3D Stripixel Detectors Simulation

Solid-state silicon detectors have replaced conventional ones in almost all recent high-energy physics experiments. Pixel silicon sensors don't have any alternative in the area near the interaction point because of their high resolution and fast operation speed. However, present detectors hardly withstand high radiation doses. Forthcoming upgrade of the LHC in 2014 requires development of a new generation of pixel detectors which will be able to operate under ten times increased luminosity. A planar fabrication technique has some physical limitations; an improvement of the radiation hardness will reduce sensitivity of a detector. In that case a 3D pixel detector seems to be the most promising device which can overcome these difficulties. The objective of this work was to model a structure of the 3D stripixel detector and to simulate electrical characteristics of the device. Silvaco Atlas software has been used for these purposes. The structures of single and double sided dual column detectors with active edges were described using special command language. Simulations of these detectors have shown that electric field inside an active area has more uniform distribution in comparison to the planar structure. A smaller interelectrode space leads to a stronger field and also decreases the collection time. This makes the new type of detectors more radiation resistant. Other discovered advantages are the lower full depletion voltage and increased charge collection efficiency. So the 3D stripixel detectors have demonstrated improved characteristics and will be a suitable replacement for the planar ones.

Induction Motor Drive Energy Efficiency - Simulation and Analysis

A coupled system simulator, based on analytical circuit equations and a finite element method (FEM) model of the motor has been developed and it is used to analyse a frequency-converterfed industrial squirrel-cage induction motor. Two control systems that emulate the behaviour of commercial direct-torque-controlled (DTC) and vector-controlled industrial frequency converters have been studied, implemented in the simulation software and verified by extensive laboratory tests. Numerous factors that affect the operation of a variable speed drive (VSD) and its energy efficiency have been investigated, and their significance in the simulation of the VSD results has been studied. The dependency of the frequency converter, induction motor and system losses on the switching frequency is investigated by simulations and measurements at different speeds for both the vector control and the DTC. Intensive laboratory measurements have been carried out to verify the simulation results.

CFD Simulation of Two-phase and Three-phase Flows in Internal-loop Airlift

Airlift reactors are pneumatically agitated reactors that have been widely used in chemical, petrochemical, and bioprocess industries, such as fermentation and wastewater treatment. Computational Fluid Dynamics (CFD) has become more popular approach for design, scale-up and performance evaluation of such reactors. In the present work numerical simulations for internal-loop airlift reactors were performed using the transient Eulerian model with CFD package, ANSYS Fluent 12.1. The turbulence in the liquid phase is described using κ- ε the model. Global hydrodynamic parameters like gas holdup, gas velocity and liquid velocity have been investigated for a range of superficial gas velocities, both with 2D and 3D simulations. Moreover, the study of geometry and scale influence on the reactor have been considered. The results suggest that both, geometry and scale have significant effects on the hydrodynamic parameters, which may have substantial effects on the reactor performance. Grid refinement and time-step size effect have been discussed. Numerical calculations with gas-liquid-solid three-phase flow system have been carried out to investigate the effect of solid loading, solid particle size and solid density on the hydrodynamic characteristics of internal loop airlift reactor with different superficial gas velocities. It was observed that averaged gas holdup is significantly decreased with increasing slurry concentration. Simulations show that the riser gas holdup decreases with increase in solid particle diameter. In addition, it was found that the averaged solid holdup increases in the riser section with the increase of solid density. These produced results reveal that CFD have excellent potential to simulate two-phase and three-phase flow system.

Effect of hydrodynamics on modelling, monitoring and control of crystallization

Crystallization is a purification method used to obtain crystalline product of a certain crystal size. It is one of the oldest industrial unit processes and commonly used in modern industry due to its good purification capability from rather impure solutions with reasonably low energy consumption. However, the process is extremely challenging to model and control because it involves inhomogeneous mixing and many simultaneous phenomena such as nucleation, crystal growth and agglomeration. All these phenomena are dependent on supersaturation, i.e. the difference between actual liquid phase concentration and solubility. Homogeneous mass and heat transfer in the crystallizer would greatly simplify modelling and control of crystallization processes, such conditions are, however, not the reality, especially in industrial scale processes. Consequently, the hydrodynamics of crystallizers, i.e. the combination of mixing, feed and product removal flows, and recycling of the suspension, needs to be thoroughly investigated. Understanding of hydrodynamics is important in crystallization, especially inlargerscale equipment where uniform flow conditions are difficult to attain. It is also important to understand different size scales of mixing; micro-, meso- and macromixing. Fast processes, like nucleation and chemical reactions, are typically highly dependent on micro- and mesomixing but macromixing, which equalizes the concentrations of all the species within the entire crystallizer, cannot be disregarded. This study investigates the influence of hydrodynamics on crystallization processes. Modelling of crystallizers with the mixed suspension mixed product removal (MSMPR) theory (ideal mixing), computational fluid dynamics (CFD), and a compartmental multiblock model is compared. The importance of proper verification of CFD and multiblock models is demonstrated. In addition, the influence of different hydrodynamic conditions on reactive crystallization process control is studied. Finally, the effect of extreme local supersaturation is studied using power ultrasound to initiate nucleation. The present work shows that mixing and chemical feeding conditions clearly affect induction time and cluster formation, nucleation, growth kinetics, and agglomeration. Consequently, the properties of crystalline end products, e.g. crystal size and crystal habit, can be influenced by management of mixing and feeding conditions. Impurities may have varying impacts on crystallization processes. As an example, manganese ions were shown to replace magnesium ions in the crystal lattice of magnesium sulphate heptahydrate, increasing the crystal growth rate significantly, whereas sodium ions showed no interaction at all. Modelling of continuous crystallization based on MSMPR theory showed that the model is feasible in a small laboratoryscale crystallizer, whereas in larger pilot- and industrial-scale crystallizers hydrodynamic effects should be taken into account. For that reason, CFD and multiblock modelling are shown to be effective tools for modelling crystallization with inhomogeneous mixing. The present work shows also that selection of the measurement point, or points in the case of multiprobe systems, is crucial when process analytical technology (PAT) is used to control larger scale crystallization. The thesis concludes by describing how control of local supersaturation by highly localized ultrasound was successfully applied to induce nucleation and to control polymorphism in reactive crystallization of L-glutamic acid.

Microscopic simulation of pigment coating consolidation

The control of coating layer properties is becoming increasingly important as a result of an emerging demand for novel coated paper-based products and an increasing popularity of new coating application methods. The governing mechanisms of microstructure formation dynamics during consolidation and drying are nevertheless, still poorly understood. Some of the difficulties encountered by experimental methods can be overcome by the utilisation of numerical modelling and simulation-based studies of the consolidation process. The objective of this study was to improve the fundamental understanding of pigment coating consolidation and structure formation mechanisms taking place on the microscopic level. Furthermore, it is aimed to relate the impact of process and suspension properties to the microstructure of the coating layer. A mathematical model based on a modified Stokesian dynamics particle simulation technique was developed and applied in several studies of consolidation-related phenomena. The model includes particle-particle and particle-boundary hydrodynamics, colloidal interactions, Born repulsion, and a steric repulsion model. The Brownian motion and a free surface model were incorporated to enable the specific investigation of consolidation and drying. Filter cake stability was simulated in various particle systems, and subjected to a range of base substrate absorption rates and system temperatures. The stability of the filter cake was primarily affected by the absorption rate and size of particles. Temperature was also shown to have an influence. The consolidation of polydisperse systems, with varying wet coating thicknesses, was studied using imposed pilot trial and model-based drying conditions. The results show that drying methods have a clear influence on the microstructure development, on small particle distributions in the coating layer and also on the mobility of particles during consolidation. It is concluded that colloidal properties can significantly impact coating layer shrinkage as well as the internal solids concentration profile. Visualisations of particle system development in time and comparison of systems at different conditions are useful in illustrating coating layer structure formation mechanisms. The results aid in understanding the underlying mechanisms of pigment coating layer consolidation. Guidance is given regarding the relationship between coating process conditions and internal coating slurry properties and their effects on the microstructure of the coating.

Identifying and Characterizing New Ingredients in vitro for Prebiotic and Synbiotic use

The endogenous microbiota, constituting the microbes that live inside and on humans, is estimated to outnumber human cells by a factor of ten. This commensal microbial population has an important role in many physiological functions, with the densest microbiota population found in the colon. The colonic microbiota is a highly complex and diverse bacterial ecosystem, and a delicate balance exists between the gut microbiota and its host. An imbalance in the microbial ecosystem may lead to severe symptoms in and also beyond the gastrointestinal tract. Due to the important role of the gut microbiota in human health, means of its modification have been introduced in the dietary concepts of pro-, pre- and synbiotics. Prebiotics, which are usually carbohydrates, strive to selectively influence beneficial microbes resident in the colon with the aim of modifying the composition and functionality of the commensal microbial population towards a purportedly healthier one. The study of prebiotic effects on colonic micro-organisms is typically done by using human faecal material, though this provides relatively little information on bacterial populations and metabolic events in different parts of the colon. For this reason, several in vitro models have been developed to investigate the gut microbiota. The aim of this doctoral thesis was to screen through some of the promising prebiotic candidates, characterize their effects on the microbiota through the use of two in vitro methods (pure microbial cultures and a colon simulator model) and to evaluate their potential as emerging prebiotics or synbiotics when combined with the probiotic Bifidobacterium lactis . As a result of the screening work and subsequent colon simulation studies, several compounds with promising features were identified. Xylo-oligosaccharides (XOS), which have previously already shown promise as prebiotic compounds, were well fermented by several probiotic Bifidobacterium lactis strains in pure culture studies and in the following simulation studies utilizing the complex microbiota by endogenous B. lactis Another promising compound was panose, a trisaccharide belonging to isomalto-oligosaccharides (IMO) that also was also able to modify the microbiota in vitro by increasing the number of beneficial microbes investigated. Panose has not been widely studied previously and therefore, this thesis work provided the first data on panose fermentation in mixed colonic microbiota. Galacto-oligosaccharide (GOS) is an established prebiotic, and it was studied here in conjunction with another potential polygosaccharide polydextrose (PDX) and probiotic B. lactis Bi-07. In this final study, the synbiotics including GOS were more effective than the constituting pro- or prebiotics alone in modulating the microbiota composition, thus indicating a synergy resulting from the combination. The results obtained in this in vitro work can be, and have already been, utilized in product development aimed at the nutritional modification of the human colonic microbiota. Some of the compounds have entered the human clinical intervention phase to nvestigate in more detail the prebiotic and synbiotic properties seen in these in vitro studies.

Tutorials for MeVEA Simulation Software

The objective of the thesis was to create three tutorials for MeVEA Simulation Software to instruct the new users to the modeling methodology used in the MeVEA Simulation Software. MeVEA Simulation Software is a real-time simulation software based on multibody dynamics. The simulation software is designed to create simulation models of complete mechatronical system. The thesis begins with a more detail description of the MeVEA Simulation Software and its components. The thesis presents the three simulation models and written theory of the steps of model creation. The first tutorial introduces the basic features which are used in most simulation models. The basic features include bodies, constrains, forces, basic hydraulics and motors. The second tutorial introduces the power transmission components, tyres and user input definitions for the different components in power transmission systems. The third tutorial introduces the definitions of two different types of collisions and collision graphics used in MeVEA Simulation Software.

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.

Learning Robot Environment through Simulation

Traditionally simulators have been used extensively in robotics to develop robotic systems without the need to build expensive hardware. However, simulators can be also be used as a “memory”for a robot. This allows the robot to try out actions in simulation before executing them for real. The key obstacle to this approach is an uncertainty of knowledge about the environment. The goal of the Master’s Thesis work was to develop a method, which allows updating the simulation model based on actual measurements to achieve a success of the planned task. OpenRAVE was chosen as an experimental simulation environment on planning,trial and update stages. Steepest Descent algorithm in conjunction with Golden Section search procedure form the principle part of optimization process. During experiments, the properties of the proposed method, such as sensitivity to different parameters, including gradient and error function, were examined. The limitations of the approach were established, based on analyzing the regions of convergence.

Simulation of Solid Processes by Aspen Plus

Solid processes are used for obtaining the valuable minerals. Due to their worth, it is obligatory to perform different experiments to determine the different values of these minerals. With the passage of time, it is becoming more difficult to carry out these experiments for each mineral for different characteristics due to high labor costs and consumption of time. Therefore, scientists and engineers have tried to overcome this issue. They made different software to handle this problem. Aspen is one of those software for the calculation of different parameters. Therefore, the aim of this report was to do simulation for solid processes to observe different effect for minerals. Different solid processes like crushing, screening; filtration and crystallization were simulated by Aspen Plus. The simulation results are obtained by using this simulation software and they are described in this thesis. It was noticed that the results were acceptable for all solid processes. Therefore, this software can be used for the designing of crushers by calculating the power consumption of crushers, can design the filter and for the calculation of material balance for all processes.

Simulation and optimization of IGCC technique for power generation and hydrogen production by using lignite Thar coal and cotton stalk

The purpose of this study was to simulate and to optimize integrated gasification for combine cycle (IGCC) for power generation and hydrogen (H2) production by using low grade Thar lignite coal and cotton stalk. Lignite coal is abundant of moisture and ash content, the idea of addition of cotton stalk is to increase the mass of combustible material per mass of feed use for the process, to reduce the consumption of coal and to increase the cotton stalk efficiently for IGCC process. Aspen plus software is used to simulate the process with different mass ratios of coal to cotton stalk and for optimization: process efficiencies, net power generation and H2 production etc. are considered while environmental hazard emissions are optimized to acceptance level. With the addition of cotton stalk in feed, process efficiencies started to decline along with the net power production. But for H2 production, it gave positive result at start but after 40% cotton stalk addition, H2 production also started to decline. It also affects negatively on environmental hazard emissions and mass of emissions/ net power production increases linearly with the addition of cotton stalk in feed mixture. In summation with the addition of cotton stalk, overall affects seemed to negative. But the effect is more negative after 40% cotton stalk addition so it is concluded that to get maximum process efficiencies and high production less amount of cotton stalk addition in feed is preferable and the maximum level of addition is estimated to 40%. Gasification temperature should keep lower around 1140 °C and prefer technique for studied feed in IGCC is fluidized bed (ash in dry form) rather than ash slagging gasifier

Playing to Learn: Business Simulation Games as Leadership Learning Environments

The aim of this dissertation is to investigate if participation in business simulation gaming sessions can make different leadership styles visible and provide students with experiences beneficial for the development of leadership skills. Particularly, the focus is to describe the development of leadership styles when leading virtual teams in computer-­supported collaborative game settings and to identify the outcomes of using computer simulation games as leadership training tools. To answer to the objectives of the study, three empirical experiments were conducted to explore if participation in business simulation gaming sessions (Study I and II), which integrate face-­to-­face and virtual communication (Study III and IV), can make different leadership styles visible and provide students with experiences beneficial for the development of leadership skills. In the first experiment, a group of multicultural graduate business students (N=41) participated in gaming sessions with a computerized business simulation game (Study III). In the second experiment, a group of graduate students (N=9) participated in the training with a ‘real estate’ computer game (Study I and II). In the third experiment, a business simulation gaming session was organized for graduate students group (N=26) and the participants played the simulation game in virtual teams, which were organizationally and geographically dispersed but connected via technology (Study IV). Each team in all experiments had three to four students and students were between 22 and 25 years old. The business computer games used for the empirical experiments presented an enormous number of complex operations in which a team leader needed to make the final decisions involved in leading the team to win the game. These gaming environments were interactive;; participants interacted by solving the given tasks in the game. Thus, strategy and appropriate leadership were needed to be successful. The training was competition-­based and required implementation of leadership skills. The data of these studies consist of observations, participants’ reflective essays written after the gaming sessions, pre-­ and post-­tests questionnaires and participants’ answers to open-­ ended questions. Participants’ interactions and collaboration were observed when they played the computer games. The transcripts of notes from observations and students dialogs were coded in terms of transactional, transformational, heroic and post-­heroic leadership styles. For the data analysis of the transcribed notes from observations, content analysis and discourse analysis was implemented. The Multifactor Leadership Questionnaire (MLQ) was also utilized in the study to measure transformational and transactional leadership styles;; in addition, quantitative (one-­way repeated measures ANOVA) and qualitative data analyses have been performed. The results of this study indicate that in the business simulation gaming environment, certain leadership characteristics emerged spontaneously. Experiences about leadership varied between the teams and were dependent on the role individual students had in their team. These four studies showed that simulation gaming environment has the potential to be used in higher education to exercise the leadership styles relevant in real-­world work contexts. Further, the study indicated that given debriefing sessions, the simulation game context has much potential to benefit learning. The participants who showed interest in leadership roles were given the opportunity of developing leadership skills in practice. The study also provides evidence of unpredictable situations that participants can experience and learn from during the gaming sessions. The study illustrates the complex nature of experiences from the gaming environments and the need for the team leader and role divisions during the gaming sessions. It could be concluded that the experience of simulation game training illustrated the complexity of real life situations and provided participants with the challenges of virtual leadership experiences and the difficulties of using leadership styles in practice. As a result, the study offers playing computer simulation games in small teams as one way to exercise leadership styles in practice.

Thinking Outside the Box: Enhancing Science Teaching by Combining (Instead of Contrasting) Laboratory and Simulation Activities

The focus of the present work was on 10- to 12-year-old elementary school students’ conceptual learning outcomes in science in two specific inquiry-learning environments, laboratory and simulation. The main aim was to examine if it would be more beneficial to combine than contrast simulation and laboratory activities in science teaching. It was argued that the status quo where laboratories and simulations are seen as alternative or competing methods in science teaching is hardly an optimal solution to promote students’ learning and understanding in various science domains. It was hypothesized that it would make more sense and be more productive to combine laboratories and simulations. Several explanations and examples were provided to back up the hypothesis. In order to test whether learning with the combination of laboratory and simulation activities can result in better conceptual understanding in science than learning with laboratory or simulation activities alone, two experiments were conducted in the domain of electricity. In these experiments students constructed and studied electrical circuits in three different learning environments: laboratory (real circuits), simulation (virtual circuits), and simulation-laboratory combination (real and virtual circuits were used simultaneously). In order to measure and compare how these environments affected students’ conceptual understanding of circuits, a subject knowledge assessment questionnaire was administered before and after the experimentation. The results of the experiments were presented in four empirical studies. Three of the studies focused on learning outcomes between the conditions and one on learning processes. Study I analyzed learning outcomes from experiment I. The aim of the study was to investigate if it would be more beneficial to combine simulation and laboratory activities than to use them separately in teaching the concepts of simple electricity. Matched-trios were created based on the pre-test results of 66 elementary school students and divided randomly into a laboratory (real circuits), simulation (virtual circuits) and simulation-laboratory combination (real and virtual circuits simultaneously) conditions. In each condition students had 90 minutes to construct and study various circuits. The results showed that studying electrical circuits in the simulation–laboratory combination environment improved students’ conceptual understanding more than studying circuits in simulation and laboratory environments alone. Although there were no statistical differences between simulation and laboratory environments, the learning effect was more pronounced in the simulation condition where the students made clear progress during the intervention, whereas in the laboratory condition students’ conceptual understanding remained at an elementary level after the intervention. Study II analyzed learning outcomes from experiment II. The aim of the study was to investigate if and how learning outcomes in simulation and simulation-laboratory combination environments are mediated by implicit (only procedural guidance) and explicit (more structure and guidance for the discovery process) instruction in the context of simple DC circuits. Matched-quartets were created based on the pre-test results of 50 elementary school students and divided randomly into a simulation implicit (SI), simulation explicit (SE), combination implicit (CI) and combination explicit (CE) conditions. The results showed that when the students were working with the simulation alone, they were able to gain significantly greater amount of subject knowledge when they received metacognitive support (explicit instruction; SE) for the discovery process than when they received only procedural guidance (implicit instruction: SI). However, this additional scaffolding was not enough to reach the level of the students in the combination environment (CI and CE). A surprising finding in Study II was that instructional support had a different effect in the combination environment than in the simulation environment. In the combination environment explicit instruction (CE) did not seem to elicit much additional gain for students’ understanding of electric circuits compared to implicit instruction (CI). Instead, explicit instruction slowed down the inquiry process substantially in the combination environment. Study III analyzed from video data learning processes of those 50 students that participated in experiment II (cf. Study II above). The focus was on three specific learning processes: cognitive conflicts, self-explanations, and analogical encodings. The aim of the study was to find out possible explanations for the success of the combination condition in Experiments I and II. The video data provided clear evidence about the benefits of studying with the real and virtual circuits simultaneously (the combination conditions). Mostly the representations complemented each other, that is, one representation helped students to interpret and understand the outcomes they received from the other representation. However, there were also instances in which analogical encoding took place, that is, situations in which the slightly discrepant results between the representations ‘forced’ students to focus on those features that could be generalised across the two representations. No statistical differences were found in the amount of experienced cognitive conflicts and self-explanations between simulation and combination conditions, though in self-explanations there was a nascent trend in favour of the combination. There was also a clear tendency suggesting that explicit guidance increased the amount of self-explanations. Overall, the amount of cognitive conflicts and self-explanations was very low. The aim of the Study IV was twofold: the main aim was to provide an aggregated overview of the learning outcomes of experiments I and II; the secondary aim was to explore the relationship between the learning environments and students’ prior domain knowledge (low and high) in the experiments. Aggregated results of experiments I & II showed that on average, 91% of the students in the combination environment scored above the average of the laboratory environment, and 76% of them scored also above the average of the simulation environment. Seventy percent of the students in the simulation environment scored above the average of the laboratory environment. The results further showed that overall students seemed to benefit from combining simulations and laboratories regardless of their level of prior knowledge, that is, students with either low or high prior knowledge who studied circuits in the combination environment outperformed their counterparts who studied in the laboratory or simulation environment alone. The effect seemed to be slightly bigger among the students with low prior knowledge. However, more detailed inspection of the results showed that there were considerable differences between the experiments regarding how students with low and high prior knowledge benefitted from the combination: in Experiment I, especially students with low prior knowledge benefitted from the combination as compared to those students that used only the simulation, whereas in Experiment II, only students with high prior knowledge seemed to benefit from the combination relative to the simulation group. Regarding the differences between simulation and laboratory groups, the benefits of using a simulation seemed to be slightly higher among students with high prior knowledge. The results of the four empirical studies support the hypothesis concerning the benefits of using simulation along with laboratory activities to promote students’ conceptual understanding of electricity. It can be concluded that when teaching students about electricity, the students can gain better understanding when they have an opportunity to use the simulation and the real circuits in parallel than if they have only the real circuits or only a computer simulation available, even when the use of the simulation is supported with the explicit instruction. The outcomes of the empirical studies can be considered as the first unambiguous evidence on the (additional) benefits of combining laboratory and simulation activities in science education as compared to learning with laboratories and simulations alone.

Improving Transportation and Warehousing Efficiency with Simulation-Based Decision Support Systems

Transportation and warehousing are large and growing sectors in the society, and their efficiency is of high importance. Transportation also has a large share of global carbondioxide emissions, which are one the leading causes of anthropogenic climate warming. Various countries have agreed to decrease their carbon emissions according to the Kyoto protocol. Transportation is the only sector where emissions have steadily increased since the 1990s, which highlights the importance of transportation efficiency. The efficiency of transportation and warehousing can be improved with the help of simulations, but models alone are not sufficient. This research concentrates on the use of simulations in decision support systems. Three main simulation approaches are used in logistics: discrete-event simulation, systems dynamics, and agent-based modeling. However, individual simulation approaches have weaknesses of their own. Hybridization (combining two or more approaches) can improve the quality of the models, as it allows using a different method to overcome the weakness of one method. It is important to choose the correct approach (or a combination of approaches) when modeling transportation and warehousing issues. If an inappropriate method is chosen (this can occur if the modeler is proficient in only one approach or the model specification is not conducted thoroughly), the simulation model will have an inaccurate structure, which in turn will lead to misleading results. This issue can further escalate, as the decision-maker may assume that the presented simulation model gives the most useful results available, even though the whole model can be based on a poorly chosen structure. In this research it is argued that simulation- based decision support systems need to take various issues into account to make a functioning decision support system. The actual simulation model can be constructed using any (or multiple) approach, it can be combined with different optimization modules, and there needs to be a proper interface between the model and the user. These issues are presented in a framework, which simulation modelers can use when creating decision support systems. In order for decision-makers to fully benefit from the simulations, the user interface needs to clearly separate the model and the user, but at the same time, the user needs to be able to run the appropriate runs in order to analyze the problems correctly. This study recommends that simulation modelers should start to transfer their tacit knowledge to explicit knowledge. This would greatly benefit the whole simulation community and improve the quality of simulation-based decision support systems as well. More studies should also be conducted by using hybrid models and integrating simulations with Graphical Information Systems.