This PDF file contains the front matter associated with SPIE Proceedings Volume 10171, including the Title Page, Copyright information, Table of Contents, and Conference Committee listing.

The paper proposes a fully mechanical air curtain system that will be powered solely by harvested energy from common hinged doors. The average person uses this type of door several times a day with an almost unconscious amount of applied force and effort. This leads to a high potential of energy to be harvested in doorways that see high traffic and frequent operation7 . Frequently opened door entry ways have always been regarded as a major element that causes significant energy loss and contaminated air conditions in buildings6 . Private companies, particularly those with warehouses, have introduced commercial electrical air curtains to block the open entrances from invading cold air11. This project intends to introduce an original design of air curtain which operates fans only when the door opens and closes, by directly converting door motion to fan rotation without any electronic motor or power cable. The air stream created by this device will prevent the transfer of outside air and contaminants. Research will be conducted to determine the most efficient method of harvesting energy from door use, and the prototyping process will be conducted to meet the required performance of current air curtain models.

Implementation of energy harvesting technology can provide a sustainable, remote power source for soldiers by reducing the battery weight and allowing them to stay in the field for longer periods of time. Among multiple energy conversion principles, electromagnetic induction can scavenge energy from wasted kinematic and vibration energy found from human motion. Hip displacement during human gait acts as a base excitation for an energy harvesting backpack system. The placement of a permanent magnet in this vibration environment results in relative motion of the magnet to the coil of copper wire, which induces an electric current. This current can be saved to a battery or capacitor bank installed on the backpack to be used to power electronic devices. The purpose of this research is to construct a reliable simulation model for an electromagnetic vibration energy harvester and use it for a multi-variable optimization algorithm to identify an optimal coil and magnet layout for highest power output. Key components of the coupled equations of motion such as the magnetic flux density and coil inductance are obtained using ANSYS multi-physics software or by measuring them. These components are fed into a harvester simulation model (e.g. coupled field equations of motion for the backpack harvester) that generates the electrical power output. The developed simulation model is verified with a case study including an experimental test. Then the optimal design parameters in the simulation model (e.g., magnet layout, coil width, outer coil diameter, external load resistance) are identified for maximum power. Results from this study will pave the way for a more efficient energy harvesting backpack while providing better insight into the efficiency of magnet and coil layout for electromagnetic applications.

Hydrogen gas can be harvested via the electrolysis of water. The gas is then fed into a proton exchange membrane fuel cell (PEMFC) to produce electricity with clean emission. Ionic polymer-metal composite (IPMC), which is made from electroplating a proton-conductive polymer film called Nafion encourages ion migration and dissociation of water under application of external voltage. This property has been proven to be able to act as catalyst for the electrolysis of pure water. This renewable energy system is inspired by photosynthesis. By using solar panels to gather sunlight as the source of energy, the generation of electricity required to activate the IPMC electrolyser is acquired. The hydrogen gas is collected as storable fuel and can be converted back into energy using a commercial fuel cell. The goal of this research is to create a round-trip energy efficient system which can harvest solar energy, store them in the form of hydrogen gas and convert the stored hydrogen back to electricity through the use of fuel cell with minimal overall losses. The effect of increasing the surface area of contact is explored through etching of the polymer electrolyte membrane (PEM) with argon plasma or manually sanding the surface and how it affects the increase of energy conversion efficiency of the electrolyser. In addition, the relationship between temperature and the IPMC is studied. Experimental results demonstrated that increases in temperature of water and changes in surface area contact correlate with gas generation.

Accidents like Fukushima Disasters push people to improve the monitoring systems for the nuclear power plants. Thus, various types of energy harvesters are designed to power these systems and the Thermoelectric Generator (TEG) energy harvester is one of them. In order to enhance the amount of harvested power and the system efficiency, the power management stage needs to be carefully designed. In this paper, a power converter with optimized Maximum Power Point Tracking (MPPT) is proposed for the TEG Energy Harvester to power the wireless sensor network in nuclear power plant. The TEG Energy Harvester is installed on the coolant pipe of the nuclear plant and harvests energy from its heat energy while the power converter with optimized MPPT can make the TEG Energy Harvester output the maximum power, quickly response to the voltage change and provide sufficient energy for wireless sensor system to monitor the operation of the nuclear power plant. Due to the special characteristics of the Single-Ended Primary Inductor Converter (SEPIC) when it is working in the Discontinuous Inductor Current Mode (DICM) and Continuous Conduction Mode (CCM), the MPPT method presented in this paper would be able to control the converter to achieve the maximum output power in any working conditions of the TEG system with a simple circuit. The optimized MPPT algorithm will significantly reduce the cost and simplify the system as well as achieve a good performance. Experiment test results have shown that, comparing to a fixed- duty-cycle SEPIC which is specifically designed for the working on the secondary coolant loop in nuclear power plant, the optimized MPPT algorithm increased the output power by 55%.

Energy Harvesting is a powerful process that deals with exploring different possible ways of converting energy dispersed in the environment into more useful form of energy, essentially electrical energy. Piezoelectric materials are known for their ability of transferring mechanical energy into electrical energy or vice versa. Our work takes advantage of piezoelectric material’s properties to covert thermal energy into electrical energy in an oscillating heat pipe. Specific interest in an oscillating heat pipe has relevance to energy harvesting for low power generation suitable for remote electronics operation as well as low-power heat reclamation for electronic packaging. The aim of this paper is develop a 2D multi-physics design analysis model that aids in predicting electrical power generation inherent to an oscillating heat pipe. The experimental design shows a piezoelectric patch with fixed configuration, attached inside an oscillating heat pipe and its behavior when subjected to the oscillating fluid pressure was observed. Numerical analysis of the model depicting the similar behavior was done using a multiphysics FEA software. The numerical model consists of a threeway physics interaction that takes into account fluid flow, solid mechanics, and electrical response of the harvester circuit.

This work presents a novel scalable and field-deployable framework for monitoring lithium-ion (Li-ion) battery state of charge (SoC) and state of health (SoH), based on ultrasonic guided waves using low-profile built-in piezoelectric transducers. The feasibility of this technique is demonstrated through experiments using surface-mounted piezoelectric disc transducers on commercial Li-ion pouch batteries. Pitch-catch guided-wave propagation is performed in synchronization with electrical charge and discharge cycling, and cycle life testing. Simple time-domain analysis shows strong and repeatable correlation between waveform signal parameters, and battery SoC and SoH. The correlation thus provides a building block for constructing a technique for accurate real-time monitoring of battery charge and health states using ultrasonic guided-wave signals. Moreover, capacity-differential signal analysis reveals the underlying physical changes associated with cyclic electrochemical activities and phase transitioning. This finding allows accurate pinpointing of the root cause of capacity fade and mechanical degradation. The results of this study indicate that the use of guided waves can potentially offer a new avenue for in-situ characterization of Li-ion batteries, providing insight on the complex coupling between electrochemistry and mechanics, heretofore not fully understood within the scientific community.

A new fiber-type Li-ion battery that consists of carbon nanotube fibers deposited with active materials has been developed and tested. The active materials, LiMn₂O₄ and Li₄Ti₅O₁₂, were deposited on the surface of carbon nanotube fibers in order to use as electrodes. Tensile strength of the CNT fibers with active material was measured by tensile tests to investigate the mechanical characteristics. Electrochemical property is also measured by a battery tester during charging and discharging. The results show that current discharge capacity is about 25 mAh/g between 3.0 V and 4.2 V. That means the fiber with active materials is good for an anode electrode. Mathematical material models considering the lithium concentration and the length of Li-C bond have been established in order to predict the effective elastic modulus of electrode composite materials.

Systems based on post-buckled structural elements have been extensively used in many applications such as actuation, remote sensing and energy harvesting thanks to their efficiency enhancement. The post-buckling snap- through behavior of bilaterally constrained beams has been used to create an efficient energy harvesting mechanism under quasi-static excitations. The conversion mechanism has been used to transform low-rate and low-frequency excitations into high-rate motions. Electric energy can be generated from such high-rate motions using piezoelectric transducers. However, lack of control over the post-buckling behavior severely limits the mechanism’s efficiency. This study aims to maximize the levels of the harvestable power by controlling the location of the snapping point along the beam at different buckling transitions. Since the snap-through location cannot be controlled by tuning the geometry properties of a uniform cross-section beam, non-uniform cross sections are examined. An energy-based theoretical model is herein developed to predict the post-buckling response of non-uniform cross-section beams. The total potential energy is minimized under constraints that represent the physical confinement of the beam between the lateral boundaries. Experimentally validated results show that changing the shape and geometry dimensions of non- uniform cross-section beams allows for the accurate control of the snap-through location at different buckling transitions. A 78.59% increase in harvested energy levels is achieved by optimizing the beam’s shape.

Recently, there has been increasing demand in developing low-cost, effective structure health monitoring system to be embedded into 3D-woven composite wind turbine blades to determine structural integrity and presence of defects. With measuring the strain and temperature inside composites at both in-situ blade resin curing and in-service stages, we are developing a novel scheme to embed a resistive-strain-based thin-metal-film sensory into the blade spar-cap that is made of composite laminates to determine structural integrity and presence of defects. Thus, with fiberglass, epoxy, and a thinmetal- film sensing element, a three-part, low-cost, smart composite laminate is developed. Embedded strain sensory inside composite laminate prototype survived after laminate curing process. The internal strain reading from embedded strain sensor under three-point-bending test standard is comparable. It proves that our proposed method will provide another SHM alternative to reduce sensing costs during the renewable green energy generation.

The increasing demand for carbon neutral energy in a challenging economic environment is a driving factor for erecting ever larger wind turbines in harsh environments using novel wind turbine blade (WTBs) designs characterized by high flexibilities and lower buckling capacities. To counteract resulting increasing of operation and maintenance costs, efficient structural health monitoring systems can be employed to prevent dramatic failures and to schedule maintenance actions according to the true structural state. This paper presents a novel methodology for classifying structural damages using vibrational responses from a single sensor. The method is based on statistical classification using Bayes’ theorem and an advanced statistic, which allows controlling the performance by varying the number of samples which represent the current state. This is done for multivariate damage sensitive features defined as partial autocorrelation coefficients (PACCs) estimated from vibrational responses and principal component analysis scores from PACCs. Additionally, optimal DSFs are composed not only for damage classification but also for damage detection based on binary statistical hypothesis testing, where features selections are found with a fast forward procedure. The method is applied to laboratory experiments with a small scale WTB with wind-like excitation and non-destructive damage scenarios. The obtained results demonstrate the advantages of the proposed procedure and are promising for future applications of vibration-based structural health monitoring in WTBs.

In recent years, image processing techniques are being applied more often for structural dynamics identification, characterization, and structural health monitoring. Although as a non-contact and full-field measurement method, image processing still has a long way to go to outperform other conventional sensing instruments (i.e. accelerometers, strain gauges, laser vibrometers, etc.,). However, the technologies associated with image processing are developing rapidly and gaining more attention in a variety of engineering applications including structural dynamics identification and modal analysis. Among numerous motion estimation and image-processing methods, phase-based video motion estimation is considered as one of the most efficient methods regarding computation consumption and noise robustness. In this paper, phase-based video motion estimation is adopted for structural dynamics characterization on a 2.3-meter long Skystream wind turbine blade, and the modal parameters (natural frequencies, operating deflection shapes) are extracted. Phase-based video processing adopted in this paper provides reliable full-field 2-D motion information, which is beneficial for manufacturing certification and model updating at the design stage. The phase-based video motion estimation approach is demonstrated through processing data on a full-scale commercial structure (i.e. a wind turbine blade) with complex geometry and properties, and the results obtained have a good correlation with the modal parameters extracted from accelerometer measurements, especially for the first four bending modes, which have significant importance in blade characterization.

Optimization of the life-cycle costs and reliability of offshore wind turbines (OWTs) is an area of immense interest due to the widespread increase in wind power generation across the world. Most of the existing studies have used structural reliability and the Bayesian pre-posterior analysis for optimization. This paper proposes an extension to the previous approaches in a framework for probabilistic optimization of the total life-cycle costs and reliability of OWTs by combining the elements of structural reliability/risk analysis (SRA), the Bayesian pre-posterior analysis with optimization through a genetic algorithm (GA). The SRA techniques are adopted to compute the probabilities of damage occurrence and failure associated with the deterioration model. The probabilities are used in the decision tree and are updated using the Bayesian analysis. The output of this framework would determine the optimal structural health monitoring and maintenance schedules to be implemented during the life span of OWTs while maintaining a trade-off between the life-cycle costs and risk of the structural failure. Numerical illustrations with a generic deterioration model for one monitoring exercise in the life cycle of a system are demonstrated. Two case scenarios, namely to build initially an expensive and robust or a cheaper but more quickly deteriorating structures and to adopt expensive monitoring system, are presented to aid in the decision-making process.

For large-scale wind turbines, reducing maintenance cost is a major challenge. Model predictive control (MPC) is a promising approach to deal with multiple conflicting objectives using the weighed sum approach. In this research, model predictive control method is applied to wind turbine to find an optimal balance between multiple objectives, such as the energy capture, loads on turbine components, and the pitch actuator usage. The actuator constraints are integrated into the objective function at the control design stage. The analysis is carried out in both the partial load region and full load region, and the performances are compared with those of a baseline gain scheduling PID controller. The application of this strategy achieves enhanced balance of component loads, the average power and actuator usages in partial load region.

Industry 4.0 stands for the fourth industrial revolution that is ongoing at present. Industry 4.0 is a terminology preferred used in Europe to characterize the integration of production and communication technologies, the so called “smart factory”. The first industrial revolution was the mechanization of work. The second was mass production and the assembly line. While the third revolution was the computer integrated manufacturing. Industry 4.0 encompasses the complete networking of all industrial areas. Lowering costs and efficient in-time production will be possible also for low numbers of very unique parts for example by additive manufacturing (3D printing). A significant aspect is also quality and maintainability of these sometimes unique structures and components. NDE has to follow these trends, not only by adapting NDE techniques to the new technologies, but also introducing the capability of cyber systems into the inspection and maintenance processes. The requirements and challenges for this new technological area will be discussed. Chances for applications of new technologies and systems for NDE will be demonstrated online.

The purpose of this paper is to demonstrate application of the time-frequency analysis (TFA) for processing guided ultrasonic waves measured by means of a specially designed ultrasonic rock bolt tester during nondestructive inspection of rock bolts. A pulse-echo method is adopted in the instrument as the most appropriate for the in-field applications. This paper presents methods for analysis of the measured guided ultrasonic waves using the TFA. The proposed TFA methodology is first demonstrated on the simulated signals and then verified using the experimental signals gathered from grouted prepared rock bolts provided with artificial defects simulating grout discontinuities.

Gas turbine engine components undergo high rotational loading another complex environmental conditions. Such operating environment leads these components to experience damages and cracks that can cause catastrophic failure during flights. There are traditional crack detections and health monitoring methodologies currently being used which rely on periodic routine maintenances, nondestructive inspections that often times involve engine and components dis-assemblies. These methods do not also offer adequate information about the faults, especially, if these faults at subsurface or not clearly evident. At NASA Glenn research center, the rotor dynamics laboratory is presently involved in developing newer techniques that are highly dependent on sensor technology to enable health monitoring and prediction of damage and cracks in rotor disks. These approaches are noninvasive and relatively economical. Spin tests are performed using a subscale test article mimicking turbine rotor disk undergoing rotational load. Non-contact instruments such as capacitive and microwave sensors are used to measure the blade tip gap displacement and blade vibrations characteristics in an attempt develop a physics based model to assess/predict the faults in the rotor disk. Data collection is a major component in this experimental-analytical procedure and as a result, an upgrade to an older version of the data acquisition software which is based on LabVIEW program has been implemented to support efficiently running tests and analyze the results. Outcomes obtained from the tests data and related experimental and analytical rotor dynamics modeling including key features of the updated software are presented and discussed.

It has long been non-destructively evaluated on weld joints of various pipes which are indispensable to most of industrial structures. Ultrasound evaluation has been used to detect flaws in welding joints, but some technical deficiencies still remain. Especially, ultrasound imaging on weld of elbow pipes has many challenging issues due to varying surface along circumferential direction. Conventional ultrasound imaging has particularly focused on ultrasonic wave propagation based on ray theory. This confines the incident angle and the position of an array transducer as well. Total focusing method (TFM), however, can provide not only high resolution images but also flexibility that enables to use ultrasonic waves to every direction that they can reach. This leads us to develop a method to get images of weld zone from an elbow part that curves. It is inevitable of each ultrasonic wave from the array transducer to transmit through different media and to be reflected from the boundary with angles along the curved surface. To form a correct PA image, careful calculation is made to ensure that time delay of receive-after-transmit is correctly shifted and summed even under non-planar boundary condition. Here, a method to calculate wave paths for the zone of interest at weld joint of an elbow pipe is presented. Numerical simulations of wave propagation on an elbow pipe are made to verify the proposed method. It is also experimentally demonstrated that the proposed method is well applied to various actual pipes that contains artificial flaws with a flexible wedge.

Nowadays, more and more, the monitoring of concrete’s setting and hardening as well as concrete’s condition assessment and mechanical characterization is realized with the Ultrasonic Pulse Velocity technique. However, despite its increasing use, the high potential and the vast applicability over a wide range of materials and structures, the aforementioned nondestructive testing technique is only partially exploited since a) a default pulse usually not selected by the user is transmitted, b) a single frequency band dependent on the testing equipment (pulse generator and sensors) is excited and c) usually the first part of the signal is only considered. Moreover, the technique, as defined by its name, is based on pulse velocity measurements which strongly rely on a predefined threshold value for the calculation of the travel time between the transmitting and receiving sensor. To overcome all these issues, in the current experimental campaign, user-defined signals are generated, a broad range of ultrasonic frequencies is excited, while the full length of the signal is also taken into account. In addition, the pulse velocity measurements are replaced by the more advanced phase velocity calculations determined by reference phase points of the time domain signals or by phase differences of the signals transformed in the frequency domain. The experiments are mainly conducted in hardened concrete specimens but the aggregates are substituted by spherical glass beads of well-defined sizes and contents in order to better control the microstructure. Reference liquid media are also examined for comparison purposes. The results in both cases show strong dispersive trends indicated by significant changes in the phase velocity.

Concrete is widely applied in the construction sector for its reliable mechanical performance, its easiness of use and low costs. It also appears promising for enhancing the thermal-energy behavior of buildings thanks to its capability to be doped with multifunctional fillers. In fact, key studies acknowledged the benefits of thermally insulated concretes for applications in ceilings and walls. At the same time, thermal capacity also represents a key property to be optimized, especially for lightweight constructions. In this view, Thermal-Energy Storage (TES) systems have been recently integrated into building envelopes for increasing thermal inertia. More in detail, numerical experimental investigations showed how Phase Change materials (PCMs), as an acknowledged passive TES strategy, can be effectively included in building envelope, with promising results in terms of thermal buffer potentiality. In particular, this work builds upon previous papers aimed at developing the new PCM-filled concretes for structural applications and optimized thermalenergy efficiency, and it is focused on the development of a new experimental method for testing such composite materials in thermal-energy dynamic conditions simulated in laboratory by exposing samples to environmentally controlled microclimate while measuring thermal conductivity and diffusivity by means of transient plane source techniques. The key findings show how the new composites are able to increasingly delay the thermal wave with increasing the PCM concentration and how the thermal conductivity varies during the course of the phase change, in both melting and solidification processes. The new analysis produces useful findings in proposing an effective method for testing composite materials with adaptive thermal performance, much needed by the scientific community willing to study building envelopes dynamics.

Exercise induced muscle damage (EIMD), is usually experienced in i) humans who have been physically inactive for prolonged periods of time and then begin with sudden training trials and ii) athletes who train over their normal limits. EIMD is not so easy to be detected and quantified, by means of commonly measurement tools and methods. Thermography has been used successfully as a research detection tool in medicine for the last 6 decades but very limited work has been reported on EIMD area. The main purpose of this research is to assess and characterize EIMD, using thermography and image processing techniques. The first step towards that goal is to develop a reliable segmentation technique to isolate the region of interest (ROI). A semi-automatic image processing software was designed and regions of the left and right leg based on superpixels were segmented. The image is segmented into a number of regions and the user is able to intervene providing the regions which belong to each of the two legs. In order to validate the image processing software, an extensive experimental investigation was carried out, acquiring thermographic images of the rectus femoris muscle before, immediately post and 24, 48 and 72 hours after an acute bout of eccentric exercise (5 sets of 15 maximum repetitions), on males and females (20-30 year-old). Results indicate that the semi-automated approach provides an excellent bench-mark that can be used as a clinical reliable tool.

One of the most environmental concerns is the climate change because of the greenhouse gasses, such as CO₂, N₂O, CH₄, and fluorinated gases. The big majority of CO₂ is coming from burning of fossil fuels to generate steam, heat and power. In order to address some of the major environmental concerns of fossil fuels, a number of different alternatives for renewable energy sources have been considered, including sunlight, wind, rain, tides and geothermal heat and biomass. In the present study, two different biomass products (three leaves and grasses) were collected from the local sources, cleaned, chopped, and mixed with corn starch as a binder prior to the briquetting process at different external loads in a metallic mold. A number of tests, including drop, ignition and mechanical compression were conducted on the prepared briquettes before and after stabilizations and carbonization processes at different conditions. The test results indicated that briquetting pressure and carbonizations are the primary factors to produce stable and durable briquettes for various industrial applications. Undergraduate students have been involved in every step of the project and observed all the details of the process during the laboratory studies, as well as data collection, analysis and presentation. This study will be useful for the future trainings of the undergraduate engineering students on the renewable energy and related technologies.

This article reports the functionality of Paint/PMN-PT and Paint/PLZT composite films for use in pyroelectric infrared sensors and energy conversion devices. Smart Paint/Lead Magnesium Niobate-Lead Titanate (Paint/PMN-PT) and Paint/Lead Lanthanum Zirconate Titanate (Paint-PLZT) nanocomposite films have been fabricated by the conventional paint-brushing technique on copper substrate. The pyroelectric, piezoelectric, and dielectric properties of the composite films were measured for their use in uncooled infrared detectors and thermal energy conversion devices. The properties investigated include: dielectric constants (epsilon' and epsilon''); pyroelectric coefficient (p); and energy conversion performance. From the foregoing parameters, material’s figure-of-merits, for infrared detection and thermal energy conversion, were calculated. The results indicated that paint composite films are functional and figure-of-merits increase with increase in amount of PMN-PT and PLZT nanoparticles in paint matrix. Based on the preliminary results obtained, composite films are reasonably attractive for use in uncooled thermal sensing elements, and thermal energy conversion devices for low power applications, especially in applications where flexible and curved surface sensors are required. With these factors in consideration, a novel cantilever system is designed and examined for its performance. The highest voltage output and power accomplished were 65 mV and 1 nano-Watts, respectively for a particular structure with a broad frequency response operating in the 31 mode of Paint/PMN-PT based harvester. Efforts have been made to investigate the performance of nanocomposite films on copper substrate to mechanical vibrations and thermal variations as well. Thus, could be utilized for energy scavenging combining piezoelectric and pyroelectric effects.

In this paper, an APP for building indoor environment evaluation and energy consumption estimation based on Android platform is proposed and established. While using the APP, the smart phone built-in sensors are called for real-time monitoring of the building environmental information such as temperature, humidity and noise, etc. the built-in algorithm is developed to calculate the heat and power consumption, and questionnaires, grading and other methods are used to feed back to the space heating system. In addition, with the application of the technology of big data and cloud technology, the data collected by users will be uploaded to the cloud. After the statistics of the uploaded data, regional difference can be obtained, thus providing a more accurate basis for macro-control and research of energy, thermal comfort, greenhouse effect.

Scanning acoustic microscopy uses a focused acoustic beam to investigate local elastic properties on the surface of a material. The measurement is based on the difference in propagation time between the direct reflection and the Rayleigh wave. This work deals with the development of a fully automated acoustic microscopy method in order to determine the near-surface elastic property and map sub-surface features in metallic and composite materials. This method allows for the detection and analysis of Rayleigh waves, which are sensitive to subtle changes in the material’s local elasticity. Via this process, the periodicity of the V_(Z) curve can be initially assessed and the local Rayleigh velocity of the material is determined. In this work, the automated acoustic microscopy method was applied for the assessment of aluminum and Al-SiC metal matrix composites.

Cement matrix composites with a conductive nano-reinforcement phase, lead to the development of innovative products. A matrix with carbon based nano-inclusions (graphene, carbon nanotubes, carbon nanofibers, carbon black) obtains multi-functional properties like enhanced mechanical, electrical, elastic and thermal properties and, therefore, the advantage of self-sensing in case of an inner defect. This research aims to characterize the nano-modified cement mortars with different concentrations of graphene nanophase. The results will be compared with data obtained from nanomaterials containing multi-walled carbon nanotubes. Comprehensive characteristics of these cement-based nanocomposites have been determined using destructive and nondestructive laboratory techniques. Flexural and compressive strength were measured. During four point bending tests, acoustic emission monitoring allowed for realtime identification of the damage process in the material. The electrical surface resistivity of graphene-reinforced cement mortars was measured by applying a known DC voltage, and compared to the electrical resistivity of nano-modified mortars with carbon nanotubes.