Structural Health Monitoring of Composite Pipelines Utilizing Fiber Optic Sensors and an AI-Based Algorithm-A Comprehensive Numerical Study.

In this paper, a structural health monitoring (SHM) system is proposed to provide automatic early warning for detecting damage and its location in composite pipelines at an early stage. The study considers a basalt fiber reinforced polymer (BFRP) pipeline with an embedded Fiber Bragg grating (FBG) sensory system and first discusses the shortcomings and challenges with incorporating FBG sensors for accurate detection of damage information in pipelines. The novelty and the main focus of this study is, however, a proposed approach that relies on designing an integrated sensing-diagnostic SHM system that has the capability to detect damage in composite pipelines at an early stage via implementation of an artificial intelligence (AI)-based algorithm combining deep learning and other efficient machine learning methods using an Enhanced Convolutional Neural Network (ECNN) without retraining the model. The proposed architecture replaces the softmax layer by a k-Nearest Neighbor (k-NN) algorithm for inference. Finite element models are developed and calibrated by the results of pipe measurements under damage tests. The models are then used to assess the patterns of the strain distributions of the pipeline under internal pressure loading and under pressure changes due to bursts, and to find the relationship of strains at different locations axially and circumferentially. A prediction algorithm for pipe damage mechanisms using distributed strain patterns is also developed. The ECNN is designed and trained to identify the condition of pipe deterioration so the initiation of damage can be detected. The strain results from the current method and the available experimental results in the literature show excellent agreement. The average error between the ECNN data and FBG sensor data is 0.093%, thus confirming the reliability and accuracy of the proposed method. The proposed ECNN achieves high performance with 93.33% accuracy (P%), 91.18% regression rate (R%) and a 90.54% F1-score (F%).

Guided wave propagation along surface of vertical solid partially submerged in horizontal liquid layer.

Guided waves can propagate along the surface of a solid structure at a large distance with little attenuation. Hidden defects within the structure can be detected based on the abnormal reflection or transmission of guided waves. The distance between the defect and the transducer can be calculated according to the arrival time of the wave package and wave speed. Therefore, the guided wave speed should be known prior. However, existing analytical models can only predict the guided wave speed along the surface of a horizontal solid covered by a liquid layer. These models are not suited for the characterization of ultrasonic nondestructive testing of ship hulls, sluice gates, water dams, bridge piers, etc. In this study, an analytical model is proposed for the guided wave propagation along a vertical solid partially inserted into a horizontal liquid layer. A secular equation is derived and solved to predict the guided wave speed at the vertical solid-liquid interface. Twenty finite element simulations and thirty-three physical experiments are conducted on different materials with different dimensions by using varying incident frequencies. The results demonstrate that the proposed model can provide accurate analytical wave speeds to guide the nondestructive testing and structural health monitoring of underwater structures.

Studying Acoustic Behavior of BFRP Laminated Composite in Dual-Chamber Muffler Application Using Deep Learning Algorithm.

Over the last two decades, several experimental and numerical studies have been performed in order to investigate the acoustic behavior of different muffler materials. However, there is a problem in which it is necessary to perform large, important, time-consuming calculations particularly if the muffler was made from advanced materials such as composite materials. Therefore, this work focused on developing the concept of the indirect dual-chamber muffler made from a basalt fiber reinforced polymer (BFRP) laminated composite, which is a monitoring system that uses a deep learning algorithm to predict the acoustic behavior of the muffler material in order to save effort and time on muffler design optimization. Two types of deep neural networks (DNNs) architectures are developed in Python. The first DNN is called a recurrent neural network with long short-term memory blocks (RNN-LSTM), where the other is called a convolutional neural network (CNN). First, a dual-chamber laminated composite muffler (DCLCM) model is developed in MATLAB to provide the acoustic behavior datasets of mufflers such as acoustic transmission loss (TL) and the power transmission coefficient (PTC). The model training parameters are optimized by using Bayesian genetic algorithms (BGA) optimization. The acoustic results from the proposed method are compared with available experimental results in literature, thus validating the accuracy and reliability of the proposed technique. The results indicate that the present approach is efficient and significantly reduced the time and effort to select the muffler material and optimal design, where both models CNN and RNN-LSTM achieved accuracy above 90% on the test and validation dataset. This work will reinforce the mufflers' industrials, and its design may one day be equipped with deep learning based algorithms.

Long-Short Term Memory Network-Based Monitoring Data Anomaly Detection of a Long-Span Suspension Bridge.

Structural health monitoring (SHM) systems have been widely applied in long-span bridges and a large amount of SHM data is continually collected. The harsh environment of sensors installed at structures causes multiple types of anomalies such as outlier, minor, missing, trend, drift, and break in the SHM data, which seriously hinders the further analysis of SHM data. In order to achieve anomaly detection from a large amount of SHM data, this paper proposes a long-short term memory (LSTM) network-based anomaly detection method. Firstly, the proposed method reduces the workload for preparing training sets. Secondly, the purpose of real-time anomaly detection can be met. Thirdly, the problem of high alarm rate can be avoided by utilizing double thresholds. To validate the effectiveness of the proposed method, a case study of finite element model simulation is firstly introduced, which illustrates the detailed implementation process. Finally, acceleration data from the SHM system of a long-span suspension bridge located in Jiangyin, China is employed. The results show that the proposed method can detect anomaly with high accuracy and identify abnormal accidents such as a ship collision quickly.

Exploration of Basalt Glasses as High-Temperature Sensible Heat Storage Materials.

Thermal energy storage (TES) systems are a key technology that utilizes renewable energy and low-level thermal energy to ensure continuous and stable operation in concentrated solar power plants, family heating, and industrial waste heat recovery fields. It solves the intermittent problem of solar radiation and significantly improves energy efficiency and economic benefits. Three varieties of natural basalt ores have been selected, namely, intermediate, basic, and ultrabasic basalt, which have been prepared into basalt glasses by the melt-quenching method. The applicability of basalt glass to high-temperature heat storage applications is studied. In the present paper, the chemical composition and structure of basalt glasses have been determined. The effect of temperature and composition on key thermophysical properties such as density, heat capacity, thermal diffusion, thermal conductivity, and thermal expansion has been analyzed during a series of thermal cycles. It has been confirmed that basalt glass has extremely high heat storage performance and thermal stability, and its working temperature is as high as 1000 °C such that it can be used as a solar energy heat storage material.

Erratum: Cheng, Y.; Zhao, C.; Zhang, J.; Wu, Z. Application of a Novel Long-Gauge Fiber Bragg Grating Sensor for Corrosion Detection via a Two-Level Strategy. Sensors 2019, 19, 954.

The authors wish to make the following erratum to this paper [...].

Application of a Novel Long-Gauge Fiber BraggGrating Sensor for Corrosion Detection via aTwo-level Strategy.

Corrosion of main steel reinforcement is one of the most significant causes of structuraldeterioration and durability reduction. This research proposes a two-level detection strategy tolocate and quantify corrosion damage via a new kind of long-gauge fiber Bragg grating (FBG) sensor.Compared with the traditional point strain gauges, this new sensor has been developed for bothlocal and global structural monitoring by measuring the averaged strain within a long gauge length.Based on the dynamic macrostrain responses of FBG sensors, the strain flexibility of structures areidentified for corrosion locating (Level 1), and then the corrosion is quantified (Level 2) in terms ofreduction of sectional stiffness of reinforcement through the sensitivity analysis of strain flexibility.The two-level strategy has the merit of reducing the number of unknown structural parametersthrough corrosion damage location (Level 1), which guarantees that the corrosion quantification(Level 2) can be performed efficiently in a reduced domain. Both numerical and experimentalexamples have been studied to reveal the ability of distributed long-gauge FBG sensors for corrosionlocalization and quantification.

Stripe-PZT Sensor-Based Baseline-Free Crack Diagnosis in a Structure with a Welded Stiffener.

This paper proposes a stripe-PZT sensor-based baseline-free crack diagnosis technique in the heat affected zone (HAZ) of a structure with a welded stiffener. The proposed technique enables one to identify and localize a crack in the HAZ using only current data measured using a stripe-PZT sensor. The use of the stripe-PZT sensor makes it possible to significantly improve the applicability to real structures and minimize man-made errors associated with the installation process by embedding multiple piezoelectric sensors onto a printed circuit board. Moreover, a new frequency-wavenumber analysis-based baseline-free crack diagnosis algorithm minimizes false alarms caused by environmental variations by avoiding simple comparison with the baseline data accumulated from the pristine condition of a target structure. The proposed technique is numerically as well as experimentally validated using a plate-like structure with a welded stiffener, reveling that it successfully identifies and localizes a crack in HAZ.

Characteristics of the tensile mechanical properties of fresh and dry forewings of beetles.

Based on a tensile experiment and observations by scanning electron microscopy (SEM), this study demonstrated the characteristics of the tensile mechanical properties of the fresh and dry forewings of two types of beetles. The results revealed obvious differences in the tensile fracture morphologies and characteristics of the tensile mechanical properties of fresh and dry forewings of Cybister tripunctatus Olivier and Allomyrina dichotoma. For fresh forewings of these two types of beetles, a viscous, flow-like, polymer matrix plastic deformation was observed on the fracture surfaces, with soft morphologies and many fibers being pulled out, whereas on the dry forewings, the tensile fracture surfaces were straightforward, and there were no features resembling those found on the fresh forewings. The fresh forewings exhibited a greater fracture strain than the dry forewings, which was caused by the relative slippage of hydroxyl inter-chain bonds due to the presence of water in the fibers and proteins in the fresh forewings. Our study is the first to demonstrate the phenomenon of sudden stress drops caused by the fracturing of the lower skin because the lower skin fractured before the forewings of A. dichotoma reached their ultimate tensile strength. We also investigated the reasons underlying this phenomenon. This research provides a much better understanding of the mechanical properties of beetle forewings and facilitates the correct selection of study objects for biomimetic materials and development of the corresponding applications.

Preparation of zinc hydroxystannate-decorated graphene oxide nanohybrids and their synergistic reinforcement on reducing fire hazards of flexible poly (vinyl chloride).

A novel flame retardant, zinc hydroxystannate-decorated graphene oxide (ZHS/GO) nanohybrid, was successfully prepared and well characterized. Herein, the ZHS nanoparticles could not only enhance the flame retardancy of GO with the synergistic flame-retardant effect of ZHS but also prevent the restack of GO to improve the mechanical properties of poly (vinyl chloride) (PVC) matrix. The structure characterization showed ZHS nanoparticles were bonded onto the surface of GO nanosheets and the ZHS nanoparticles were well distributed on the surface of GO. Subsequently, resulting ZHS/GO was introduced into flexible PVC and fire hazards and mechanical properties of PVC nanocomposites were investigated. Compared to neat PVC, thermogravimetric analysis exhibited that the addition of ZHS/GO into PVC matrix led to an improvement of the charring amount and thermal stability of char residue. Moreover, the incorporation of 5 wt.% ZHS/GO imparted excellent flame retardancy to flexible PVC, as shown by increased limiting oxygen index, reduced peak heat release rate, and total heat release tested by an oxygen index meter and a cone calorimeter, respectively. In addition, the addition of ZHS/GO nanohybrids decreased the smoke products and increased the tensile strength of PVC. Above-excellent flame-retardant properties are generally attributed to the synergistic effect of GO and ZHS, containing good dispersion of ZHS/GO in PVC matrix, the physical barrier of GO, and the catalytic char function of ZHS.

Distributed Long-Gauge Optical Fiber Sensors Based Self-Sensing FRP Bar for Concrete Structure.

Brillouin scattering-based distributed optical fiber (OF) sensing technique presents advantages for concrete structure monitoring. However, the existence of spatial resolution greatly decreases strain measurement accuracy especially around cracks. Meanwhile, the brittle feature of OF also hinders its further application. In this paper, the distributed OF sensor was firstly proposed as long-gauge sensor to improve strain measurement accuracy. Then, a new type of self-sensing fiber reinforced polymer (FRP) bar was developed by embedding the packaged long-gauge OF sensors into FRP bar, followed by experimental studies on strain sensing, temperature sensing and basic mechanical properties. The results confirmed the superior strain sensing properties, namely satisfied accuracy, repeatability and linearity, as well as excellent mechanical performance. At the same time, the temperature sensing property was not influenced by the long-gauge package, making temperature compensation easy. Furthermore, the bonding performance between self-sensing FRP bar and concrete was investigated to study its influence on the sensing. Lastly, the sensing performance was further verified with static experiments of concrete beam reinforced with the proposed self-sensing FRP bar. Therefore, the self-sensing FRP bar has potential applications for long-term structural health monitoring (SHM) as embedded sensors as well as reinforcing materials for concrete structures.

[Determination of Total Iron and Fe2+ in Basalt].

Basalt is the raw material of basalt fiber. The content of FeO and Fe2O3 has a great impact on the properties of basalt fibers. ICP-OES and dichromate method were used to test total Fe and Fe(2+) in basalt. Suitable instrument parameters and analysis lines of Fe were chosen for ICP-OES. The relative standard deviation (RSD) of ICP-OES is 2.2%, and the recovery is in the range of 98%~101%. The method shows simple, rapid and highly accurate for determination of total Fe and Fe(2+) in basalt. The RSD of ICP-OES and dichromate method is 0.42% and 1.4%, respectively.

Review of beetle forewing structures and their biomimetic applications in China: (I) On the structural colors and the vertical and horizontal cross-sectional structures.

This paper discusses the progress made in China in terms of the structural colors, microstructure and mechanical properties of the beetle forewing. 1) The forewing microstructures can be classified into six phases, the first three of which are characterized by sandwich, multilayer and fiber layer structures, respectively. The fracture behaviors resulting from these three phases suggest that different scale microstructures or coupled adjacent scale microstructures can determine the macroscopic mechanical behavior of the forewing. 2) The forewing colors are derived from three features: regulation of the structural parameters of the internal optical structures, i.e., a sculpted multilayer composite two-dimensional nanopillar structure grating system; scattering on the three-dimensional surface of the bowl-shaped structure; and reversible color changes due to changes in the physical microstructure of fluffs. Their formation mechanisms were clarified, and fibers with ecological biomimetic structural colors have been developed. 3) Beetles exhibit a lightweight sectional frame structure with a trabecular core structure. Both of the joints on the left and right are concave-convex butt-joint structures with burrs, which provide an efficient docking mechanism with high intensity. The forewing of dichotoma exhibits a non-equiangular layered structure, which results in anisotropy in its tensile strength. Finally, the authors propose potential new research directions for the next 20 years.

Simulated effect on the compressive and shear mechanical properties of bionic integrated honeycomb plates.

Honeycomb plates can be applied in many fields, including furniture manufacturing, mechanical engineering, civil engineering, transportation and aerospace. In the present study, we discuss the simulated effect on the mechanical properties of bionic integrated honeycomb plates by investigating the compressive and shear failure modes and the mechanical properties of trabeculae reinforced by long or short fibers. The results indicate that the simulated effect represents approximately 80% and 70% of the compressive and shear strengths, respectively. Compared with existing bionic samples, the mass-specific strength was significantly improved. Therefore, this integrated honeycomb technology remains the most effective method for the trial manufacturing of bionic integrated honeycomb plates. The simulated effect of the compressive rigidity is approximately 85%. The short-fiber trabeculae have an advantage over the long-fiber trabeculae in terms of shear rigidity, which provides new evidence for the application of integrated bionic honeycomb plates.

Superhydrophobic cuprous oxide nanostructures on phosphor-copper meshes and their oil-water separation and oil spill cleanup.

A simple aqueous solution-immersion process was established to fabricate highly dense ordered Cu2O nanorods on commercial phosphor-copper mesh, with which the preparation was accomplished in distilled water. The present method, with the advantages of simple operation, low cost, short reaction time, and environmental friendliness, can be well adopted to fabricate desired Cu2O nanostructures on the phosphor-copper mesh under mild conditions. After surface modification with 1-dodecanethiol, the Cu2O nanostructure obtained on the phosphor-copper mesh exhibits excellent superhydrophobicity and superoleophilicity. Besides, a "mini boat" made from the as-prepared superhydrophobic phosphor-copper mesh can float freely on water surface and in situ collect oil from water surface. This demonstrates that the present approach, being facile, inexpensive, and environmentally friendly, could find promising application in oil-water separation and off shore oil spill cleanup.

A hybrid LPG/CFBG for highly sensitive refractive index measurements.

A simple and high sensitive method employing a hybrid long period grating (LPG)/chirped fiber Bragg grating (CFBG) for refractive index (RI) measurements is proposed and investigated experimentally. The wide wavelength range of backward cladding modes are excited through the coupling and recoupling between LPG and CFBG. Experimental results indicate that the recoupled cladding modes between LPG and CFBG and core mode are modulated by the surrounding RI and highly sensitive RI measurements can be achieved by simply measuring the reflected intensity changes of the recoupled cladding modes and core mode.

Superhydrophobic and superoleophilic nanoparticle film: synthesis and reversible wettability switching behavior.

The present work describes a one-step facile spray deposition process for the fabrication of superhydrophobic and superoleophilic nanoparticle film. The film shows fast response wettability transition between superhydrophobicity and hydrophilicity. The reversible superhydrophobicity to hydrophilicity switching can be easily carried out by adjusting the temperature. The film also demonstrates oil uptake ability and can selectively adsorb oil floating on water surface. Furthermore, the film surface shows the antifouling performance for organic solvents, which can self-remove the organic solvents layer and recover its superhydrophobic behavior. The advantage of the present approach is that the damaged film can be easily repaired by spraying again.

Coaction of sub-band and doped nitrogen on visible light photoactivity of N-doped TiO2.

We found in our previous work that the high photoactivity of N-doped TiO(2) for the oxidation of propylene under visible light was attributed to the photoactive center V(o)(•)-NO-Ti and the formation of sub-band originated from a large amount of single-electron-trapped oxygen vacancies (denoted as V(o)(•); C. X. Feng, Y. Wang, Z. S. Jin, J. W. Zhang, S. L. Zhang, Z. S. Wu, Z. J. Zhang [2008], New J. Chem. 32, 1038). In the present study, the structure of the sub-band within E(g) of a representative sample N-NTA-400 was investigated by means of photoluminescence (PL) spectrometry and ultraviolet-visible light-near infrared diffuse reflectance spectra. The coaction of the sub-band and doped nitrogen on visible light photocatalytic activity of N-doped TiO(2) was also investigated. The electron spin resonance spectra measured under laser irradiation (λ = 532 nm) indicate that the doped nitrogen may contribute to stabilize the trapping electron center, i.e. surface oxygen vacancy (V(o)(••)), and hence suppress the PL, enhancing the photocatalytic activity.

Preparation of In2S3 nanopraricle by ultrasonic dispersion and its tribology property.

In this paper, we describe a facile and rapid method for preparing In2S3 nanoparticles via ultrasound dispersion. This method allows us to prepare In2S3 nanoparticles from bulk indium and sulfur with ease and without using expensive agents and in a short time. The possible growing mechanism of the In2S3 nanoparticles was presented. In addition, we provide detailed characterizations including TEM, XRD, TG-DTA, and XPS to study the shape, composition and structure of In2S3 nanoparticles. We also studied the tribology property of In2S3 nanoparticles made using this novel recipe.

Oscillation of absorption bands of Zn(1-x)Mn(x)S clusters: an experimental and theoretical study.

Electroporation of synthetic vesicles is utilized for the preparation of molecular size uncapped Zn(1-x)Mn(x)S clusters. The absence of caps permits (i) continued growth of the Zn(1-x)Mn(x)S clusters formed, (ii) the assessment of their true absorption spectra unaltered by stabilizing ligands, and (iii) the previously inaccessible live observation of the growth of the clusters in the molecular size regime. Upon cluster growth, the UV spectra exhibit novel, time-dependent, oscillation of red and blue shifts of the characteristic absorption band. The structure and electronic properties of Zn(N-1)MnS(N) clusters with N = 1-9 are calculated using the first-principles DMol(3) package. On the basis of similarities between the oscillating trend of the experimentally observed absorption spectra and that of the calculated highest occupied molecular orbital-lowest unoccupied molecular orbital (HOMO-LUMO) gap of Zn(N-1)MnS(N) clusters with N = 1-9, the wavelengths of the sequential spectral peaks can be assigned to Zn(2)MnS(3), Zn(3)MnS(4), Zn(4)MnS(5), Zn(6)MnS(7), and Zn(8)MnS(9), respectively. Our results demonstrate that both the cluster size and the composition can be used to tune the optical properties.