Bryony DuPont

A Method for Understanding Sustainable Design Trade-Offs During the Early Design Phase

The purpose of this research is to present a new method for integrating sustainable design knowledge into the early design phase of new products and processes. A novel organized search tree is constructed to enable the application of sustainable design knowledge before and during concept generation. To further facilitate its application, this search tree is embedded in an easy-to-use web-based application called the GREEn Quiz (Guidelines and Regulations for Early design for the Environment). As a designer progresses through the quiz, user responses are compiled and weighted, and a final environmental impact report is provided to the user. Two research studies are explored to validate the proposed method. The results of these studies show that the search-tree format and presentation of the collection of design knowledge presented in this work provide design engineers with a valuable and informative resource for facilitating the design of products with reduced environmental impacts.

Wave Energy Converter Array Optimization: A Review of Current Work and Preliminary Results of a Genetic Algorithm Approach Introducing Cost Factors

Currently, ocean wave energy is a novel means of electricity generation that is projected to potentially serve as a primary energy source in coastal areas. However, for wave energy converters (WECs) to be applicable on a scale that allows for grid implementation, these devices will need to be placed in close relative proximity to each other. From what’s been learned in the wind industry of the U.S., the placement of these devices will require optimization considering both cost and power. However, current research regarding optimized WEC layouts only considers the power produced. This work explores the development of a genetic algorithm (GA) that will create optimized WEC layouts where the objective function considers both the economics involved in the array’s development as well as the power generated. The WEC optimization algorithm enables the user to either constrain the number of WECs to be included in the array, or allow the algorithm to define this number. To calculate the objective function, potential arrays are evaluated using cost information from Sandia National Labs Reference Model Project, and power development is calculated such that WEC interaction affects are considered. Results are presented for multiple test scenarios and are compared to previous literature, and the implications of a priori system optimization for offshore renewables are discussed.Copyright

Exploring the Retention of Sustainable Design Principles in Engineering Practice Through Design Education

The School of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University is home to one of the largest academic Mechanical Design groups in the country. As a leader in undergraduate design education, we have been able to keep in touch with a large group of mechanical design graduates, and as such are capable of assessing how students retain information learned in undergraduate coursework to see how this understanding is employed in real-world engineering practice. However, the principles governing the design of sustainable products and processes are relatively novel and are only now being integrated into the undergraduate and graduate mechanical design curriculum. It is our hypothesis that particular means of learning and understanding sustainable design — via lectures, homework assignments, design projects, and the use of various sustainability-related LCA tools — will enable the highest retention of sustainable design understanding, and a higher likelihood that this sustainable design knowledge will be propagated into design practice in industry. Multiple curricular studies that explore dissemination and retention of sustainable design skills are being explored, including a junior-level introductory mechanical design course and a graduate level sustainable product development course. In the junior-level course, baseline sustainability knowledge is tested by allowing students to make sustainable design decisions by applying varied skill sets, including general principles, a list of sustainable design guidelines, and an innovative online survey (The GREEn Quiz). The graduate-level course, which employs sustainable design principles within a larger product development architecture, will capitalize on more “expert” knowledge. Future work will also be discussed, including planned validation studies and curriculum improvements, as well as the means of quantifying the retention of sustainable design information.Copyright

New perspectives on design automation: Celebrating the 40th anniversary of the ASME Design Automation Conference

The ASME Design Automation Conference and Committee (DAC) were initiated more than 40 years ago by a group of engineering visionaries to mark the dawn of the computer era in engineering design. Along the way, a strong and diverse community of academic, industrial, and government researchers have made the DAC community what it is today: a vibrant and energetic research community and a place to share the thoughts and ideas that fuel a common passion for engineering design automation (DA). To celebrate the legacy of the DAC and to spark common visions of the DAC’s future, the Design Automation Committee organized a 40th anniversary symposium at the 2014 ASME International Design Engineering Technical Conferences (IDETC). A capacity crowd of hundreds of DA researchers attended the program, which was organized into three segments. First, Kenneth Ragsdell, one of the founding members of the DAC, spoke of the founding of the conference and committee. He was followed by Panos Papalambros and Farrokh Mistree, who described the impact of 40 years of DA research and education along with some thoughts on the future of the DAC. The program ended with a series of six lightning talks from early career members of the DAC community offering their vision of emerging research opportunities in DA.

Employing Wind Farm Performance Data for Model Validation and Turbine Layout/Geometry Optimization

he increase in demand for electricity in the United States motivates a unique opportunity for researching alternative energy sources – the need for electricity is mounting, while traditional sources for electrical generation, such as coal, are depleting and becoming more costly to access. Exploring alternative energy sources, such as wind power, are therefore ideal, as wind is readily available and will not deplete with use. However, the optimization of wind farms is imperative to ensure that wind farm power development is as high as possible, and that prediction of wind farm performance prior to installation is accurate. To meet this goal, the modeling that is being employed within wind farm optimization schemes must be reflective of real-world wind farm conditions, using site-specific parameters to ensure that researchers can accurately predict the potential power development and costs for resulting wind farm designs.

DECISION MAKING FOR THE COLLABORATIVE ENERGY SUPPLY SYSTEM OF OREGON AND WASHINGTON

As demand for electricity in the United States continues to increase, it is necessary to explore the means through which the modern power supply system can accommodate both increasing affluence (which is accompanied by increased per-capita consumption) and the continually growing global population. Though there has been a great deal of research into the theoretical optimization of large-scale power systems, research into the use of an existing power system as a foundation for this growth has yet to be fully explored. Current successful and robust power generation systems that have significant renewable energy penetration — despite not having been optimized a priori — can be used to inform the advancement of modern power systems to accommodate the increasing demand for electricity. Leveraging ongoing research projects at Oregon State University and the National Energy Technology Laboratory, this work explores how an accurate and state-of-the-art computational model of the Oregon/Washington (OR/WA) energy system can be employed as part of an overarching power systems optimization scheme that looks to inform the decision making process for next generation power supply systems. Research scenarios that explore an introductory multi-objective power flow analysis for the OR/WA grid will be shown, along with a discussion of future research directions.Copyright