Wind tunnel simulation of atmospheric boundary layer flows

The present work shows how thick boundary layers can be produced in a short wind tunnel with a view to simulate atmospheric flows. Several types of thickening devices are analysed. The experimental assessment of the devices was conducted by considering integral properties of the flow and the spectra: skin-friction, mean velocity profiles in inner and outer co-ordinates and longitudinal turbulence. Designs based on screens, elliptic wedge generators, and cylindrical rod generators are analysed. The paper describes in detail the experimental arrangement, including the features of the wind tunnel and of the instrumentation. The results are compared with experimental data published by other authors and with naturally developed flows.

Seismic motion simulation based on Cassino Parallel Manipulator

In this paper we present a study of feasibility by using Cassino Parallel Manipulator (CaPaMan) as an earthquake simulator. We propose a suitable formulation to simulate the frequency, amplitude and acceleration magnitude of seismic motion by means of the movable platform motion by giving a suitable input motion. In this paper we have reported numerical simulations that simulate the three principal earthquake types for a seismic motion: one at the epicenter (having a vertical motion), another far from the epicenter (with the motion on a horizontal plane), and a combined general motion (with a vertical and horizontal motion).

Testing and simulation of fractionary electromechanical rotative drives

This paper concerns the development of drives that use electromechanical rotative motor systems. It is proposed an experimental drive test structure integrated to simulation softwares. The objective of this work is to show that an affordable model validation procedure can be obtained by combining a precision data acquisition with well tuned state-of-the-art simulation packages. This is required for fitting, in the best way, a drive to its load or, inversely, to adapt loads to given drive characteristics.

Numerical Simulation of Stochastic Di erential Equations

Stochastic differential equation (SDE) is a differential equation in which some of the terms and its solution are stochastic processes. SDEs play a central role in modeling physical systems like finance, Biology, Engineering, to mention some. In modeling process, the computation of the trajectories (sample paths) of solutions to SDEs is very important. However, the exact solution to a SDE is generally difficult to obtain due to non-differentiability character of realizations of the Brownian motion. There exist approximation methods of solutions of SDE. The solutions will be continuous stochastic processes that represent diffusive dynamics, a common modeling assumption for financial, Biology, physical, environmental systems. This Masters' thesis is an introduction and survey of numerical solution methods for stochastic differential equations. Standard numerical methods, local linearization methods and filtering methods are well described. We compute the root mean square errors for each method from which we propose a better numerical scheme. Stochastic differential equations can be formulated from a given ordinary differential equations. In this thesis, we describe two kind of formulations: parametric and non-parametric techniques. The formulation is based on epidemiological SEIR model. This methods have a tendency of increasing parameters in the constructed SDEs, hence, it requires more data. We compare the two techniques numerically.

Video transcoding in a distributed cloud computing environment

Video transcoding refers to the process of converting a digital video from one format into another format. It is a compute-intensive operation. Therefore, transcoding of a large number of simultaneous video streams requires a large amount of computing resources. Moreover, to handle di erent load conditions in a cost-e cient manner, the video transcoding service should be dynamically scalable. Infrastructure as a Service Clouds currently offer computing resources, such as virtual machines, under the pay-per-use business model. Thus the IaaS Clouds can be leveraged to provide a coste cient, dynamically scalable video transcoding service. To use computing resources e ciently in a cloud computing environment, cost-e cient virtual machine provisioning is required to avoid overutilization and under-utilization of virtual machines. This thesis presents proactive virtual machine resource allocation and de-allocation algorithms for video transcoding in cloud computing. Since users' requests for videos may change at di erent times, a check is required to see if the current computing resources are adequate for the video requests. Therefore, the work on admission control is also provided. In addition to admission control, temporal resolution reduction is used to avoid jitters in a video. Furthermore, in a cloud computing environment such as Amazon EC2, the computing resources are more expensive as compared with the storage resources. Therefore, to avoid repetition of transcoding operations, a transcoded video needs to be stored for a certain time. To store all videos for the same amount of time is also not cost-e cient because popular transcoded videos have high access rate while unpopular transcoded videos are rarely accessed. This thesis provides a cost-e cient computation and storage trade-o strategy, which stores videos in the video repository as long as it is cost-e cient to store them. This thesis also proposes video segmentation strategies for bit rate reduction and spatial resolution reduction video transcoding. The evaluation of proposed strategies is performed using a message passing interface based video transcoder, which uses a coarse-grain parallel processing approach where video is segmented at group of pictures level.

Distributed document migration between ERP systems by means of messaging and event sourcing

This bachelor’s thesis, written for Lappeenranta University of Technology and implemented in a medium-sized enterprise (SME), examines a distributed document migration system. The system was created to migrate a large number of electronic documents, along with their metadata, from one document management system to another, so as to enable a rapid switchover of an enterprise resource planning systems inside the company. The paper examines, through theoretical analysis, messaging as a possible enabler of distributing applications and how it naturally fits an event based model, whereby system transitions and states are expressed through recorded behaviours. This is put into practice by analysing the implemented migration systems and how the core components, MassTransit, RabbitMQ and MongoDB, were orchestrated together to realize such a system. As a result, the paper presents an architecture for a scalable and distributed system that could migrate hundreds of thousands of documents over weekend, serving its goals in enabling a rapid system switchover.

A Model-Based Development and Verification Framework for Distributed System-on-Chip Architecture

The capabilities and thus, design complexity of VLSI-based embedded systems have increased tremendously in recent years, riding the wave of Moore’s law. The time-to-market requirements are also shrinking, imposing challenges to the designers, which in turn, seek to adopt new design methods to increase their productivity. As an answer to these new pressures, modern day systems have moved towards on-chip multiprocessing technologies. New architectures have emerged in on-chip multiprocessing in order to utilize the tremendous advances of fabrication technology. Platform-based design is a possible solution in addressing these challenges. The principle behind the approach is to separate the functionality of an application from the organization and communication architecture of hardware platform at several levels of abstraction. The existing design methodologies pertaining to platform-based design approach don’t provide full automation at every level of the design processes, and sometimes, the co-design of platform-based systems lead to sub-optimal systems. In addition, the design productivity gap in multiprocessor systems remain a key challenge due to existing design methodologies. This thesis addresses the aforementioned challenges and discusses the creation of a development framework for a platform-based system design, in the context of the SegBus platform - a distributed communication architecture. This research aims to provide automated procedures for platform design and application mapping. Structural verification support is also featured thus ensuring correct-by-design platforms. The solution is based on a model-based process. Both the platform and the application are modeled using the Unified Modeling Language. This thesis develops a Domain Specific Language to support platform modeling based on a corresponding UML profile. Object Constraint Language constraints are used to support structurally correct platform construction. An emulator is thus introduced to allow as much as possible accurate performance estimation of the solution, at high abstraction levels. VHDL code is automatically generated, in the form of “snippets” to be employed in the arbiter modules of the platform, as required by the application. The resulting framework is applied in building an actual design solution for an MP3 stereo audio decoder application.

Simulation of new p-type pixel strip detector with enhanced multiplication effect

This Master’s Thesis is dedicated to the simulation of new p-type pixel strip detector with enhanced multiplication effect. It is done for high-energy physics experiments upgrade such as Super Large Hadron Collider especially for Compact Muon Solenoid particle track silicon detectors. These detectors are used in very harsh radiation environment and should have good radiation hardness. The device engineering technology for developing more radiation hard particle detectors is used for minimizing the radiation degradation. New detector structure with enhanced multiplication effect is proposed in this work. There are studies of electric field and electric charge distribution of conventional and new p-type detector under reverse voltage bias and irradiation. Finally, the dependence of the anode current from the applied cathode reverse voltage bias under irradiation is obtained in this Thesis. For simulation Silvaco Technology Computer Aided Design software was used. Athena was used for creation of doping profiles and device structures and Atlas was used for getting electrical characteristics of the studied devices. The program codes for this software are represented in Appendixes.

Transient current technique simulation of semiconductor detectors

Nowadays advanced simulation technologies of semiconductor devices occupies an important place in microelectronics production process. Simulation helps to understand devices internal processes physics, detect new effects and find directions for optimization. Computer calculation reduces manufacturing costs and time. Modern simulation suits such as Silcaco TCAD allow simulating not only individual semiconductor structures, but also these structures in the circuit. For that purpose TCAD include MixedMode tool. That tool can simulate circuits using compact circuit models including semiconductor structures with their physical models. In this work, MixedMode is used for simulating transient current technique setup, which include detector and supporting electrical circuit. This technique was developed by RD39 collaboration project for investigation radiation detectors radiation hard properties.

A distributed, cloud-ready, digital content processing and transformation platform and a specific use case

Poster at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Distributed Repositories of Medieval Calendars and Crowd-Sourcing of Transcription

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

A Distributed Microservices Framework Integrating Taverna

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Warranty Prediction Using Weibull Simulation

The main objective of this master’s thesis is to examine if Weibull analysis is suitable method for warranty forecasting in the Case Company. The Case Company has used Reliasoft’s Weibull++ software, which is basing on the Weibull method, but the Company has noticed that the analysis has not given right results. This study was conducted making Weibull simulations in different profit centers of the Case Company and then comparing actual cost and forecasted cost. Simula-tions were made using different time frames and two methods for determining future deliveries. The first sub objective is to examine, which parameters of simulations will give the best result to each profit center. The second sub objective of this study is to create a simple control model for following forecasted costs and actual realized costs. The third sub objective is to document all Qlikview-parameters of profit centers. This study is a constructive research, and solutions for company’s problems are figured out in this master’s thesis. In the theory parts were introduced quality issues, for example; what is quality, quality costing and cost of poor quality. Quality is one of the major aspects in the Case Company, so understand-ing the link between quality and warranty forecasting is important. Warranty management was also introduced and other different tools for warranty forecasting. The Weibull method and its mathematical properties and reliability engineering were introduced. The main results of this master’s thesis are that the Weibull analysis forecasted too high costs, when calculating provision. Although, some forecasted values of profit centers were lower than actual values, the method works better for planning purposes. One of the reasons is that quality improving or alternatively quality decreasing is not showing in the results of the analysis in the short run. The other reason for too high values is that the products of the Case Company are com-plex and analyses were made in the profit center-level. The Weibull method was developed for standard products, but products of the Case Company consists of many complex components. According to the theory, this method was developed for homogeneous-data. So the most im-portant notification is that the analysis should be made in the product level, not the profit center level, when the data is more homogeneous.

On advancing business intelligence in the electricity retail market

In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.