Research Papers: Design Theory and Methodology

J. Mech. Des. 2017;140(3):031101-031101-13. doi:10.1115/1.4038565.

This study examines how the quantity of ideas and analog transfer in design-by-analogy (DbA) are affected by multiple analogs and extraneous information, or noise, using a between-subjects, factorial experiment. To evaluate the effects of multiple analogs and noise on ideation, the study uses two metrics in conjunction with one another; namely, number of ideas (most typical in engineering design) and recognition of high-level principle (more common in psychology). The quantity analysis included three components: number of ideas generated, number of ideas that use example products (analogs and noise stimuli), and number of ideas that use analogs. The results indicate two important findings: (1) providing multiple analogs during ideation had a positive impact on ideation quantity and analog transfer. Specifically, the number of analog-based ideas increased with increasing number of analogs but eventually reached a “saturation point”; (2) introducing extraneous information (noise) diminished the successful mapping of analogs to design solutions. The presence of extraneous information did not significantly affect student designers' ability to identify high-level principles in analogs. The study demonstrated that some extraneous information was perceived as surface similar analogs. Any design analog retrieval method or automated tool will produce extraneous information, and more work is needed to understand and minimize its impact.

Topics: Noise (Sound) , Design
Commentary by Dr. Valentin Fuster
J. Mech. Des. 2018;140(3):031102-031102-9. doi:10.1115/1.4038264.

Functional fixedness refers to a cognitive bias that prevents people from using objects in new ways and more abstractly from perceiving problems in new ways. Supporting people in overcoming functional fixedness could improve creative problem solving and capacities for creative design. A study was conducted to detect whether a relationship exists between participants' tendency to reorient objects presented as stimuli in an alternative uses test (AUT) and their creativity, also measured using the Wallach Kogan (WaKo) pattern meanings test. The AUT measures creativity as a function of identifying alternative uses for traditional objects. The WaKo pattern meanings test detects the ability to see an abstract pattern as different possible objects or scenes. Also studied is whether Kruglanski's need for closure (NFC) scale, a psychological measure, can predict the ability to incorporate reorientation cues when identifying uses. This study revealed highly significant, high correlations between reorientation and several creativity measures, and a correlation between reorientation and the predictability subscale of the NFC scale. A qualitative exploration of participants' responses reveals further metrics that may be relevant to assessing creativity in the AUT.

Topics: Creativity
Commentary by Dr. Valentin Fuster

Research Papers: Design Automation

J. Mech. Des. 2017;140(3):031401-031401-11. doi:10.1115/1.4038566.

In probabilistic approaches to engineering design, including robust design, mean and variance are commonly used as the optimization objectives. This method, however, has significant limitations. For one, some mean–variance Pareto efficient designs may be stochastically dominated and should not be considered. Stochastic dominance is a mathematically rigorous concept commonly used in risk and decision analysis, based on the cumulative distribution function (CDFs), which establishes that one uncertain prospect is superior to another, while requiring minimal assumptions about the utility function of the outcome. This property makes it applicable to a wide range of engineering problems that ordinarily do not utilize techniques from normative decision analysis. In this work, we present a method to perform optimizations consistent with stochastic dominance: the Mean–Gini method. In macroeconomics, the Gini Index is the de facto metric for economic inequality, but statisticians have also proven a variant of it can be used to establish two conditions that are necessary and sufficient for both first and second-order stochastic dominance . These conditions can be used to reduce the Pareto frontier, eliminating stochastically dominated options. Remarkably, one of the conditions combines both mean and Gini, allowing for both expected outcome and uncertainty to be expressed in a single objective which, when maximized, produces a result that is not stochastically dominated given the Pareto front meets a convexity condition. We also find that, in a multi-objective optimization, the Mean–Gini optimization converges slightly faster than the mean–variance optimization.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2018;140(3):031402-031402-12. doi:10.1115/1.4038209.

This paper proposes an optimum design method for a two-dimensional microchannel heat sink under a laminar flow assumption that simultaneously provides maximal heat exchange and minimal pressure drop, based on a topology optimization method incorporating Pareto front exploration. First, the formulation of governing equations for the coupled thermal-fluid problem and a level set-based topology optimization method are briefly discussed. Next, an optimum design problem for a microchannel heat sink is formulated as a bi-objective optimization problem. An algorithm for Pareto front exploration is then constructed, based on a scheme that adaptively determines weighting coefficients by solving a linear programming problem. Finally, in the numerical example, the proposed method yields a Pareto front approximation and enables the analysis of the trade-off relationship between heat exchange and pressure drop, confirming the utility of the proposed method.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2018;140(3):031403-031403-11. doi:10.1115/1.4038645.

A reliability-based topology optimization (RBTO) approach is presented using a new mean-value second-order saddlepoint approximation (MVSOSA) method to calculate the probability of failure. The topology optimizer uses a discrete adjoint formulation. MVSOSA is based on a second-order Taylor expansion of the limit state function at the mean values of the random variables. The first- and second-order sensitivity derivatives of the limit state cumulant generating function (CGF), with respect to the random variables in MVSOSA, are computed using direct-differentiation of the structural equations. Third-order sensitivity derivatives, including the sensitivities of the saddlepoint, are calculated using the adjoint approach. The accuracy of the proposed MVSOSA reliability method is demonstrated using a nonlinear mathematical example. Comparison with Monte Carlo simulation (MCS) shows that MVSOSA is more accurate than mean-value first-order saddlepoint approximation (MVFOSA) and more accurate than mean-value second-order second-moment (MVSOSM) method. Finally, the proposed RBTO-MVSOSA method for minimizing a compliance-based probability of failure is demonstrated using two two-dimensional beam structures under random loading. The density-based topology optimization based on the solid isotropic material with penalization (SIMP) method is utilized.

Commentary by Dr. Valentin Fuster

Research Papers: Design for Manufacture and the Life Cycle

J. Mech. Des. 2018;140(3):031701-031701-12. doi:10.1115/1.4038686.

This paper presents a method for automated manufacturing process selection during conceptual design. It is helpful to know which manufacturing processes can produce a design at an early stage, when the overall design can be changed for less cost. Early during new product development, geometric dimensions and tolerances may not yet be specified, but a general three-dimensional (3D) model is often under development. In this work, algorithms are presented to interrogate 3D models to calculate machining-based manufacturability metrics. These algorithms are used on a dataset of 86 computer-aided design (CAD) models classified as machined or cast-then-machined. The metrics, such as visibility, reachability, and setup orientations, seek to characterize a part's manufacturability using machining domain knowledge. These metrics serve as inputs to machine learning models, which are used to classify parts by manufacturing process with 86% accuracy. Some of the incorrectly classified parts were instances that had robust designs capable of being manufactured using machining or casting. The results of the machine learning models indicate that the machining metrics can be used to provide process selection feedback during conceptual design.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2018;140(3):031702-031702-12. doi:10.1115/1.4038922.

Part count reduction (PCR) is one of the typical motivations for using additive manufacturing (AM) processes. However, the implications and trade-offs of employing AM for PCR are not well understood. The deficits are mainly reflected in two aspects: (1) lifecycle-effect analysis of PCR is rare and scattered; (2) current PCR rules lack full consideration of AM capabilities and constraints. To fill these gaps, this paper first summarizes the main effect of general PCR (G-PCR) on lifecycle activities to make designers aware of potential benefits and risks and discusses in a point-to-point fashion the new opportunities and challenges presented by AM-enabled PCR (AM-PCR). Second, a new set of design rules and principles are proposed to support potential candidate detection for AM-PCR. Third, a dual-level screening and refinement design framework is presented aiming at finding the optimal combination of AM-PCR candidates. In this framework, the first level down-samples combinatory space based on the proposed new rules while the second one exhausts and refines each feasible solution via design optimization. A case study of a motorcycle steering assembly is considered to demonstrate the effectiveness of the proposed design rules and framework. In the end, possible challenges and limitations of the presented design framework are discussed.

Topics: Manufacturing , Design
Commentary by Dr. Valentin Fuster

Research Papers: Design of Mechanisms and Robotic Systems

J. Mech. Des. 2018;140(3):032301-032301-10. doi:10.1115/1.4039005.

A kinematic model of the planetary roller screw mechanism (PRSM) is proposed, which accounts for the run-out errors of the screw, roller, nut, ring gear, and carrier, and the position errors of the nut and the pinhole in the carrier. The roller floating region, which contains all the possible positions of the roller inside the pinhole, is obtained by analyzing the axial clearances between mating thread surfaces and the radial clearance between the roller and carrier. The proposed model is based on the constraint that the set of roller floating region is not empty. Then, the additional rigid-body movement on the nut is derived and the path of motion transfer from the screw to the nut is obtained. According to the fundamental property of rigid-body kinematics, the axial velocity of the nut is derived and the transmission error of the PRSM is calculated. The proposed model is verified by comparing the calculated transmission error with experimental one. The results show that the transmission error of the PRSM with run-out and position errors is cyclic with a period corresponding to the rotation period of the screw and the magnitude of the transmission error can be much larger than the lead error of the screw. Besides, due to the run-out and position errors, the roller can move radially or transversally inside the pinhole of the carrier when the elements in the PRSM are regarded as rigid bodies.

Commentary by Dr. Valentin Fuster
J. Mech. Des. 2018;140(3):032302-032302-8. doi:10.1115/1.4038924.

Planar motion coordination of an unoriented line passing through a point or tangent to a conic is a well-known problem in kinematics. In Yaglom's algebraic geometry, oriented lines in a plane are represented with dual numbers. In the present paper, such algebraic geometry is applied in the kinematic synthesis of an inverted slider–crank for prescribed three and four finitely separated positions of the coupler. No previous application of Yaglom's algebraic geometry in the area of linkage kinematic synthesis is recorded. To describe the planar finite displacement of an oriented line about a given rotation pole, new dual operators are initially obtained. Then, the loci of moving oriented lines whose three and four homologous planar positions are tangent to a circle are deduced. The paper proposes the application of findings to the mentioned kinematic synthesis of the inverted slider–crank. Numerical examples show the reliability of the proposed approach. Finally, it is also demonstrated that, for a general planar motion, there is not any line whose five finitely separated positions share the same concurrency point. For the case of planar infinitesimal displacements, the same property was established in a paper authored by Soni et al. (1978, “Higher Order, Planar Tangent-Line Envelope Curvature Theory,” ASME J. Mech. Des., 101(4), pp. 563–568.)

Commentary by Dr. Valentin Fuster

Research Papers: Design of Direct Contact Systems

J. Mech. Des. 2017;140(3):033301-033301-9. doi:10.1115/1.4038646.

With the advantages of high torque and low noise, traction drive continuously variable transmissions (TDCVTs) have a promising application in future vehicles. However, their efficiency is limited by spin losses caused by the different speed distributions between the contact areas of the traction. To overcome this shortcoming, this paper proposes a novel zero-spin design methodology applicable to any type of TDCVTs. The methodology analyzes the features of TDCVTs in terms of the variation of contact position and the shifting motion of traction components. It also establishes a mathematical model resulting in differential equations, whose general solution is the substitute for the equation of traction components generatrix. After applications of the methodology to two original TDCVTs, two zero-spin TDCVTs are proposed. A computational method of spin ratios, which are in direct proportion to spin losses, of four TDCVTs is introduced. The results of comparisons demonstrate that the proposed methodology can dramatically reduce the spin losses.

Commentary by Dr. Valentin Fuster

Design Innovation Papers

J. Mech. Des. 2017;140(3):035001-035001-7. doi:10.1115/1.4038211.

This study presents the design and validation of on-line pressure-compensating (PC) drip irrigation emitters with a substantially lower minimum compensating inlet pressure (MCIP) than commercially available products. A reduced MCIP, or activation pressure, results in a drip irrigation system that can operate at a reduced pumping pressure, has lower power and energy requirements, requires a lower initial capital cost, and facilitates solar-powered irrigation systems. The technology presented herein can help spread drip irrigation to remote regions and contribute to reducing poverty, particularly in developing countries. The activation pressures of drip emitters at three flow rates were minimized using a genetic algorithm (GA)-based optimization method coupled with a recently published fluid–structure interaction analytical model of on-line PC drip emitter performance. The optimization took into account manufacturing constraints and the need to economically retrofit existing machines to manufacture new emitters. Optimized PC drip emitter designs with flow rates of 3.3, 4.2, and 8.2 lph were validated using precision machined prototype emitters. The activation pressure for all was ≤0.2 bar, which is as low as 16.7% that of commercial products. A limited production run of injection molded 8.2 lph dripper prototypes demonstrated they could be made with conventional manufacturing techniques. These drippers had an activation pressure of 0.15 bar. A cost analysis showed that low MCIP drip emitters can reduce the cost of solar-powered drip irrigation systems by up to 40%.

Commentary by Dr. Valentin Fuster

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