Thermoplastic variable stiffness composites with embedded, networked sensing, actuation, and control

We present a composite material consisting of a thermoplastic base material and embedded, networked sensing, actuation, and control to vary its stiffness locally based on computational logic. A polycaprolactone grid provides stiffness at room temperature. Each polycaprolactone element within the grid is equipped with a dedicated heating element, thermistor, and networked microcontroller that can drive the element to a desired temperature/stiffness. We present experimental results using a 4 × 1 grid that can assume different global conformations under the influence of gravity by simply changing the local stiffness of individual parts. We describe the composite structure and its manufacturing, the principles behind variable stiffness control using Joule heating, local sliding mode control of each polycaprolactone bar’s temperature and function, and limitations of the embedded multi-hop communication system. The function of the local temperature controller is evaluated experimentally.

[1]  B. Wunderlich,et al.  Heat Capacity and Other Thermodynamic Properties of Linear Macromolecules. VIII. Polyesters and Polyamides , 1983 .

[2]  B. Wunderlich,et al.  Heat Capacity and Other Thermodynamic Properties of Linear Macromolecules. IX. Final Group of Aromatic and Inorganic Polymers , 1983 .

[3]  Roderic S. Lakes,et al.  Deformation mechanisms in negative Poisson's ratio materials: structural aspects , 1991 .

[4]  Matthew M. Williamson,et al.  Series elastic actuators , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[5]  K. J. Gabriel,et al.  Distributed MEMS: new challenges for computation , 1997 .

[6]  Randy H. Katz,et al.  Next century challenges: mobile networking for “Smart Dust” , 1999, MobiCom.

[7]  J. A. Brydson,et al.  1. – The Historical Development of Plastics Materials , 1989 .

[8]  Chris Hanson,et al.  Amorphous computing , 2000, Commun. ACM.

[9]  L. Avérous,et al.  Properties of thermoplastic blends: starch-polycaprolactone , 2000 .

[10]  F. Chang,et al.  Detection and monitoring of hidden fatigue crack growth using a built-in piezoelectric sensor/actuator network: I. Diagnostics , 2004 .

[11]  R. Reis,et al.  Thermal and Thermomechanical Behaviour of Polycaprolactone and Starch/Polycaprolactone Blends for Biomedical Applications , 2005 .

[12]  Billie F. Spencer,et al.  Distributed computing strategy for structural health monitoring , 2006 .

[13]  M. Zrínyi,et al.  Magnetic field sensitive functional elastomers with tuneable elastic modulus , 2006 .

[14]  Chris Henry,et al.  Cellular variable stiffness materials for ultra-large reversible deformations in reconfigurable structures , 2006, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[15]  Joseph L. Rose,et al.  Active health monitoring of an aircraft wing with embedded piezoelectric sensor/actuator network: I. Defect detection, localization and growth monitoring , 2007 .

[16]  Farhan Gandhi,et al.  Beams with controllable flexural stiffness , 2007, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[17]  Chiman Kwan,et al.  Active health monitoring of an aircraft wing with an embedded piezoelectric sensor/actuator network: II. Wireless approaches , 2007 .

[18]  I. Bond,et al.  Morphing skins , 2008, The Aeronautical Journal (1968).

[19]  D. Tyler,et al.  Stimuli-Responsive Polymer Nanocomposites Inspired by the Sea Cucumber Dermis , 2008, Science.

[20]  Chang Liu,et al.  Development of a Latchable Microvalve Employing a Low-Melting-Temperature Metal Alloy , 2008, Journal of Microelectromechanical Systems.

[21]  D. Hutmacher,et al.  return of a forgotten polymer — Polycaprolactone n the 21 st century aria , 2010 .

[22]  Stuart J. Rowan,et al.  Biomimetic mechanically adaptive nanocomposites , 2010 .

[23]  Wei-Hsin Liao,et al.  Design, testing and control of a magnetorheological actuator for assistive knee braces , 2010 .

[24]  R. Wood,et al.  Tunable elastic stiffness with microconfined magnetorheological domains at low magnetic field , 2010 .

[25]  Rebecca K. Kramer,et al.  Hyperelastic pressure sensing with a liquid-embedded elastomer , 2010 .

[26]  Farhan Gandhi,et al.  Multi-layered controllable stiffness beams for morphing: energy, actuation force, and material strain considerations , 2010 .

[27]  Nikolaus Correll,et al.  Soft Autonomous Materials - Using Active Elasticity and Embedded Distributed Computation , 2010, ISER.

[28]  Damiano Pasini,et al.  Optimum stacking sequence design of composite materials Part II: Variable stiffness design , 2010 .

[29]  Heinrich M. Jaeger,et al.  Universal robotic gripper based on the jamming of granular material , 2010, Proceedings of the National Academy of Sciences.

[30]  Walter Lang,et al.  Sensorial materials—A vision about where progress in sensor integration may lead to , 2011 .

[31]  Walter Lang,et al.  From embedded sensors to sensorial materials—The road to function scale integration , 2011 .

[32]  Daniel J. Inman,et al.  A Review of Morphing Aircraft , 2011 .

[33]  Nikolaus Correll,et al.  Bloom Filter-Based Ad Hoc Multicast Communication in Cyber-Physical Systems and Computational Materials , 2012, WASA.

[34]  Nikolaus Correll,et al.  Establishing Multi-cast Groups in Computational Robotic Materials , 2012, 2012 IEEE International Conference on Green Computing and Communications.

[35]  Srinivas Vasista,et al.  Realization of Morphing Wings: A Multidisciplinary Challenge , 2012 .

[36]  Carmel Majidi,et al.  Soft-matter composites with electrically tunable elastic rigidity , 2013 .

[37]  Bernd Krieg-Brückner,et al.  From sensorial to smart materials: Intelligent optical sensor network for embedded applications , 2013 .

[38]  Terrence A. Weisshaar,et al.  Morphing Aircraft Systems: Historical Perspectives and Future Challenges , 2013 .

[39]  C. Majidi,et al.  Thermal analysis and design of a multi-layered rigidity tunable composite , 2013 .

[40]  Jianhua Zhang,et al.  On-Board Computing for Structural Health Monitoring with Smart Wireless Sensors by Modal Identification Using Hilbert-Huang Transform , 2013 .