Tian Chen
ETH Zurich
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Featured researches published by Tian Chen.
Scientific Reports | 2017
Tian Chen; Jochen A. Müller; Kristina Shea
Multi-material 3D printing has created new opportunities for fabricating deployable structures. We design reversible, deployable structures that are fabricated flat, have defined load bearing capacity, and multiple, predictable activated geometries. These structures are designed with a hierarchical framework where the proposed bistable actuator serves as the base building block. The actuator is designed to maximise its stroke length, with the expansion ratio approaching one when serially connected. The activation force of the actuator is parameterised through its joint material and joint length. Simulation and experimental results show that the bistability triggering force can be tuned between 0.5 and 5.0 N. Incorporating this bistable actuator, the first group of hierarchical designs demonstrate the deployment of space frame structures with a tetrahedron module consisting of three active edges, each containing four serially connected actuators. The second group shows the design of flat structures that assume either positive or negative Gaussian curvature once activated. By flipping the initial configuration of the unit actuators, structures such as a dome and an enclosure are demonstrated. A modified Dynamic Relaxation method is used to simulate all possible geometries of the hierarchical structures. Measured geometries differ by less than 5% compared to simulation results.
Proceedings of the National Academy of Sciences of the United States of America | 2018
Tian Chen; Osama R. Bilal; Kristina Shea; Chiara Daraio
Significance A major challenge in soft robotics is the integration of sensing, actuation, control, and propulsion. Here, we propose a material-based approach for designing soft robots. We show an untethered, soft swimming robot, which can complete preprogrammed tasks without the need for electronics, controllers, or power sources on board. To achieve propulsion, we use bistable shape memory polymer muscles connected to paddles that amplify actuation forces. As a proof of principle, we show that these robots can be preprogrammed to follow specific routes or deliver a cargo and navigate back to their deployment point. The proposed design principle can have a broad impact in soft robotics based on programed materials. In most macroscale robotic systems, propulsion and controls are enabled through a physical tether or complex onboard electronics and batteries. A tether simplifies the design process but limits the range of motion of the robot, while onboard controls and power supplies are heavy and complicate the design process. Here, we present a simple design principle for an untethered, soft swimming robot with preprogrammed, directional propulsion without a battery or onboard electronics. Locomotion is achieved by using actuators that harness the large displacements of bistable elements triggered by surrounding temperature changes. Powered by shape memory polymer (SMP) muscles, the bistable elements in turn actuate the robot’s fins. Our robots are fabricated using a commercially available 3D printer in a single print. As a proof of concept, we show the ability to program a vessel, which can autonomously deliver a cargo and navigate back to the deployment point.
Volume 3: 17th International Conference on Advanced Vehicle Technologies; 12th International Conference on Design Education; 8th Frontiers in Biomedical Devices | 2015
Tian Chen; Paul Egan; Fritz Stöckli; Kristina Shea
Additive Manufacturing (AM) is a revolutionary technology in the manufacturing sector, although it has yet to become a cornerstone of formal engineering education. This paper discusses the procedure, result, and impact of incorporating physical prototyping, design iteration, and Design for Additive Manufacturing (DfAM) in a first-year, first-semester technical drawing and CAD course. In the course, students design balloon powered model car assemblies and are expected to learn core concepts of engineering design, such as modeling, assemblies, and tolerancing. The course consists of 473 students that each design up to two unique model cars. These model cars are fabricated using AM from these CAD designs and returned to students for assembly. Surveys are given to students to empirically validate the usefulness of incorporating AM in the course, with regards to motivating students and improving their ability to accurately translate imagined designs from CAD to physical products. The results show improvement in student intrinsic motivation concerning CAD processes. Student design abilities are also assessed: when student designs do not function as intended, it corresponds with a greater mismatch in how they imagine their CAD design in comparison to its final physical assembly. The mismatch on average decreases for students who design a second model car, which suggests an improvement in design skills. As a whole, our findings demonstrate the feasibility and benefits of including AM in a first-year course, particularly with respect to improving student motivation and their development of key CAD-related skills. Such motivation and skill development is particularly important early in an engineer’s career as it can impact their potential to learn and design over the course of their budding career.Copyright
3D Printing and Additive Manufacturing | 2018
Tian Chen; Kristina Shea
Abstract Autonomous deployment and shape reconfiguration of structures are a crucial field of research in space exploration with emerging applications in the automotive, building, and biomedical industries. Challenges in achieving autonomy include the following: bulky energy sources, imprecise deployment, jamming of components, and lack of structural integrity. Leveraging advances in the fields of shape memory polymers, bistability, and three-dimensional (3D) multimaterial printing, we present a 3D-printed programmable actuator that enables the autonomous deployment and shape reconfiguration of structures activated through surrounding temperature change. Using a shape memory polymer as the temperature controllable energy source and a bistable mechanism as the linear actuator and force amplifier, the structures achieve precise geometric activation and quantifiable load-bearing capacity. The proposed unit actuator integrates these two components and is designed to be assembled into larger deployable and sha...Abstract Autonomous deployment and shape reconfiguration of structures are a crucial field of research in space exploration with emerging applications in the automotive, building, and biomedical in...
Seventh International Conference on Design Computing and Cognition (DCC'16) | 2017
Luca Zimmermann; Tian Chen; Kristina Shea
Advancements in 3D printers are challenging engineers to design ever more complex, customizable and unique products. This paper presents a method that facilitates design by combining 3D spatial grammars, structural simulation and optimization. The proposed method is generic and illustrated here through the design of wheels for inline skates since they have both aesthetic and functional requirements. A new spatial grammar for wheel spoke design is described that integrates constraints from additive manufacture such that the wheels can be directly fabricated. Next, the necessary adjustments to enable automated FE simulation with invariant boundary conditions are shown. The design selection process during generation is driven by simulated annealing optimization and a spatial grammar specific neighborhood definition is introduced for shape modification. Results presented for the case of the inline skate wheel show promise both in automatically generating many different yet valid concepts and in obtaining a structurally optimized design .
Archive | 2017
Tian Chen; Osama R. Bilal; Kristina Shea; Chiara Daraio
design automation conference | 2016
Tian Chen; Kristina Shea
DS 80-2 Proceedings of the 20th International Conference on Engineering Design (ICED 15) Vol 2: Design Theory and Research Methodology Design Processes, Milan, Italy, 27-30.07.15 | 2015
Tian Chen; Kristina Shea
arxiv:physics.app-ph | 2018
Tian Chen; Osama R. Bilal; Robert Lang; Chiara Daraio; Kristina Shea
Structural and Multidisciplinary Optimization | 2018
Jonas Schwarz; Tian Chen; Kristina Shea; Tino Stanković