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Issues
May 2022
ISSN 1050-0472
EISSN 1528-9001
Research Papers
Design Theory and Methodology
Can Induced Gratitude Improve Creative Performance on Repurposing Tasks?
J. Mech. Des. May 2022, 144(5): 051401.
doi: https://doi.org/10.1115/1.4052586
Topics:
Blades
,
Creativity
,
Engineering design
,
Turbines
,
Wind
,
Design
,
Wind turbines
,
Electromagnetic induction
A Graph Partitioning Technique to Optimize the Physical Integration of Functional Requirements for Axiomatic Design
J. Mech. Des. May 2022, 144(5): 051402.
doi: https://doi.org/10.1115/1.4052702
Topics:
Algorithms
,
Design
Design Automation
Stochastic Crashworthiness Optimization Accounting for Simulation Noise
J. Mech. Des. May 2022, 144(5): 051701.
doi: https://doi.org/10.1115/1.4052903
Topics:
Crashworthiness
,
Design
,
Noise (Sound)
,
Optimization
,
Simulation
,
Uncertainty
,
Optimization algorithms
OTL-PEM: An Optimization-Based Two-Layer Pointwise Ensemble of Surrogate Models
J. Mech. Des. May 2022, 144(5): 051702.
doi: https://doi.org/10.1115/1.4053011
Topics:
Optimization
,
Proton exchange membranes
,
Weight (Mass)
,
Errors
Fluid-Thermal Topology Optimization of Gas Turbine Blade Internal Cooling Ducts
J. Mech. Des. May 2022, 144(5): 051703.
doi: https://doi.org/10.1115/1.4053042
Topics:
Blades
,
Cooling
,
Ducts
,
Flow (Dynamics)
,
Fluids
,
Gas turbines
,
Geometry
,
Optimization
,
Pressure drop
,
Shapes
Robust Topology Optimization of Graphene Platelets Reinforced Functionally Graded Materials Considering Hybrid Bounded Uncertainties
J. Mech. Des. May 2022, 144(5): 051704.
doi: https://doi.org/10.1115/1.4053045
Topics:
Functionally graded materials
,
Graphene
,
Optimization
,
Platelets
,
Stress
,
Topology
,
Uncertainty
,
Design
,
Materials properties
A Reliability-Based Formulation for Simulation-Based Control Co-Design Using Generalized Polynomial Chaos Expansion
J. Mech. Des. May 2022, 144(5): 051705.
doi: https://doi.org/10.1115/1.4052906
Topics:
Design
,
Pendulums
,
Reliability
,
Simulation
,
Suspension systems
,
Event history analysis
,
Polynomials
,
Optimization
,
Uncertainty
Design for Manufacture and the Life Cycle
Development of Technical Creativity Featuring Modified TRIZ-AM Inventive Principle to Support Additive Manufacturing
J. Mech. Des. May 2022, 144(5): 052001.
doi: https://doi.org/10.1115/1.4052758
Topics:
Additive manufacturing
,
Design
,
Manufacturing
Design of Mechanisms and Robotic Systems
Novel Design of a Rotation Center Auto-Matched Ankle Rehabilitation Exoskeleton With Decoupled Control Capacity
J. Mech. Des. May 2022, 144(5): 053301.
doi: https://doi.org/10.1115/1.4052842
Topics:
Exoskeleton devices
,
Rotation
,
Design
,
Actuators
,
Kinematics
Design, Analysis, and Test of a Novel Cylinder-Driven Mode Applied to Microgripper
J. Mech. Des. May 2022, 144(5): 053302.
doi: https://doi.org/10.1115/1.4053043
Topics:
Cylinders
,
Design
,
Displacement
,
Finite element analysis
,
Grasping
,
Modeling
,
Hinges
,
Pressure
Technical Briefs
Phrase Embedding and Clustering for Sub-Feature Extraction From Online Data
J. Mech. Des. May 2022, 144(5): 054501.
doi: https://doi.org/10.1115/1.4052904
Topics:
Batteries
,
Design
,
Feature extraction
,
Fingerprints
,
Noise (Sound)
,
Preferences
,
Product design
,
Security
,
Storage
,
Natural language processing
Rapid Response! Investigating the Effects of Problem Definition on the Characteristics of Additively Manufactured Solutions for COVID-19
J. Mech. Des. May 2022, 144(5): 054502.
doi: https://doi.org/10.1115/1.4052970
Topics:
Additive manufacturing
,
Creativity
,
Design
,
Doors
,
Pandemics
,
Manufacturing
Design and Analysis of a Compact Piezo-Actuated Microgripper With a Large Amplification Ratio
J. Mech. Des. May 2022, 144(5): 054503.
doi: https://doi.org/10.1115/1.4053113
Topics:
Bending (Stress)
,
Design
,
Finite element analysis
,
Hinges
,
Kinematics
,
Modeling
,
Stiffness
,
Displacement
,
Statics
Design Innovation Paper
Design and Experimental Characterization of Hydraulically Actuated Revolute Joint Based on Multimaterial Additive Manufacturing
J. Mech. Des. May 2022, 144(5): 055001.
doi: https://doi.org/10.1115/1.4052905
Discussion
Discussion: “Bayesian Optimal Design of Experiments for Inferring the Statistical Expectation of Expensive Black-Box Functions” (Pandita, P., Bilionis, I., and Panchal, J., 2019, ASME J. Mech. Des., 141(10), p. 101404)
J. Mech. Des. May 2022, 144(5): 055501.
doi: https://doi.org/10.1115/1.4053112
Topics:
Computation
,
Experimental design