3D printing technologies have advanced significantly in recent years allowing for additive manufacturing of new structured materials, expanding the range, function, and capabilities of manufactured components. In this work, flexible capacitors were produced using additive manufacturing and compared to commercially available capacitance sensors in strain testing. The sensors utilize thermoplastic polyurethane (TPU) printed using fused filament fabrication methods as a dielectric substrate and a combination of flexible inks for production of the conductive surface. Flexible inks were printed using syringe based deposition methods on a custom designed printer using the TPU substrate. Results demonstrated successful capacitor production with capacitance values ranging from 2–70 pF depending on geometry, material, and printing conditions. The 3D printed flexible capacitors were characterized over a frequency range of 100 Hz to 10 kHz and compared to commercial roll-to-roll produced capacitors. Strain testing was conducted from 0–50% strain using a mechanical testing machine for the range of sensors and final capacitance post strain was measured to calculate deviation from original capacitance values. The sensors exhibited a relatively linear increase in capacitance when strained and returned to a resting position upon release of strain with minimal hysteresis effects, demonstrating their utility as 3D printed sensors.

As a smart material thermal shape memory alloys (SMAs) feature actuator behavior combined with self-sensing capabilities. With their high energy density and design flexibility they are predestined to be used in soft robotics and the emerging field of morphing surfaces. Such shape changing surfaces can be used for novel human-machine interaction (HMI) elements based on mode-/situation-dependent interfaces that may be applied to all kind of machines, appliances and smart home devices as well as automotive interiors. Since many of those contain textile surfaces, it is of special interest to place SMA-based actuator-sensor-elements beneath a textile cover or integrated them in the textile itself. In this study, the unique features of SMAs are used to design a system which represents an active “morphing” button. It can lower into the surface it is integrated in, pops up to be used and shows a proportional signal output depending on the pushing stroke. The system is characterized concerning haptics and sensor technology. The button consists of a TPU structure, to which two NiTi wires are attached. When activated, the SMAs contract and the structure curves upwards. The user can now push on the device to use it as a button. In the future, the use of SMA wires and for example TPU fibers enables direct integration in the production process of a possible smart and functional textile.

A machine learning algorithm that performs multifidelity domain decomposition is introduced. While the design of complex systems can be facilitated by numerical simulations, the determination of appropriate physics couplings and levels of model fidelity can be challenging. The proposed method automatically divides the computational domain into subregions and assigns required fidelity level, using a small number of high fidelity simulations to generate training data and low fidelity solutions as input data. Unsupervised and supervised machine learning algorithms are used to correlate features from low fidelity solutions to fidelity assignment. The effectiveness of the method is demonstrated in a problem of viscous fluid flow around a cylinder at Re ≈ 20. Ling et al. built physics-informed invariance and symmetry properties into machine learning models and demonstrated improved model generalizability. Along these lines, we avoid using problem dependent features such as coordinates of sample points, object geometry or flow conditions as explicit inputs to the machine learning model. Use of pointwise flow features generates large data sets from only one or two high fidelity simulations, and the fidelity predictor model achieved 99.5% accuracy at training points. The trained model was shown to be capable of predicting a fidelity map for a problem with an altered cylinder radius. A significant improvement in the prediction performance was seen when inputs are expanded to include multiscale features that incorporate neighborhood information.

This work draws inspiration from totipotent cellular systems to design smart materials whose compositions and properties can be learned or evolved. Totipotency refers to the inherent genetic potential of a single cell to adapt and produce all types of differentiated cells within an organism. To study this principal and apply it synthetically, tissue-like compartmentalized assemblies are constructed via lipid membrane-separated aqueous droplets in a hydrophobic medium through the droplet interface bilayer (DIB) method. Within our droplets, we explore synthetic totipotency via cell-free reactions including actin polymerization and cell free protein synthesis (CFPS). The transcription and translation of our CFPS reactions are controlled by stimuli-responsive riboswitches (RS). Via this scheme, adaptable material properties and functions are achieved in vitro via protein production from cell-free machinery administered through RS governance. Here, we present thermally or chemically-triggered riboswitches for orthogonal production of representative fluorescent protein products, as well functional proteins. To characterize the material properties of target proteins, we study the formation of polymerized actin shells to stabilize organically-encased droplets and span DIBs. We present a modified protocol for chemically-triggered actin polymerization as well as a thermally triggered actin RS. We characterize theophylline (TP)-triggered production of alpha hemolysin (α-HL) through CFPS and synthesized an organic-soluble trigger that can be sensed from the oil phase by a RS in an aqueous bioreactor droplet. We also demonstrate increased droplet conductivity when CFPS α-HL products are incorporated in DIBs. This interdisciplinary work involves cell culture, gene expression, organic synthesis, vesicle formation, protein quantification, tensiometry, droplet aspiration, microplate fluorescence/absorption experiments, fluorescent microscopy, and electrophysiology. This project is an essential design analysis for creating smart, soft materials using synthetic biology and provides motivation for artificial tissues capable of adapting in response to external stimuli.

In machine tool engineering, the impact of thermal issues on machine precision and efficiency has been outlined in numerous studies. One of the major challenges is the energy-efficient distribution of heat within the machine structure. In order to control occurring heat fluxes without additional energy input into the machine tool, smart materials can be used for load-dependent adjustment of heat transfer characteristics. The present study illustrates the development and examination of heat transfer switch mechanisms using shape memory alloys. Experimental and numerical results demonstrate how different types of actuators can be used to enable an energy self-sufficient thermal switch function between heat source and heat sink. Different scenarios are considered and the combination of thermal switches with highly conductive heat-transfer devices and latent heat storages is evaluated.

This paper proposes a broadband rotational energy harvesting setup by using micro piezoelectric energy harvester (PEH). When driven in different rotating speed, the PEH can output relatively high power which exhibits the phenomenon of frequency up-conversion transforming the low frequency of rotation into the high frequency of resonant vibration. It aims to power self-powered devices used in the applications, like smart tires, smart bearings, and health monitoring sensors on rotational machines. Through the excitation of the rotary magnetic repulsion, the cantilever beam presents periodically damped oscillation. Under the rotational excitation, the maximum output voltage and power of PEH with optimal impedance is 28.2 Vpp and 663 μW, respectively. The output performance of the same energy harvester driven in ordinary vibrational based excitation is compared with rotational oscillation under open circuit condition. The maximum output voltage under 2.5g acceleration level of vibration is 27.54 Vpp while the peak output voltage of 36.5 Vpp in rotational excitation (in 265 rpm).

In the new data intensive world, predictive maintenance has become a central issue for the modern industrial plants. Monitoring of electric machinery is one of the most important challenges in predictive maintenance. Adaptive manufacturing processes/plants may be possible through the monitored conditions. In this respect, several attempts have been made to utilize deep learning algorithms for rotating machinery fault detection and diagnosis. Among them, deep autoencoders are very popular, because of their denoising effect. They are also implemented in electric machinery fault diagnostics in order to obtain lower order representation of signals. However, none of these efforts regard the autoencoders as compression units. Bearing in mind that spectra of vibration and current signals that are collected from electric machinery are critical instruments for detection and diagnosis of their faults, we propose that deep stacked autoencoder can be utilized as spectrum compression units. The performance of the proposed strategy are assessed using a bearing data set in three ways: (1)Rule-based classifiers are implemented on raw and compressed-decompressed spectrum and their performance are compared. (2) It is shown that the several machine learning classifiers such as support vector machines, artificial neural networks and k-nearest neighbour classifiers on compressed-decompressed spectrum achieves the performance of them on raw data. (3) A multi-layer perceptron (MLP) classifier is implemented on the low dimensional representation and it is demonstrated that the strategy of employing the same autoencoder as pretraining of feature extraction module cannot outperform the performance of this MLP classifier.

Shape Memory Alloys (SMAs) are often used for robotic, biomedical, and aerospace applications because of their unique ability to undergo large amounts of stress and strain during thermomechanical loading compared to traditional metals. While SMAs such as NiTi have been used in wire, plate, and tubular forms, NiTi as a woven dry fabric has yet to be analyzed for use as protective materials and actuators. Applications of SMA fabric as a “passive” material include shields, seatbelts, watchbands and window screens. Applications as an “active” material include robotic actuators, wearable medical and therapy devices, and self-healing shields and screens. This paper applies a macro-mechanical model from composites analysis to NiTi plain woven fabric to determine the effective elastic constants. The fabric model is based on actual weave geometry, including the presence of open gaps and wire cross-sectional area, and with the same diameter and alloy in the warp and weft. A woven NiTi ribbon has been manufactured (Figure 1) using a narrow weaving machine and has been tested in uniaxial tension. Planar fabric constants were measured at a range of temperatures. The analytically and experimentally derived constants for various weave patterns and cover factor combinations are presented and compared. It was determined that in uniaxial tension the fabric behaves like a collection of unidirectional wires, but has 78% of the rigidity, on average, across all test temperatures. This result is predicted by the fabric model with a 16% error, demonstrating that the proposed analytical model offers a useful tool for design and simulation of SMA fabrics.

Knitted Textiles made from Nickel-Titanium (NiTi) shape memory alloy wires are a new structural element with enhanced properties for a variety of applications. Potential advantages of this structural form include enhanced bending flexibility, tailorable in-plane, and through-thickness mechanical performance, and energy absorption and damping. Inspection of the knit pattern reveals a repeating cell structure of interlocking loops. Because of this repeating structure, knits can be evaluated as cellular structures that leverage their loop-based architecture for mechanical robustness and flexibility. The flexibility and robustness of the structure can be further enhanced by manufacturing with superelastic NiTi. The stiffness of superelastic NiTi, however, makes traditional knit manufacturing techniques inadequate, so knit manufacturing in this research is aided by shape setting the superelastic wire to a predefined pattern mimicking the natural curve of a strand within a knit fabric. This predefined shape-set geometry determines the outcome of the knit’s mechanical performance and tunes the mechanical properties. In this research, the impact of the shape setting process on the material itself is explored through axial loading tests to quantify the effect that heat treatment has on a knit sample. A means of continuously shape setting and feeding the wire into traditional knitting machines is described. These processes lend themselves to mass production and build upon previous textile manufacturing technologies. This research also proposes an empirical exploration of superelastic NiTi knit mechanical performance and several new techniques for manufacturing such knits with adjustable knit parameters. Displacement-controlled axial loading tests in the vertical (wale) direction determined the recoverability of each knit sample in the research and were iteratively increased until failure resulted. Knit samples showed recoverable axial strains of 65–140%, which could be moderately altered based on knit pattern and loop parameters. Furthermore, this research demonstrates that improving the density of the knit increases the stiffness of the knit without any loss in recoverable strains. These results highlight the potential of this unique structural architecture that could be used to design fabrics with adjustable mechanical properties, expanding the design space for aerospace structures, medical devices, and consumer products.

Robotic Materials are materials that have sensing, computation and, possibly actuation, distributed throughout the bulk of the material. In such a material, we envision semiconducting polymer based sensing, actuation, and information processing for on-board decision making to be designed, in tandem, with the smart product that will be implemented with the smart material. Prior work in printing polymer semiconductors for sensing and cognition have focused on highly energetic inkjet printing. Alternatively, we are developing liquid polymer extrusion processes to work hand-in-hand with existing solid polymer extrusion processes (such as Fused Deposition Manufacturing - FDM) to simultaneously deposit sensing, computation, actuation and structure. We demonstrate the successful extrusion printing of conductors and capacitors to impedance-match a new, higher-performance organic transistor design that solves the cascading problem of the device previously reported and is more amenable to liquid extrusion printing. Consequently, these printed devices are integrated into a sheet material that is folded into a 3-D, six-legged walking machine with attached electric motor.

Photochemical actuation systems, those that employ coupled photo-stimuli and chemical reactions to power and control mechanical motion, have the potential to combine the benefits of precise light driven control with chemical energy storage. Furthermore, these systems are inherently soft, making them ideal for use in the emerging field of soft robotics. However, such systems have received comparatively little attention, perhaps due to the poor cycle life and limited activation time of past systems. Here we address these two challenges by switching from the technique of past systems, that of aqueous photoacid solutions and pH-responsive hydrogel actuators, to one employing organic solvents instead. While this switch of solvents successfully eliminates cycle life constraints and allows for tuning of the activation recovery time it also shifts the relative activation point of the hydrogel actuator in such a way that actuation is no longer observed. Several options for addressing this are discussed, with the prospect of using the lessons learned within to make a more informed selection of a different photoacid compound considered the most feasible. While the exploration of photochemical actuation systems is still in a nascent stage, we have great hope for such systems to form the basis of future smart machines with unique functionality.

In this paper, we present characterization results for thermal, mechanical, and electrical properties of a 3D-printed conductive polylactic acid (PLA) composite material. The material exhibits electrically controllable stiffness, allowing for the fabrication of novel robotic and biomedical devices. In particular, an applied voltage induces a Joule heating effect, which modulates the material stiffness. Dumbbell samples are 3D-printed and loaded into a universal testing machine (UTM) to measure their Young’s moduli at different temperatures. The conductive PLA composite shows 98.6% reduction of Young’s modulus, from 1 GPa at room temperature to 13.6 MPa at 80 °C, which is fully recovered when cooled down to its initial temperature. Measurements with differential scanning calorimeter (DSC) and thermal diffusivity analyzer are conducted to investigate the thermal behavior of this material. Electrical conductivity of the material is measured under different temperatures, where the resistivity increases about 60% from 30 °C to 100 °C and hysteresis between the resistivity and the temperature is observed. These tests have shown that the conductive PLA composite has a glass transition temperature (Tg) of 56.7 °C, melting point (Tm) of 153.8 °C, and thermal conductivity of 0.366 W/(mK). The obtained results can be used as design parameters in finite element models and computational tools to rapidly simulate multi-material components for several applications such as object manipulation, grasping, and flow sensing.

Airfoil camber adaptation may be the key for the performance improvement of wings for many specific applications, including shorter take-off distance, compensation of weight variation and so on. Following the successful experiences gained in SARISTU, where an adaptive trailing edge device was developed for medium to large size commercial aircraft, the authors propose to exploit the developed architecture to a small aircraft wing. The basic reasons behind that mainly rely on the associated possibility to access easier implementation onto a real aircraft instead of referring to wing segments for wind tunnel or ground tests. In this way, many operative problems are faced, that would be otherwise neglected in usual lab experimentation. First of all, the integration of the proposed device onto a flying machine, that in turn pose the problem of facing the interface with the existing systems. Secondly, the necessity of including the device into the flap while fully preserving its current functionality. Furthermore, the necessity of developing a robust design process that allows having the release of the permit-to-fly. Each of the above steps, non-exhaustive in illustrating the difficulty of the addressed challenge, is structured in many other sub-segments, ranging from a suitable FHA analysis to a full re-design of the existing high lift systems or the adaptation of the architecture of the reference morphing trailing edge itself. This last item poses the classical challenge of the scaling issues, requiring the structural and the actuation subsystems to entirely fit into the new geometry. The objective of the present research is then to verify the feasibility of applying a certain architectural morphing philosophy onto a real aircraft, taking into account all the operational difficulties related to such an operation. This paper reports the activities related to the exploitation of the reference adaptive structural architecture, to the geometry of a flap of a small aircraft. In detail, the system layout is presented, followed by a FE analysis of the structural system under the operational loads and an estimation of the weight penalty associated to this transformation. Interfaces of the flap system with the main aircraft body are considered as constraints to the design development, so that the only flap is affected.

State-of-the-art actuators that produce rotatory motion and torsional moment are based on either combustion engines, electro-motors, hydraulic or pneumatic machines. Each of these actuation methods has several drawbacks. All of these systems often come with high initial costs, big weight and need a lot of construction space because of their dimensions. Shape memory alloys are known for their superior energy density. That allows for the construction of very compact and light-weight actuator systems. In this paper, the design and construction of a light weight rotational actuator based on SMA wires is presented. The design is based on a modular concept, with each module contributing to the total rotational radius. This way, the actuator can be custom fitted to specific application needs.

Due to their very high applicable forces, frequencies and their stiffness, piezoceramics are feasible to serve as integrated actuators in machines. The application of piezo based components in production engineering was subject of plenty of investigations in the past. That focuses primarily on systems for condition monitoring, structural vibration reduction or chatter prevention. However there are currently also few approaches that aim to use piezo actuators for directly induced vibrations for improved machining processes. In this paper we present an overview of such systems, their parameters and the technological background. Known approaches will be classified and divided into groups considering their working principles, actuator performance and application technology. Ultra sonic machining (USM) for example is a comparatively old approach which applies ultrasonic vibrations of a sonotrode to an abrasive slurry for machining hard, brittle and nonconductive material. Vibration assisted machining (VAM) systems are rather different. They are characterized by low stroke, uncontrolled but highly frequent resonant vibrations of the tool to achieve enhanced chipping behavior or generally enable to machine certain hard materials. Fast Tool servo (FTS) systems are even more complex. They apply an overlaid controlled movement of the cutting edge to manufacture microstructures or possess to manufacture complex geometries like non circular bores or turned parts. Selected systems will be presented in detail showing their design approach, actuator parameters, control considerations and measurement data of manufactured parts. These will be for instance an ultrasonic deep hole drilling tool, a form honing system, an active spindle mounting for micro contouring and a piezo based machine table for manufacturing non circular bores in small workpieces. Summarized the existing systems will be compared considering their advantages and eventual hindrances. Beyond that the outlook will show problems, which need to be solved in the future to enable piezo assisted machining systems a more comprehensive application in manufacturing.

This paper deals with active vibration isolation of unbalance-induced oscillations in rotors using gain-scheduled H ∞ -controller via active bearings. Rotating machines are often exposed to gyroscopic effects, which occur due to bending deformations of rotors and the consequent tilting of rotor disks. The underlying gyroscopic moments are proportional to the rotational speed and couple the rotor’s radial degrees of freedom. Accordingly, linear time-varying models are well suited to describe the system dynamics in dependence on changing rotational speeds. In this paper, we design gain-scheduled H ∞ -controllers guaranteeing both robust stability and performance within a predefined range of operating speeds. The paper is based on a rotor test rig with two unbalance-induced resonances in its operating range. The rotor has two discs and is supported by one active and one passive bearing. The active support consists of two piezoelectric stack actuators and two collocated piezoelectric load washers. In addition, the rig is equipped with four inductive displacement sensors located at the discs. Closed-loop performance is assessed via isolation of unbalance-induced vibrations using both simulation and experimental data. This contribution is the next step on our path to achieving the long-term objective of combined vibration attenuation and isolation.

Circular saws are a common tool for cutting a variety of materials like stone, wood or alloys. Cutting results are significantly influenced by vibrations occurring during processing. Negative consequences are for example increased cutting width and noise emissions. Vibration results from impulses generated at the entrance of the tool teeth into the work piece, from axial run of the cutting tool as well as vibrations transmitted from the machines drive. Therefore, the implementation of effective and cost efficient damping measures is of significant interest. Passive damping approaches are favored because of their low costs. One approach to dampen vibrations in circular tools and tool flanges passively is the use of shape memory alloys (SMA) as damping elements. SMA and especially NiTi are able to convert large amounts of mechanical stress into heat energy by a stress induced austenite-martensite phase transformation providing the potential to dampen vibrations with more compact damping elements in contrast to other common damping materials like steel or copper used in circular saws. SMA are suitable for damping low frequencies at high amplitudes, e.g. during earthquakes and the damping of single or repetitive shocks, such as those occurring in positioning. The attenuation of higher-frequency vibrations caused by machining with fast rotating cutting tools has so far been considered inadequate but has not been sufficiently investigated in relevant frequency ranges for industrial circular saws. This paper compares the damping properties of NiTi to those of copper and steel for industrial circular saws. Therefore, the first chapter introduces different sources and types of vibrations in industrial cutting processes while the second chapter describes exemplarily the vibrations occurring in an industrial circular saw. Based on this, the third chapter illustrates common approaches to modify the static and dynamic behavior of circular saws. The fourth chapter gives a brief description of internal damping mechanism, especially the damping mechanism of SMA. The experimental methodology and evaluation of NiTi, steel and copper is in the focus of the fifth chapter. The paper concludes with a summary of findings and an outlook on following work packages.

Polymeric composite laminates play a vital role in the fabrication of strong, lightweight materials. Composites also play a critical role in the aerospace and automotive industries. They are the very things that protect us from harsh environments. Due to widespread usage, it is important to understand how these materials age and perform over time. The advantages of polymeric composites are high rigidity, high strength to weight ratio, corrosion resistance, high fatigue strength, low thermal expansion, and manufacturability. The advantages of polymeric composite parts in machines and vehicles are low mass, high speed of operation, excellent fatigue resistance, quiet running due to shock absorption, easy installment and demounting, low maintenance cost, low energy costs during production and life cycle. Despite the advantages, there are concerns regarding the long-term durability of these composites especially when it comes to performances under critical and varying conditions. Since Terfenol-D, a magnetostrictive material will be placed in these polymeric composites for structural health monitoring, it is imperative to understand the microstructure of the particles and their net effect on the resin, e.g. distortions, volume fraction, and induced strain. Terfenol-D (Tb 1−x Dy x Fe 2 ) is of the cubic laves phase structure in which there is less plastic deformation which in turn makes the particles hard and brittle.

In the paper the problem of examining of a damaged tool in the manufacturing process is presented by the example of the identification of a damaged die for creating a screw drive on a screw head. The operation of the screw head production is known as cold heading. One of the production stage is when a die cuts the head of the screw blank into an appropriate shape. Unfortunately, the die is often damaged before reaching its limit. In this case, the faulty semi-finished products are further processed because the cold heading is only the first operation required to produce a screw. If screws made of high-quality pure stainless steel are considered the economic loss is significant. The measurement automatic systems for identification of damaged dies can be found in the newest machines but they are in minority in comparison to the older ones which work without such systems. It was the reason why attempt was made to construct the prototype diagnostic system for die state assessment, which is presented in the article.

A digital energy harvester that captures electrical energy from complicated random or multimodal vibrations is proposed. The novel energy harvester is digital, autonomous, and controlled by a self-powered microprocessor. The digital self-powered microprocessor automatically and synchronously changes the circuit components with the vibration phase, and can therefore achieve autonomous harvesting. The multifunctional and self-controlled microprocessor is only driven by the voltage of the piezoelectric transducer, and no external power is required. The harvester exhibits great potential and versatility and is applicable to many machines and devices.