Official ASME Group

Journal of Mechanical Design

The ASME Journal of Mechanical Design (JMD) serves the broad design community as a venue for scholarly, archival research in all aspects of the design activity.
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News & Updates


    Toumadher Barhoumi and Dongsuk Kum
    J. Mech. Des 139(8), 083301; doi: 10.1115/1.4036583 

    Power-split hybrid electric vehicles embody two electric machines in addition to the internal combustion engine, and it employs one or more planetary gear sets (PG) while disposing of the transmission. Most of the prior studies on the design of power-split hybrids focused on finding optimal powertrain configurations, which are configurations specifying the components connections. However, a selected powertrain configuration cannot be physically realized as it does not specify the components arrangements in three dimensional space. Therefore, a given powertrain configuration should be depicted into feasible kinematic diagrams, which are used to generate the three dimensional drawings used for manufacturing. Multiple kinematic diagrams can be depicted for a given powertrain configuration as each kinematic diagrams specifies the exact components arrangements in addition to their connections. In this work, an automatic approach is developed to generate all the feasible kinematic diagrams for any given power-split powertrain configuration with a single PG. First, all the possible components arrangements, i.e. positioning diagrams, are generated. Then, a set of developed feasibility rules are applied on each positioning diagram in order to filter out infeasible components arrangements. Lastly, feasible kinematic diagrams are depicted for each feasible positioning diagram, and a set of preferred design criteria are used to select arrangements that best suit the vehicle’s manufacturability, packaging, maintenance, and cost. The proposed methodology guarantees automatically finding the components arrangements that best suit the desired vehicle through the search of the entire design space.
    For Full Article visit ASME's Digital Collection
  • Call For Papers: Special Issue: Design of Engineered Materials and Structures

    The design of engineered materials and structures is a growing and increasingly impactful field of research that intersects materials science, engineering design, engineering mechanics, manufacturing, and data science.  The overarching goal is to accelerate the discovery of new materials for engineering applications.  The approach compliments a traditionally empirical, trial-and-error approach to discovery with an inverse, requirements-driven approach that strategically leverages material databases, simulations and engineering design algorithms and methods to synthesize new materials and structures.  Papers are sought that integrate materials modeling, data collection, simulation, and prediction capabilities with engineering design methods, principles, algorithms, and tools to enable the design of new materials and structures.  To be appropriate for this special issue in the Journal of Mechanical Design (JMD), papers must demonstrate an intellectual emphasis on engineering design. 

    Representative topics include: 
    ·       Simulation-based design methods for enabling accelerated design, development, and insertion of engineering materials
    ·       Integration of theory, simulations, and experiments in the design of materials and structures
    ·       Novel design representation in design of materials and structures
    ·       Multiscale and multiphysics modeling and simulation to support the design of advanced materials and structures
    ·       Data-driven design of materials and structures; data mining and informatics for material and structural design
    ·       Integrated design of products, fabrication processes, and materials
    ·       Topology optimization theory and applications with an emphasis on design of materials and/or integrated design of materials and structures
    ·       Stochastic topology optimization and uncertainty quantification and management for materials and structures
    ·       Manufacturing considerations in design, including in topology, size, and shape optimization
    ·       Rigorous multiscale design, including multiscale topology optimization of materials and structures
    ·       Geometric modeling for design of materials and structures
    ·       Novel materials and structures by design, and their applications

    Submission Instructions
    Please submit your paper to ASME at and note on the cover page that your paper is intended for the special issue on “Design of Engineered Materials and Structures”. Please also alert the JMD Editor by email ( that your paper is intended for the special issue. Information about the Journal of Mechanical Design can be found at Early submission before the deadline is strongly encouraged.

    Publication Target Dates
    Authors submit papers by:                    March 1, 2018
    Initial review completed by:                   April 15, 2018
    Publication of special issue by:             November 2018

    Early submissions are strongly encouraged.  Papers submitted by March 1, 2018 will be reviewed in time for inclusion in the special issue.  Papers received after that date may still be considered for the special issue, if time and space permit. Papers that are not ready for production in time for inclusion in the special issue may be considered for a regular issue of the journal.  

    Guest Editors
    Carolyn Seepersad, University of Texas at Austin,
    Raymundo Arroyave, Texas A&M,
    James Guest, Johns Hopkins University,
    Andres Tovar, Indiana University-Purdue University Indianapolis,
    Yan Wang, Georgia Tech,
  • Special Section: Designing for Additive Manufacturing: Recent Advances in Design for Additive Manufacturing

    J. Mech. Des 139(10), 100901; doi: 10.1115/1.4037555 

    Now in its 40th year of existence, ASME's Journal of Mechanical Design has covered a wide range of topics on behalf of the Design Engineering Division. The past 40 years have seen countless advances in mechanical design, developing new knowledge in areas ranging from simulation to representation to communication, among others. These advances have often been complemented by similar advances in manufacturing, and traditional manufacturing processes such as machining and injection molding have been investigated heavily by the engineering design community. Today, however, we are in the midst of a paradigm shift. Whereas design methods in the past sought to overcome the design constraints imposed by manufacturing technologies, emerging digital manufacturing processes are removing many of these barriers and introducing new ones that are not yet fully understood. As a result, the additional degrees-of-freedom offered via selective (multi-) material addition/subtraction have exceeded our current design proficiencies. Additive manufacturing (AM) is at the forefront of this shift, and our engineering design software, methods, and tools are struggling to keep pace.

    As many readers know, AM provides unprecedented freedom for designing and engineering parts that are fabricated layer-by-layer. AM enables novel designs for a wide array of uses and applications in a range of industries, including aerospace, consumer goods, defense, energy, and medical, among others. Components can be easily light-weighted with topology optimization and lattice structures, complex assemblies can be consolidated into single 3D-printed geometries to reduce manufacturing complexity, and multimaterial fabrication techniques made possible by several AM processes enable never before seen functionally graded materials. In short, AM is changing not only what we design but also how we design, and a recent National Science Foundation Workshop on Additive Manufacturing Education and Training revealed that Design for Additive Manufacturing was the most pressing need for (re)training the engineering workforce. Consequently, this Special Section explores recent advances in the theories, methods, tools, and guidelines in Designing for Additive Manufacturing (DFAM). These contributions are empowering engineers to design and realize new parts, products, and systems that leverage AM processes' full capabilities, and in turn, are accelerating the adoption and application of AM technology.

    This Special Section is the second of its kind within the Journal of Mechanical Design, following the 2015 Special Issue: Design for Additive Manufacturing: A Paradigm Shift in Design, Fabrication, and Qualification. Since the previous issue, AM has maintained a high level of interest and continues to flourish as design and manufacturing technology have advanced at a feverish pace. America Makes, the first Manufacturing USA Institute, remains a strong advocate for AM technology, providing numerous partnership opportunities for industry and academia to join forces to help accelerate AM adoption. The Additive Manufacturing Standards Collaborative has documented the needs for Design for AM standards and development. Meanwhile, DARPA's transformative design (TRADES) program was established to advance the foundational mathematics and computational tools required to generate and better manage the enormous complexity of design in today's increasingly digital manufacturing environment. Finally, companies like Autodesk, Dassault, Parametric Technologies Corporation, and Siemens are in a neck-and-neck race to field integrated computer-aided design, modeling/simulation, and process planning software support for AM.

    Like the previous special issue, we have aimed to present readers with state-of-the-art research regarding DFAM in this special section. The papers in this special section can be categorized into three broad categories: (1) Review of State-of-the-Art, (2) Advances in State-of-the-Art, and (3) DFAM Case studies. Together, these papers highlight the advancements made in the past 2 years in DFAM in the engineering design community. This snapshot of where we currently stand as a design community, and how AM technologies are driving advances in new design paradigms and industrial applications, demonstrates how far we have come within a short period of time. The industrial adoption of AM continues to expand, with numerous companies now using AM processes to produce end-use artifacts in large quantities. AM technologies and material capabilities have continued to rapidly improve, and in turn, have continued to spur new opportunities for design theory, methodology, and automation.

    We expect that this will not be the last Special Issue or Special Section on Design for Additive Manufacturing—only the latest. As industry increasingly recognizes AM as viable production technology and integrates it within their existing manufacturing process chain, the need for expanding the mechanical design capabilities for engineers is sure to follow.

    Guest Editors
    Timothy W. Simpson, Pennsylvania State University,
    Jesse Boyer, Pratt & Whitney,
    Carolyn Seepersad, University of Texas, Austin,
    Christopher B. Williams, Virginia Tech,
    Paul Witherell, NIST,
    For the Full Special Section visit ASME's Digital Collection
  • Featured Article: Cyber-Empathic Design: A Data-Driven Framework for Product Design

    Dipanjan Ghosh, Andrew Olewnik, Kemper Lewis, Junghan Kim and Arun Lakshmanan
    J. Mech. Des 139(9), 091401 (Jul 12, 2017); doi: 10.1115/1.4036780 

    Understanding consumer perceptions of products and the potential impact of those perceptions on purchase decisions is critical information that should influence product development decisions. Though firms often seek consumer feedback on products, such feedback often occurs long after product use and lacks specific details about the interaction, usage context, etc. This work introduces a novel framework – Cyber-Empathic Design – that integrates sensor data and real-time user feedback to develop a more accurate model of user perceptions. The framework is applied to a case study focused on user perceptions of shoes. The results of this work demonstrate the potential for product developers to leverage the IoT (internet-of-things) movement, real-time user feedback, and advances in machine learning to connect user perceptions to specific engineered product features. 
    Figure: Data collection method (left) and resulting perceptual model (right). 

    For the Full Article visit ASME's Digital Collection.