<p dir="ltr">Phenylalanine (Phe) is an essential amino acid that has uses in the feed, food and pharmaceutical industries. There is a large and growing market for Phe as a precursor to the production of artificial sweetener. Industrially, Phe is produced by feeding glucose to genetically modified strains of heterotrophic organisms such as <i>E. coli </i>or Corynebacterium in a stainless-steel fermenter. Cyanobacteria are photosynthetic microalgae which could replace heterotrophic production thereby reducing land use for crops required for glucose production. SYN-PHE, a strain of <i>Synechococcus</i> elongatus sp. PCC 11801 which was previously developed in the Morgan lab at Purdue University, produces Phe at 1 g/L in 3 days in shake flask cultures. In this thesis, a techno-economic analysis of Phe production by <i>E. coli </i>and SYN-PHE were compared. Results indicate that Phe produced by SYN-PHE is a promising competitor of <i>E. coli </i>produced Phe at an industrial scale. Further strain engineering to improve the titer of Phe is needed to be economically competitive. Additionally, efforts are needed for low capital cost photobioreactors that can enable both high biomass concentrations and high Phe titers.</p>

<p>Producing bio-based commodity chemicals, such as polymers and fuels, is of significant interest as petroleum reserves continue to decline. A major roadblock to bio-based production is high processing costs. These costs are associated with the need for highly-specialized catalysts to produce bio-based commodity chemicals from agricultural products and wastes. This prevents bioprocessing facilities from fully taking advantage of commodities of scale, where purchasing materials in greater quantities reduces the material cost. Discovering catalysts capable of being used in multiple production pathways could reduce the per unit processing of a biorefinery. <br> Recent works have shown that maleic acid can be used for multiple conversion reactions of plant material to valuable products: xylose to furfural, glucose to hydroxymethylfurfural (HMF), and the pretreatment of lignocellulosic material for second generation biofuel production. This work evaluates the use of maleic acid as a catalyst for producing HMF from corn starch, with a specific focus on reducing operating costs. Additionally, the use of maleic acid as a liquefaction catalyst for producing corn stover slurries is tested. </p> <p>To evaluate HMF production from starch, a combined computational and experimental approach is used. Through modelling and experimental validation, molar HMF yields of ~30% are reached by incorporating dilute dimethylsulfoxide and acetonitrile into the reaction mixture. However, HMF yield was limited by low stability in the reaction media. The addition of activated carbon to the reactor overcomes challenges with second order side reactions, resulting in HMF selling prices that are competitive with similar petroleum-derived chemicals. The key technical roadblocks to commercialization of HMF production are identified as solvent recycling and HMF separation efficiency in a sensitivity analysis. During liquefaction of corn stover, maleic acid was found to reduce the yield stress required to begin slurry flow through a pipe. However, a reduction in the free water content of the reactor through binding of water in the matrix of biomass limited liquefaction, resulting in solids concentrations not financially feasible at scale. To overcome this, maleic acid treatment was performed at solids contents of 25%, followed by a water removal step and enzymatic liquefaction at 30% solids. Yield stress was reduced from >6000 Pa for untreated samples to ~50 Pa for samples treated with maleic acid and enzymes sequentially. Such treatment reduces the challenges associated with feeding solid biomass into a pretreatment reactor. Additionally, reduced slurry yield stress results in lower capital costs, since smaller pumps can be used in the production facility. </p> This work provides a step forward in transitioning away from a petroleum-based economy to a bio-based economy without significant disruptions in product pricing and availability.

<p>Research in pre-college engineering education has been on a sharp rise in the last two decades. However, less research has been conducted to explore and characterize the engineering thinking and engagement of young children, with limited attention to children with special needs. Conversations on broadening participation and diversity in engineering usually center around gender, socio-economic status, race and ethnicity, and to a lesser extent on neurodiversity. Autism is the fastest growing neurodiverse population who have the potential to succeed in engineering. In order to promote the inclusion of children with autism in engineering education, we need to gain a deep understanding of their engineering experiences. </p> <p> </p> <p>The overarching research question that I intend to answer is <i>how do children with mild autism engage in engineering design tasks</i>? Grounding this study in theories of Constructivism and Defectology, I focused on children’s engagement in engineering design practices and the ways their parents supported their engagements. To engage children with mild autism in engineering, I have developed an engineering design activity by considering suggestions from these theories and previous literature on elementary-aged children’s engagement in engineering design, and by focusing on individuals with mild autism strengths in STEM. This activity provides opportunities for children to interact with their parents while solving engineering design problems. The families are asked to use a construction kit and design their solutions to the problem introduced in the engineering design activity. The engineering design activity consists of a series of five challenges, ranging from well- to ill-structed.</p> <p> </p> <p>This is an exploratory qualitative case study, using a multiple case approach. These cases include 9-year-old children with autism and their families. Video recordings of the families are the main source of data for this study. Triangulation of data happens through interviewing parents and children, pictures of children’s artifacts (i.e. their prototypes), and use of the Empathizing-Systemizing survey to capture background information and autism characteristics. Depending on the data source, I utilized different methods including video analysis, thematic analysis and artifact analysis. </p> <p>This study expands our understanding of what engineering design can look like when enacted by children with mild autism, particularly as engineering design is considered to be a very iterative process with multiple phases and actions associated with it. The findings of this study show that these children can engage in all engineering design phases in a very iterative process. Similarities and differences between these children’s design behaviors and the existing literature were discussed. Additionally, some of the behaviors these children engaged in resemble the practices of experienced designers and engineers. The findings of this study suggest that while children were not socially interacting with their family members when addressing the challenges, their parents played an important role in their design engagement. Parents used different strategies during the activity that supported and facilitated children’s engineering design problem-solving. These strategies include soliciting information, providing guidance, assisting both verbally and hands-on, disengagement and being a student of the child. </p> <p> </p> This study provides aspirations for future research with the aim to promote the inclusion of children with neurodiversity. It calls for conducting similar research in different settings to capture the engineering design engagement of children with mild autism when interacting with teachers, peers, siblings in different environments. Additionally, the findings of this study have implications for educators and curators of engineering learning resources.

Thesis (MScEng)-- Stellenbosch University, 2013. / ENGLISH ABSTRACT: A wide variety of design methodologies exist in literature and the methodologies employed may differ among companies and even among design teams. Therefore a software tool, called DiDeas II, is being developed for the early phases of mechanical engineering design. DiDeas II is customisable to accommodate various design methodologies. An approach for customisability which allows the user interface and data structure to be customised without changing the source code has been implemented in previous developments via an approach combining ontology and conceptual graphs. This approach is expanded in this thesis to allow for the implementation of various design methodologies through the use of tables for the display of information with inheritance of data among these tables. During groupwork, communication is both asynchronous and synchronous. DiDeas II has been developed in this thesis to facilitate and capture both asynchronous and synchronous communication between team members. Capturing such communications has the potential to provide insight into design decisions. The communication functionality was assessed in case studies in an academic environment. DiDeas II proved to be effective at recording “soft” information during design and placing the information into context for future reference. The degree to which DiDeas II could be customised to suit the design process at different companies was assessed through discussions with engineers in industry. These discussions showed that it was possible to customise DiDeas II according to the design processes followed by the participants. / AFRIKAANSE OPSOMMING: „n Wye verskeidenheid ontwerpsmetodologieë bestaan in die literatuur en die metodologieë wat gebruik word kan tussen maatskappye en selfs tussen ontwerpspanne verskil. Daarom word „n sagteware-hulpmiddel, genaamd DiDeas II, ontwikkel vir die vroeë fases van meganiese ingenieursontwerp. DiDeas II is pasbaar om voorsiening te maak vir verskeie ontwerpsmetodologieë. „n Benadering vir pasbaarheid wat toelaat dat die gebruikerskoppelvlak en datastruktuur aangepas kan word sonder om veranderings aan die bron-kode te maak, is geïmplementeer in vorige ontwikkelings deur „n benadering wat ontologie en konseptuele grafieke kombineer. Hierdie benadering is in hierdie tesis uitgebrei om voorsiening te maak vir die implementering van verskeie ontwerpsmetodologieë d.m.v. tabelle vir die vertoon van informasie, met data wat “oorgeërf” word tussen hierdie tabelle. Kommunikasie is beide asinkroon en sinkroon tydens groepwerk. DiDeas II is in hierdie tesis verder ontwikkel om beide asinkrone en sinkrone kommunikasie metodes te bemiddel en daarvan rekord te hou. Die rekordhouding van sulke kommunikasie het die potensiaal om insig te bied aangaande ontwerpbesluite. Die kommunikasie funksionaliteit is geassesseer in gevallestudies in „n akademiese omgewing. DiDeas II was effektief in die rekordhouding van “sagte” informasie tydens ontwerp, sowel as om sulke informasie binne konteks te plaas vir latere verwysing. Die mate waartoe DiDeas II aangepas kan word om voorsiening te maak vir die ontwerpsprosesse van verskillende maatskappye, is geassesseer deur gesprekke met ingenieurs in industrie. Hierdie gesprekke het getoon dat dit moontlik is om DiDeas II aan te pas volgens die ontwerpsprosesse wat die deelnemers gebruik.

<div>In the United States, there has been an increased emphasis on science, technology, engineering, and mathematics (STEM), and especially engineering, in pre-college settings. There are several potential benefits of this, including: increasing the quantity and diversity of students who pursue STEM careers, improving all students’ technological literacy, and improving student learning in the STEM disciplines. While current standards support the integration of the four STEM disciplines in pre-college classrooms, research still needs to be done to determine which models of STEM integration are effective and how and why they impact student learning. The context of this study is a model of STEM integration called engineering design-based STEM integration. The purpose of this study was to do an in-depth exploration of students’ use of science conceptions during an engineering design-based STEM integration unit, with additional focus on how engineering design, redesign, teamwork, and communication influence students’ use of science conceptions. For this study, the unit was designed to address middle school-level physical science concepts related to heat transfer, including temperature, thermal energy, and processes of heat transfer (i.e., conduction, convection, and radiation).</div><div><br></div><div>An embedded case study design was used to explore students’ science conceptions while they participated in an engineering design STEM integration unit. The case was one student team from a seventh-grade science class, and the students within the team were the embedded sub-units. Data were collected on each day of the unit’s implementation; these data included video of the student team and entire classroom, audio of the student team, observations and field notes, and student artifacts, including their engineering notebooks. Data were analyzed primarily using methods from qualitative content analysis. Themes emerged for the whole team, with emphasis on specific students when appropriate.</div><div><br></div><div>The results show that there were a few key features of engineering (i.e., engineering design, redesign, teamwork, and communication) that influenced students’ use of heat transfer conceptions. During much of the problem scoping stage, which included the science lessons focused on heat transfer, students mostly used scientific conceptions about conduction, convection, and radiation. However, when they needed to think about those three processes of heat transfer together, as well as apply them to the context of the engineering design challenge, the students began to use a larger mix of scientific conceptions and alternative conceptions. Several alternative conceptions emerged when they combined ideas and vocabulary from conduction and radiation to create one set of rules about thermal properties of materials (i.e., did not distinguish between conduction and radiation). Even when they used scientific conceptions, the students sometimes applied the conceptions unscientifically when designing, which led them to create a prototype that performed poorly. However, the student team then learned from the failures of their first design and redesigned, during which they appropriately used mostly scientific conceptions. In other words, the opportunity to learn from failure and redesign was critical to this team’s use of correct conceptions about heat transfer. Two other features of engineering that emerged were teamwork and communication through notebooks. Students on the team learned from each other, but they learned both scientific and alternative conceptions from each other and from their peers on other teams. Engineering notebooks proved to be somewhat helpful to students, since they referred to them a few times when designing, but more importantly they were helpful in revealing students’ conceptions, especially for one student on the team who rarely spoke.</div><div><br></div><div>The findings of this study contribute to future development and implementation of other engineering design-based STEM integration curricula because they show how various features of engineering influenced this student team’s use of science conceptions. In particular, the results demonstrate the importance of giving students the opportunity to learn from failure and redesign, since this process can help students use more scientific conceptions and potentially repair their alternative conceptions. Additionally, it is important for curriculum developers and teachers to think carefully about the transition from problem scoping to solution generation and how to include effective scaffolds for students to help them combine their conceptions from science lessons and apply them correctly when designing. These results also have implications related to heat transfer conceptions, as the student team in this study demonstrated some scientific and alternative conceptions that were already in the literature. Additionally, they used alternative conceptions when they confused concepts from conduction and radiation, which are not in literature about pre-college heat transfer conceptions. These findings suggest that more research should be done to explore the interaction of engineering design and students’ science conceptions, especially heat transfer conceptions.</div>

This work proposes a framework of concept generation and evaluation that takes into consideration the benefit of creativity and innovation in current market trends. By educating engineers in how to increase creativity in concept design and assess it quantitatively, the next generation of designers will be a step ahead of the market. This research begins with an in-depth survey of current creativity assessment methods in engineering in order to determine where the limitations currently lie in this field of study. The limitations discovered based on this unique analysis were used as motivation for the development of the proposed creativity assessment method. Specifically, we introduce a set of metrics that break down concepts to their component and subfunction level to assess the novelty and quality of component solutions ��� called the Comparative Creativity Assessment (CCA) Method. Secondly, we break down market-tested innovative products to isolate innovation information to utilize in concept generation inspiration ��� called the Repository of Innovative Products (RIP). Finally, revisions to the initial CCA method and RIP are proposed and analysis of past data results are compared to the new revised results. Revisions to the CCA method include additional metrics that factor in interaction effects from function pairing and component assemblies deemed innovative as well as eliminate evaluator subjectivity in the analysis. Observations from the experiments conducted are presented in a Lessons Learned chapter. / Graduation date: 2013

In the modem automotive industry product times to market are being increasingly compressed. In the earthmoving and construction machine industry this is also true with the manufacturer having to respond to new customer requirements quickly and decisively. Virtual prototyping is a vital tool in the vehicle engineer's armoury, allowing a large portion of developmental investigation to be done on the virtual model with the attendant savings in time and cost and allowing often dangerous manoeuvres to be predicted and investigated prior to actual physical prototype testing. The University of Natal BELL Equipment collaborative effort involves the vehicle dynamics modelling and model validation of a BELL Equipment manufactured B40C Articulated Dump Truck (ADT). The modelling was completed using the multibody system (MBS) simulation software package, ADAMS. Initial modelling and simulation results are presented with specific attention paid to the introduction of valid data for compliant joints in the MBS as well as modelling of the tire. The physical testing of the ADT is also presented as well as a discussion of the data acquisition system. Key results from the physical testing of the ADT are also presented and discussed. / Thesis (M.Sc.Eng.)-University of Natal,Durban, 2003.

Computational models and simulations are essential system design tools that allow for improved decision making and cost reductions during all phases of the design process. However, the most accurate models are often computationally expensive and can therefore only be used sporadically. Consequently, designers are often forced to choose between exploring many design alternatives with less accurate, inexpensive models and evaluating fewer alternatives with the most accurate models. To achieve both broad exploration of the alternatives and accurate determination of the best alternative with reasonable costs incurred, surrogate modeling and variable accuracy modeling are used widely. A surrogate model is a mathematically tractable approximation of a more expensive model based on a limited sampling of that model, while variable accuracy modeling involves a collection of different models of the same system with different accuracies and computational costs. As compared to using only very accurate and expensive models, designers can determine the best solutions more efficiently using surrogate and variable accuracy models because obviously poor solutions can be eliminated inexpensively using only the less expensive, less accurate models. The most accurate models are then reserved for discerning the best solution from the set of good solutions. In this thesis, a Value-Based Global Optimization (VGO) algorithm is introduced. The algorithm uses kriging-like surrogate models and a sequential sampling strategy based on Value of Information (VoI) to optimize an objective characterized by multiple analysis models with different accuracies. It builds on two primary research contributions. The first is a novel surrogate modeling method that accommodates data from any number of analysis models with different accuracies and costs. The second contribution is the use of Value of Information (VoI) as a new metric for guiding the sequential sampling process for global optimization. In this manner, the cost of further analysis is explicitly taken into account during the optimization process. Results characterizing the algorithm show that VGO outperforms Efficient Global Optimization (EGO), a similar global optimization algorithm that is considered to be the current state of the art. It is shown that when cost is taken into account in the final utility, VGO achieves a higher utility than EGO with statistical significance. In further experiments, it is shown that VGO can be successfully applied to higher dimensional problems as well as practical engineering design examples.

In design and optimization of a complex system, there exist various methods for defining the relationship between the system as a whole, the subsystems and the individual components. Traditional methods provide requirements at the system level which lead to a set of design targets for each subsystem. Meeting these targets is sometimes a simple task or can be very difficult and expensive, but this is not captured in the design process and therefore unknown at the system level. This work compares Requirements Allocation (RA) with Distributed Value Driven Design (DVDD). A computational experiment is proposed as a means of evaluating RA and DVDD. A common preliminary design is determined by optimizing the utility of the system, and then a Subsystem of Interest (SOI) is chosen as the focal point of subsystem design. First the behavior of a designer using Requirements Allocation is modeled with an optimization problem where the distance to the design targets is minimized. Next, two formulations of DVDD objective functions are used to approximate the system-level value function. The first is a linear approximation and the second is a nonlinear approximation with higher fidelity around the preliminary design point. This computational experiment is applied to a series hybrid vehicle where the SOI is the electric motor. In this case study, RA proves to be more effective than DVDD on average. It is still possible that the use of objectives is superior to design targets. This work shows that, for this case study, a linear approximation as well as a slightly higher fidelity approximation are not well suited to find the design alternative with the highest expected utility.

The world of engineering design finds itself at a crossroads. The technical and scientifically rooted tools that propelled humankind into the modern age are now insufficient as evidenced by a growing number of failures to meet design expectations and to deliver value for users and society in general. In the empirical world, a growing consensus among many design practitioners has emerged that engineering design efforts are becoming too unmanageable and too complex for existing design management systems and tools. One of the key difficulties of engineering design is the coordination and management of the underlying collaboration processes. Development efforts that focus on the design of complex artefacts, such as a satellite or information system, commonly require the interaction of hundreds to thousands of different disciplines. What makes these efforts and the related collaboration processes complex from the perspective of many practitioners is the strong degree of interdependency between design decision-making occurring, often concurrently, across multiple designers who commonly reside in different organizational settings. Not only must a design account for and satisfice these dependencies, but it must remain also acceptable to all design participants. Design in effect represents a coevolution between the problem definition and solution, with a finalized design approach arising not from a repeatable series of mathematical optimizations but rather through the collective socio-technical design activities of a large collaboration of designers. Despite the importance of understanding design as a socio-technical decision-making entity, many of the existing design approaches ignore socio-technical issues and often view them as either too imprecise or too difficult to consider. This research provides a performance measurement framework to explore these factors by investigating design as a socio-technical complex adaptive collaborative process between the designer, artefact, and user (DAU). The research implements this framework through an agent-based model, the Complex Adaptive Performance Evaluation Method for Collaboration Design (C2D). This approach allows a design management analyst to generate insights about potential design strategies and mechanisms as they relate to design complexity by examining the simulated performance of a design collaboration as it explores theoretical design fitness landscapes with various degrees of ruggedness. / Ph. D.