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Research Papers: Design Theory and Methodology

J. Mech. Des. 2018;140(12):121101-121101-9. doi:10.1115/1.4039494.

Parameter estimates in large-scale complex engineered systems (LaCES) affect system evolution, yet can be difficult and expensive to test. Systems engineering uses analytical methods to reduce uncertainty, but a growing body of work from other disciplines indicates that cognitive heuristics also affect decision-making. Results from interviews with expert aerospace practitioners suggest that engineers bias estimation strategies. Practitioners reaffirmed known system features and posited that engineers may bias estimation methods as a negotiation and resource conservation strategy. Specifically, participants reported that some systems engineers “game the system” by biasing requirements to counteract subsystem estimation biases. An agent-based model (ABM) simulation which recreates these characteristics is presented. Model results suggest that system-level estimate accuracy and uncertainty depend on subsystem behavior and are not significantly affected by systems engineers' “gaming” strategy.

Commentary by Dr. Valentin Fuster

Research Papers: Design Automation

J. Mech. Des. 2018;140(12):121401-121401-8. doi:10.1115/1.4041171.

The complexity of design for development (D4D), humanitarian engineering (HE), and similar projects emerges from multiple sources, including the overarching requirement to address complex sociotechnical problems by effectively engaging community members. However, missing from the literature on enacting D4D/HE projects is a clear framework that classifies extant community participation methods based on key characteristics, especially vis-à-vis level of community participation in problem definition and solution processes. To address this lack of a classification framework, we first conducted a systematized literature search to identify methods used in D4D/HE projects. This literature search resulted in 64 identified methods. Following an iterative, inductive, and systematic process to develop classification systems combined with content analysis, a bidimensional framework emerged to classify the methods. The first dimension of the framework organizes methods according to a spectrum of three levels of community engagement: (1) passive, (2) consultative, and (3) coconstructive. The second dimension classifies methods based on the part of the design process in which it is most appropriate to use them. We conclude the paper by discussing considerations engineers should reflect upon when using the framework to inform their projects, as well as opportunities for future research.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2018;140(12):121402-121402-8. doi:10.1115/1.4041172.

Reliability-based design optimization (RBDO) algorithms typically assume a designer's prior knowledge of the objective function along with its explicit mathematical formula and the probability distributions of random design variables. These assumptions may not be valid in many industrial cases where there is limited information on variable variability and the objective function is subjective without mathematical formula. A new methodology is developed in this research to model and solve problems with qualitative objective functions and limited information about random variables. Causal graphs and design structure matrix are used to capture designer's qualitative knowledge of the effects of design variables on the objective. Maximum entropy theory and Monte Carlo simulation are used to model random variables' variability and derive reliability constraint functions. A new optimization problem based on a meta-objective function and transformed deterministic constraints is formulated, which leads close to the optimum of the original mathematical RBDO problem. The developed algorithm is tested and validated with the Golinski speed reducer design case. The results show that the algorithm finds a near-optimal reliable design with less initial information and less computation effort as compared to other RBDO algorithms that assume full knowledge of the problem.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2018;140(12):121403-121403-12. doi:10.1115/1.4040913.

In the buying decision process, online reviews become an important source of information. They become the basis of evaluating alternatives before making purchase decision. This paper proposes a methodology to reveal one of the hidden alternative evaluation processes by identifying the relation between the observable online customer reviews and sales rank. This methodology applies a combined approach of word embedding (word2vec) and X-means clustering, which produces product-feature words. It is followed by identifying sentiment words and their intensity, determining connection of words from dependency tree, and finally relating variables from the reviews to the sales rank of a product by a regression model. The methodology is applied to two data sets of wearable technology and laptop products. As implied by the high predicted R-squared values, the models are generalizable into new data sets. Among the interesting findings are the statements of problems or issues of a product are related to better sales rank, and many product features that are mentioned in the review title are significantly related to sales rank. For product designers, the significant variables in the regression models suggest the possible product features to be improved.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2018;140(12):121404-121404-10. doi:10.1115/1.4040487.

A technique based on a skeleton-section template for parameterizing finite element (FE) models is reported and applied to shape optimization of thin-walled beam components. The template consists of a skeletal curve and a set of cross-sectional profiles. The skeletal curve can be used to derive global model variations, while the cross section is designed to obtain local deformations of the given shape. A mesh deformation method based on the radial basis functions (RBF) interpolation is employed to derive the shape variations. Specifically, the skeleton-embedding space and an anisotropic distance metric are introduced to improve the RBF deformation method. To validate the applicability of the proposed template-based parameterization technique to general shape optimization frameworks, two proof-of-concept numerical studies pertaining to crashworthiness design of an S-shaped frame were implemented. The first case study focused on global deformations with the skeletal curve, and the second treated the cross-sectional profiles as design parameters to derive local reinforcements on the model. Both studies showed the efficiency of the proposed method in generation of quality shape variants for optimization. From the numerical results, considerable amount of improvements in crashworthiness performances of the S-shaped frame were observed as measured by the peak crushing force (PCF) and the energy absorption. We conclude that the proposed template-based parameterization technique is suitable for shape optimization tasks.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2018;140(12):121405-121405-14. doi:10.1115/1.4040985.

To reduce the computational cost, surrogate models have been widely used to replace expensive simulations in design under uncertainty. However, most existing methods may introduce significant errors when the training data is limited. This paper presents a confidence-driven design optimization (CDDO) framework to manage surrogate model uncertainty for probabilistic design optimization. In this study, a confidence-based Gaussian process (GP) modeling technique is developed to handle the surrogate model uncertainty in system performance predictions by taking both the prediction mean and variance into account. With a target confidence level, the confidence-based GP models are used to reduce the probability of underestimating the probability of failure in reliability assessment. In addition, a new sensitivity analysis method is proposed to approximate the sensitivity of the reliability at the target confidence level with respect to design variables, and thus facilitate the CDDO framework. Three case studies are introduced to demonstrate the effectiveness of the proposed approach.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2018;140(12):121406-121406-12. doi:10.1115/1.4040883.

Due to the nested optimization loop structure and time-demanding computation of structural response, the computational accuracy and cost of reliability-based design optimization (RBDO) have become a challenging issue in engineering application. Kriging-model-based approach is an effective tool to improve the computational efficiency in the practical RBDO problems; however, a larger number of sample points are required for meeting high computational accuracy requirements in traditional methods. In this paper, an adaptive directional boundary sampling (ADBS) method is developed in order to greatly reduce the computational sample points with a reasonable accuracy, in which the sample points are added along the ideal descending direction of objective function. Furthermore, only sample points located near the constraint boundary are mainly selected in the vicinity of the optimum point according to the strategy of multi-objective optimization; thus, substantial number of sample points located in the failure region is neglected, resulting in the improved performance of computational efficiency. Four numerical examples and one engineering application are provided for demonstrating the efficiency and accuracy of the proposed sampling method.

Commentary by Dr. Valentin Fuster

Research Papers: Design Education

J. Mech. Des. 2018;140(12):122001-122001-9. doi:10.1115/1.4040880.

Engineering design has been a requirement in the curriculum for engineering accreditation since the mid-90 s. This emphasis on engineering design has introduced significant changes to engineering curricula in freshmen and senior years with many engineering programs offering capstone (senior) and/or cornerstone (freshmen) design courses. Yet design-related content and experiences in the second and third years of the engineering curricula remain less common due to the heavy emphasis on fundamental engineering science courses in the middle years. This study investigated the possibility of developing design ability (thinking, process, and skills) in one of these courses. The method used was to incorporate real world, open-ended problem solving, specifically authentic engineering problem centered learning (AEPCL), into a junior-level heat transfer course. AEPCL uses authentic engineering problems (AEPs) as the backdrop to develop students' design abilities through solving open-ended, ill-structured problems. Results indicate that students who experienced AEPCL showed better design abilities than comparable students who did not experience AEPCL. Through AEPCL, students learn how to collect better information, make more reasonable assumptions, engage in better processes, and arrive at a more plausible, error-free, and high-quality solution in engineering design.

Commentary by Dr. Valentin Fuster

Research Papers: Design of Direct Contact Systems

J. Mech. Des. 2018;140(12):123301-123301-12. doi:10.1115/1.4041053.

Land widths and relief angles of a dual-cone double-enveloping hourglass worm gear hob are important factors that influence the life and the hobbing performance of the hob. Both of them are obtained by generating relief surfaces of the hob. Due to the reason that all teeth of this type of hob have different profiles with each other, all of the relief surfaces are difficult to generate for keeping all cutting teeth with uniformed relief angles and uniformed land widths. For the purpose that land widths and relief angles could be machined precisely, this paper puts forward a designing and generating method for grinding the relief surfaces. The relief surfaces are ground using the same double-cone grinding wheel as grinding the helical surfaces of the worm. Based on the theory of gearing, the mathematical model for grinding relief surfaces is built. Motion parameters when grinding the different points of the land edges on different teeth of the hob are solved. A generating simulation is built by putting those motion parameters into a four-axis hourglass worm-grinding machine. The results of the simulation show that the relief surfaces can be ground continuously and the land widths and the relief angles meet the requirements.

Commentary by Dr. Valentin Fuster

Design Innovation Paper

J. Mech. Des. 2018;140(12):125001-125001-10. doi:10.1115/1.4037621.

This paper presents a new bistable collapsible compliant mechanism (BCCM) that is utilized in a lamina-emergent frustum. The mechanism is based on transforming a polygon spiral into spatial frustum shape using a mechanism composed of compliant links and joints that exhibits a bistable behavior. A number of mechanism types (graphs) were considered to implement the shape-morphing spiral, including 4-bar, 6-bar, and 8-bar chains. Our design requirements permitted the selection of a particular 8-bar chain as the basis for the BCCM. The bistable behavior was added to the mechanism by introducing a snap-through bistability as the mechanism morphs. A parametric CAD was used to perform the dimensional synthesis. The design was successfully prototyped. We anticipate that the mechanism may be useful in commercial small animal enclosures or as a frame for a solar still.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2018;140(12):125002-125002-6. doi:10.1115/1.4041175.

This paper presents the embodiment design of an interchangeable print head based on twin-screw extrusion, specially developed to allow in-process multimaterial mixing and direct deposition of the product to structure three-dimensional (3D) parts. The print head focus on research applications with middle-end 3D printers. Commercial extrusion-based 3D printers have limited applicability due to the scarce variety of plastic filaments available. In that context, one important trend for the advance of additive manufacturing (AM) is the design of systems capable of using alternative material types in different states. The systematic process is presented as a case study and brings together concepts from mechanical design and polymer processing. The main contribution of this paper is to provide general guidelines to be used on similar projects, in view of the crescent demand for more adequate and flexible additive processes.

Commentary by Dr. Valentin Fuster

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