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We have recently developed and tested a new computational method for experiment prototyping at the Advanced Test Reactor (ATR). The method significantly reduces neutronic computation time while maintaining computational accuracy. In this thesis, we present the method and describe the techniques that we used to implement it. We then qualitatively and quantitatively analyze its performance for absorptive and multiplicative experiment perturbations over a single region and across multiple regions of the ATR. We conclude with a discussion of future research that might be conducted on the method.
This book delivers a methodological approach on the experimentation and/or simulation processes from the disclaiming hypothesis on a physical phenomenon to the validation of the results. The main benefit of the book is that it discusses all the topics related to experimentation and validation of the outcome including state-of-the-art applications and presents important theoretical, mathematical and experimental developments, providing a self-contained major reference that is appealing to both the scientists and the engineers. At the same time, these topics are encountered in a variety of scientific and engineering disciplines. As a first step, it presents the theoretical and practical implications on the formation of a hypothesis, considering the existing knowledge collection, classification and validation of the particular areas of experimenting interest. Afterwards, the transition from the knowledge classes to the experimentation parameters according to the phenomena evolution contributors and the systemic properties of the descriptors are discussed. The major experimenting requirements focus on the conditions to satisfy a potential disclaim of the initial hypothesis as conditions. Furthermore, the experimentation outcome, as derived via the previous experimentation process set-up, would be validate for the similarities among the existing knowledge and derived new one. The whole methodology offers a powerful tool towards the minimization of research effort wastes, as far as it can identify the lacks of knowledge, thus the areas of interest where the current research has to work on. The special features of this book are (a) the use of state-of-the-art techniques for the classification of knowledge, (b) the consideration of a realistic systemic world of engineering approached phenomena, (c) the application of advanced mathematical techniques for identifying, describing and testing the similarities in the research results and conclusions, and (d) the experimental investigation of relevant phenomena.
This book presents a comprehensive set of techniques that enhance all key aspects of a modern Virtual Prototype (VP)-based design flow. The authors emphasize automated formal verification methods, as well as advanced coverage-guided analysis and testing techniques, tailored for SystemC-based VPs and also the associated Software (SW). Coverage also includes VP modeling techniques that handle functional as well as non-functional aspects and also describes correspondence analyses between the Hardware- and VP-level to utilize information available at different levels of abstraction. All approaches are discussed in detail and are evaluated extensively, using several experiments to demonstrate their effectiveness in enhancing the VP-based design flow. Furthermore, the book puts a particular focus on the modern RISC-V ISA, with several case-studies covering modeling as well as VP and SW verification aspects.
Of the estimated 140 billion US dollars spent in new product development by large companies each year, around 40% is wasted on failed products. The largest sunk cost in new product development occurs during prototyping activities. We know prototyping activities are critical to the design process as they translate often fuzzy ideas into physical artefacts, support communication, enhance design development, and aid in decision-making. Engineering design research has failed to provide designers and engineerspractitioners as well as educatorswith formal methods or approaches for prototyping to help reduce these losses and increase the likelihood of product success. Instead, designers and engineers must rely on experience, tacit knowledge, and individual judgment to navigate prototyping activities, often resulting in the inefficient use of resources and time. An extensive literature review of prototyping research and a study of novice designers perceptions of prototyping are used in this work to develop and validate a set of specifications for a holistic and structured prototyping framework. A novel framework to help structure prototyping, Prototype for X (PFX), is proposed as an alternative to traditional prototyping approaches in engineering design. The PFX framework is composed of three main phases: (1) Frame, (2) Build, and (3) Test. The phases of PFX help designers optimize resources to build prototypes that test core assumptions and inform the design and development new products. Similar to the illities in Design for X, PFX uses lenses to structure and scaffold the prototyping process to make improvements in specific areas. In order to validate the PFX framework, in this work we study the effects of three lenses, namely, Prototype for Desirability, Prototype for Feasibility, and Prototype for Viability. These lenses are based on Human-Centered Design and Design Thinking frameworks for innovation and innovative products. In order to evaluate the effectiveness of PFX at improving technical quality, manufacturability, and user satisfaction of end designs, we assess functional prototypes developed in a junior-level mechanical engineering design course. Results from a between-subjects analysis indicate that using PFX can help increase the desirability, feasibility, and viability of functional prototypes when those lenses are applied; specifically, student teams introduced to PFX produced prototypes that outperformed those from control teams with no formal prototyping methods on user satisfaction, perceived value, and manufacturability metrics. This study confirms the impact that structured prototyping methods like PFX can have on the prototyping process and final designs. In order to understand the effect of structured and holistic prototyping models on designers themselves, we evaluate the impact PFX has on designers prototyping awareness. The prototyping literature has typically evaluated the few prototyping methods, tools, and frameworks using design-based metrics, such as binary evaluations of completion of a design task. Based on a detailed literature review, we hypothesize that structured prototyping methods, specifically PFX, can increase novice designers and engineering students self-efficacy, leading to an increase in feelings of control throughout the prototyping process, which may lead to an increase in creative output, higher levels of motivation, and an increase in the quality of final designs. As an initial step in the measurement of these outcomes, we sought to understand if PFX influences designers prototyping awareness. In order to measure prototyping awareness, a new measurement tool is proposed and validated, the Prototyping AWareness Scale (PAWS). Results from this study partially support the notion that structured prototyping frameworks influence the prototyping awareness of novice engineering designers. Finally, the work concludes with a study exploring the effect that PFX might have on the prototyping process itself. We sought to understand how the order or sequence of PFX lenses might affect the feasibility, viability, and desirability of an end design and the prototyping awareness of engineering designers. The results of our findings indicate that the sequence of PFX lenses has some effect on product outcomes and prototyping awareness. The contributions from this research lie primarily in the field of engineering design, specifically in the area of prototyping during the new product design process. They include: 1) establishment of four specifications for a structured and holistic prototyping framework, 2) development of the Prototype for X framework, 3) creation of alternative metrics to evaluate prototypes, 4) creation of a scale to measure prototyping awareness and 5) validation of the effect of a structured prototyping framework on the many facets of a product. Future work will explore in more detail the full effect of lens sequencing on design and designer outcomes, but this initial work highlights the potential of PFX to be used in new product development to positively influence products and designers. Future work will focus on validating the PFX framework in industry settings and studying the effects of PFX on the designers understanding of prototyping, the decisions made during prototyping, and the artifact produced during prototyping.
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