MCViNE -- An object oriented Monte Carlo neutron ray tracing simulation package

MCViNE (Monte-Carlo VIrtual Neutron Experiment) is a versatile Monte Carlo (MC) neutron ray-tracing program that provides researchers with tools for performing computer modeling and simulations that mirror real neutron scattering experiments. By adopting modern software engineering practices such as using composite and visitor design patterns for representing and accessing neutron scatterers, and using recursive algorithms for multiple scattering, MCViNE is flexible enough to handle sophisticated neutron scattering problems including, for example, neutron detection by complex detector systems, and single and multiple scattering events in a variety of samples and sample environments. In addition, MCViNE can take advantage of simulation components in linear-chain-based MC ray tracing packages widely used in instrument design and optimization, as well as NumPy-based components that make prototypes useful and easy to develop. These developments have enabled us to carry out detailed simulations of neutron scattering experiments with non-trivial samples in time-of-flight inelastic instruments at the Spallation Neutron Source. Examples of such simulations for powder and single-crystal samples with various scattering kernels, including kernels for phonon and magnon scattering, are presented. With simulations that closely reproduce experimental results, scattering mechanisms can be turned on and off to determine how they contribute to the measured scattering intensities, improving our understanding of the underlying physics.Comment: 34 pages, 14 figure

A generalised powertrain component size optimisation methodology to reduce fuel economy variability in hybrid electric vehicles

Although hybrid electric vehicles (HEVs) generally improve fuel economy (FE) compared to conventional vehicles, evidence of higher FE variability in HEVs compared to conventional vehicles indicates that apart from the improvement in FE, the reduction of FE variability is also of significant importance for HEVs. Over the years research on how to optimise powertrain component sizes of HEVs has generally focused on improving FE over a given driving pattern; FE variability over a realistic range of driving patterns has generally been overlooked, and this can lead to FE benefits of HEVs not being fully realised in real-world usage. How to reduce the FE variability in HEVs due to variation in driving patterns through the optimisation of powertrain component sizes is considered as the research question. This research proposes a new methodology in which powertrain components are optimised over a range of driving patterns representing different traffic conditions and driving styles simultaneously. This improves upon the traditional methodology followed in the reviewed literature, where an optimisation is performed for each individual driving pattern. An analysis shows that the traditional methodology could produce around 20% FE variability due to variation in driving patterns. This study considers a computer simulation model of a series-parallel Toyota Prius HEV for the investigation. Four powertrain components, namely, internal combustion engine, generator, motor, and battery of the Toyota Prius are optimised for FE using a genetic algorithm. For both the proposed and traditional methodologies, the powertrain components are optimised based on 5 standard driving patterns representing different traffic conditions and driving styles. During the optimisation, the proposed methodology considers all the 5 driving patterns simultaneously, whereas the traditional methodology considers each driving pattern separately. The optimum designs of both the methodologies and the simulation model of the Toyota Prius which is the benchmark vehicle for this study are evaluated for FE over the aforementioned 5 standard driving patterns and also 10 real-world driving patterns of a predefined route consisting of urban and highway driving patterns. The proposed methodology provides a single optimum design over the 5 standard driving patterns, whereas the traditional methodology provides 5 different optimum designs, one for each driving pattern. The single optimum design produced by the proposed methodology is independent of the sequence of driving patterns. The proposed methodology reduces FE variability by 5.3% and up to 48.9% with comparable average FE compared to the Toyota Prius and traditional methodology, respectively over the 10 real-world driving patterns, whereas none of the optimum designs of the traditional methodology is able to reduce FE variability compared to the Toyota Prius. This research provides a promising direction to address customer concerns related to FE in the real-world and improves understanding of the effect of driving patterns on the design of powertrain components

A simulation-based method to evaluate the impact of product architecture on product evolvability

Products evolve over time via the continual redesigns of interdependent components. Product architecture, which is embodied in the structure of interactions among components, influences the ability for the product to be subsequently evolved. Despite extensive studies of change propagation via inter-component connections, little is known about the specific influences of product architecture on product evolvability. Related metrics and methods to assess the evolvability of products with given architectures are also under-developed. This paper proposes a simulation-based method to assess the isolated effect of product architecture on product evolvability by analyzing a design structure matrix. We define product evolvability as the ability of the product’s design to subsequently generate heritable performance-improving variations, and propose a quantitative measure for it. We demonstrate the proposed method by using it to investigate a wide spectrum of model-generated DSMs representing products with varied architectures, and show that modularity and inter-component influence cycles promote product evolvability. Our primary contribution is a repeatable method to assess and compare alternative product architectures for architecture selection or redesign for evolvability. A second contribution is the simulation-based evidence about the impacts of two particular product architectural patterns on product evolvability. Both contributions aim to aid in designing for evolvability.SUTD-MIT International Design Centre (IDC

Component-based tools for educational simulations

e-Learning is an effective medium for delivering knowledge and skills. In spite of improvements in electronic delivery technologies, e-Learning is still a long way away from offering anything close to efficient and effective learning environments. To improve e-Learning experiences, much literature supports simulation based e-Learning. This thesis begins identifying various types of simulation models and their features that induce experiential learning. We focus on designing and constructing an easy-to-use Discrete Event Simulation (DES) tool for building engaging and informative interactive DES models that allow learners to control the models' parameters and visualizations through runtime interactions. DES has long been used to support analysis and design of complex systems but its potential to enhance learning has not yet been fully utilized. We first present an application framework and its resulting classes for better structuring DES models. However, importing relevant classes, establishing relationships between their objects and representing lifecycles of various types of active objects in a language that does not support concurrency demand a significant cognitive workload. To improve this situation, we utilize two design patterns to ease model structuring and logic representation (both in time and space) through a drag and drop component approach. The patterns are the Delegation Event Model, used for linking between components and delegating tasks of executing and updating active objects' lifecycles, and the MVC (Model-View-Controller) pattern, used for connecting the components to their graphical instrumentations and GUIs. Components implementing both design patterns support the process-oriented approach, can easily be tailored to store model states and visualizations, and can be extended to design higher level models through hierarchical simulation development. Evaluating this approach with both teachers and learners using ActionScript as an implementation language in the Flash environment shows that the resulting components not only help model designers with few programming skills to construct DES models, but they also allow learners to conduct various experiments through interactive GUIs and observe the impact of changes to model behaviour through a range of engaging visualizations. Such interactions can motivate learners and make their learning an enjoyable experienc

Desen: Specification of Sociotechnical Systems via Patterns of Regulation and Control

We address the problem of engineering a sociotechnical system (STS) with respect to its stakeholders’ requirements. We motivate a two-tier STS conception comprising a technical tier that provides control mechanisms and describes what actions are allowed by the software components, and a social tier that characterizes the stakeholders’ expectations of each other in terms of norms. We adopt agents as computational entities, each representing a different stakeholder. Unlike previous approaches, our framework, Desen, incorporates the social dimension into the formal verification process. Thus, Desen supports agents potentially violating applicable norms—a consequence of their autonomy. In addition to requirements verification, Desen supports refinement of STS specifications via design patterns to meet stated requirements. We evaluate Desen at three levels. We illustrate how Desen carries out refinement via the application of patterns on a hospital emergency scenario. We show via a human-subject study that a design process based on our patterns is helpful for participants who are inexperienced in conceptual modeling and norms. We provide an agent-based environment to simulate the hospital emergency scenario to compare STS specifications (including participant solutions from the human-subject study) with metrics indicating social welfare and norm compliance, and other domain dependent metrics

Systems biology markup language (SBML) level 3 package: multistate, multicomponent and multicompartment species, version 1, release 2

Rule-based modeling is an approach that permits constructing reaction networks based on the specification of rules for molecular interactions and transformations. These rules can encompass details such as the interacting sub-molecular domains and the states and binding status of the involved components. Conceptually, fine-grained spatial information such as locations can also be provided. Through “wildcards” representing component states, entire families of molecule complexes sharing certain properties can be specified as patterns. This can significantly simplify the definition of models involving species with multiple components, multiple states, and multiple compartments. The systems biology markup language (SBML) Level 3 Multi Package Version 1 extends the SBML Level 3 Version 1 core with the “type” concept in the Species and Compartment classes. Therefore, reaction rules may contain species that can be patterns and exist in multiple locations. Multiple software tools such as Simmune and BioNetGen support this standard that thus also becomes amedium for exchanging rule-based models. This document provides the specification for Release 2 of Version 1 of the SBML Level 3 Multi package. No design changes have been made to the description of models between Release 1 and Release 2; changes are restricted to the correction of errata and the addition of clarifications

Systems biology markup language (SBML) level 3 package: multistate, multicomponent and multicompartment species, version 1, release 2

Rule-based modeling is an approach that permits constructing reaction networks based on the specification of rules for molecular interactions and transformations. These rules can encompass details such as the interacting sub-molecular domains and the states and binding status of the involved components. Conceptually, fine-grained spatial information such as locations can also be provided. Through “wildcards” representing component states, entire families of molecule complexes sharing certain properties can be specified as patterns. This can significantly simplify the definition of models involving species with multiple components, multiple states, and multiple compartments. The systems biology markup language (SBML) Level 3 Multi Package Version 1 extends the SBML Level 3 Version 1 core with the “type” concept in the Species and Compartment classes. Therefore, reaction rules may contain species that can be patterns and exist in multiple locations. Multiple software tools such as Simmune and BioNetGen support this standard that thus also becomes amedium for exchanging rule-based models. This document provides the specification for Release 2 of Version 1 of the SBML Level 3 Multi package. No design changes have been made to the description of models between Release 1 and Release 2; changes are restricted to the correction of errata and the addition of clarifications

Improving Networked Learning in Higher Education: Language Functions and Design Patterns

The thesis of this study is that two seemingly disparate research disciplines can be coalesced to develop an effective pedagogical framework for educational design in the context of networked learning. That contention is grounded in, and inspired by, the rapid developments in educational technologies which have greatly changed the landscape in teaching and learning in higher education over the last decade. The study attempts to add to the corpus of contemporary learning theory which sees students not merely as passive recipients of knowledge, but as active participants in the learning process, having much greater control over their selection of technological learning tools, learning resources and learning methodologies. This is very much in line with the shift from the traditional focus on content design and knowledge transmission towards a more student-centred design for knowledge co-construction, a development which demands the type of new thinking about the design of learning tasks and learning resources contained in this study. Also set out are new lines of action for the fashioning of a collaborative learning environment, for community interaction and the sharing of knowledge, and for promoting good teaching and learning practice. The central argument of the study is that such pedagogical goals may be attained by juxtaposing the theories of Systemic Functional Linguistics (hereafter SFL) and pattern languages. These have not, thus far, been used in combination. SFL is a well established theory in the study of language, and is used in this thesis to help analyse and classify discourses produced and shared by teachers and students in networked learning. Pattern languages have their origin in architecture. Design patterns can be used as a means of representing and sharing important and specific empirical research results and design experiences. This new knowledge can be used to support and improve the quality of educational design. The study has two central components. The first uses the SFL theoretical framework to demonstrate how text is used as a key medium in networked learning. In other words, it is argued in this section that the quality of texts has a direct impact on the quality of learning and learning outcomes. The quality of text is assessed by means of a detailed discourse analysis of selected texts. This process involves deconstructing, identifying and capturing the linguistic resources and language strategies used in the texts. The detailed discourse analysis also illustrates and reveals how language is used in the construction of knowledge and the promotion of collaboration in teaching and learning. The second component centres on the argument that SFL provides valuable language knowledge which can be represented by using Alexander’s design patterns. New knowledge encoded in these design patterns can be used by teachers and designers as reusable and shared resources to help them improve their design work. The empirical research was carried out in three phases. The first involved a) the identification of text patterns of discourses used in networked learning based on detailed discourse analysis; b) Interviewing experienced academic staff to identify their perspectives on good online teaching practices and success factors. The second phase involved using the data which emerged from these interviews and discourse analysis to model illustrative patterns. (Here, illustrative means that due to the scope of the study, it is only possible to develop a limited number of patterns to illustrate the methods used for pattern development. It is not the intention to develop a full repository of design patterns in this study). In the third (validation) phase the patterns were reviewed by two groups of academic staff, with the aim of improving these patterns. Improved patterns were then tested on a group of educational design students for their usefulness and application. It is concluded from this research that it is possible to develop design patterns which ensure the best use of linguistic resources in both the teaching and learning process. Finally, it is argued that the combination of SFL and pattern languages provides a promising theoretical framework for the complex and demanding task of educational design. Future research could make use of such a framework to explore a fuller application of the pattern- based approach for the representation of new knowledge for educational design. Suggested additional research directions include finding new ways of capturing a new pedagogical approach to mobile learning and blended learning. Also, a promising direction could be the use of SFL Appraisal theory (Martin, 2000) for the investigation on how students construct interpersonal relationships (appraise peer work) in online joint projects. In the conclusion, it is contended that through its exploration of new ground in the use of SFL and pattern language theory in the construction of education design patterns, the study makes a significant contribution to knowledge in the field of networked learning

Improving Networked Learning in Higher Education: Language Functions and Design Patterns

The thesis of this study is that two seemingly disparate research disciplines can be coalesced to develop an effective pedagogical framework for educational design in the context of networked learning. That contention is grounded in, and inspired by, the rapid developments in educational technologies which have greatly changed the landscape in teaching and learning in higher education over the last decade. The study attempts to add to the corpus of contemporary learning theory which sees students not merely as passive recipients of knowledge, but as active participants in the learning process, having much greater control over their selection of technological learning tools, learning resources and learning methodologies. This is very much in line with the shift from the traditional focus on content design and knowledge transmission towards a more student-centred design for knowledge co-construction, a development which demands the type of new thinking about the design of learning tasks and learning resources contained in this study. Also set out are new lines of action for the fashioning of a collaborative learning environment, for community interaction and the sharing of knowledge, and for promoting good teaching and learning practice. The central argument of the study is that such pedagogical goals may be attained by juxtaposing the theories of Systemic Functional Linguistics (hereafter SFL) and pattern languages. These have not, thus far, been used in combination. SFL is a well established theory in the study of language, and is used in this thesis to help analyse and classify discourses produced and shared by teachers and students in networked learning. Pattern languages have their origin in architecture. Design patterns can be used as a means of representing and sharing important and specific empirical research results and design experiences. This new knowledge can be used to support and improve the quality of educational design. The study has two central components. The first uses the SFL theoretical framework to demonstrate how text is used as a key medium in networked learning. In other words, it is argued in this section that the quality of texts has a direct impact on the quality of learning and learning outcomes. The quality of text is assessed by means of a detailed discourse analysis of selected texts. This process involves deconstructing, identifying and capturing the linguistic resources and language strategies used in the texts. The detailed discourse analysis also illustrates and reveals how language is used in the construction of knowledge and the promotion of collaboration in teaching and learning. The second component centres on the argument that SFL provides valuable language knowledge which can be represented by using Alexander’s design patterns. New knowledge encoded in these design patterns can be used by teachers and designers as reusable and shared resources to help them improve their design work. The empirical research was carried out in three phases. The first involved a) the identification of text patterns of discourses used in networked learning based on detailed discourse analysis; b) Interviewing experienced academic staff to identify their perspectives on good online teaching practices and success factors. The second phase involved using the data which emerged from these interviews and discourse analysis to model illustrative patterns. (Here, illustrative means that due to the scope of the study, it is only possible to develop a limited number of patterns to illustrate the methods used for pattern development. It is not the intention to develop a full repository of design patterns in this study). In the third (validation) phase the patterns were reviewed by two groups of academic staff, with the aim of improving these patterns. Improved patterns were then tested on a group of educational design students for their usefulness and application. It is concluded from this research that it is possible to develop design patterns which ensure the best use of linguistic resources in both the teaching and learning process. Finally, it is argued that the combination of SFL and pattern languages provides a promising theoretical framework for the complex and demanding task of educational design. Future research could make use of such a framework to explore a fuller application of the pattern- based approach for the representation of new knowledge for educational design. Suggested additional research directions include finding new ways of capturing a new pedagogical approach to mobile learning and blended learning. Also, a promising direction could be the use of SFL Appraisal theory (Martin, 2000) for the investigation on how students construct interpersonal relationships (appraise peer work) in online joint projects. In the conclusion, it is contended that through its exploration of new ground in the use of SFL and pattern language theory in the construction of education design patterns, the study makes a significant contribution to knowledge in the field of networked learning