Load Location Research Articles

Feasibility analysis of implementing a logistics integration center in amazon region using AHP

The celebrated and constant evolution of operating operations and market companies compensate for the integration of process participants and the need to promote new operating strategies, as well as the integration of process participants, as well as the need for integration of participants in the process resources involved in the supply chain. From this scenario of need for evolution and modification of market relations, the use and implementation of outstanding projects of logistics integration centers as a way of improving the logistics reality. Corroborating this reality, the main objective of this research was to verify the feasibility and benefits generated from the implementation of a Logistics Integration Center in the State of Pará - CILOG, from the perspective of the demand for production flow, availability of modal and location. To verify the feasibility of production for implementation, foam consulted without data regarding load states and load locations in adjacent areas, as well as potential, functionalities and resources of the implementation systems, with flow as the main centers of selection and, systematic and systematic way, of the feasibility and evaluation of the benefits generated from the implementation of the needs of the demand for services of attendance of the neighboring states, as well as of the entrances for the attendance of the neighboring states demand of flow of the production, availability of modals and geographic location. For this, an A-SWOT hybrid methodology was applied to define the HP location criteria and the decision factors that characterize the implementation of logistics such as the Logistics Integration Center (CILOG) in the Amazon Region, as well as the definition of the best for this implementation, based on three local alternatives: Santarém, Alça Viária and Miritituba. With the evaluation, Santarém (on the banks of the Amazon River) was listed as the best location for the installation, from the perspective of locational, operational, relating to capacity and territories

Recursive Bayesian estimation of wind load on a monopile-supported offshore wind turbine using output-only measurements

Offshore wind turbine structures experience combined wind and wave loading during their lifetime, and the cyclic characteristics of these loads significantly impact the fatigue life of the support structure. Continuous monitoring of stress-related quantities, such as strain time histories at hotspot locations of the structure, can help to estimate the fatigue life. However, sparse measurements from the substructure necessitate using a digital twin as a tool for structural health monitoring by creating a virtual model. This virtual model relies on real-time input loads for virtual sensing and stress-related quantities prediction. However, the exact loading on these structural systems is often unknown or estimated with considerable uncertainty. This paper implements a recursive window-based Bayesian estimator for input load estimation and virtual sensing of acceleration and strain time history at unmeasured critical locations using output-only measurements. The estimator is numerically and experimentally validated in the context of input load estimation for an offshore wind turbine, and the results are compared with a traditional augmented Kalman filter and a linear regression approach for the quasi-static component of loading. The method is first demonstrated through a numerical study using a finite element model of a 6 MW offshore wind turbine, where input wind load time histories are accurately estimated. Then, the framework is applied to the real data measured from an offshore wind turbine in the North Sea. The study demonstrates the window-based Bayesian input estimator as a promising tool for the digital twinning of offshore wind turbines, demonstrating superior accuracy in input load estimations and full response predictions compared to the augmented Kalman filter and linear regression methods without the constraint of collocated measurements at input load locations.

Population-based in silico modeling of anatomical shape variation of the knee and its impact on joint loading in knee osteoarthritis.

Anatomical knee joint features and osteoarthritis (OA) severity are associated, however confirming causals link to altered knee loading is challenging. This study leverages statistical shape models (SSM) to investigate the relationship between joint shape/alignment and knee loading during gait in knee OA(KOA) patients to understand their contribution to elevated medial knee loading in OA. Musculoskeletal (MSK) models were created for the mean as well as the first eightSSM principal modes of variation (-3,-2,-1, +1, +2, +3 standard deviations for each mode) and used as input to a MSK modeling framework. Using an identical KOA gait pattern (i.e., joint kinematics and ground reaction forces), we ran simulations for each MSK model and evaluated medial compartment loading magnitude and contact distribution at the instant of first and second peak of knee joint loading. An increase in external rotation, posterior tibia translation and a decrease in medial joint space and medial femoral condylar size predisposed the medial compartment knee joint to overloading during gait. This was coupled with an anterior and medial shift in contact location with increasing external rotated tibial position and increasing posterior tibial translation with respect to the femur. Next, results also highlighted a posterior shift of the medial compartment loading location with decreasing medial joint space. This study provides important population-based insights on how knee shape and alignment predispose individuals with KOA to elevated medial compartmental knee loading. This information can be crucial in assessing the risk for medial KOA development and progression.

Efficient Schemes for Optimizing Load Balancing and Communication Cost in Edge Computing Networks

Edge computing architectures promise increased quality of service with low communication delays by bringing cloud services closer to the end-users, at the distributed edge servers of the network edge. Hosting server capabilities at access nodes, thereby yielding edge service nodes, offers service proximity to users and provides QoS guarantees. However, the placement of edge servers should match the level of demand for computing resources and the location of user load. Thus, it is necessary to devise schemes that select the most appropriate access nodes to host computing services and associate every remaining access node with the most proper service node to ensure optimal service delivery. In this paper, we formulate this problem as an optimization problem with a bi-objective function that aims at both communication cost minimization and load balance optimization. We propose schemes that tackle this problem and compare their performance against previously proposed heuristics that have been also adapted to target both optimization goals. We study how these algorithms behave in lattice and random grid network topologies with uniform and non-uniform workloads. The results validate the efficiency of our proposed schemes in addition to the significantly lower execution times compared to the other heuristics.

Probabilistic modeling of multivariate extreme non-Gaussian wind loads and its applications in envelope engineering

Probabilistic modeling for non-Gaussian wind load fields under extreme winds is crucial to the quantitative risk and reliability analysis of envelope structures. Based on the multi-point synchronous wind load data during typhoons, a probabilistic model is proposed to characterize multivariate non-Gaussian wind loads to improve the accuracy of the risk analysis considering data dimension reduction. In the proposed model, the Pareto distribution function is utilized to fit the marginal distribution, and the copula function is employed to construct the dependent structure of wind loads from different locations. In the marginal fitted results, the extreme wind load value in the edge region is about 0.10–0.15 higher than those from inner measurement points at quantile p = 95 %. In addition, the variation gradient from the different variable directions is approximately equal, and a sharp variation occurs at the point (0.10, 0.10) for bivariate joint distributions. Engineering applications given in this article are composed of three parts: calculating regional exceeding probability, estimating wind load vector under a specific regional exceeding probability, and determining the location of joint extreme wind loads using the joint gradient value. Finally, risk analysis of existing roof coverings is carried out, the edge corner region is weaker, and two engineering recommendations are given. For determining the regional design wind load, a comprehensive calculation framework considering the temporal dependence of different locations is established, and the reduction rates are in the range (5 %, 25 %).

RNA Nanotechnology for Codelivering High-Payload Nucleoside Analogs to Cancer with a Synergetic Effect.

Nucleoside analogs are potent inhibitors for cancer treatment, but the main obstacles to their application in humans are their toxicity, nonspecificity, and lack of targeted delivery tools. Here, we report the use of RNA four-way junctions (4WJs) to deliver two nucleoside analogs, floxuridine (FUDR) and gemcitabine (GEM), with high payloads through routine and simple solid-state RNA synthesis and nanoparticle assembly. The design of RNA nanotechnology for the co-delivery of nucleoside analogs and the chemotherapeutic drug paclitaxel (PTX) resulted in synergistic effects and high efficacy in the treatment of Triple-Negative Breast Cancer (TNBC). The 4WJ-drug complexes were confirmed to have efficient tumor spontaneous targeting and no toxicity because the motility of RNA nanoparticles has been previously shown to enable these RNA-drug complexes to spontaneously accumulate in tumor blood vessels. The negative charge of RNA enables those RNA complexes that are not targeted to tumor vasculature to circulate in the blood and enter the urine through the kidney glomerulus, without accumulating in organs, therefore being nontoxic. Drug incorporation into RNA 4WJ can be precisely controlled with a defined loading amount, location, and ratio. The incorporation of nucleoside analogs into 4WJ only requires one step using nucleoside analogue phosphoramidites during solid-phase RNA synthesis, without the need for additional conjugation and purification processes.

Analysis of the stress-deformed state of the structure of road clothing depending on the location of the load relative to the edges of the combined slab

Abstract. Problem. Cement-concrete coatings are characterized by the complexity of repair work, therefore, for their repair or new construction, it is advisable to use asphalt-concrete coating. This constructive solution during the repair of cement concrete slabs helps to improve their technical and operational condition since the asphalt concrete layer performs the function of a protective or wearresistant layer on cement concrete slabs. The operating conditions of asphalt concrete layers on cement concrete slabs are significantly different from those typical for other structural solutions. The existing methods of calculating the strength of asphalt concrete coatings for hard road wear are not accurate enough, because they take into account only certain criteria of the strength of the asphalt concrete layer. The specifics of the stress-strain state of the asphalt concrete layer on cement concrete slabs under different load conditions, such as the middle of the slab, the edge of the slab, and the corner of the slab, are not taken into account. Given the complex stressstrain state of the asphalt concrete layer on a rigid base, the analysis of the stress-strain state is particularly relevant, aimed at determining the most dangerous variant of the location of the transport load to ensure the strength of the asphalt concrete layer. Goal. The purpose of this article is to determine the stress-deformed state of an asphalt concrete layer on a rigid base with various options for applying a transport load, which will allow the establishment of the most dangerous option for the location of the load. Methodology. General methods of solving problems of the mechanics of a deformed solid body were used to develop a calculation scheme and select a material model. Simulation of the stress-strain state of the road surface was carried out using the finite element method using the ANSYS software complex, investigating three options for placing the transport load: in the center of the slab, on its edge, and in the corner. Results. According to the results of the simulation of the stress-strain state of a combined slab made of an asphalt concrete layer on a rigid base, it was established that the edge of the slab is the most unsafe both in terms of tensile and shear stresses for a cement concrete slab. For the asphalt concrete layer, placing the load in the corner of the slab is the most dangerous both in terms of tangential shear stresses and Mises stresses. Originality. According to the results of the simulation of the stress-strain state of a combined slab made of an asphalt concrete layer on a rigid base, it was established that the edge of the slab is the most unsafe both in terms of tensile and shear stresses for a cement concrete slab. Practical value. Based on the results of modeling the stress-strain state of a combined slab made of an asphalt concrete layer on a rigid base, it was established that the edge of the slab is the most dangerous both in terms of tensile and shear stresses for a cement concrete slab. For the asphalt concrete layer, placing the load in the corner of the slab is the most dangerous both in terms of tangential shear stresses and Mises stresses

The characterization of zein/xanthan gum composite oleogel: A comparative study of bioactive substances in interface and oil phases

Bioactive substances can be strategically positioned in different locations within a system to regulate its functionality. In this study, we investigated the effects of loading curcumin into two different mediums (interface layer (M1O) and corn oil (M2O)) on the macro- and micro-properties of a zein-xanthan gum (XG) oleogel, aimed at utilizing the oleogel as a fat substitute. The results revealed that the oleogel exhibited a spongy porous bridging network structure, particularly prominent in M2O, which showed a higher elastic modulus (G′) and an impressive structural recovery rate, reaching up to 98.50 ± 0.60%. While the location of curcumin loading had minimal impact on the oleogel's macro-properties (such as rheology, thermal behavior, and oil binding capacity), significant differences were observed in the micro-properties. The oleogel maintained a high encapsulation efficiency (EE), exceeding 85% in both loading locations, with M1O slightly outperforming M2O. Notably, M2O showed lower free fatty acid release and higher bioaccessibility (about 10% greater than M1O), which was attributed to a denser spongy porous network enhanced by electrostatic attraction, hydrogen bonding, and hydrophobic interactions within the zein-XG matrix. Curcumin underwent significant degradation under prolonged UV and alkaline conditions, but showed minimal damage when exposed to heat in both mediums. Additionally, M2O demonstrated superior UV and thermal stability compared to M1O, which showed better pH stability. Cookies made with oleogel as a butter alternative exhibited improved appearance and quality when added at medium or low levels. This study suggests a viable method for manipulating the loading locations of bioactive substances in oleogel according to specific needs, potentially paving the way for the development of zein-XG oleogel as an effective butter substitute.

Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin

Accurately detecting the location and intensity of impacts is crucial for ensuring structural safety. Currently, AI-based structural impact detection methods are widely used for their excellent detection accuracy. However, their generalization capability is limited by the scenarios present in the training data. Many complex and dangerous impact scenarios are difficult to conduct real-world experiments on to collect sufficient samples. To capture all impact scenarios and fully leverage the advantages of AI-based detection technologies, advanced methods involve combining real-world structural monitoring data with corresponding numerical models to construct digital twins. These methods continuously refine the created numerical models with limited real-world data and provide diverse impact scenarios through numerical model simulations. However, there are inevitable differences between digital models and physical models that are challenging to correct through mechanical means. This discrepancy in data distribution between the two models significantly hinders the application of digital twin technology in impact/event identification tasks. To address this challenge, this study proposes a novel model based on autoencoders, named Transfer-AE. Transfer-AE encodes the common features of digital twins in the latent space to bridge the uncertainty gap at a macro scale between numerical models and physical models and synchronously fits the magnitude and location of the impact load in the decoder. This enables consistent detection results for the same impact event, whether the sample comes from the numerical model or the physical model. Transfer-AE includes two operating modes: Mode 1 has a fixed computational complexity with stable inference speed, but the training cost and difficulty increase with data distribution. Mode 2's computational complexity increases with data distribution, but it has a fixed training cost and speed. In both cases involving the geodesic dome structure simulating a deep space habitat and the IASC-ASCE benchmark structure, Transfer-AE demonstrated the best performance in impact localization and quantification tasks compared to mainstream domain-adaptive transfer models.

Load magnitude and location estimation on additively manufactured circular structures using deep learning

Additively Manufactured (AM) metal parts have been used at critical engineering applications. Estimation of load and its location is important to avoid accidents. Since the excitation signals move through multiple paths, estimation of load and its location is difficult. In this study, surface response to excitation method (SuRE) was implemented with multiple steps by considering the challenges of the geometry. Two 3D printed stainless steel rocket nozzle type structures with two different sizes and a C shaped tube section were used. Two different PZT placements were used for the big nozzle while the PZTs were located at the opposite sides of the small nozzle. The large nozzle had 280 test cases for 9 categories, while the smaller nozzle had 60 test cases for 5 categories. Finally, the C shaped specimen had 48 test cases for three categories. Continuous wavelet transform (CWT) was used to obtain more representative presentation of the data to the deep learning algorithm. Convolutional Neural Networks (CNNs) were used for classification. Wavelet transformation – Deep learning combination yielded 100 % accuracy for the large nozzle and 97.14 % for the smaller nozzle. These findings demonstrate the effectiveness of this technique on curved surfaces representative of real-world parts. The proposed method estimated the load location with 100 % accuracy.

Mechanical Behavior of Buried HDPE Pipe Subjected to Surface Load: Constitutive Modeling and Finite Element Method Simulations

Abstract In this paper, the Sherwood–Frost constitutive model was first used to simulate the stress response and deformation process of buried high-density polyethylene (HDPE) pipe subjected to surface load, where parameters in this model were obtained by fitting the results of uniaxial tensile tests with different rates and the pipe–soil model was conducted in abaqus. Apparent stress concentration and large deformation are observed in pipe cross section and are closely related to the magnitude and location of surface load. The increments of surface load and offset displacement have opposite effects on the mechanical behavior of pipes. Additionally, the location of the maximum stress appears to shift from the top or bottom to the left and right sides of the pipe cross section with the increment of surface load, and the region of peak hoop stress will show a decreasing trend of counterclockwise rotation. Then, based on stress failure criterion, the relationship between the ultimate bearing capacity of the pipe and the offset displacement was determined, which decided by the angle between the ground and the line connecting load center and cross section center of pipe. Finally, an offset of 0.6 m is a value of interest. When the offset between the load position and the pipe exceeds 0.6 m, the ultimate bearing capacity of the pipe will increase significantly with the increase of the offset. The results of the above research could provide the reference for the safety evaluation and maintenance strategy of gas polyethylene pipe under the surface load.

Experimental and numerical investigation on deck system of a 102 m simply supported prestressed UHPC box-girder highway bridge

To address two main challenges (excessive mid-span deflections and numerous cracks in the main girder) in long-span prestressed concrete (PC) box-girder bridges, this paper proposes a long-span simply-supported UHPC box-girder bridge. In comparison to conventional PC box-girder bridges with three-dimensional prestress, the proposed UHPC box-girder consists only one-dimensional (longitudinal) prestress, and the thickness of the bottom/top plate and web of the UHPC box-girder are relatively thin and are strengthened with dense diaphragms and stiffening ribs. The 4th Beijiang River Bridge adopts this type of bridge with a span of 102 m, which is the longest span simply supported prestressed UHPC box-girder highway bridge in the world. Considering the fact that the thickness of the top plate of the UHPC box-girder is relatively thin (only 20 cm) and the transverse prestress is removed from the top plate, thus, under the direct action of wheel loads, the risk of bridge deck cracking may correspondingly increase. To investigate the mechanical behavior of the deck system of UHPC box-girder bridges, a 1:2 scaled experimental specimen associated with the field bridge is tested. The mechanical behavior of the new deck system is investigated and discussed. It is found that because the support strength of the stiffening rib is significantly weaker than that of the web, the UHPC deck slab should still be regarded as a two-way slab rather than a one-way slab in the elastic stage. In addition, although the test load location is unfavorable to the UHPC deck slab and the first crack appears on the UHPC deck slab, this deck system finally suffers from bending failure of the transverse rib. Furthermore, finite element analysis is carried out to study the mechanical behavior of this new deck system. Parametric analysis considers some factors including the reinforcement ratio in the transverse rib, the height of the transverse rib, and the space between transverse ribs. The results provide a good reference for design and optimization in the new deck system of UHPC box-girder bridges.

Influence of passive arm-support exoskeleton on static postural balance in load-holding tasks: effects of supportive force, weight and load location

This study systematically investigated the influence of a passive arm-support exoskeleton (ASE) on static postural balance in load-holding tasks under different weight conditions and load locations, and the relationship between such influence and the exoskeleton’s supportive force profile. Using a 3 (exoskeleton interventions) ×3 (weight conditions) ×3 (load locations) within-subjects design, the research found that wearing ASE with supportive force significantly reduced postural sway by 17.84% and 15.19% across all conditions compared to without wearing the exoskeleton and with deactivated support, respectively. These improvements were consistent with subjective assessments. The stability benefits varied with the weight and load location, reflecting the exoskeleton’s supportive force profile. Overall, the study suggests that the supportive force from the ASE can enhance static postural balance, with effectiveness dependent on weight conditions and load locations. This highlights the potential of passive ASEs for improving stability and reducing fall risks in work environments.

Nonlinear Analysis of Electric Potential in a Piezoelectric Thin Plate as Pressure Sensor

Piezoelectric materials are widely applied in electronic components due to their ability to couple electric and mechanical fields. For the piezoelectric thin plate as a pressure sensor, we extend the modified first-order piezoelectric plate theory to explore the nonlinear solution of electric potential and discuss the relevant regulation mechanisms. Based on the piezoelectric effect, the electric potential generated by deformation is not linear with thickness. A quadratic function of electric potential across thickness is introduced. However, the electric potential on upper and lower electrodes is an unknown constant, which can be determined by the nonlinear complementary equation based on the Gauss theorem. It is shown that the nonlinear results of electric potential are consistent with outcomes by the three-dimensional finite element method. Furthermore, relevant regulation mechanisms are discussed on electric potential, including supported conditions, plate thickness, and load area. In addition, the influence of load locations on the electric potential response is analyzed. It is expected that these findings will be instructive to the structural design of piezoelectric pressure sensors.

A hierarchical Bayesian model updating method for bridge structures by fusing multi-source information

The expanding structural health monitoring (SHM) systems on bridge structures have provided an abundance of multi-source data for finite element model updating (FEMU). The SHM systems on bridges usually include surveillance cameras, vibration sensors (e.g., accelerometers, strain gauges, and displacement sensors), and sometimes a weight-in-motion (WIM) system. Currently, the majority of FEMU studies focus on identified modal parameters derived from vibration data, neglecting the incorporation of video and WIM data in the updating process, which impedes a thorough quantification of uncertainty associated with the structural parameters of interest. Therefore, this paper proposes a hierarchical Bayesian FEMU framework to comprehensively integrate a variety of information sources, including videos, WIM, and vibration data. The data features comprise the static deflections of the bridge under traffic load and modal parameters identified from acceleration measurements. The measured static deflections are extracted from raw displacement data using the locally weighted regression and smoothing scatterplots method. Computer vision-based technology is employed to pinpoint the location of vehicle load on the bridge, which is then integrated into a FEM to predict vehicle-load-induced static deflection. A two-stage Markov Chain Monte Carlo sampling approach is proposed to evaluate the high-dimensional posterior distribution efficiently. The effectiveness of the proposed method is demonstrated on a laboratory three-span bridge model. The results show that the hierarchical Bayesian FEMU can provide accurate estimation and uncertainty quantification on structural stiffness and mass parameters. The updated model accurately predicts both static deflection and modal parameters, exhibiting model-predicted variability in close alignment with the identified values for observed and unobserved responses. Remarkably, this holds true even for unseen loading conditions which are not included in the updating process. These observations validate the capability of the proposed method for multi-source data fusion and uncertainty quantification of real-world bridge structures under operational conditions.

Automated Load and Dump Detection for CO2 Reduction

In this paper, we detail our methodology for addressing the challenge of reducing CO2 emissions in road construction from construction machines in a Norwegian construction site. In particular, we focus on the automatic detection of load and dump locations from various data sources

Rational steel mesh layout influence on plate utilization of large span corrugated steel structure

Corrugated steel structures buried in the surrounding soil are currently used worldwide in road and railway engineering as culverts, pedestrian and animal crossings, tunnels and bridges. The need of large span corrugated steel structures is rapidly growing however their behavior analysis is still understudied. There is also a lack of discussion about the impact of additional strengthening elements for the behavior of corrugated steel structures. This study analyses the influence of rational steel mesh layout on the behavior of a large span deepest corrugation steel structure. The numerical two-dimensional model of two-radius 17.5 m span profile with corrugation of 237 mm depth and 500 mm pitch was developed to replicate the ongoing project in Lithuania. Originally the stiffness of the structure from both sides was increased by six layers of steel meshes as lateral support. Nevertheless, the current study was looking for rational steel mesh layout. Also, the influence of different layouts of steel mesh on corrugated steel plate utilization to buckling failure in the peaking, dead load and in the most unfavorable live load location phase was analyzed. The finite element model results indicated that steel meshes could be used to control structure deformations and internal reactions. Vertical displacement of the crown of the structure could be reduced by 45% in the peaking phase when using proper steel meshes layout. Furthermore, steel meshes could be a decisive factor for the bearing capacity of corrugated steel structure in a positive sense.

Study on the truss damage measurement based on Bayesian updating

Bayesian updating can integrate new observations in real time. This online updating property makes the Bayesian approach particularly suitable for dynamic monitoring of structural damage. In this paper, the node displacements are obtained by the finite element software OpenSees, assuming that the bars are damaged and the stiffness is reduced. Rejection Sampling method is used to determine the stiffness drop interval. During the sampling process, different load sizes, load locations, errors and types are selected to realize the updating of the stiffness of the top chord bar, bottom chord bar, vertical web bar, and diagonal web bar. A Pratt-type truss is used as an example, combined with displacement data. The proposed stiffness damage measurement method is demonstrated by updating the stiffness of four types of bars separately. The results shows that damage in structures can be accurately identified by Bayesian updating methods. This method not only pinpoints the location of the damage, but also quantifies the extent of the damage.

An electrical impedance tomography based artificial soft skin pressure sensor: Characterisation and force modelling

Using electrical impedance tomography (EIT) to drive a pressure mapping device shows great potential, due to the customisability of the sensing domain and the non-invasive nature of the boundary electrodes. A pressure mapping system has been developed in this work that uses a carbon black silicone rubber (CBSR) nanoparticle sensing domain, giving the sensing domain a comparable softness to human skin tissue. To take this technology into a commercial application the performance of such an EIT-based sensor must be quantifiable and repeatable. In this work a series of experiments were repeated for various load locations, strains, and carbon black percentages. Capturing this data gave insight into the how the sensing domain performs over time and captured the transient events limiting the sensor. Metrics were determined to quantify the sensor’s spatial resolution. Load localisation could be determined with error values as low as 0.67 mm. A series of randomised test loads gave similar spatial performance results to the more structured experiments. A quasi-static conductance-force model of the material was developed with an accuracy of ± 0.78 N. One important metric is temporal resolution, as it is the least quantified performance metric in literature, however can be the most important for some applications. For the sensor domains tested, average settling times of between 19.0 – 44.5 s and 22.5 – 36.0 s were determined for 8 and 9 wt% CBSR samples. This sensor platform shows promise for future soft surface pressure mapping applications. Further use of the developed performance metrics will allow for a variety of sensor applications to be validated.

Dynamic Response of the Tunnel Lining with a Circumferential Crack Subjected to a Harmonic Point Load

Cracks are one of the most common diseases of tunnel lining, and the structural dynamic response can be used to assess the health of a tunnel. Hence, this paper investigates the dynamic response of shield tunnel lining with a partly circumferential crack. The shield tunnel lining is regarded as a thin cylindrical shell and analyzed independently. The research methodology integrates the wave propagation method, the local flexibility matrix, the line spring model and the wave superposition principle. The results show that the position and depth of a partly circumferential crack can influence the natural frequency of the shield tunnel lining. Under the fixed-position load, as the distance from the monitoring point to the crack increases, the difference in displacement response amplitude between the undamaged and cracked linings diminishes. Moreover, deepening cracks enlarge the magnitude of amplitude differences. When the load approaches the crack, the radial amplitude difference first increases and then decreases as the monitor moves away from the crack. This finding helps determine the required monitor position. The displacement response of the selected monitor indicates that the closer the load position is to the crack, the larger the amplitude difference. The results aid in identifying the crack position and selecting corresponding load and monitor locations.