Privatization of forests : a real options approach

Cataloged from PDF version of article.This thesis analyzes the privatization of forests. It suggests that privatization can be regarded as a real option. The thesis develops a model that determines the optimal conditions for privatization of forests. Working in a real option framework, I show that delaying privatization could have a positive value attached to it and obtain the critical value at which the government privatizes the forest. I also show that the fundamental variables in the economy such as the interest rate and uncertainty can affect the decision to privatize.Siyahhan, BaranM.S

Procedure for experimental data assessment for numerical solver validation in the context of model based prediction of powder coating patterns

In the scope of this study an experimental powder coating setup is designed and the method to extract statistically significant trends from the data generated is developed. The ultimate goals are to i) validate a previously developed 3D Euler-LaGrangian numerical solver and to ii) characterize the essential parameters for industrial powder coating processes in subsequent phases. The experiments involved coating a flat plate substrate with a corona spraying pistol. The resulting coating thickness has been quantified through the state of the art Coatmaster technology. The raw data generated from the Coatmaster has been filtered and rigorously analyzed to identify statistically significant trends. Furthermore, characteristic variables have been constructed for subsequent comparison to the numerical solver. This study reveals the challenges involved in assessing experimental data to extract meaningful comparisons for numerical solver validation

Multiphysics Simulation of Particle-Surface Interaction and its Effect on Powder Patterns and Process Optimization

In industrial processes, powder coating is widely utilized to attain functional or aesthetic surface properties on manufactured parts. A Eulerian-Lagrangian Multiphysics solver has been developed within the OpenFOAM framework in order to simulate and optimize such processes with regards to coating efficiency and homogeneity. In the scope of this study, the powder particle-substrate and particle-particle interactions that occur on the surface of a substrate during the coating process are investigated. This is instigated by the observation that some particles glide over the substrate, rather than sticking to the substrate upon first contact. The phenomenon is governed by the balance of pressure, fluid shear stress traction, electrostatic particle-particle repulsion and gravity forces on the substrate. On the basis of experimental data previously gathered, it is demonstrated that the surface interactions are essential to predicting the coating outcome accurately enough, such as to serve as basis for later process-optimization steps. Furthermore, a dimensional analysis illustrates the weight of the individual force contributions on the overall force balance

Kartezyen hesaplama ağları için üç boyutlu Euler çözücüsü geliştirilmesi

TÜBİTAK MAG01.08.200

A massive simultaneous cloud computing platform for OpenFOAM

Today the field of numerical simulation in is faced with increasing demands for data-intensive investigations. On the one hand Engineering tasks call for parameter-studies, sensitivity analysis and optimization runs of ever-increasing size and magnitude. In addition the field of Artificial Intelligence (AI) with its notorious hunger for data, urges to provide ever more extensive, numerically derived learning-, testing- and validation input for training e.g. Artificial Neural Networks (ANN). On the other hand the current ‘age of cloud computing’ has set the stage such that nowadays any user of simulation software has access to potentially limitless hardware resources. In the light of these challenges and opportunities, Zurich University of Applied Sciences (ZHAW) and Kaleidosim Technologies AG (Kaleidosim) have developed a publically available Massive Simultaneous Cloud Computing (MSCC) platform for OpenFOAM. The platform is specifically tailored to yield vast amounts of simulation data in minimal Wall Clock Time (WCT). Spanning approximately nine-man-years of development effort the platform now features: • An instructive web-browser-based user interface (Web Interface); • An Application Programming Interface (API); • A Self-Compile option enabling users to run self-composed OpenFOAM applications directly in the cloud; • The Massive Simultaneous Cloud Computing (MSCC) feature which allows the orchestration of up to 500 cloud-based OpenFOAM simulation runs simultaneously; • The option to run Paraview in Batch Mode such that (semi-) automated cloud-based post-processing can be performed; • The Katana File Downloader (KFD) allowing the selective download of specific output dat

Multiphysics Modelling of Powder Coating of U-Profiles: Towards Simulation-based Optimization of Key-Performance Attributes by Variation of Powder-Parameters

Multiphysics simulation software has been developed to predict the key performance attributes of industrial powder coating applications based on applied process-parameter settings. The software is a Eulerian-Lagrangian finite-volume Multiphysics solver based on OpenFOAM, capable of modelling mass transfer effects between powder-coating pistols and electrically grounded metallic substrates. It considers various factors such as fluid dynamics of process airflow, coating-particle dynamics, particle-substrate interactions, and particle charging mechanisms within the corona. The software is fully compatible with Massive Simultaneous Cloud Computing technology, allowing hundreds of simulated coating scenarios to be computed simultaneously. Experimental validation efforts have been conducted, indicating a high degree of practical relevance of the technology. The current simulation study aims to demonstrate the potential of the simulation software for adjusting coating lines and optimizing powder coating of U-profiles. Specifically, the study focuses on optimizing the key-performance-attributes of the powder coating application with respect to varying material parameters of the applied powder, namely mean particle diameter, standard deviation of Gaussian particle size distribution, and powder particle density. The software predicts and visualizes coating patterns, coating efficiencies, and the batch-based standard deviation of coating thickness on a U-shaped metallic substrate, resulting in concrete and optimized powder settings. The presented results and the applied software are highly relevant for powder material suppliers

Multiphysics Eulerian-Lagrangian electrostatic particle spray- and deposition model for OpenFOAM® and KaleidoSim® cloud-platform

A finite volume based Eulerian-Lagrangian model has been created within OpenFOAM® in order to predict the behavior of particle clouds as well as particle deposition thicknesses on substrates under the influence of electro-static effects. The model resolves close to electrode effects as well as phenomena within the entire coating chamber. It considers fluid dynamic effects, particle inertia, gravity, electric- as well as mechanic particle-particle interaction, corona formation, dynamic particle charging mechanisms, and coupling of particle motion to Reynolds-Averaged Navier-Stokes (RANS) based flow simulations. Resulting coating pattern predictions were experimentally validated. It is demonstrated qualitatively and quantitatively that the measured coating thicknesses and patterns vary by; i) applied voltage, ii) airflow rate, pistol-substrate iii) -distance and iv) –angle. Furthermore, the software has been prepared such that it works on the cloud computing software KaleidoSim®, which enables the simultaneous browser-based running of hundreds of cases for large parameter studies

Barrier dysfunction or drainage reduction: differentiating causes of CSF protein increase

BACKGROUND Cerebrospinal fluid (CSF) protein analysis is an important element in the diagnostic chain for various central nervous system (CNS) pathologies. Among multiple existing approaches to interpreting measured protein levels, the Reiber diagram is particularly robust with respect to physiologic inter-individual variability, as it uses multiple subject-specific anchoring values. Beyond reliable identification of abnormal protein levels, the Reiber diagram has the potential to elucidate their pathophysiologic origin. In particular, both reduction of CSF drainage from the cranio-spinal space as well as blood-CNS barrier dysfunction have been suggested ρas possible causes of increased concentration of blood-derived proteins. However, there is disagreement on which of the two is the true cause. METHODS We designed two computational models to investigate the mechanisms governing protein distribution in the spinal CSF. With a one-dimensional model, we evaluated the distribution of albumin and immunoglobulin G (IgG), accounting for protein transport rates across blood-CNS barriers, CSF dynamics (including both dispersion induced by CSF pulsations and advection by mean CSF flow) and CSF drainage. Dispersion coefficients were determined a priori by computing the axisymmetric three-dimensional CSF dynamics and solute transport in a representative segment of the spinal canal. RESULTS Our models reproduce the empirically determined hyperbolic relation between albumin and IgG quotients. They indicate that variation in CSF drainage would yield a linear rather than the expected hyperbolic profile. In contrast, modelled barrier dysfunction reproduces the experimentally observed relation. CONCLUSIONS High levels of albumin identified in the Reiber diagram are more likely to originate from a barrier dysfunction than from a reduction in CSF drainage. Our in silico experiments further support the hypothesis of decreasing spinal CSF drainage in rostro-caudal direction and emphasize the physiological importance of pulsation-driven dispersion for the transport of large molecules in the CSF

Efficiency, Leverage and Exit: The Role of Information Asymmetry in Concentrated Industries Human Capital Investment and the Completion of Risky R&D Projects Migration Options for Skilled Labor and Optimal Investment in Human Capital

Efficiency, Leverage and Exit: The Role of Information Asymmetry in Concentrated Industries This paper develops a real options model of imperfect competition with asymmetric information that analyzes firms' exit decisions. Optimal exit decision is linked to firm characteristics such as financial leverage and efficiency. The model shows that informational asymmetries can lead more efficient and less leveraged firms to leave the product market prematurely. It also demonstrates how firm efficiency can increase debt capacity relative to rival firms. The model also has implications for firm risk and asset returns. Specifically, the paper shows that, when there is information asymmetry among rivals, rival actions can have a "news effect" that change a firm's dynamic risk structure. Human Capital Investment and the Completion of Risky R&D Projects We consider a firm that employs human capital to make a technological breakthrough. Since the probability of success of the breakthrough depends on the current stock of human capital the firm has an incentive to expand its human capital stock. The present value of the patent is stochastic but can be observed during the R\&D phase of the project. The exogenous value of the patent determines the firm's decisions to invest in human capital, to abandon the project if necessary, and to invest in marketing the new product. We study the corresponding optimal stopping times, determine their value and risk consequences, and derive optimal investment in the stock of human capital. While optimal investment in human capital is very sensitive to its productivity do increase the probability of a breakthrough it is insensitive to changes in the volatility of the present value of the patent. The value of the firm is driven by fixed labor costs that occur until the breakthrough is made, the call option to invest in human capital and market the product, and the put option to abandon the project. These options together with labor costs' based operating leverage determine the risk dynamics. Risk varies non-monotonically with the stochastic value of the patent and is U-shaped. Migration Options for Skilled Labor and Optimal Investment in Human Capital This paper develops a model of optimal education choice of an agent who has an option to emigrate. Using a real options framework, we analyze the time evolution of human capital in the country of origin and investigate the role of migration possibilities in the accumulation of different types of human capital. The analysis shows that the accumulation of human capital depends crucially on the level of uncertainty and the transferability of human capital across countries. Government subsidies are an important determinant of the composition of different types of human capital and can be crucial in alleviating the brain drain problem. (author's abstract