Monte Carlo-based radiation transport codes provide an opportunity to simulate situations with various levels of activation and different induced nuclides. However, to test their reliability, it is important to verify the simulation codes by comparing them with experimental data. In this study, validation of simulation models with experiments was performed with the purpose of determining the reliability of the simulation/experimental results. Concrete is the most generally used shield material as it is inexpensive and adjustable for any construction design. Radiation shielding properties of concrete may vary depending on the concrete composites. In this thesis, the fluences (i.e. the flux integrated over time) of neutrons impinging on the shielding nuclear material were studied using FLUKA Monte Carlo package. The rectangular blocks of shielding nuclear materials such as concrete ingredients: cement, sand and water were irradiated with a beam of 14 MeV neutrons and the shielding properties of these materials were investigated using FLUKA Monte Carlo simulation code. The simulation set-up replicates the experimental measurements performed within the nuclear laboratory in the Department of Physics at the University of Cape Town. The comparison of the effective removal cross-section shows a good agreement between experiments and FLUKA. The results from these two approaches show general agreement for sand and cement, but show some minor deviations for water and concrete. The source of these deviations is discussed, along with potential solutions. FLUKA has been well benchmarked and validated against other Monte Carlo codes. The discrepancies obtained on water and concrete may have occurred from the material properties in the input file. Comparisons of results are presented and the discrepancies and agreements between the two methods are discussed for these target materials. The effective removal cross section of a concrete mix was measured by simulation to be 0.1038 +/- 0.0005 cm-1 and by experiment to be 0.1230 +/- 0.0002 cm-1 of 14 MeV neutrons. This illustrates a broad agreement between experiment and simulation in the case of concrete ingredients. Validation and comparison of measured and simulated neutron irradiation on concrete ingredients shows good agreement, supporting the use of FLUKA for estimating the neutron transmission into the shielding material.

Digital halftoning is a crucial technique used in digital printers to convert a continuoustone image into a pattern of black and white dots. Halftoning is used since printers have a limited availability of inks and cannot reproduce all the color intensities in a continuous image. Error Diffusion is an algorithm in halftoning that iteratively quantizes pixels in a neighborhood dependent fashion. This thesis focuses on the development and design of a parallel scalable hardware architecture for high performance implementation of a high quality Stacked Error Diffusion algorithm. The algorithm is described in ‘C’ and requires a significant processing time when implemented on a conventional CPU. Thus, a new hardware processor architecture is developed to implement the algorithm and is implemented to and tested on a Xilinx Virtex 5 FPGA chip. There is an extraordinary decrease in the run time of the algorithm when run on the newly proposed parallel architecture implemented to FPGA technology compared to execution on a single CPU. The new parallel architecture is described using the Verilog Hardware Description Language. Post-synthesis and post-implementation, performance based Hardware Description Language (HDL), simulation validation of the new parallel architecture is achieved via use of the ModelSim CAD simulation tool.

Discrete event simulation is a widely used technique for decision support. The results of the simulation must be reliable for critical decision making problems. Therefore, much research has concentrated on the verification and validation of simulations. In this thesis, we apply a well-known dynamic verification technique, assertion checking method, as a validation technique. Our aim is to validate the particular runs of the simulation model, rather than the model itself. As a case study, the operations of a manufacturing cell have been simulated. The cell, which is METUCIM Laboratory at the Mechanical Engineering Department of METU, has a robot and a conveyor to carry the materials, and two machines to manufacture the items, and a quality control to measure the correctness of the manufactured items. This simulation is monitored and checked by using the Monitoring and Checking (MaC) tool, a prototype developed at the University of Pennsylvania. The separation of low-level implementation details (pertaining to the code) from the high-level requirement specifications (pertaining to the simuland) helps keep monitoring and checking the simulations at an abstract level.

Simulation-based training has gained widespread attention recently as a response to drawbacks associated with traditional training approaches, such as high training costs (instructors, equipment, etc.), high risks (e.g. pilot training), and ethical issues (e.g. medical training), as well as a lack of availability of certain training environments (e.g. space exploration). Apart from their target training domains, many of aspects of simulations differ, such as their degree of physical realism (fidelity), scenarios (e.g. story), and pedagogical aspects (e.g. after-action reviews and collaborative learning). Among those aspects, designers have mostly focused on developing high-fidelity simulations with the expectation of increasing the effectiveness of training. However, some authors suggest that the above belief is a myth as researchers have failed to identify a linear relationship between the (physical) fidelity and training effectiveness of simulations.  Most researchers have therefore evaluated the correspondence between the behaviours of trainees in both real world and simulated contexts, however, the existing methods of simulation validation using behavioural measures have a number of drawbacks, such as the fact that they do not address certain complex phenomena of skills acquisition. Bridging the above knowledge gap, this research reports on empirical investigations using an improved methodology for validating training simulations. This research includes an investigation of the user experience of trainees, with respect to the acceptance of virtual scenarios provoking a similar psychophysiological response as in real world scenarios, and the training potential of simulations with respect to the positive transfer of training from a simulator to real world operational contexts. The most prominent features of the proposed methodology include the use of psychophysiological measures in addition to traditional behavioural measures and the use of natural (quasi-) experiments. Moreover, its conceptual framework was influenced by contemporary theories in cognitive science (e.g. constructivism and embodied cognition). The results of this research have several important theoretical and methodological implications, involving, for example, the dependency of the effectiveness of simulations on the perceived realism of trainees, which is more embodied than has been predicted by previous researchers, and the requirement of several different types/levels of adaptive training experience, depending on the type of trainee. / Träning i simulatorer har på senare år fått ökad uppmärksamhet som en respons på problem och svårigheter förknippade med traditionella träningsansatser, såsom höga kostnader (instruktörer och utrustning, etc.), hög risk (t.ex. träning av piloter), och etiska aspekter (t.ex. träning av kirurger), likaväl som avsaknaden av träningsmöjligheter och miljöer (t.ex. forskning om rymden). Bortsett från vad som specifikt tränas så skiljer sig simuleringar åt i ett flertal olika aspekter såsom fysisk realism (eng. fidelity), scenarier (handling) och pedagogiska aspekter (t.ex. genomgång efter övning och kollaborativt lärande).  Bland dessa aspekter så har designers ofta fokuserat att utveckla simuleringar med hög realism med förväntningen att detta ska göra träningen mer effektiv. Litteraturen antyder dock att denna föreställning inte stämmer och att de flesta simuleringar med hög realism inte har lyckats uppnå denna målsättning. En slutsats är därför att det finns ett behov av metoder som kan validera potentialen hos simuleringar avsedda att stödja träning – redan innan dessa används. Enligt litteraturen så är utbildningspotentialen hos en simulering starkt kopplad till hur väl den psykologiska effekten en simulering har, stämmer överens med en verklig upplevelse. Forskning har emellertid identifierat ett flertal svagheter hos existerande ansatser för att validera simuleringar; de är oftast baserade på prestations- och/eller subjektiva mätningar; de har fokuserat en eller ett fåtal psykologiska aspekter; och de bygger på traditionella teorier. Baserat på resultat från studier av en kör-simulator presenteras och föreslås i denna avhandling ett förbättrat ramverk för utvärdering. De mest centrala egenskaperna hos det föreslagna ramverket inbegriper användandet av psyko-fysiologiska mått tillsammans med mer traditionella mått; det konceptuella ramverket bygger på samtida teoretiska ansatser (tex konstruktivism och kroppslig kognition); samt användandet av fält (kvasi-) experiment. Utöver uppnåendet av uppsatta mål för forskningen så har resultaten ett flertal teoretiska och metodologiska implikationer. Bland dessa återfinns beroendet mellan effektiviteten hos en simulering och den upplevelse av realitet som de tränade har, vilken är mer grundläggande än vad som rapporterats i tidigare forskning, samt kravet på flera och olika typer av anpassning av träningsupplevelse för den tränade för att förhöja potentialen hos träningssimulatorer. / SIDA Funded National e-Learning Centre Project at the University of Colombo School of Computing, Sri Lanka

Das Simulationsprogramm Delphin ermöglicht die Berechnung des gekoppelten Wärme-, Feuchte-, Luft- und Stofftransports in kapillarporösen Materialien. Die Simulation verwendet ein numerisches Lösungsverfahren für die Differentialgleichungen welche die Transportprozesse beschreiben. Zur Kontrolle der numerischen Fehler sowie der korrekten Implementierung der physikalischen Gleichungen werden Validierungsrechnungen durchgeführt. Dafür werden vordefinierte Testfälle eingegeben, gerechnet und mit Referenzlösungen bzw. den Ergebnissen anderer Simulationsprogramme verglichen. In diesem Artikel werden die Ergebnisse der Validierung der Delphin Versionen 5.6, 5.8, 6.0 und 6.1 zusammengefasst. Es wurden folgende Testfälle gerechnet: HAMSTAD Benchmarks 1 bis 5, DIN EN ISO 10211 Fall 1 und 2, DIN EN 15026 und der Aufsaug-Trocknungs-Test. Die Validierung von Delphin erfolgte hinsichtlich des Wärme-, Feuchte- und Lufttransports bei ein- und zweidimensionalen Problemstellungen. Alle Programmversionen erfüllen die Anforderungen aller Testfälle.:1 Einleitung 1.1 Fehlerquellen bei numerischen Lösungsverfahren 1.2 Validierungssystematik 1.3 Beschreibung der Testfälle 2 Materialgenerierung 2.1 Konstante Speichereigenschaften 2.2 Konstante Transporteigenschaften 2.3 Feuchtespeicherung 2.4 Feuchtetransport 2.5 Wärmeleitung 2.6 Materialdatei 3 HAMSTAD Benchmark 1 3.1 Materialdaten 3.2 Klimadaten und Randbedingungen 3.3 Validierungsrechnung 4 HAMSTAD Benchmark 2 4.1 Materialdaten 4.2 Klimadaten und Randbedingungen 4.3 Validierungsrechnung 5 HAMSTAD Benchmark 3 5.1 Materialdaten 5.2 Klimadaten und Randbedingungen 5.3 Validierungsrechnung 6 HAMSTAD Benchmark 4 6.1 Materialdaten 6.2 Klimadaten und Randbedingungen 6.3 Validierungsrechnung 7 HAMSTAD Benchmark 5 7.1 Materialdaten 7.2 Klimadaten und Randbedingungen 7.3 Validierungsrechnung 8 DIN EN ISO 10211 Fall 1 8.1 Materialdaten 8.2 Klimadaten und Randbedingungen 8.3 Validierungsrechnung 9 DIN EN ISO 10211 Fall 2 9.1 Materialdaten 9.2 Klimadaten und Randbedingungen 9.3 Validierungsrechnung 10 DIN EN 15026 10.1 Materialdaten 10.2 Klimadaten und Randbedingungen 10.3 Validierungsrechnung 11 Aufsaug-Trocknungs-Testfall (Wetting&Drying) 11.1 Materialdaten 11.2 Klimadaten und Randbedingungen 11.3 Validierungsrechnung 12 Zusammenfassung