title: Towards sensor array materials: can failure be delayed?
abstract: Further to prior development in enhancing structural health using smart materials, an innovative class of materials characterized by the ability to feel senses like humans, i.e. 'nervous materials', is discussed. Designed at all scales, these materials will enhance personnel and public safety, and secure greater reliability of products. Materials may fail suddenly, but any system wishes that failure is known in good time and delayed until safe conditions are reached. Nervous materials are expected to be the solution to this statement. This new class of materials is based on the novel concept of materials capable of feeling multiple structural and external stimuli, e.g. stress, force, pressure and temperature, while feeding information back to a controller for appropriate real-time action. The strain-stress state is developed in real time with the identified and characterized source of stimulus, with optimized time response to retrieve initial specified conditions, e.g. shape and strength. Sensors are volumetrically embedded and distributed, emulating the human nervous system. Immediate applications are in aircraft, cars, nuclear energy and robotics. Such materials will reduce maintenance costs, detect initial failures and delay them with self-healing. This article reviews the common aspects and challenges surrounding this new class of materials with types of sensors to be embedded seamlessly or inherently, including appropriate embedding manufacturing techniques with modeling and simulation methods.
authors.affiliation: Mechanical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
authors.forename: Samir
authors.initials: S
authors.lastname: Mekid
authors.affiliation: Mechanical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia; CENT, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
authors.forename: Nouari
authors.initials: N
authors.lastname: Saheb
authors.affiliation: Mechanical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
authors.forename: Shafique M A
authors.initials: SM
authors.lastname: Khan
authors.affiliation: Electrical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
authors.forename: Khurram K
authors.initials: KK
authors.lastname: Qureshi
keywords: embedded sensors; nervous materials; sensor materials; smart materials