a dose-dependent antinociceptive effect in the tail flick test (a model of phasic pain) and reduced the first phase (phasic pain) of the animal response to formalin also in a dose-dependent manner. The second phase (tonic pain) of the response to formalin, however, was slightly reduced after a longer period of time only by the higher dose of the anticholinesterase. The effect of neostigmine was not significantly different when the drug was injected into rats submitted exclusively to the tail flick test. The second phase of the animal response to formalin was slightly reduced by neostigmine (8.25 nmol) and strongly inhibited by the higher dose of the anticholinesterase when injection was made after the first phase. We conclude that phasic and tonic pain can both be controlled by high doses of neostigmine. In addition, we show that inhibition by a lower dose of neostigmine of the formalin-induced phasic pain did not prevent the subsequent occurrence of tonic pain produced by the irritant

The relationship between anxiety and depression in animal models: a study using the forced swimming test and elevated plus-maze

The present study evaluated the correlation between the behavior of mice in the forced swimming test (FST) and in the elevated plus-maze (PM). The effect of the order of the experiments, i.e., the influence of the first test (FST or PM) on mouse behavior in the second test (PM or FST, respectively) was compared to handled animals (HAND). The execution of FST one week before the plus-maze (FST-PM, N = 10), in comparison to mice that were only handled (HAND-PM, N = 10) in week 1, decreased % open entries (HAND-PM: 33.6 ± 2.9; FST-PM: 20.0 ± 3.9; mean ± SEM; P<0.02) and % open time (HAND-PM: 18.9 ± 3.3; FST-PM: 9.0 ± 1.9; P<0.03), suggesting an anxiogenic effect. No significant effect was seen in the number of closed arm entries (FST-PM: 9.5 (7.0-11.0); HAND-PM: 10.0 (4.0-14.5), median (interquartile range); U = 46.5; P>0.10). A prior test in the plus-maze (PM-FST) did not change % immobility time in the FST when compared to the HAND-FST group (HAND-FST: 57.7 ± 3.9; PM-FST: 65.7 ± 3.2; mean ± SEM; P>0.10). Since these data suggest that there is an order effect, the correlation was evaluated separately with each test sequence: FST-PM (N = 20) and PM-FST (N = 18). There was no significant correlation between % immobility time in the FST and plus-maze indexes (% time and entries in open arms) in any test sequence (r: -0.07 to 0.18). These data suggest that mouse behavior in the elevated plus-maze is not related to behavior in the forced swimming test and that a forced swimming test before the plus-maze has an anxiogenic effect even after a one-week interval.

Linguistic models for decision support

Linguistic modelling is a rather new branch of mathematics that is still undergoing rapid development. It is closely related to fuzzy set theory and fuzzy logic, but knowledge and experience from other fields of mathematics, as well as other fields of science including linguistics and behavioral sciences, is also necessary to build appropriate mathematical models. This topic has received considerable attention as it provides tools for mathematical representation of the most common means of human communication - natural language. Adding a natural language level to mathematical models can provide an interface between the mathematical representation of the modelled system and the user of the model - one that is sufficiently easy to use and understand, but yet conveys all the information necessary to avoid misinterpretations. It is, however, not a trivial task and the link between the linguistic and computational level of such models has to be established and maintained properly during the whole modelling process. In this thesis, we focus on the relationship between the linguistic and the mathematical level of decision support models. We discuss several important issues concerning the mathematical representation of meaning of linguistic expressions, their transformation into the language of mathematics and the retranslation of mathematical outputs back into natural language. In the first part of the thesis, our view of the linguistic modelling for decision support is presented and the main guidelines for building linguistic models for real-life decision support that are the basis of our modeling methodology are outlined. From the theoretical point of view, the issues of representation of meaning of linguistic terms, computations with these representations and the retranslation process back into the linguistic level (linguistic approximation) are studied in this part of the thesis. We focus on the reasonability of operations with the meanings of linguistic terms, the correspondence of the linguistic and mathematical level of the models and on proper presentation of appropriate outputs. We also discuss several issues concerning the ethical aspects of decision support - particularly the loss of meaning due to the transformation of mathematical outputs into natural language and the issue or responsibility for the final decisions. In the second part several case studies of real-life problems are presented. These provide background and necessary context and motivation for the mathematical results and models presented in this part. A linguistic decision support model for disaster management is presented here – formulated as a fuzzy linear programming problem and a heuristic solution to it is proposed. Uncertainty of outputs, expert knowledge concerning disaster response practice and the necessity of obtaining outputs that are easy to interpret (and available in very short time) are reflected in the design of the model. Saaty’s analytic hierarchy process (AHP) is considered in two case studies - first in the context of the evaluation of works of art, where a weak consistency condition is introduced and an adaptation of AHP for large matrices of preference intensities is presented. The second AHP case-study deals with the fuzzified version of AHP and its use for evaluation purposes – particularly the integration of peer-review into the evaluation of R&D outputs is considered. In the context of HR management, we present a fuzzy rule based evaluation model (academic faculty evaluation is considered) constructed to provide outputs that do not require linguistic approximation and are easily transformed into graphical information. This is achieved by designing a specific form of fuzzy inference. Finally the last case study is from the area of humanities - psychological diagnostics is considered and a linguistic fuzzy model for the interpretation of outputs of multidimensional questionnaires is suggested. The issue of the quality of data in mathematical classification models is also studied here. A modification of the receiver operating characteristics (ROC) method is presented to reflect variable quality of data instances in the validation set during classifier performance assessment. Twelve publications on which the author participated are appended as a third part of this thesis. These summarize the mathematical results and provide a closer insight into the issues of the practicalapplications that are considered in the second part of the thesis.