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This paper presents 3D printed strain sensors based on alkali activated cement repairs, demonstrating a fixed-cost method for remotely deploying a combined monitoring and maintenance technology for construction. Experimental protocols to quantitatively assess the compatibility of cements and 3D printing processes are defined and investigated in this paper. The strain sensing response of printed self-sensing cements is then investigated under compression and tension by monitoring changes in material electrical impedance. Gauge factors for self-sensing repairs printed onto concrete substrates were 8.6 ± 1.6 under compression, with an average adhesion strength of 0.6 MPa between printed repair and concrete substrate. Gauge factors for repairs printed onto glass fibre reinforced polymers were 38.4 ± 21.6 under tension: more variable than for concrete substrates due to incompatibilities between the repair and the polymer substrate. This proof-of-concept is a step towards monitoring and maintenance methods that are more compatible with the time and cost drivers of modern construction.

Chloride-induced corrosion of reinforced concrete costs the global economy billions of dollars every year. Despite concerted research effort, the non-invasive, continuous monitoring of sodium chloride in concrete structures is still an unsolved problem. Here, we outline a first-time demonstration of a sodium chloride sensor based on alkali-activated cements: a class of cementitious, electrolytically conductive materials which are typically used for concrete construction and repair. In this work, internal sodium chloride concentrations ranging from 0–22 wt% were measured independently of moisture contents via shifts in electrical impedance. The typical sodium chloride measurement precision was 0.85 wt%. Non-linearity of the sensor response due to signal saturation began at sodium chloride concentrations >5 wt%. We use experimental measures of ion dynamics to link this saturation to the deleterious effect of high concentrations on ion mobility. This study demonstrates sensor feasibility, and provides new experimental evidence to further our understanding of ionic conductivity mechanisms in these materials. The work will allow for the development of self-sensing repair and construction materials for locating and quantifying sodium chloride levels within concrete structures — a valuable technology for supporting concrete health monitoring and maintenance.

In this work, structural health monitoring data is applied to underpin a long-term wind farm lifetime extension strategy. Based on the outcome of the technical analysis, the case for an extended lifetime of 15 years is argued. Having established the lifetime extension strategy, the single wind turbine investigated within a wind farm is subjected to a bespoke economic lifetime extension case study. In this case study, the local wind resource is taken into consideration, paired with central, optimistic, and pessimistic operational cost assumptions. Besides a deterministic approach, a stochastic analysis is carried out based on Monte Carlo simulations of selected scenarios. Findings reveal the economic potential to operate profitably in a subsidy-free environment with a P90 levelised cost of energy of £25.02 if no component replacement is required within the nacelle and £42.53 for a complete replacement of blades, generator, and gearbox.

This paper provides an overview of recent highlights and new work from our development of robotically deployed, self-sensing alkali-activated materials: a cement technology which can be used to simultaneously repair and monitor concrete structures. The paper focuses on deployments using robotic spray coating and 3D printing, and on moisture, chloride, and damage monitoring, showing pilot data. The electrical impedance of self-sensing materials follows an exponential decrease with increasing levels of moisture, chloride contamination and temperature as expected. The work demonstrates the promise of using these novel self-sensing materials for measuring environmental measurands that are responsible for the majority of concrete structural health degradation in the field.

Monitoring civil infrastructure is paramount due to the ageing of existing civil infrastructure. Apart from electronic devices, self-sensing materials are also used for these types of applications. In this paper, we present 3D printed self-sensing coatings for civil infrastructure. The coating is an alkali-activated material, which attains similar properties to ordinary Portland cement binders but is more electrically conductive due to the alkali ions in the matrix. The coatings were printed onto concrete cubes and glass fiber reinforced plastic sheets to investigate their strain response under cyclic loading in compression and tension. The electrical response under compression presented reasonable repeatability among loading cycles. In tension, the patches presented slight repeatability issues in subsequent cycles. For both compression and tension the patches present a linear electrical response in regards to the applied strain. The gauge factor of the coatings was calculated as 657 for compression and 144 for tension. 3D printed coatings have shown the potential of acting as a nondestructive evaluation method of existing infrastructure.

In this paper, we showcase initial results from a bespoke, low-cost interrogator for complex impedance measurements of our robotically deployed self-sensing cement (geopolymer) technology for concrete monitoring and maintenance. Our low-cost (£30, $40 USD) interrogation system is benchmarked against the performance of a £12k ($16k USD) commercially available lab-spec electrical impedance analyser. Results show the low-cost interrogator is able to match the commercial interrogation system well-enough for the field measurement of impedance, with an impedance root mean square error (RMSE) of ±5.4 % for an ideal cell. For pure geopolymer samples, similar results are found, with an RMSE of ±5.2 %. During patch measurements, although non-linearity was witnessed, the low-cost interrogator showcased the ability to measure the impedance and impedance-frequency variations. Therefore, the first iteration of low-cost interrogator design shows promise for monitoring geopolymer self-sensing repair complex impedances in the field.

Sensors and new materials can support optimised concrete maintenance, and produce the data needed to justify new, low carbon structural designs. While these technologies are affordable, the process of manual installation in a construction context comes with acute and unfamiliar risks to productivity, personnel safety, and confidence in the quality of workmanship. The installation of smart materials using robotics could address some of these issues, but there are few proofs-of-concept at the time of writing. Here, we present a robotically controlled process for spray coating geopolymers — a class of self-sensing concrete repair materials. By tuning mix design, robotic toolpaths and spray dispenser parameters, we show reliable and automated spray coating of 250 mm2 patches in a laboratory setting. The cured geopolymer has a compressive strength of 20 MPa, and a bond strength to the concrete substrate of 0.5 MPa. Electrical interrogation of patches, via a set of four electrodes, produces strain and temperature measurements of the underlying concrete substrate with resolutions of 1 μe and 0.2 °C, respectively. This demonstration multifunctional material deposition using robotics is a step towards remote, traceable, and low-risk technology deployment across civil engineering sectors. This could support more widespread adoption of novel concrete health monitoring and repair systems in future.

Multifunctional coating materials have enjoyed extensive development within civil engineering in the last few decades, with numerous proposals for self-sensing and self-healing repairs. Less thought has been afforded to coating material deployment, but a reliance on conventional manual methods is leading to high costs and variabilities in performance. This is prohibiting the application of new materials in the field. This paper addresses this issue by outlining, for the first time a 3D printable temperature sensing repair for concrete. The multifunctional material used in this study is a geopolymer: a durable alternative to ordinary Portland cement repairs, which can be electrically interrogated to act as a sensor. In this paper, we outline the material and 3D printing process development, and demonstrate 3D printed repair patches with a temperature sensing precision of 0.1 °C, a long-term sensing repeatability of 0.3 °C, a compressive strength of 24 MPa, and an adhesion strength to concrete of 0.6 MPa. The work demonstrates the feasibility of using additive manufacturing as a new means of applying repairs to concrete substrates, and provides one clear pathway to removing some of the barriers to the field deployment of multifunctional materials in a civil engineering context. The process shown here could enhance the design versatility of self-sensing repairs, unlock remote deployment, and de-cost and de-risk actions that prolong the lifespan and performance of existing concrete structures.

Continuous monitoring allows informed maintenance to more effectively prolong the lifespan of civil infrastructure. In this paper, we outline a 3D printing process for smart materials that could simultaneously support the distributed sensing and maintenance of reinforced concrete structures. The smart material employed in this research is alkali-activated metakaolin. It is already well-known that alkali activated metakaolin can attain comparable mechanical characteristics to ordinary Portland cement and is thus able to repair and restore the structural integrity of damaged concrete infrastructure. However, these materials also exhibit a higher electrical conductivity than conventional cements due to the presence of free ions in their matrix. This allows temperature and strain to be monitored through variations in electrical impedance. Here, we demonstrate additive manufacturing of these materials to allow remote installation, with greater design flexibility and repeatability. In this paper, the electrical response of printed samples is outlined, and we discuss how sensor data can be interpreted to detect strain variations for structural health monitoring applications.

Self-sensing cements offer a unique opportunity to unify our approach to the remote monitoring and maintenance of concrete assets. The objective of this work is to develop a remotely-deployable, “smart cement” technology that can simultaneously repair damage, monitor underlying structural strain and attempt to detect further defects. Automating the deployment of these materials using robotics will improve the efficiency of installation and permit application to areas with restricted access or hazardous environments. Here, we present our latest progress in manufacturing and robotically spraycoating smart cement sensor-repairs onto concrete substrates. Spray-coating provides controllable, high pressure distribution of the material, providing high geometrical accuracy in addition to high adhesion. The smart cements are based on metakaolin geopolymers — a novel class of cement-like binders that cure to a strong, chemically resistant, electrically conductive shell. In this work, the manufacturing process of the geopolymer patch is presented before investigating the sensing capability. Initial results regarding the temperature and strain sensing of the patch demonstrate the dependence of measurements on the frequency of the applied potential. Furthermore, exploiting this dependence presents the possibility of self-compensating for temperature.

In this paper, preliminary results from a concrete fatigue experiment using a custom built machine are demonstrated. A pre-cracked concrete member is instrumented with bespoke metallic-bonded and epoxy-bonded fiber Bragg grating (FBG) displacement sensors, retrofitted over the crack. Fatigue loading is applied to the beam, with cycle magnitudes replicating results from a previous industrial trial concerning structural health monitoring (SHM) of a wind turbine foundation. Results are compared to an FEM model for verification. The new metallic-bonded crack displacement sensor design is compared in performance with the traditional epoxy-bonded design. Both sensors were sufficiently resilient under dynamic loading to successfully undergo 105 cycle fatigue test. The sensors display a linear relationship with respect to one another; however, from the initial thermal characterization of the devices between 20 and $65^{\circ}C$, the epoxy-bonded sensor exhibited considerable drift with every subsequent temperature cycle while the metallic-bonded construction was stable within the experimental error. The set up can be used over a long term to validate in situ results from distributed SHM sensors and for initial testing of sensors and data analytics strategies prior to any future field installations.

This paper presents preliminary results for metal-packaged fiber Bragg grating strain and temperature sensors designed specifically for structural health monitoring in civil engineering applications. The laboratory experiments show that the in-house manufactured metal-packaged sensors are sufficiently resilient, under dynamic loading, to successfully undergo a million cycle fatigue test without adverse deterioration in performance. In addition, from the thermal characterization of the devices, a conclusion can be drawn that the metal-packaged sensors offer superior performance over sensors assembled using epoxy bonding. These early results are very promising, inspiring confidence in the adopted methodologies, and giving the mandate to proceed with more detailed laboratory testing to evaluate reliability and lifetime of the transducers in the future work.

This paper presents experimental results from fatigue and static loading tests performed on both epoxy and braze-welded FBG strain sensors. Most FBG attachment methods are relatively understudied, with epoxy the most commonly used. Long curing times and humidity sensitivity during curing render epoxy inappropriate for certain implementations. This work shows that a bespoke braze-welded attachment design is able to achieve a higher static failure limit of 22kN when compared to strain gauge epoxies, which fail at 20kN. Both methods demonstrate high fatigue life, with no significant deterioration after two million cycles. Epoxy swelling was observed when the sensors were held at a relative humidity of 96%, applying ~0.6 mϵ of tension to the FBG, whereas a braze-weld attachment was unaffected by humidity.

This paper demonstrates how Tipping Point Analysis can be used to predict the onset of structural strain, induced by ice formation. In civil structures, water-ice transitions present many potential issues that can lead to structural damage or plant shutdowns. Examples include freeze-thaw damage in concrete and masonry, and ice build-up on moving parts such as wind turbine blades. Early indication of ice formation could prevent irreparable damage if this information could be used to actuate de-icing procedures. The transition considered in this work is the strain induced in a polypropylene container by the volume change of water as it freezes, measured using surface-mounted fibre-optic strain sensors. This first order phase transition can be detected early on using degenerate fingerprinting, which identifies “slowing down” of the noise prior to the critical point of the transition. Water was supercooled which, at freezing, causes a rapid increase in temperature, presenting an identifiable specific transition point for reference. The analysis was able to consistently predict freezing around 5-10 minutes prior to the transition. A linear relationship was found between mass calculated from the calorimetric equation and mass from experimental measurements. Strain could not be estimated from this mass, since the random process of freezing in an open top container causes an irregular distribution of force. These tests will allow the method and the model to be continually developed towards a more practical application.