Impact Force Research Articles

Enhancing tsunami resilience for coastal bridge piers through seawall-integrated breakwaters: An experimental study

In ocean engineering, breakwater plays a crucial role in protecting coastal structures such as bridge pier from the impact of extreme sea waves. However, enhancing the existing breakwaters' ability to withstand extreme wave remains an urgent issue to address. This study explores the reinforcement strategy of breakwater against extreme sea waves by installing seawalls on the breakwater. Utilizing dam-break wave generation techniques to simulate tsunamis, the study experimentally evaluates the effectiveness of seawalls in reducing the tsunami forces exerted on bridge pier model and numerically investigates the tsunami forces on the seawalls. The focus of this research is to analyze the pressure distribution on seawalls and the impact of different seawall configurations on the reduction of tsunami forces on bridge pier model. Results show that: Under the tested wave condition (a) The height of the seawall on the breakwater is a critical parameter, as increasing wall height reduces the tsunami forces exerted on the bridge pier behind it. The taller seawalls are subjected to greater tsunami forces in tested cases; (b) The trend of extreme pressure values for different seawalls starts increasing at the bottom and then decreases; (c) There is a critical distance that the breakwater being most effective at reducing tsunami impact forces between the bridge pier model and the breakwater. This study not only deepens the understanding of the interaction between tsunami waves and seawalls but also offers practical guidance for designing structures with disaster resilience, significantly influencing the future design and construction of tsunami-resistant coastal infrastructure.

Geometry-modulated all organic 3D printed smart PLA fibers for flextension amplified giant mechanical energy harvesting and Machine learning assisted pressure mapping

Piezoelectret sensors offer a promising avenue for harvesting abundant mechanical energy in the environment, providing a sustainable power solution for low-powered electronics. However, effectively harnessing large impact mechanical energy remains a challenge. In this study, we introduce a novel 3D cylindrical self-powered piezoelectret sensor capable of converting irregular axial impact forces into uniform radial pressures, enabling efficient large-scale impact mechanical energy harvesting. The cylindrical piezoelectret sensor, operating via a flextensional mechanism, was fabricated using 3D printed poly(lactic acid) (PLA) fibers as the piezoelectret layer and poly(3,4-ethylenedioxythiophene) (PEDOT)-coated PLA as the electrode layer. Our cylindrical sensor demonstrates the output voltage, and current of ∼ 11.4 V and 7.2 μA, representing remarkable improvement of 250 % and 160 % respectively, compared to flat fiber membrane device. Furthermore, we leverage IoT connectivity and machine learning techniques to utilize the fabricated robotic sensor for pressure mapping applications. Through machine learning algorithms, we achieve a remarkable accuracy of 100 % in character identification based on sensor data. This work highlights the potential of organic robotic sensors for efficient energy harvesting and intelligent pressure mapping applications, paving the way for the development of sustainable and adaptive sensor systems for various real-world scenarios.

Identification of modal parameters of soil specimen based on impact force

This study used vibration testing signals of soil samples under external loading to identify modal parameters (including natural frequencies and damping ratios) with different compaction degrees. Based on these parameters, a novel approach was proposed for reliable roadbed vibration compaction control and compaction process optimization. The experimental section utilized six soil samples with varying compaction degrees as experimental subjects, using the hammering method as the excitation mode. Subsequently, the frequency response function and modal parameters of the sample system were obtained through the acquisition, analysis, and parameter identification of samples’ acceleration signals. Firstly, samples with compaction degrees ranging from 88 % to 97 % primarily exhibited three modes, with the second modal frequency response displaying the weakest amplitude, and the fundamental mode being the dominant one. Additionally, parameter identification results revealed that the fundamental modal frequency exhibited a significant negative exponential growth with increasing compaction degree, while the second and third modal frequencies showed significant linear growth. Furthermore, the average damping ratio also demonstrated a tendency toward linear change with increasing compaction degree. Finally, the feasibility of modal parameters being actively used in practical engineering is discussed. Consequently, this study aimed to propose an indicator system for accurately assessing the bearing level of compacted soils from a modal dynamics perspective and to integrate modal dynamic indicators with density-class indicators into further optimization design work on road compaction processes.

Theoretical and experiment optimization research of a frequency up-converted piezoelectric energy harvester based on impact and magnetic force

Harvesting environmental vibrations to power electronic components is an essential approach for addressing the power supply challenge in MEMS. However, conventional vibration energy harvesting systems frequently suffer from limited frequency bandwidth and high-frequency deficiencies. This paper proposes a novel up-frequency structure for piezoelectric vibration energy harvesting (VEH) that relies on both nonlinear magnetic force and piecewise linear force. The proposed VEH’s nonlinear dynamic characteristics are analyzed theoretically, and an experimental prototype machining and vibration test platform are constructed. Theoretical and experimental results are compared and analyzed by conducting basic experiments and key parameter optimization experiments. The research results demonstrate that the proposed VEH can efficiently harvest vibration energy in low-frequency and wide-band environments. Regarding the system parameters, higher vibration acceleration results in increased output voltage and wider working frequency bandwidth. Reducing the gap distance enhances piecewise linear vibration, which broadens the working frequency bandwidth. Furthermore, the proposed VEH’s ability to harvest low-frequency vibrations can be enhanced by reducing the magnet distance, thereby reducing the linear resonance frequency of the system. The findings of this study offer valuable insights for advancing the engineering application of MEMS self-power supply technology.

Analysis and evaluation of development characteristics of debris flow in Longshougou

Long Shougou is located at the exit of Hei he River in Zhang ye City, which is directly facing the reservoir of Long Shougou Hydropower Station. Through site survey, UAV flight and indoor simulation calculation, the development characteristics and risk of Long Shougou debris flow were analyzed and evaluated. The results show that: Long Shougou debris flow is in the "development period", belonging to "small", "easy" and "high frequency" debris flow; The length of Long Shougou Channel is 1.70 km, the circumference is 3.76 km, the area is 0.72 km2 , the relative height difference is nearly 584 m, the longitudinal gradient is 342.27 ‰, and the overall bending coefficient is 1.14; Gully sediments are mainly gully bed deposits and slope collapse deposits, with total reserves of 20.94 ×104 m3 and dynamic reserves of 7.76 ×104 m3 ; Calculated according to the designed rainstorm frequency of 1%, the flow velocity of debris flow at the gully mouth is 2.64m /s, the total amount of primary overflow is 17,296.41m3 , the primary outflow of solid matter is 7956.35m3 , and the overall impact pressure of debris flow is 16.32kPa. The maximum impact force of a single stone is 2.56kN according to 0.5m; It is suggested to consider the impact of the annual inflow of debris flow on the water quality of the Longshou hydropower station reservoir and the impact on the power station switching station near the Gulou port, and do a good job in the relevant sediment discharge measures.

Porosity suppression mechanism analysis in narrow-gap oscillating laser-MIG hybrid welding of aluminum alloys based on keyhole stability and molten pool flow behavior

In this study, the keyhole dynamic behavior and molten pool flow were investigated to elucidate the effects of oscillating laser on porosity in narrow-gap oscillating laser-MIG hybrid welding of aluminum alloys. A weld with a porosity of 0.08% was produced at the laser oscillating frequency of 600 Hz and diameter of 1 mm, while 2.27% without oscillating laser. Compared to non-oscillating laser, keyhole opening size increased by about 2.3 times and keyhole depth fluctuation was suppressed. The forces acted on the interface between keyhole wall and molten pool became more balanced. The increased vapor recoil pressure overcame the combined closure effect of gravity and molten pool pressure. While applying oscillating laser, the vortex in molten pool was eliminated and the liquid metal flow was more stable. The combined impact force caused by droplets transfer and liquid metal convection due to constraining effect of narrow gap was buffered, which had less effect on molten pool and keyhole stability. The liquid metal tended to flow from the molten pool inside to surface, which favored the escape of bubbles from the molten pool.

Daidzin improves neurobehavioral outcome in rat model of traumatic brain injury

Traumatic brain injury (TBI) is associated with the etiology of multiple neurological disorders, including neurodegeneration, leading to various cognitive deficits. Daidzin (obtained from kudzu root and soybean leaves) is known for its neuroprotective effects through multiple mechanisms. This study aimed to investigate the pharmacological effects of Daidzin on sensory, and biochemical parameters, cognitive functions, anxiety, and depressive-like behaviors in the TBI rat model. Rats were divided into four groups (Control, TBI, TBI + Ibuprofen (30 mg/kg), and TBI + Daidzin (5 mg/kg)). Rats were subjected to TBI by dropping a 200 g rod from a height of 26 cm, resulting in an impact force of 0.51 J on the exposed crania. Ibuprofen (30 mg/kg) was used as a positive control reference/standard drug and Daidzin (5 mg/kg) as the test drug. Neurological severity score (NSS) assessment was done to determine the intactness of sensory and motor responses. Brain tissue edema and acetylcholine levels were determined in the cortex and hippocampus. Cognitive functions such as hippocampus-dependent memory, novel object recognition, exploration, depressive and anxiety-like behaviors were measured. Treatment with Daidzin improved NSS, reduced hippocampal and cortical edema, and improved levels of acetylcholine in TBI-induced rats. Furthermore, Daidzin treatment improved hippocampus-dependent memory, exploration behavior, and novel object recognition while reducing depressive and anxiety-like behavior. Our study revealed that Daidzin has a therapeutic potential comparable to Ibuprofen and can offer neuroprotection and enhanced cognitive and behavioral outcomes in rats after TBI.

Influence of steel slag as partial replacement of coarse aggregate in the fibre reinforced concrete curved beam under static and impact load

The investigation is focused on the utility of steel slag in the reinforced concrete beams under static and impact loads through the experiment and simulations. The partial substitution of conventional coarse aggregate with steel slag aggregate 30 % and fibre volume was fixed at 0.75 %, were considered. The three-point bending test is used to evaluate the static response, while a impact test was employed for impact tests. It was observed that the influence of steel slag in the curved beam is found to be increased 36 % as compared to curved beam without steel slag, however, the addition of steel slag aggregate in the straight beam improves marginally, i.e. 4 % under static loading. In case of impact loading, the influence of steel slag in the curved beam is found to be increased 14 % whereas the addition of steel slag aggregate in the straight beam improves, i.e. 7 %, as compared to curved beam without steel slag. It is also concluded that the measured peak acceleration of MSS0 beams found higher as compared to the MSS30 and the reason may be due to the material density influences the acceleration of wave generated by the impact load. Also, the crack width in the straight beam MSS30 is 15 mm whereas same for the MSS0 mix found to be 35 mm and the reason for lesser crack width attributed to the good bonding between the steel slag aggregate and the concrete matrix lead to better ITZ. It was also observed that the crack width in the curved beam found to be 10 and 30 mm for MSS30 and MSS0, respectively. The measured acceleration found to be higher of MSS0 as compared to the MSS30. Further, the finite element analysis was performed using ABAQUS CAE and the concrete damage plasticity model and Johnson-Cook (J-C) material model were used in order to model the behavior of concrete and steel bar, respectively. The maximum deviation on the impact force on straight beam under static analysis (ABAQUS/Standard) found to be 21 % whereas same was found to be 12 % in the impact analysis (ABAQUS/Explicit).

Analysis of the dynamic contact behaviour of high-speed train transmission gear excited by wheel defects

Studies on wheel flatness and polygonal wear have demonstrated that wheel defects cause severe impact forces at the wheel–rail interfaces. This study investigated the dynamic contact mechanical behaviour of high–speed train transmission gears when subjected to wheel defects. First, a train-track coupling dynamics model was established, considering the localized contact characteristics of transmission gears. This model was developed using the slice method and the Hertz contact model, exploring the spatial coupling effects between the gear contact interface and the train–track interface. Subsequently, the dynamic model was employed to extract essential contact mechanical parameters of the transmission gear under the influence of wheel defects, including gear meshing load, gear contact stress, and sliding velocity. Furthermore, an analysis was conducted to uncover and elucidate the mechanism by which wheel flatness and polygonal wear impact the dynamic contact behaviour of the transmission gear. This study underscores the importance of considering wheel defects when assessing the contact fatigue and wear performance of high-speed train transmission gears.

Bionic design and mechanical performance of spiderweb-inspired mesh fabrics

The mesh structure is widely applied due to its unique structure and exceptional performance, especially spider web structural materials, which have attracted widespread interest. However, the existing flexible spider web structural materials face problems such as low production efficiency and structural defects, constraining their practical application. This study proposed two types of no-knot mesh fabrics according to the topological structure of spider web and explored their mechanical properties. Both knitted loop divergent and ring spiral mesh fabrics showed excellent mechanical performance, with the ring spiral fabric demonstrating higher maximum failure forces (2217 N in tensile and 5738 N in bursting tests) and superior impact performance in terms of maximum impact force and energy absorption. Both fabrics exhibited similar creep behaviors and could withstand 70 J impact energy with an energy absorption rate around 90 %. This work may provide new strategies and inspiration for the preparation of high-performance flexible mesh materials and further helps in developing applications of spiderweb-inspired mesh fabrics in engineering fields.

Machine learning approach to evaluating impact behavior in fabric-laminated composite materials

Fabric-layered composites play a crucial role in safety and surveillance applications, making it imperative to accurately predict their impact behavior. This research focuses on creating a machine-learning model to predict the impact behavior of fabric-stacked composites, specifically carbon and Kevlar fabrics. Low-velocity impact tests were performed with varying parameters, and the impact energy and laminate thickness information were used to train machine-learning models to predict impact properties such as impact force, displacement, and absorbed energy. It was observed that the impact force increased by 118.5 % in carbon-laminated fibers and 175.8 % in Kevlar-laminated fibers, while the hybrid layer showed a 101.4 % increase upon impact from 16J. Displacement can affect the stability of the layered structure; thus, a similar stacking sequence is less stable than the hybrid laminated structure. In terms of absorbed energy, as the laminated layers increase, carbon fiber laminate absorbs 4.8 times more energy, and Kevlar fiber and hybrid laminated structures absorb 3 times more energy at higher impact energy. Furthermore, four machine learning models were used to investigate the impact behavior of identical and mixed-layered laminated composites. The impact force and displacement were predicted with higher accuracy using the polynomial regression model, achieving 80 % and 89 % accuracy, respectively. The support vector machine predicted the absorbed energy with approximately 96 % accuracy. In continuing, the experimental results closely matched the predictions made by the other machine learning models utilized in this study. Additionally, the importance of distinctive features and their influence on the performance of the machine learning-based model were interpreted using transposed features of importance and dependency plots. Various failure modes in fabric laminated composites were also identified, providing insights to enhance the performance of stacked fiber materials.

Experimental investigation on the horizontal impact response of precast RC bridge piers with grouted sleeve connections considering defects

To investigate the behaviour of precast bridge piers with grouted sleeve connections under horizontal low-velocity impact loads, twelve precast reinforced concrete (RC) bridge pier specimens and two cast-in-place reference specimens were tested to study the effect of grouting defect degree, impact velocity and fabricated method (precast vs. cast-in-place) on the impact response of RC piers. The failure modes, rebar strains, impact forces, displacement, and energy dissipation capacity of both cast-in-place and precast specimens were compared and analyzed. The results indicate that due to inertial effects induced by impact loading, the peak impact forces were three to seven times greater than the peak static loads. Transverse cracks were more likely to initiate in the grout layer for precast specimens, with diagonal cracks extending from the loading position to the pier bottom after impact. As horizontal impact velocity increased, the impact force, maximum displacement, and energy absorption ratio also significantly increased. The impact force-time curves of the pier specimens with grouting fullness ranging from 30 % to 100 % showed minimal differences compared to the cast-in-place specimen. A decrease in grouting fullness led to an increase in the maximum displacement of the pier specimens and reduced the transmission of impact waves between the reinforcement bars.

Boosting piezoelectric properties of PVDF nanofibers via embedded graphene oxide nanosheets

Tremendous research efforts have been directed toward developing polymer-based piezoelectric nanogenerators (PENG) in a promising step to investigate self-charging powered systems (SCPSs) and consequently, support the need for flexible, intelligent, and ultra-compact wearable electronic devices. In our work, electrospun polyvinylidene fluoride (PVDF) nanofiber mats were investigated while graphene oxide (GO) was added with different concentrations (from 0 to 3 wt.%). Sonication treatment was introduced for 5 min to GO nanosheets before combined PVDF solution. A comprehensive study was conducted to examine the GO incremental effect. Microstructural and mechanical properties were examined using a scanning electron microscope (SEM) and a texture analyzer. Moreover, piezoelectric properties were assessed via various tests including impulse response, frequency effect, d33 coefficient, charging and discharging analysis, and sawyer tower circuit. Experimental results indicate that incorporation of GO nanosheets enhances piezoelectric properties for all concentrations, which was linked to the increase in β phase inside the nanofibers, which has a significant potential of enhancing nanogenerator performance. PVDF-GO 1.5 wt.% shows a notably higher enhancing effect where the electroactive β-phase and γ-phase are recorded to be boosted to ~ 68.13%, as well as piezoelectric coefficient (d33 ~ 55.57 pC/N). Furthermore, increasing impact force encouraged the output voltage. Also noted that the delivered open circuit voltage is ~ 3671 V/g and the power density is ~ 150 µw/cm2. It was observed that GO of concentration 1.5 wt.% recorded a conversion efficiency of ~ 74.73%. All results are in line, showing better performance for PVDF-GO 1.5 wt.% for almost all concentrations.

Water Impact: When a Sphere Becomes Flat.

A large hydrodynamic force accompanies the vertical impact of bodies on water. While added mass phenomena govern these forces for both spherical and flat impactors, the dynamics of a trapped gas layer critically alters the flat case, reducing the peak pressure below that predicted by water hammer theory. An impactor with a spherical nose cap looks increasingly flat as the nose curvature approaches zero. This causes one to ask at what curvature a spherical cap impactor transitions to flat impact behavior. We find this transition, relate limiting behaviors to theories, and dispel the long-held belief that the largest water impact forces occur for flat bodies.

Impact Force Localization and Reconstruction via ADMM-based Sparse Regularization Method

In practice, simultaneous impact localization and time history reconstruction can hardly be achieved, due to the ill-posed and under-determined problems induced by the constrained and harsh measuring conditions. Although ℓ1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ell_{1}$$\\end{document} regularization can be used to obtain sparse solutions, it tends to underestimate solution amplitudes as a biased estimator. To address this issue, a novel impact force identification method with ℓp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ell_{p}$$\\end{document} regularization is proposed in this paper, using the alternating direction method of multipliers (ADMM). By decomposing the complex primal problem into sub-problems solvable in parallel via proximal operators, ADMM can address the challenge effectively. To mitigate the sensitivity to regularization parameters, an adaptive regularization parameter is derived based on the K-sparsity strategy. Then, an ADMM-based sparse regularization method is developed, which is capable of handling ℓp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ell_{p}$$\\end{document} regularization with arbitrary p values using adaptively-updated parameters. The effectiveness and performance of the proposed method are validated on an aircraft skin-like composite structure. Additionally, an investigation into the optimal p value for achieving high-accuracy solutions via ℓp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ell_{p}$$\\end{document} regularization is conducted. It turns out that ℓ0.6\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ell_{0.6}$$\\end{document} regularization consistently yields sparser and more accurate solutions for impact force identification compared to the classic ℓ1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ell_{1}$$\\end{document} regularization method. The impact force identification method proposed in this paper can simultaneously reconstruct impact time history with high accuracy and accurately localize the impact using an under-determined sensor configuration.

Online Flow Measurement of Liquid Metal Solutions Based on Impact Force Sequences: Modeling Analysis, Simulation, and Validation of Experimental Results.

Aiming at the existing high-temperature liquid metal flow online accurate measurement by the metal melt characteristics, installation space, and high-temperature environment adaptability limitations, this paper innovatively puts forward a soft measurement method based on the impact force generated in the fluid flow process as an observational variable series. Fluid mechanics theory and simulation software are used to analyze and verify the feasibility of the impact force as an observable variable to measure the flow rate, followed by the construction of the CNN-LSTM-CNN-Double (CLCD) flow measurement model of impact force and flow rate based on the parameters of the learning rate and the number of training times, and finally the construction of a test platform for the flow measurement, and the validity of the method is verified through actual operation.

Application of the material point method (MPM) to characterise the impact forces of granular landslides on rigid obstacles

This study deploys the Material Point Method (MPM) to investigate the soil pressures exerted on a 3D rigid obstacle partially obstructing a dry granular flow; a configuration not previously addressed in the literature on a numerical modelling basis. A 2D simulation is first developed and validated against a flume experiment that monitors the interaction of dry granular flows with retaining structures under varying flume angles. The model is then extended to 3D, enabling the adjustment of the obstacle's geometry to observe the impact of granular flows on impermeable rigid obstacles partially obstructing the soil material. The trend in the recorded soil forces exhibits an initial peak that occurs simultaneously with the first impact, followed by a steep degradation branch as the soil deposits in front of the structure, thus reducing the flow's dynamics. The numerical simulation is subsequently upscaled to ensure that macroscopic dimensional analysis adequately interprets small-scale numerical observations to mimic prototype conditions using the MPM approach. Simplified factors are finally derived to represent the response characteristics of large-scale simulations based on the original findings.

Analysis of sensitive clay landslide mechanism and impact pipeline bearing characteristics considering spatial variability

Landslides caused by the progressive failure of sensitive clay slopes may cause substantial economic losses and environmental pollution to pipelines. This study utilizes the Karhunen-Loève (K-L) expansion method, the coupled Eulerian-Lagrangian (CEL) method, and the Monte Carlo method to model the large deformation behaviour of slopes with spatial variability. The proposed RCEL-MC framework for joint analysis of extensive deformation-probability statistics of landslide impact on pipelines confirms that the spatial variability clay slope instability failure mechanism, considering the soil softening effect under earthquake action, aligns more closely with real-world scenarios. Furthermore, based on the statistical failure probability of pipelines impacted by landslides, a sensitive clay slope pipeline safety design method is suggested. The research highlights that the random field parameters significantly influence the load-bearing characteristics of pipelines affected by spatially variable slope progressive failure landslides. The uncertainty surrounding the maximum impact force on pipelines notably increases with the rise of the horizontal correlation length and variability coefficient. When accounting for spatial variability, the maximum impact force on landslide pipelines surpasses the deterministic model analysis results by 28-69 %. It is emphasized that the deterministic model analysis, which neglects the spatial variability of soil and the soil softening effect, may seriously underestimate landslide risk. Based on the criteria for pipeline buckling failure and yield failure, it is advised that the safe design parameters for pipelines in practical projects should fall within the intersection of the secure regions defined by the two failure criteria.

Influence of manufactured sand, recycled aggregate, reinforcement ratio and wire mesh on the response of reinforced concrete slabs under impact loading

Targeting towards the sustainable goal, the emergence of manufacturing sand (M-sand) and recycled coarse aggregate (RCA) as an alternate for natural aggregates has unfolded new prospects for constructional practices in the world. Therefore, the investigation is focused to study the influence of RCA, M-Sand, Combination of RCA and M-sand, wire mesh and steel reinforcement under impact loading. The reinforced concrete slabs (1 layer @ 25 mm c/c) slabs [S1-S4, S9, S11, S13 and S15] was studied using M-sand (100 %) and recycled coarse aggregate (25 %) with a concrete compressive strength of 40–50 MPa. Also, the flexural reinforcement was varied as 0.23, 0.32 and 0.39 % of the cross-section area. The experimental results were presented in terms of failure pattern, impact force-reaction force, midpoint displacement and energy absorption capacity. It was observed that the spalling of concrete to the conventional slab (S1) whereas, the spalling of concrete as well as formation of radial cracks were observed on slab with RCA (S2). It was also observed that the severe spalling with formation of radial cracks in the slab with M-sand and RCA (S4), however the impactor did not perforate. The peak impact force on control slab, S1, S2, S3 and S4 was 145, 187, 122 and 167 kN, respectively. The significant increase in peak impact force in S2 is due to the use of micro silica fume treatment which enhanced the mechanical properties of RCA. The peak impact force in slab S3 by M-sand found reduced by 15 %, whereas the same was found increased by 15 % in case of slab S4 by RCA and M-sand, as compared to S1. The maximum crack width in slab S15 was limited to 1–2 mm whereas same was found to be 9–10 mm in case of slab S13. The use of wire mesh found to enhance the global bending deformations as well as crack width in the slab. It is concluded that the utilization of wire mesh along with steel reinforcement proves to be an effective method to diminish the permanent deformation. Further, finite element software ABAQUS was used to model the slab under impact loading and the results were compared with the experimental results. The predicted peak impact force of slab S1 was found to be good agreement with the experimental results. However, the predicted peak impact force on slab S2-S4 found to have maximum deviation 11 % as compared to experimental results.

Measurement of sand particle motion speed in multiphase wind-sand flow based on piezoelectric ceramic sensors

Abstract Utilizing Pb(ZrTi)O3-5A piezoelectric ceramic (hereafter referred to as PZT-5A) as sensors, we studied the movement speed of sand particles in multiphase wind-sand flows. We developed a mathematical model that effectively links the impact force of sand grains with the output voltage of PZT-5A, incorporating factors such as the piezoelectric coefficient and sand particle characteristics. Additionally, we proposed a new method to accurately determine the elastic recovery coefficient of sand particles using PZT-5A sensor measurements and experimental setups, which is significant for the field of material science. Wind tunnel experiments revealed that at heights ranging from 0.1 to 1.0m, sand particle speeds range from 52.8% to 91.4% of wind speeds. As wind speed increases to 15m/s, sand particle speed nears 91.4% of wind speed. Yet, at a constant wind speed, sand speed drops as sediment discharge rises. This research offers fresh insights into sand particle dynamics in wind-sand contexts.