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Structural engineering is a promising approach to enhance the performance of racetrack devices in term of power consumption for domain wall dynamics and shift errors via the control of the in-plane shape anisotropy in magnetic nanowires. Because the in-plane shape anisotropy is determined by the nanowire width, it is essential to incorporate the width effect into the demagnetizing tensor to design racetrack devices through a structural approach; however, a quantitative evaluation of the width effect on the demagnetizing tensor is still lacking. In this work, we have derived the formula for the effective demagnetizing tensor in nanowires with finite width. We also analytically revealed that the special width, at which intrinsic pining potential vanishes, is proportional to the domain wall width. The derived formulas were in good agreement with the two-dimensional micromagnetic simulation results at various nanowire widths, demonstrating their validity. Our results provide a guideline for designing racetrack devices with low power consumption and minimal shift errors via structural engineering. [ABSTRACT FROM AUTHOR]

Modern software engineering of electronic structure codes has seen a paradigm shift from monolithic workflows toward object-based modularity. Software objectivity allows for greater flexibility in the application of electronic structure calculations, with particular benefits when integrated with approaches for data-driven analysis. Here, we discuss different approaches to create deep modular interfaces that connect big-data workflows and electronic structure codes and explore the diversity of use cases that they can enable. We present two such interface approaches for the semi-empirical electronic structure package, DFTB+. In one case, DFTB+ is applied as a library and provides data to an external workflow; in another, DFTB+receives data via external bindings and processes the information subsequently within an internal workflow. We provide a general framework to enable data exchange workflows for embedding new machine-learning-based Hamiltonians within DFTB+ or enabling deep integration of DFTB+ in multiscale embedding workflows. These modular interfaces demonstrate opportunities in emergent software and workflows to accelerate scientific discovery by harnessing existing software capabilities. [ABSTRACT FROM AUTHOR]

As a newly synthesized two-dimensional (2D) carbon material, monolayer quasi-hexagonal phase fullerene (qHP C60) has an excellent electronic structure and low thermal conductivity. qHP C60 attracted significant attention from scientists because it has potential applications in thermoelectric materials. Thermoelectric properties of 2D materials significantly depend on the transport of carriers (such as electrons and phonons), and strain engineering is an essential method for modulating the transport of electrons and phonons in 2D materials. However, the strain engineering method for the modulation of the thermoelectric properties of monolayer qHP C60 has not been reported yet. In the present paper, the first-principles combined with the non-equilibrium Green's function method are used to investigate the ballistic transport properties of electrons and phonons in monolayer qHP C60. The effects of temperature, chemical potential, and biaxial tensile strain on the thermoelectric transport parameters (including conductivity, Seebeck coefficient, power factor, and thermal conductivity) as well as the figure of merit (ZT) of monolayer qHP C60 are presented, compared, discussed, and analyzed. We found that monolayer qHP C60 exhibits anisotropic characteristics in electron and phonon transport properties, showcasing outstanding thermoelectric properties. The distinctive quasi-hexagonal phase fullerene network structure offers a novel platform for exploring innovative 2D thermoelectric materials in research. This study provides crucial theoretical insights to guide the designing and implementation of 2D thermoelectric materials based on fullerenes. [ABSTRACT FROM AUTHOR]

The time-modulated active medium with linear independent frequency conversion method has been demonstrated to enable wave orientation and reconstruction. However, due to the symmetric scattering field, this technique requires intricate microcircuit designs. To overcome this limitation, this paper proposes a tunable piezoelectric metasurface based on acoustic black holes (ABHs) to redirect flexural wave reflections. The system can convert an incident flexural wave into a reflected wave of any direction and frequency. This is accomplished through the linear time modulation of the sensing signal, which breaks the constraints of Snell's law inherent in traditional designs and is insensitive to the incident amplitude. The coupling of the ABH damping system with a linear independent frequency conversion mechanism allows for the conversion of an incident flexural wave into a reflected wave in any direction and frequency while also eliminating the influence of second harmonic reflection on the wave field and simplifying the time modulation circuit. In addition, this paper demonstrates arbitrary angle reflection, focusing, beam splitting, and frequency conversion of the incident wave. By improving the flexibility of elastic wave manipulation, this paper introduces a new approach for active control of elastic waves and provides a design method that can be employed in a variety of applications ranging from vibration protection of engineering structures to vibration sensing and evaluation. [ABSTRACT FROM AUTHOR]

Aqueous Zn-ion hybrid supercapacitors (AZHSCs) combining the advantages of high‐energy batteries and high‐power supercapacitors see a bright future, but they still suffer from the poor capacity of carbonic cathodes. Herein, a functionalized porous carbon cloth (denoted as FPCC) electrode is demonstrated based on commercial carbon cloth (denoted as CC) tuning by structural and surface engineering. The constructed exfoliated porous carbon layer and the negatively charged functionalized interface not only increase the electrical double layer capacitance but also favor the chemical adsorption of Zn2+ to obtain additional pseudocapacitance. Consequently, the FPCC electrode delivers a high capacity of 0.16 mAh cm−2 at 4 mA cm−2, which is 923.8 times higher than CC, and a long cycle life (85.0% capacity retention after 30 000 cycles). More importantly, the Zn//FPCC AZHSC possesses an impressive energy density (3.3 mWh cm−3) and power density (240 mW cm−3), superior to many advanced batteries and supercapacitors. The quasi-solid-state device is also assembled as a demo. This modification strategy may provide new opportunities for high-performance AZHSCs. [ABSTRACT FROM AUTHOR]

This work presents procedures and results from quasi-static uniaxial tensile experiments carried out on hybrid bolted bonded (HBB) joints using carbon fibre reinforced plastic (CFRP) adherends. The impact of various dimensional parameters, including lap length (L), lap width (W), number of bolts (N), bolt diameter (D), and bolt arrangement, on its ultimate load and failure modes of the HBB joint is investigated. The failure mechanism of the HBB joint is examined and summarized, offering theoretical insights for the engineering application of this structural configuration. The findings of the study indicate that the ultimate load capacity of the hybrid joint is notably enhanced by increasing both the lap length and lap width, and is further influenced by the effective dimensions at the edges and end distances. The transverse configuration of multiple bolts within the adhesive-bolt hybrid joint demonstrates superior maximum load capacity and average stiffness in comparison to a longitudinal arrangement. During tensile testing, the primary mode of failure observed in the Hybrid Bolted-Bonded (HBB) joint is adhesive failure, often accompanied by delamination. Cleavage failure is predominantly observed in configurations with longitudinally aligned multiple bolts arranged in a singular row. On the other hand, shear tear-out and bearing failures are commonly encountered in single-bolt joints characterized by a substantial width-to-diameter (W/D) ratio. Specifically, shear tear-out failure tends to manifest in cases with a small length-to-diameter (L/D) ratio, whereas bearing failure is more prevalent in instances with a large L/D ratio. [ABSTRACT FROM AUTHOR]

The most likely scenario for civil engineering structures is that only some components or parts of a structure are complex, while the rest of the structure can be well physically modeled. In this case, utilizing powerful neural networks to model these complex components or parts only and embedding the neural network models into the structure might be a viable choice. However, few studies have considered the real‐time interaction between the neural network model and another model. In this paper, a new hybrid structural modeling strategy that incorporates the neural network model is proposed. Structures installed with energy dissipation devices (EDDs) are investigated, where continuous‐time state‐space neural network (CSNN) models are adopted to represent EDDs and to couple with the physical model of the structure excluding EDDs through the state‐space substructuring method. First, CSNN models with an identical model configuration are trained to represent different physical models of EDDs and fit the experimental results of a damper to evaluate the CSNN model at the model level. Then, to demonstrate the hybrid structural analysis method, the CSNN‐based structural models of the interfloor‐damped and base‐isolated structures are established for seismic analyses. It is observed that CSNN‐based models exhibit high prediction performance and are easy to implement. Therefore, the developed hybrid structural analysis method that adopts CSNN models for EDDs is engineering practical. [ABSTRACT FROM AUTHOR]

After high-temperature etching of metal-free porous N -doped carbon with NaCl, the doped Cl atoms significantly enhance the peroxidase-like activity of the nanozyme. [Display omitted] Metal-free carbon-based nanozymes often exhibit superior chemical stability and detection reliability compared to their metal-doped counterparts. However, their catalytic activity remains an area ripe for further enhancement. Herein, we successfully prepared a chlorine (Cl)-modified, metal-free, and porous N -doped carbon nanozyme (Cl x -pNC) via NaCl molten etching. The incorporation of Cl induced an increase in the intrinsic defects of sp3-hybridized carbon within Cl x -pNC and optimized the electronic structure of the N -connected carbon atoms. Remarkably, the peroxidase (POD)-like activity of Cl x -pNC was enhanced twelvefold compared to porous N -doped carbon (pNC). Theoretical simulations highlighted that the introduction of Cl not only promoted H 2 O 2 adsorption but also lowered the energy barrier for its decomposition, facilitating the generation of active intermediates and thus boosting POD-like activity. Based on the POD mimic activity of Cl x -pNC, we developed a colorimetric platform for OPs detection utilizing a cascade amplification strategy. This work provides insights into the rational design of carbon-based nanozymes and the development of nanozyme-based colorimetric biosensors. [ABSTRACT FROM AUTHOR]

In urban concentrated area, the disturbance caused by construction affects significantly the sustainability of adjacent existing structures. It is essential to capture the mechanical response of existing structures to adjacent deep excavation. The objective of this paper is to investigate the displacement and internal force behavior of elevated bridge piles (BP) subject to influence of deep excavation. A three-dimensional finite element model is established by taking the project of a deep excavation near elevated bridge as an example. The numerically calculated results agree well with the measured data, which verifies the established numerical model. On the basis of this model, the influence of deep excavation on the mechanical characteristics of adjacent piles is captured. The results show that the displacement, bending moment, and shear force of piles are sensitive to the excavation depth. Their magnitudes increase with the increase of excavation depth. When the excavation is completed, the maximum displacements of piles in horizontal direction and vertical direction are 2.3 mm and 10.05 mm, respectively. The maximum bending moment is 1,140.8 kN·m. The maximum and minimum shear forces are 1,206 kN and -2,282 kN, respectively. The piles are mainly under pressure. The maximum pressure is -13,116 kN. The axial force is not sensitive to the depth of excavation. The deformation and internal force of piles exhibit obvious spatial distribution characteristics, and the closer the distance to the middle of the long side of the deep excavation, the greater the value. The research results have a positive effect on the optimization of related engineering structures and the promotion of sustainable development in urban concentrated area. [ABSTRACT FROM AUTHOR]

The acoustic emission (AE) technique is commonly utilized for identifying source mechanisms and material damage. In applications requiring numerous sensors and limited detection areas, achieving significant cost savings, weight reduction, and miniaturization of AE sensors is crucial. This prevents excessive weight burdens on structures while minimizing interference with structural integrity. Thin Piezoelectric Wafer Active Sensors (PWAS), compared to conventional commercially available sensors, offer a miniature, lightweight, and affordable alternative. The low signal-to-noise ratio (SNR) of PWAS sensors and their limited effectiveness in monitoring thick structures result in the decreased reliability of a single classical PWAS sensor for damage detection. This research aims to enhance the functionality of PWAS in AE applications by employing multiple thin PWAS and performing a data-level fusion of their outputs. To achieve this, as a first step, the selection of the optimal PWAS is performed and a configuration is designed for multiple sensors. Pencil break lead (PBL) tests were performed to investigate the compatibility between selected PWAS and traditional WSα and R15α sensors. The responses of all sensors from different AE sources were compared in both the time and frequency domains. After that, convolutional neural networks (CNNs) combined with principal component analysis (PCA) are proposed for signal processing and data fusion. The signals generated by the PBL tests were used for network training and evaluation. This approach, developed by the authors, fuses the signals from multiple PWAS and reconstructs the signals obtained from conventional bulky AE sensors for damage detection. Three CNNs with different architectures were built and tested to optimize the network. It is found that the proposed methodology can effectively reconstruct and identify the PBL signals with high precision. The results demonstrate the feasibility of using a deep-learning-based method for AE monitoring using PWAS for real engineering structures. [ABSTRACT FROM AUTHOR]

Excavation of underground engineering structures involving deeply buried water-rich soft rocks is generally carried out using the artificial freezing method. A series of undrained uniaxial and triaxial shear and creep tests were conducted on soft rocks under different confining pressures (0, 0.2, 0.5, and 1.0 MPa) at different freezing temperatures (room temperature, -5°C, -10°C, and -15°C). Test results indicate that the frozen soft rocks show strain softening characteristics. The stress—strain curve changes from a straight line to a curve as deviatoric stress constantly increases, while it decreases abruptly after the deviatoric stress reaches the peak and is slightly affected by the freezing temperature. At the same temperature, shear strength increases at a rate of 5.6 MPa/°C with increasing confining pressure; as freezing temperature decreases, the shear strength increases at 0.34 MPa/°C, and cohesion increases at 0.6 MPa/°C. Under the same confining pressure, the failure strain of soft rock decreases with the decrease of temperature. The Mohr-Coulomb (M-C) criterion can accurately describe the failure process of frozen soft rocks in the pre-peak stage, with a correlation coefficient greater than 0.98. Within the test stress range, soft rocks display attenuated stable creep deformation. Acoustic emission (AE) tests were conducted to further verify that the soft rocks show shear failure under load, with a shear plane showing an angle of 45° with the horizontal. The research findings provide technical support and theoretical reference for studying rock mechanical properties as well as for designing and carrying out underground freezing of rocks in a low-temperature environment. [ABSTRACT FROM AUTHOR]

With the progress of technologies in data collection systems, structural engineers are faced with a large amount of unlabeled data gathered from various states of different structures, directing studies toward using improved classifiers in machine learning approaches of structural health monitoring. In this research, Laplacian Support Vector Machines (LapSVMs) are used as a semi-supervised learning algorithm to classify mentioned data. Using vibrational data of structure, dynamic properties of the structure are extracted. Modal strain energy is used as damage sensitive features (DSF) to perform damage assessment in a statistical pattern recognition framework by a semi-supervised learning algorithm using LapSVMs to classify unlabeled and labeled data. Also, Support Vector Machines (SVMs) and Regularized Least Square Classifier (RLSC) are used as classifiers to compare results. To compare the effectiveness of the proposed algorithm, different states of structural response are determined by labeled and unlabeled data. These results show high accuracy of LapSVM methods compared to others in cases where the labeled dataset is small. [ABSTRACT FROM AUTHOR]

The practical application of aqueous zinc ion batteries (AZIBs) is impeded by the instability of the Zn anode|electrolyte interface, including dendrite growth, hydrogen evolution reaction (HER), and corrosion. Herein, the periodical micro‐nano structure is constructed on the surface of Zn anode through picosecond laser lithography (PLL) technology. This micro‐nano surface structure is conductive to obtain hydrophobicity for diminishing direct contact between the electrolyte and Zn anode, enhancing the corrosion resistance of the Zn anode. Simultaneously, the low surface energy and reconstructed electric field are achieved through laser‐induced texture microstructure, leading to the oriented Zn2+ deposition along the (002) plane. As a result, the lower electrochemical polarization and long cycling stability of 1400 h for Zn||Zn symmetric cell is achieved at 4 mA cm−2 and 2 mAh cm−2. The average coulombic efficiency (CE) of the Zn||Cu cell is enhanced to 99.83% at 2 mA cm−2, while the Zn||MnO2 cell delivers a capacity retention of 68.7% after 600 cycles at 1 A g−1. Consequently, the advantages of micro‐nano structure can highlight the importance of surface structure design for the development of stable Zn anode. [ABSTRACT FROM AUTHOR]

Developing robust nonprecious metal-based electrocatalysts toward hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is essential for hydrogen production via electrochemical water splitting. Herein, the NiFeCoCuTi alloy is described as a multisite electrocatalyst for highly effective hydrogen and oxygen evolution in alkaline environments. This is achieved by utilizing heterogeneous atoms on the surface that exhibit distinct adsorption behaviors for hydrogen and hydroxyl, thereby accelerating the dissociation of water and mediating the adsorption of hydrogen intermediates required for molecule formation. The monolithic nanoporous multi-metal NiFeCoCuTi alloy electrode displays remarkable alkaline HER and OER electrocatalysis, exhibiting low overpotentials of 48.7 and 264.2 mV, respectively, to deliver a current density of 10 mA cm−2. Furthermore, it demonstrates exceptional stability for over 100 h in 1 M KOH electrolyte. The exceptional qualities of nanoporous NiFeCoCuTi alloy electrodes make them a highly desirable option for utilization as the cathode and anode material in water electrolysis, which produces hydrogen. They also imply that this is the optimal platform for the development of multisite electrocatalysts. [Display omitted] • The multi-metal NiFeCoCuTi alloys were synthesized by dealloying. • The precursor species and dealloying parameters were investigated. • The 4-NiFeCoCuTi catalyst exhibits excellent HER and OER catalytic properties. • Local structure engineering improves catalytic properties. [ABSTRACT FROM AUTHOR]

In this paper, we present the design and fabrication of a plasmonic metasurface based on titanium dioxide (TiO2) nanowire arrays integrated with plasmonic layers. The structure is engineered to produce Fano resonances within the visible spectrum, resulting from the coupling of localized surface plasmon resonances, lattice modes, and nanowire's optical modes. Experimentally, we show that by tuning the geometrical features of the metasurface, such as the length, diameter, and period of the nanowires, a high-quality factor single peak can be achieved in the reflection spectra, resulting in vivid structural colors in bright field. To our knowledge, this is the first demonstration of such vivid colors with nanowire arrays in bright field reflections. When characterized by refractive index fluids around the refractive index of water, the plasmonic metasurface also showed great potential for biochemical colorimetric sensing. The best design demonstrated a bulk sensitivity of 183 nm/RIU with high Q resonance features and linear changes in color values using image processing. [ABSTRACT FROM AUTHOR]

Traditional chemical additives inevitably pollute, damage, and destroy the ecological environment and natural resources while simultaneously addressing the requirements of engineering construction in loess areas. Additionally, freeze–thaw cycles exert a substantial influence on the long‐term durability of engineering structures located in areas with loess deposits. Thus, it is a considerable benefit to identify and utilize materials that are beneficial to the environment and which will augment the engineered performance and freeze–thaw resistant capacity of loess. The purpose of this research is to evaluate the impact of freezing and thawing cycles on the mesostructural attributes using loess reinforced with lignin fiber and to elucidate an effect of varying fiber doses in relation to the response of loess to freezing and thawing. The findings illustrate that the incorporation of fiber effectively eliminates the presence of overhead pores in the loess. Furthermore, the freeze–thaw action induces the formation of long‐narrow pores along the fiber surface in the reinforced loess. Adding the fiber reduces the characteristic parameters of the loess mesostructure. On the other hand, the freezing and thawing action increases the apparent void ratio, the mean pore area, and the area probability distribution index of the reinforced loess, while decreasing the probability entropy and bringing the fractal dimension very close. Freeze–thaw has the least effect on the apparent void ratio and microfine pore area ratio of 1% fiber loess. The filling and bridge effects of lignin fiber serve as the primary means of enhancing the strength of loess. Through its control of water, fiber bears the influence of some loess particles and pores, thus improving the freeze–thaw resistant capacity of loess. [ABSTRACT FROM AUTHOR]

This paper deals with the analysis of wave propagation characteristics in various prestressed structures with geometric nonlinearities using the Carrera Unified Formulation (CUF). CUF provides a versatile platform to model a wide range of structures and nonlinearities that can take care of all wave propagation aspects. In this work, different geometric nonlinearities for which representative governing equations have been derived and numerical solutions have been obtained through a unified approach are considered. The study investigates in detail the effect of prestress and geometric nonlinearity on wave propagation behavior. The results indicate that prestress has a very influential effect on modal frequency and dispersion characteristics for wave propagation. Specifically, three CUF-modeled beams are considered herein, having a sandwich, metallic portal, and metallic box cross section, respectively. Initially, the principal cross-sectional modal shapes of the unstressed, linear, and full nonlinear (i.e., full three-dimensional Green-Lagrange strain matrix) beam with a prestress are investigated, among which torsional and flexural modes can be recognized. Afterward, the equilibrium curves of such structures for various geometrical nonlinear approximations are traced, highlighting that most types of nonlinearity induce a hardening behavior in the system, which increases with the preload, directly leading to a variation in modal frequencies. The dispersion relations of the full nonlinear structure examined as a function of the applied preload are further compared, enriching the investigation by exploiting wave finite element method capabilities. This knowledge paves the way toward the design and optimization of prestressed systems with enhanced acoustic performance, and that fosters the development of sound absorption, noise insulation, and structural isolation. [ABSTRACT FROM AUTHOR]

Identifying the weak stiffness positions of a machine tool is crucial for enhancing its overall structural rigidity. In 1high-value engineering structures such as machine tools or aviation fields, generating the data first by simulation is often necessary. Thus, the required model often corresponds to the actual working conditions. However, achieving an equal spacing sensor distribution during the actual measurement process in the actual damage identification project is often difficult because of the occlusion of the sensor position arranged by the measured structure. In damage identification, the identification indexes designed by equidistant sensor distribution often fail or have large errors. In this study, a damage identification index (ae″) method independent of the distribution of equidistant sensors is proposed based on the flexibility curvature matrix. The element stiffness matrix and the element mass matrix for solving the flexibility curvature matrix are adjusted according to the actual sensor spacing, and the obtained flexibility matrix is calculated twice by difference to obtain a new damage identification index. A cantilever beam is employed as a reference to confirm the efficacy of the damage identification index via numerical simulation. Thus, the robustness of this damage identification index in identifying damage across various scenarios of damage and amidst noise interference is demonstrated. Further validation of the index utility is conducted on a gear grinding machine, thereby confirming its adaptability even with sensors spaced unevenly. [ABSTRACT FROM AUTHOR]

Product design changes are implemented to remain competitive in the market. Product change propagates in design and manufacturing system. Completing product change prediction analysis well in advance is the key in successful engineering change management. Manufacturing companies are facing challenges to control changes in a process during implementation phase. Process parameters are required to be reset against product changes with multiple production trials. This delay in change implementation phase increases obsolescence cost along with high chances of product quality failures. Our research objective is to reduce overall time required to implement product design change in manufacturing system. It is proposed to extend the concept of design structure matrix from design phase to production environment through a machine learning tool. A case study is conducted on the riveting process parameters in an automotive company. Riveting process is decomposed with process parameters by use of design structure matrix. Machine learning tool is used to extract relationship between process parameter and part features with scientific method. Prediction results of the case study from machine learning tool are evaluated with actual design of experiments trials. Prediction results are found very close to results from DOE trials. The results from case study supports to research objective by early prediction of impact on process parameter. [ABSTRACT FROM AUTHOR]

ABSTRACT The high load with very low occurrence probability in the fatigue load spectrum may introduce the favorable residual stress at the metal structure notch, so it is necessary to clip the high load of spectrum to avoid a dangerous test result. Based on the time‐domain extrapolation principle and the extreme value theory, the probability distribution of high load in the whole‐life load spectrum was predicted. Considering the dispersion of high load and the influence of high load on the structural fatigue life, a selection criterion of high load clipping level was proposed, which makes the test result under the corresponding clipped spectrum both conservative and authentic. To demonstrate the rationality and practicality of criterion, the transport aircraft load spectrum was extrapolated and the spectral fatigue tests of 2024‐T3 aluminum alloy sheet were conducted, providing reference for the design of fatigue test load spectrum of aircraft structure in practical engineering. [ABSTRACT FROM AUTHOR]

There is currently minimal data that may be used for retention and recruitment strategies for timber professional engineering in Canada. A comprehensive survey performed in 2022 to address this lack of data are discussed. The survey was generated and analyzed by York University (Canada) and distributed through the Canadian Wood Council's membership directory. This survey explored participants' motivations for working on timber-based structural projects and the existing state of EDI training within the workspace. Findings from the context of analysis illustrated that retention in the work force appears not to be affected by gender, with participants overwhelmingly indicating their plan is to continue to work in the timber structural engineering sector. Gender specific findings suggest that most men who practice timber structural design have had more recorded work experience, whereas women were more likely to obtain a PhD when pursuing graduate school. [ABSTRACT FROM AUTHOR]

Purpose: The aging and deterioration of engineering building structures present significant risks to both life and property. Fiber Bragg grating (FBG) sensors, acclaimed for their outstanding reusability, compact form factor, lightweight construction, heightened sensitivity, immunity to electromagnetic interference and exceptional precision, are increasingly being adopted for structural health monitoring in engineering buildings. This research paper aims to evaluate the current challenges faced by FBG sensors in the engineering building industry. It also anticipates future advancements and trends in their development within this field. Design/methodology/approach: This study centers on five pivotal sectors within the field of structural engineering: bridges, tunnels, pipelines, highways and housing construction. The research delves into the challenges encountered and synthesizes the prospective advancements in each of these areas. Findings: The exceptional performance of FBG sensors provides an ideal solution for comprehensive monitoring of potential structural damages, deformations and settlements in engineering buildings. However, FBG sensors are challenged by issues such as limited monitoring accuracy, underdeveloped packaging techniques, intricate and time-intensive embedding processes, low survival rates and an indeterminate lifespan. Originality/value: This introduces an entirely novel perspective. Addressing the current limitations of FBG sensors, this paper envisions their future evolution. FBG sensors are anticipated to advance into sophisticated multi-layer fiber optic sensing networks, each layer encompassing numerous channels. Data integration technologies will consolidate the acquired information, while big data analytics will identify intricate correlations within the datasets. Concurrently, the combination of finite element modeling and neural networks will enable a comprehensive simulation of the adaptability and longevity of FBG sensors in their operational environments. [ABSTRACT FROM AUTHOR]

In order to address the energy dilemma and meet environmental protection requirements, it is an urgent need to develop lead-free piezoelectric energy harvesters (PEHs). However, the low output power density has seriously hindered the application of lead-free piezoceramics as high efficiency energy harvesters. To solve above question, the combination of phase structure regulation and texturing technique in the K 0.5 Na 0.5 NbO 3 - x Bi 0.5 Na 0.5 ZrO 3 -0.5%wtBiFeO 3 (KNN- x BNZ) ceramics was adopted in this work. Because of both the Rhombohedral-Orthorhombic-Tetragonal (R-O-T) multiphases coexistence and texturing engineering, an ultrahigh piezoelectric activity quality factor d 33 × g 33 ∼ 18324 × 10−15 m2 N−1 was achieved in the textured KNN-0.05BNZ (T-KNN-0.05BNZ) ceramics, which is about third times higher than that of random KNN-0.05BNZ (R-KNN-0.05BNZ) (d 33 × g 33 ∼ 6672 × 10−15 m2 N−1) ones. A high output power of ∼0.32 mW was also obtained in the T-KNN-0.05BNZ ceramics by cantilever beam-based energy harvester devices under the resonance frequency of 75 Hz and matched R L of 1.2 MΩ, suggesting that the T-KNN-0.05BNZ ceramics have a great potential for application in the PEHs devices. This result also reveals that the combination of phase structure regulation and texturing technique is an effective way to achieved a high energy harvesting performances. [ABSTRACT FROM AUTHOR]

We use the spatial map of the logarithm of past estimated released earthquake energies as input of fully convolutional networks (FCN) to forecast future earthquakes. This model is applied to California and compared with an elaborated version of the epidemic type aftershock sequence (ETAS) model. Our long-term earthquake forecast simulations show that the FCN model is close to the ETAS model in forecasting earthquakes with |$M \ge 3.0,\,\,4.0,\,\,{\rm{and\,\,}}5.0$| according to the Molchan diagram. Moreover, training and implementing the FCN model is 2000–4000 times faster than calibrating the ETAS model and generating its probabilistic forecasts. The FCN model is straightforward in terms of its neural network structure and feature engineering. It does not require extensive knowledge of statistical seismology or the analysis of earthquake catalogue completeness. Using the earthquake catalogue with |$M \ge 0$| as FCN input can enhance the model's performance in some time–magnitude forecasting windows. [ABSTRACT FROM AUTHOR]

This paper assesses the impact of utilizing statistically defined residual stress fields from cold expansion (Cx) in linear elastic, multi‐point fracture mechanics analyses using the spatial analysis of residual stress (SpARS) methodology. There is significant value and interest in leveraging the increased fatigue life afforded by Cx, but it is imperative to quantify the variability of the residual stress to understand the expected variability in benefit due to Cx. Comparisons of the predicted fatigue lives from SpARS‐produced statistical residual stress fields are made to fatigue test data. Results demonstrated that the less compressive 95% upper bound from the mean residual stress would be a reasonable strategy as it supplies a compromise between safety and inherent material and process variability while still producing a sizable improvement in predicted fatigue life. In this study, using SpARS to incorporate statistically representative residual stress fields in fatigue crack growth analyses demonstrates a methodology to aircraft structural engineers for improved fleet management and allow increased aircraft availability through fewer inspections. [ABSTRACT FROM AUTHOR]

Nonpersistent joints are prevalent in engineering rock masses and are sensitive to cyclic loads induced by geological movements and engineering disturbances. Therefore, studying the fatigue mechanisms of rock masses with nonpersistent joints under cyclic compressive loads is crucial for ensuring the rational design and long‐term stability of rock engineering structures. Based on laboratory experiments, this study employed the discrete element method to create specimens with different nonpersistent joints, and uniaxial compressive cyclic loading tests were conducted on these specimens with different maximum cyclic stress levels. The results show that the joint inclination significantly affects the characteristics of jointed rock, such as deformation modulus, irreversible strain, energy evolution, and crack characteristics. Increasing the maximum stress in the stress path results in a rapid release of hysteretic energy in the jointed regions of the rock, which leads to an exponential decrease in fatigue life while an increase in initial irreversible strain, final irreversible strain, and hysteretic energy density. Additionally, the shear fracture zones on both sides of the model expand, and the propagation and merging of cracks between joints become more extensive and complex. The results are significant for studying rock fatigue instability and structure engineering design. [ABSTRACT FROM AUTHOR]

Colonizing other planets, like Mars, marks a significant milestone in the pursuit of a multi-planetary existence. Millions of people would settle on Mars in self-sufficient bases. Colonizing Mars is a long-term mission that demands self-sufficient, secure habitats and comprehensive planning. Importing structures, such as inflatable structures, from Earth is cost-prohibitive, making the utilization of in-situ resources and onsite construction the most viable approach for preparing the required buildings. Studies have shown that it is possible to produce and craft several kinds of binders and concretes with appropriate mechanical behavior using Martian soil composition; however, determining the optimal option for onsite construction remains a challenge. This study investigates available cement/concrete options for onsite construction on Mars from a structural engineering perspective, taking into account the available resources and technologies. In this regard, the observations and data provided by Martian landers, rovers, orbiters and methods such as Viking-1 & 2, Pathfinder, Spirit, Opportunity, Curiosity, Mars Express, Ultraviolet–visible/Near-infrared reflectivity spectra and Alpha particle X-ray spectrometer were used to obtain a comprehensive and detailed investigation. Eleven types of Martian cement/concrete based on the in-situ resources, soil composition, and available technologies were compared based on the criteria and indices defined in accordance with the structural engineering point of view to select the best practical option for onsite construction. These criteria encompass factors such as mechanical behavior, Martian structural loads, raw material accessibility, available sources, energy required for production, water requirement, curing and hardening time, possibility of using 3D printers, byproduct usefulness, conditions required for hardening and curing, importation requirements from Earth, production complexity, long-term durability and behavior under galactic cosmic rays (GCRs) and solar energetic particles (SEPs). The pros and cons of each cement/concrete option are thoroughly assessed, considering the harsh conditions on Mars. Additionally, the study highlights extra considerations that are crucial for onsite construction on Mars. To determine the best practical option for onsite construction and sustainable colonization, the proposed cements/concretes were compared using multi-scale spider/radar diagrams and a quantitative point of view. This perspective was enabled by assigning weights to each criterion through expert consultation, experimental data, and literature review, ensuring that the diagrams accurately reflect the features of each concrete mix. This comprehensive investigation aims to provide valuable insights into selecting the most suitable cement/concrete for onsite construction on Mars, considering the structural engineering perspective and the long-term goal of sustainable colonization. • The Martian soil composition is investigated using data from Martian landers and orbiters. • Eleven types of Martian concrete/cements are proposed based on available resources and technologies. • Structural engineering criteria and indices are defined to select the best option for onsite construction. • The best practical option for onsite construction is determined using multi-scale spider/radar diagrams. [ABSTRACT FROM AUTHOR]