The Effects of Crystalline Admixture on the Self-Healing Performance and Mechanical Properties of Mortar with Internally Added Superabsorbent Polymer.

Crystalline admixture (CA) can be incorporated into concrete to achieve self-healing of concrete cracks. In this study, both CA and superabsorbent polymer (SAP) were used as self-healing agents to investigate the effects of CA on the self-healing performance and mechanical properties of mortar with internally added SAP at different self-healing ages. The healing effect of cracks in mortar is assessed by crack observation and impermeability. The structure and composition of the filler in the cracks were analyzed by microscopic experiment. The experimental results indicate that CA enhances the healing of cracks in mortar specimens. The chemical reactions of CA primarily contribute to significantly improving the early-age crack-healing ability of the specimens, and the water absorption and expansion ability as well as the internal curing effect of SAP also facilitate the crack-healing process. Increasing the CA content leads to an increase in the Ca/Si ratio of C-S-H, causing a transition from a layered structure to a more compact needle-like structure. When 4% CA was added to the mortar, it resulted in an adequate formation of needle-like C-S-H structures, which eventually penetrate and fill the pits formed by SAP, compensating for the strength loss caused by SAP.

A New Method Based on Time-Varying Filtering Intrinsic Time-Scale Decomposition and General Refined Composite Multiscale Sample Entropy for Rolling-Bearing Feature Extraction.

The early fault diagnosis of rolling bearings has always been a difficult problem due to the interference of strong noise. This paper proposes a new method of early fault diagnosis for rolling bearings with entropy participation. First, a new signal decomposition method is proposed in this paper: intrinsic time-scale decomposition based on time-varying filtering. It is introduced into the framework of complete ensemble intrinsic time-scale decomposition with adaptive noise (CEITDAN). Compared with traditional intrinsic time-scale decomposition, intrinsic time-scale decomposition based on time-varying filtering can improve frequency-separation performance. It has strong robustness in the presence of noise interference. However, decomposition parameters (the bandwidth threshold and B-spline order) have significant impacts on the decomposition results of this method, and they need to be artificially set. Aiming to address this problem, this paper proposes rolling-bearing fault diagnosis optimization based on an improved coyote optimization algorithm (COA). First, the minimal generalized refined composite multiscale sample entropy parameter was used as the objective function. Through the improved COA algorithm, optimal intrinsic time-scale decomposition parameters based on time-varying filtering that match the input signal are obtained. By analyzing generalized refined composite multiscale sample entropy (GRCMSE), whether the mode component is dominated by the fault signal is determined. The signal is reconstructed and decomposed again. Finally, the mode component with the highest energy in the central frequency band is selected for envelope spectrum variation for fault diagnosis. Lastly, simulated and experimental signals were used to verify the effectiveness of the proposed method.

Rolling Bearing Fault Diagnosis Based on Refined Composite Multi-Scale Approximate Entropy and Optimized Probabilistic Neural Network.

A rolling bearing early fault diagnosis method is proposed in this paper, which is derived from a refined composite multi-scale approximate entropy (RCMAE) and improved coyote optimization algorithm based probabilistic neural network (ICOA-PNN) algorithm. Rolling bearing early fault diagnosis is a time-sensitive task, which is significant to ensure the reliability and safety of mechanical fault system. At the same time, the early fault features are masked by strong background noise, which also brings difficulties to fault diagnosis. So, we firstly utilize the composite ensemble intrinsic time-scale decomposition with adaptive noise method (CEITDAN) to decompose the signal at different scales, and then the refined composite multi-scale approximate entropy of the first signal component is calculated to analyze the complexity of describing the vibration signal. Afterwards, in order to obtain higher recognition accuracy, the improved coyote optimization algorithm based probabilistic neural network classifiers is employed for pattern recognition. Finally, the feasibility and effectiveness of this method are verified by rolling bearing early fault diagnosis experiment.

Internal Curing Effect of Pre-Soaked Zeolite Sand on the Performance of Alkali-Activated Slag.

This study clarifies the effects of pre-soaked zeolite sand as an internal curing material on the hydration, strength, autogenous shrinkage, and durability of alkali-activated slag (AAS) mortars. The liquid-to-binder ratio (L/b) of all of the AAS mortars was 0.55. Sodium hydroxide solution was used as an alkali activator and an internal curing liquid. Calcined zeolite and natural zeolite sand replaced the standard sand at 15% and 30%, respectively. The setting time, autogenous shrinkage, compressive strength, ultrasonic pulse velocity, and surface electrical resistivity were tested. The following conclusions were drawn: (1) The addition of zeolite significantly reduces the autogenous shrinkage of AAS mortar. Compared with the control group, 30% calcined zeolite reduced the autogenous shrinkage by 96.4%. Moreover, the autogenous shrinkage of the AAS mortars was noticed in two stages (a variable temperature stage and an ambient temperature stage), and the two stages split at one day of age. (2) The compressive strength of all of the specimens increased as the zeolite sand content increased, and the highest compressive strength was obtained for AAS combined with 30% natural zeolite sand. (3) Internal curing accelerated the formation of the second peak of heat flow and reduced the accumulated heat release. (4) Calcined zeolite sand delayed the setting time of the AAS mortars. (5) The addition of zeolite significantly reduced the surface electrical resistivity of the AAS mortars. In summary, zeolite sand is extremely useful as an internal curing agent to reduce autogenous shrinkage and to increase the compressive strength of AAS mortars.

Effect of Pre-Wetted Zeolite Sands on the Autogenous Shrinkage and Strength of Ultra-High-Performance Concrete.

In this study, the carrier effect of zeolite sands in reducing the autogenous shrinkage and optimizing the microstructure of ultra-high-performance concrete (UHPC) is studied. Pre-wetted calcined zeolite sand (CZ), calcined at 500 °C for 30 min, and natural zeolite sand (NZ), with 15 wt.% and 30 wt.% in UHPC, are used to partially replace standard sands. On that basis, a series of experiments are executed on the developed UHPC, including compressive strength, autogenous shrinkage, X-ray diffraction (XRD), and isothermal calorimetry experiments. With the increase of the zeolite sand content, the autogenous shrinkage of UHPC decreases gradually. Moreover, when the added CZ content is 30 wt.% (CZ30 specimen), it is effective in reducing autogenous shrinkage. Meanwhile, at the age of 28 days, the compressive strength of CZ30 is 97% of the control group. In summary, it is possible to effectively reduce the autogenous shrinkage of UHPC containing 30 wt.% CZ, without sacrificing its mechanical properties.

Stereotactic Administration of Edaravone Ameliorates Collagenase-Induced Intracerebral Hemorrhage in Rat.

BACKGROUND: Edaravone is widely used for treating ischemic stroke, but it is not still confirmed in intracerebral hemorrhage (ICH) as an ideal medication targeting the brain parenchyma. We aimed to investigate the neuroprotective effects of stereotactic administration of edaravone (SI) into the brain parenchyma. METHODS: Intracerebral hemorrhage rat models were established by infusion of collagenase into the caudate nucleus. Neural functional recovery was assessed using modified neurological severity scores (mNSS). A comparative study of therapeutic effects between SI and intraperitoneal injection of edaravone (IP) involved in cerebral edema, blood-brain barrier (BBB) permeability, hematoma absorption, inflammatory response and neuronal apoptosis. RESULTS: Compared with IP, the mNSS was significantly (P < 0.05) improved by SI; cerebral edema and BBB permeability were dramatically ameliorated (P < 0.05); IL-4 and IL-10 levels increased, but IL-1ß and TNF-α levels significantly decreased; neuron apoptosis decreased markedly (P < 0.05); and caspase-3 and Bax expression significantly dropped, but Bcl-2 increased in SI group (P < 0.05). CONCLUSION: SI markedly improved neurological deficits in ICH rat models via antiinflammatory and antiapoptosis mechanisms and promoted M2-type microglia differentiation. SI was effective in rats with collagenase-induced ICH.