Accepted Manuscripts

Nicole Damen and Christine Toh
J. Mech. Des   doi: 10.1115/1.4042223
Although trust can have a positively mediating effect on information technology adoption and usage, the concept has not been extensively investigated in the home automation field. Therefore, this work is aimed at exploring the role of agent location and the gender of the agent's voice on users' perception of trust towards automation through two experimental studies (N=8 & N=20) and a web-based smart lock simulation. Explicit trust behavior was captured using directly observable behaviors and decisions, while implicit trust behavior was captured using detailed click-level user behaviors with the smart lock simulation as a proxy for reaction time. The results show that users displayed more explicit trusting behavior towards the system when it displayed design characteristics that were stereotype congruent (female-home and male-office) compared to stereotype incongruent systems (male-home and female-office). These results show that users carry over the social expectations and roles encountered in human-to-human relationships to interactions with simulated automated agents. These findings empirically demonstrate the influence of design characteristics on the formation of trust relationships between users and automated devices and provide a foundation for future research geared at critically examining our evolving relationship with technology.
TOPICS: Design, Locks (Waterways), Simulation
Technical Brief  
Chi Wu, Yunkai Gao, Jianguang Fang, Erik Lund and Qing Li
J. Mech. Des   doi: 10.1115/1.4042222
This study developed a discrete topology optimization procedure for simultaneous design of ply orientation and thickness for carbon fiber reinforced plastic (CFRP) laminated structures. A gradient-based discrete material and thickness optimization (DMTO) algorithm was proposed by adopting the casting based explicit parameterization for suppressing intermediate void across the laminate thickness. A benchmark problem was first studied to compare the DMTO approach with the sequential three-phase design method with free size, ply thickness and stacking sequence of laminates. Following this, the DMTO approach was applied to a real-life design problem, namely CFRP laminated engine hood by minimizing the overall compliance subject to volume and stiffness constraints under multiple load cases. To validate the optimized design, the CFRP engine hood was prototyped in a real size and the experimental tests were then carried out. The results demonstrated that the simultaneous discrete topology optimization of ply orientation and thickness is an effective approach for the design of CFRP laminated structures.
TOPICS: Carbon reinforced plastics, Optimization, Topology, Design, Engines, Laminates, Stress, Algorithms, Design methodology, Stiffness, Casting
Neunghwan Yim, Seokwon Kang and Yoon Young Kim
J. Mech. Des   doi: 10.1115/1.4042212
Topology optimization for mechanism synthesis has been developed for the simultaneous determination of the number and dimension of mechanisms. However, these methods can be used to synthesize linkage mechanisms that consist only of links and joints because other types of mechanical elements such as gears cannot be simultaneously synthesized. In this study, we aim to develop a gradient-based topology optimization method which can be used to synthesize mechanisms consisting of both linkages and gears. For the synthesis, we propose a new ground model defined by two superposed design spaces: the linkage and gear design spaces. The gear design space is discretized by newly proposed gear blocks, each of which is assumed to rotate as an output gear, while the linkage design space is discretized by zero-length-spring-connected rigid blocks. Another set of zero-length springs is introduced to connect gear blocks to rigid blocks, and their stiffness values are varied to determine the existence of gears when they are necessary to produce the desired path. After the proposed topology-optimization-based synthesis formulation and its numerical implementation are presented, its effectiveness and validity are checked with various synthesis examples involving gear-linkage and linkage-only mechanisms
TOPICS: Linkages, Gears, Optimization, Topology, Design, Space, Springs, Stiffness, Dimensions
Lin Guo, Hamed Zamanisabzi, Thomas Neeson, Janet K. Allen and Farrokh Mistree
J. Mech. Des   doi: 10.1115/1.4042211
In a multi-reservoir system, ensuring adequate water availability while managing conflicting goals is critical to making the social-ecological system sustainable in the presence of considerable uncertainty. The priorities of multiple user-groups and availability of the water resource vary with time, weather and other factors. Uncertainties such as variations in precipitation intensify the discrepancies between water supply and water demand. To reduce such discrepancies, we seek to satisfice conflicting goals, considering typical uncertainties. We observe that models are incomplete and inaccurate, which calls into question using a single point solution and suggests the need for solutions which are robust to uncertainties. So, we explore satisficing solutions that are relatively insensitive to uncertainties, by incorporating different design preferences, identifying sensitive segments and improving the design accordingly. In this article we present an example of the exploration of the solution space to enhance sustainability in multi-disciplinary systems, when goals conflict, preferences are evolving, and uncertainties add complexity, which can be applied in mechanical design. In this paper, we focus on the method rather than the results.
TOPICS: Dams, Space, Water, Uncertainty, Preferences, Sustainability, Design, Design engineering, Reservoirs, Precipitation, Water supply
Paul Egan, Isabella Bauer, Kristina Shea and Stephen Ferguson
J. Mech. Des   doi: 10.1115/1.4042213
Advances in 3D printing are enabling the design and fabrication of tailored lattices with high mechanical efficiency. Here, we use an integrated design, manufacturing, and experiment approach to mechanically characterize and configure beam-based lattices intended for use in spinal cages for bone fusion. Polymer lattices with 50% and 70% porosity were fabricated with beam diameters of 0.4mm to 1.0mm using polyjet printing, with measured effective elastic moduli from 28MPa to 213MPa. Effective elastic moduli decreased with higher lattice porosity, increased with larger beam diameters, and were highest for lattices compressed perpendicular to their original build direction. Cages were designed with 50% and 70% lattice porosities and included central voids for increased nutrient transport, reinforced shells for increased stiffness, or both. Cage stiffnesses ranged from 4.1kN/mm to 9.6kN/mm with yielding after 0.36mm to 0.48mm displacement, thus suggesting their suitability for typical spinal loads of 1.65kN. Findings demonstrate the merits in using integrated design approaches for 3D printed structures, particularly for developing novel biomedical devices.
TOPICS: Biomedicine, Additive manufacturing, Design, Manufacturing, Elastic moduli, Porosity, Printing, Shells, Stiffness, Stress, Bone, Polymers, Displacement, Mechanical efficiency
Yanbin Luo, Bo Zhong, Xiaojie Zhang, Yanrong Wang and Jiazhe Zhao
J. Mech. Des   doi: 10.1115/1.4042189
The effects of stress gradient and size effect on fatigue life are investigated based on the distributions of stress at notch root of the notched specimens of GH4169 alloy. The relationship between the life of the notched specimens and the smooth specimens is correlated by introducing the stress gradient effect factor, and a new life model of predicting the notched specimens based on the Walker modification for the mean stress effect is established. In order to improve the prediction precision of life model with the equation parameters having a definite physical significance, the relationships among fatigue parameters, monotonic ultimate tensile strength and reduction of area are established. Three-dimensional elastic finite element (FE) analysis of a vortex reducer is carried out to obtain the data of stress and strain for predicting its life. The results show that there is a high-stress gradient at the edge of the air holes of the vortex reducer, and it is thus a dangerous point for fatigue crack initiation. The prediction result of the vortex reducer is more reasonable if the mean stress, stress gradient and size effect are considered comprehensively. The developed life model can reflect the effects of many factors well, especially the stress concentration. The life of the notched specimens predicted by this model give a high estimation precision, and the prediction life data mainly fall into the scatter band of factor 2.
TOPICS: Stress, Vortices, Fatigue life, Size effect, Tensile strength, Fatigue cracks, Fatigue, Alloys, Stress concentration, Electromagnetic scattering, Finite element analysis
Yoshichi Otake
J. Mech. Des   doi: 10.1115/1.4042190
The geometrical tooth surface properties of skew gears have a significant influence on gear performance. We consider the contact line angle, slip rate, and relative curvature as tooth surface properties. An overall image of the tooth surface properties is an effective means of optimization. However, this whole image is unknown, because the tooth surface properties are represented by four elements of the tooth surface, and it is difficult to express them in one coordinate space. This problem is overcome by expressing the tooth surface properties using three elements. First, three-element expressions for the tooth surface properties are derived and the tooth surface property space, which expresses the overall image of the tooth surface properties, is constructed using the three elements as coordinate axes. Next, the characteristic surface of the tooth surface property space is clarified and an image of the space is simulated. From this, it is possible to visually and intuitively capture the features of the tooth surface property space, i.e., the whole image. Finally, the wide range of applications of the tooth surface property space is discussed. This demonstrates that the tooth surface property space provides important indicators and standards for the future development and designs.
TOPICS: Gears, Surface properties, Optimization
Christine Toh and Scarlett Miller
J. Mech. Des   doi: 10.1115/1.4042154
Creativity is universally acknowledged as an important attribute of successful engineering design, but imperfect human decision-making can influence whether creative ideas come to fruition during the design process. However, few studies have explored the factors that can predict creative concept generation and selection. Thus, the current study was developed to provide an empirical understanding of how student designers' preferences for creativity predicts their ability to generate or select creative design alternatives during the concept screening process above and beyond the effects of personality through an empirical study with 178 engineering students. The factors explored included the Big 5 factors of personality, the Preferences for Creativity Scale (PCS), and the novelty and quality of ideas generated and screened. The results show that the Openness personality trait can predict the Novelty of Generated Ideas as well as the Novelty and Quality of Selected Ideas during the concept screening process and that the Creative Confidence and Preference Factor of the PCS can predict the Novelty of Generated Ideas and the Novelty and Quality of Selected ideas during the concept screening process better than the Big 5 Factors of Personality. A similar finding was obtained for the Risk Tolerance Factor of the PCS. These findings demonstrate the importance of an individual's attitude towards risk and their creative confidence in the generation and selection of ideas in engineering education and provide a foundation for future research geared at building student innovation capacities.
TOPICS: Creativity, Engineering students, Preferences, Risk, Students, Innovation, Engineering design, Design, Decision making, Engineering education
Min-Yeong Moon, KK Choi, Nicholas Gaul and David Lamb
J. Mech. Des   doi: 10.1115/1.4042149
Accurately predicting the reliability of a physical system under aleatory uncertainty requires a very large number of physical output testing. Alternatively, a simulation-based method can be used, but it would involve epistemic uncertainties due to imperfections in input distribution models, simulation models, and surrogate models, as well as a limited number of output testing due to cost. Biasness of the simulation model could be due to assumptions and idealizations used in the modeling process, and thus the estimated output distributions and their corresponding reliabilities would become uncertain. One way to treat epistemic uncertainty is to use a hierarchical Bayesian approach; however, this could result in an overly conservative reliability by integrating possible candidates of input distribution. In this paper, a new confidence-based reliability assessment method that reduces unnecessary conservativeness is developed. The epistemic uncertainty induced by a limited number of input data is treated by approximating an input distribution model using a bootstrap method. Two engineering examples and one mathematical example are used to demonstrate that the proposed method (1) provides less conservative reliability than the hierarchical Bayesian analysis, yet (2) predicts the reliability of a physical system that satisfies the user-specified target confidence level, and (3) shows convergence behavior of reliability estimation as numbers of input and output test data increase.
TOPICS: Reliability, Uncertainty, Testing, Simulation models, Simulation, Modeling
Xingqiao Deng, Jie Wang, Shike Wang, Shisong Wang, Jinge Wang, Shuangcen Li, Yucheng Liu and Ge He
J. Mech. Des   doi: 10.1115/1.4042155
This paper proposes a single roller enveloping hourglass worm gear design. The main goal of this paper is to verify the advantages of the proposed single roller worm gear system compared to the existing double roller worm gear system and the conventional worm gear set. Our hypothesis is that the single roller worm gear with appropriate configurations and parametric values is capable of eliminate the backlash in mating gear transmission while maintains advantages of the double roller worm gears while significantly simplifying the configuration and therefore reducing the manufacturing and maintenance costs. Also, the self-rotation of the rollers when they are in the worm tooth space will help the gear system to avoid jamming and gear tooth scuffing/seizing problems caused by zero backlash and thermal expansion. In order to test that hypothesis, a mathematical model for the single roller enveloping hourglass worm gear is developed for the first time, which includes a gear engagement equation and a tooth profile equation. Using that mathematical model, a parametric study is conducted to inspect the influences of center distance, roller radius, transmission ratio, and the radius of base circle on the worm gear meshing characteristics (backlash, contact curves, and tooth profile). From the parametric study it is found that the most effective way in eliminating the backlash is to adjust the roller radius and the radius of base circle correspondingly. Finally, a single roller enveloping hourglass worm gear set is manufactured using a hopping machine with the assistance of auxiliary equipment.
TOPICS: Worm gears, Rollers, Theoretical analysis, Gears, Gear teeth, Design, Rotation, Thermal expansion, Machinery, Maintenance, Manufacturing
Dongyang Sun, Yan Shi and Baoqiang Zhang
J. Mech. Des   doi: 10.1115/1.4042111
The dynamic characteristics of planar mechanisms with fuzzy joint clearance and random geometry are studied in this paper. The dynamics model for the mechanism is constructed by utilizing Baumgarte approach, in which the clearance size is a fuzzy number, while the geometry parameters are assumed as random variables. A hybrid contact force model, which consists of the Lankarani-Nikravesh model, improved Winkler elastic foundation model and modified Coulomb friction force model, is applied to construct revolute clearance joint. In order to solve the dynamics model, two methodologies are developed: confidence region method for quantification of random and fuzzy uncertainties (CRMQRFU), and confidence region method with transformation method (CRMTM). In the CRMQRFU, fuzzy numbers are firstly decomposed into intervals under the given membership level. Then, a general framework is proposed for quantification of random and interval uncertainties in the mechanism. In the CRMTM, a transformation method is applied to transform intervals into deterministic arrays, while probability theory is used to obtain the confidence regions under the given fuzzy values. The confidence region, considering random and fuzzy uncertainties, is obtained by fuzzy set theory. Finally, two examples are used to demonstrate the validity and feasibility of these methods.
TOPICS: Clearances (Engineering), Dynamic analysis, Geometry, Uncertainty, Dynamics (Mechanics), Friction, Coulombs, Fuzzy set theory, Probability
Erva Ulu, Runze Huang, Levent Burak Kara and Kate S. Whitefoot
J. Mech. Des   doi: 10.1115/1.4042112
Metals-additive manufacturing (MAM) is enabling the possibility of significant environmental and economic benefits in many different industries. However, total production costs of MAM will need to be reduced substantially before it will be widely adopted across the manufacturing sector. Current topology optimization approaches focus on reducing material volume as a means of reducing material costs, but they do not account for other production costs that are influenced by a part's structure such as machine time and scrap. Moreover, concurrently optimizing MAM process variables with a part's structure has the potential to further reduce production costs. This paper demonstrates an approach to use process-based cost modeling in MAM topology optimization to minimize total production costs, including material, labor, energy, and machine costs, using cost estimates from industrial MAM operations. The approach is demonstrated on various 3D geometries for the electron beam melting process with Ti64 material. Concurrent optimization of the structures and process variables are compared to optimization of the structure alone. Results indicate that, once process variables are considered, more cost effective results can be obtained with similar amount of material through a combination of (1) building high stress regions with lower power to obtain larger yield strength and (2) increasing the power elsewhere to reduce the number of passes required, thereby reducing build time. In our case studies, concurrent optimization of part structure and MAM process parameters leads to up to 15% lower production costs and 21% faster build time than optimizing structure alone.
TOPICS: Metals, Optimization, Additive manufacturing, Topology, Machinery, Manufacturing, Cathode ray oscilloscopes, Electron beams, Stress, Melting, Project cost estimation, Modeling, Yield strength
Benson Isaac and Douglas Allaire
J. Mech. Des   doi: 10.1115/1.4042113
The optimization of black-box models is a challenging task owing to the lack of analytic gradient information and structural information about the underlying function, and also due often to significant run times. A common approach to tackling such problems is the implementation of Bayesian global optimization techniques. However, these techniques often rely on surrogate modeling strategies that endow the approximation of the underlying expensive function with non-existent features. Further, these techniques tend to push new queries away from previously queried design points,making it difficult to locate an optimum point that rests near a previous model evaluation. To overcome these issues, we propose a gold rush policy that relies on purely local information to identify the next best design alternative to query. The method employs a surrogate constructed point-wise, that adds no additional features to the approximation. The result is a policy that performs well in comparison to state of the art Bayesian global optimization methods on several benchmark problems. The policy is also demonstrated on a constrained optimization problem using a penalty method.
TOPICS: Optimization, Approximation, Design, Modeling
Seung-Hyun Ha, Hak Yong Lee, Kevin Hemker and James K. Guest
J. Mech. Des   doi: 10.1115/1.4042114
Three-dimensional weaving has recently arisen as viable means for manufacturing metallic, architected micro-lattices. Herein we describe a topology optimization approach for designing the architecture of such 3-D woven lattices. A ground structure design variable representation is combined with linear manufacturing constraints and a projection mapping to realize lattices that satisfy the rather restrictive topological constraints associated with 3-D weaving. The approach is demonstrated in the context of inverse homogenization to design lattices with maximized fluid permeability. Stokes flow equations with no-slip conditions governing unit cell flow fields are interpolated using the Darcy-Stokes finite element model, fully leveraging existing work in the topology optimization of fluids. The combined algorithm is demonstrated to design manufacturable lattices with maximized permeability whose properties have been validated experimentally in other published work.
TOPICS: Design, Optimization, Topology, Fluids, Permeability, Manufacturing, Algorithms, Creeping flow, Finite element model, Flow (Dynamics)
Binyang Song, Jianxi Luo and Kristin Wood
J. Mech. Des   doi: 10.1115/1.4042083
A properly designed product-system platform can reduce the cost and lead time to design and develop a product family and thus achieve the tradeoff between economy of scope from product variety and economy of scale from platform sharing. Traditionally, product platform planning uses heuristic and manual approaches and relies on expertise and intuition. In this paper, we propose a data-driven method to draw the boundary of a platform, complementing other platform design approaches and assisting designers in the architecting process. The method generates a network of functions through relationships of their co-occurrences in prior designs of a product domain and uses a network analysis algorithm to identify an optimal core-periphery structure. Functions identified in the network core co-occur cohesively and frequently with one another in prior designs, and thus are suggested for inclusion in the potential platform to be shared across a variety of product-systems with peripheral functions. We apply the method to identifying the platform functions for spherical rolling robots, based on patent data.
TOPICS: Design, Network analysis, Patents, Economics , Robots, Algorithms, Tradeoffs
Xuan Zheng and Scarlett Miller
J. Mech. Des   doi: 10.1115/1.4042081
Ownership bias is a type of decision making bias that leads to an individual's tendency to prefer his or her own ideas over the ideas of others during the design process. While prior work has identified the existence of this effect in design professionals, this prior research failed to investigate the characteristics of the idea set that impact the effects. In other words, is a preference for one's own ideas a bad thing if your ideas are truly better? This paper sought to fill this research void through two design thinking workshops with 45 design professionals recruited from two engineering companies. During the study, design professionals individually generated and selected ideas as part of a 2-hour team design challenge. The ideas were rated for their perceived future value through team consensus and for their creativity by expert ratings. The results suggest that design professionals only exhibited ownership bias for ideas that were assessed to have little to no future value in the design process (low in idea goodness). In addition, professionals showed preferences for self-generated ideas that were of high usefulness and elegance but low in creativity indicating an impact of creativity on ownership bias. These findings provide new evidence on the negative effects of ownership bias on the design process.
TOPICS: Creativity, Design, Teams, Preferences, Workshops (Work spaces), Decision making, Experimental design
Hari P.N. Nagarajan, Hossein Mokhtarian, Hesam Jafarian, Saoussen Dimassi, Shahriar Bakrani Balani, Azarakhsh Hamedi, Eric Coatanéa, Gary Wang and Karl R. Haapala
J. Mech. Des   doi: 10.1115/1.4042084
Additive manufacturing (AM) continues to rise in popularity due to its various advantages over traditional manufacturing processes. AM interests industry, but achieving repeatable production quality remains problematic for many AM technologies. Thus, modeling different process variables in AM using machine learning can be highly beneficial in creating useful knowledge of the process. Such developed artificial neural network (ANN) models would aid designers and manufacturers to make informed decisions about their products and processes. However, it is challenging to define an appropriate ANN topology that captures the AM system behavior. Towards that goal, an approach combining dimensional analysis conceptual modeling (DACM) and classical ANNs is proposed to create a new type of knowledge based artificial neural network (KB-ANN). This approach integrates existing literature and expert knowledge of the AM process to define a topology for the KB-ANN model. The proposed KB-ANN is a hybrid learning network that encompasses topological zones derived from knowledge of the process and other zones where missing knowledge is modelled using classical ANNs. The usefulness of the method is demonstrated using a case study to model wall thickness, height of part, and total mass of the part in a Fused Deposition Modeling (FDM) process. The KB-ANN based model for FDM has same performance with better generalization capabilities with less number of weights trained in comparison to a classical ANN.
TOPICS: Modeling, Optimization, Artificial neural networks, Topology, Additive manufacturing, Machine learning, Dimensional analysis, Manufacturing, Wall thickness
M. Giselle Fernandez-Godino, S. Balachandar and Raphael Haftka
J. Mech. Des   doi: 10.1115/1.4042047
When simulations are expensive and multiple realizations are necessary, as is the case in uncertainty propagation, statistical inference and optimization, surrogate models can achieve accurate predictions at low computational cost. In this paper, we explore options for improving the accuracy of a surrogate if the modeled phenomenon presents symmetries. These symmetries allow us to obtain free information and, therefore, the possibility of more accurate predictions. We present an analytical example along with a physical example that present parametric symmetries. Although imposing parametric symmetries in surrogate models seems to be a trivial matter, there is not a single way to do it and, furthermore, the achieved accuracy might vary. We present different ways of imposing symmetry in surrogate models. The performance of the options was compared with 100 random design of experiments where symmetries were not imposed. We found that each of the options to include symmetries performed the best in one or more of the studied cases and, in all cases, the errors obtained imposing symmetries were substantially smaller than the worst cases among the 100. We explore the options for using symmetries in two surrogates that present different challenges and opportunities: Kriging and linear regression. Kriging is often used as a black box, therefore we consider approaches to include the symmetries without changes in the main code. On the other hand, since linear regression is often built by the user owing to its simplicity we consider also approaches that modify the linear regression basis functions to impose the symmetries.
TOPICS: Matter, Simulation, Engineering simulation, Optimization, Errors, Experimental design, Uncertainty
Daniel Henderson, Kathryn Jablokow, Shanna Daly, Seda McKilligan, Eli Silk and Jennifer Bracken
J. Mech. Des   doi: 10.1115/1.4042048
Many tools, techniques, and other interventions have been developed to support idea generation within the design process. In previous research, we explored the separate effects of three such design interventions: teaming, problem framing, and design heuristics. In the teaming intervention, participants discussed a design prompt together but recorded their own ideas separately. In problem framing, multiple versions ("framings") of each design prompt were used to elicit different solutions. In design heuristics, participants used specially designed cards to prompt new ways of thinking about the given design problem. In the current work, we compared the effects of these three interventions on students' design ideas with respect to one idea attribute in particular–quality. In total, 1088 design concepts were collected from 171 undergraduate students in engineering and industrial design from two universities. Individual cognitive style was also assessed using Kirton's Adaption-Innovation inventory (KAI). Six metrics taken from the design literature were used to assess the quality of each concept, namely: acceptability, applicability, clarity, effectiveness, implementability, and implicational explicitness. Paired t-tests and Pearson correlations were used to assess differences in quality between concepts generated with and without the three interventions; in addition, secondary effects were sought based on the cognitive styles and academic standings of the participants. Statistically significant differences were observed in design concept quality for the teaming and design heuristics interventions over the full sample and for some sub-groups separated by cognitive style and academic standing. These results have implications for both educators and students.
TOPICS: Reflection, Design, Students, Structural frames, Framing (Construction), Industrial design, Engineering teachers, Undergraduate students, Innovation
Wei Chen
J. Mech. Des   doi: 10.1115/1.4042049
This is the editorial for the Special Issues on Selected Papers from IDETC 2018 (Part I & Part II)

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In