Analysis of the interaction between bolt-reinforced rock and surface support in tunnels based on convergence-confinement method

To investigate the interaction of the bolt-reinforced rock and the surface support,an analytical model of the convergence-confinement type is proposed,considering the sequential installation of the fully grouted rockbolts and the surface support.The rock mass is assumed to be elastic-brittle-plastic material,obeying the linear Mohr-Coulomb criterion or the non-linear Hoek-Brown criterion.According to the strain states of the tunnel wall at bolt and surface support installation and the relative magnitude between the bolt length and the plastic depth during the whole process,six cases are categorized upon solving the problem.Each case is divided into three stages due to the different effects of the active rockbolts and the passive surface support.The fictitious pressure is introduced to quantify the threedimensional(3D)effect of the tunnel face,and thus,the actual physical location along the tunnel axis of the analytical section can be considered.By using the bolt-rock strain compatibility and the rocksurface support displacement compatibility conditions,the solutions of longitudinal tunnel displacement and the reaction pressure of surface support along the tunnel axis are obtained.The proposed analytical solutions are validated by a series of 3D numerical simulations.Extensive parametric studies are conducted to examine the effect of the typical parameters of rockbolts and surface support on the tunnel displacement and the reaction pressure of the surface support under different rock conditions.The results show that the rockbolts are more effective in controlling the tunnel displacement than the surface support,which should be installed as soon as possible with a suitable length.For tunnels excavated in weak rocks or with restricted displacement control requirements,the surface support should also be installed or closed timely with a certain stiffness.The proposed method provides a convenient alternative approach for the optimization of rockbolts and surface support at the preliminary stage of tunnel design.

A methodology for damage evaluation of underground tunnels subjected to static loading using numerical modeling

We have proposed a methodology to assess the robustness of underground tunnels against potential failure.This involves developing vulnerability functions for various qualities of rock mass and static loading intensities.To account for these variations,we utilized a Monte Carlo Simulation(MCS)technique coupled with the finite difference code FLAC^(3D),to conduct two thousand seven hundred numerical simulations of a horseshoe tunnel located within a rock mass with different geological strength index system(GSIs)and subjected to different states of static loading.To quantify the severity of damage within the rock mass,we selected one stress-based(brittle shear ratio(BSR))and one strain-based failure criterion(plastic damage index(PDI)).Based on these criteria,we then developed fragility curves.Additionally,we used mathematical approximation techniques to produce vulnerability functions that relate the probabilities of various damage states to loading intensities for different quality classes of blocky rock mass.The results indicated that the fragility curves we obtained could accurately depict the evolution of the inner and outer shell damage around the tunnel.Therefore,we have provided engineers with a tool that can predict levels of damages associated with different failure mechanisms based on variations in rock mass quality and in situ stress state.Our method is a numerically developed,multi-variate approach that can aid engineers in making informed decisions about the robustness of underground tunnels.

Stability analysis of tunnel face reinforced with face bolts

Face bolting has been widely utilized to enhance the stability of tunnel face,particularly in soft soil tunnels.However,the influence of bolt reinforcement and its layout on tunnel face stability has not been systematically studied.Based on the theory of linear elastic mechanics,this study delved into the specific mechanisms of bolt reinforcement on the tunnel face in both horizontal and vertical dimensions.It also identified the primary failure types of bolts.Additionally,a design approach for tunnel face bolts that incorporates spatial layout was established using the limit equilibrium method to enhance the conventional wedge-prism model.The proposed model was subsequently validated through various means,and the specific influence of relevant bolt design parameters on tunnel face stability was analyzed.Furthermore,design principles for tunnel face bolts under different geological conditions were presented.The findings indicate that bolt failure can be categorized into three stages:tensile failure,pullout failure,and comprehensive failure.Increasing cohesion,internal friction angle,bolt density,and overlap length can effectively enhance tunnel face stability.Due to significant variations in stratum conditions,tailored design approaches based on specific failure stages are necessary for bolt design.

Anisotropic spin transport and photoresponse characteristics detected by tip movement in magnetic single-molecule junction

Orientation-dependent transport properties induced by anisotropic molecules are enticing in single-molecule junctions.Here,using the first-principles method,we theoretically investigate spin transport properties and photoresponse characteristics in trimesic acid magnetic single-molecule junctions with different molecular adsorption orientations and electrode contact sites.The transport calculations indicate that a single-molecule switch and a significant enhancement of spin transport and photoresponse can be achieved when the molecular adsorption orientation changes from planar geometry to upright geometry.The maximum spin polarization of current and photocurrent in upright molecular junctions exceeds 90%.Moreover,as the Ni tip electrode moves,the tunneling magnetoresistance of upright molecular junctions can be increased to 70%.The analysis of the spin-dependent PDOS elucidates that the spinterfaces between organic molecule and ferromagnetic electrodes are modulated by molecular adsorption orientation,where the molecule in upright molecular junctions yields higher spin polarization.Our theoretical work paves the way for designing spintronic devices and optoelectronic devices with anisotropic functionality base on anisotropic molecules.

Magnetic Switching Dynamics and Tunnel Magnetoresistance Effect Based on Spin-Splitting Noncollinear Antiferromagnet Mn_(3)Pt

In comparison to ferromagnets,antiferromagnets are believed to have superior advantages for applications in next-generation magnetic storage devices,including fast spin dynamics,vanishing stray fields and robust against external magnetic field,etc.However,unlike ferromagnetic orders,which could be detected through tunneling magnetoresistance effect in magnetic tunnel junctions,the antiferromagnetic order(i.e.,Néel vector)cannot be effectively detected by the similar mechanism due to the spin degeneracy of conventional antiferromagnets.Recently discovered spin-splitting noncollinear antiferromagnets,such as Mn_(3)Pt with momentum-dependent spin polarization due to their special magnetic space group,make it possible to achieve remarkable tunneling magnetoresistance effects in noncollinear antiferromagnetic tunnel junctions.Through first-principles calculations,we demonstrate that the tunneling magnetoresistance ratio can reach more than 800% in Mn_(3)Pt/perovskite oxides/Mn_(3)Pt antiferromagnetic tunnel junctions.We also reveal the switching dynamics of Mn_(3)Pt thin film under magnetic fields using atomistic spin dynamic simulation.Our study provides a reliable method for detecting Néel vector of noncollinear antiferromagnets through the tunnel magnetoresistance effect and may pave its way for potential applications in antiferromagnetic memory devices.

Roof collapse mechanism of weak surrounding rock for deep-buried tunnels under high geostress conditions

High geostress,a typical attribute of tunnels located at significant depths,is crucial in causing stress-induced failure and influencing the stability of the tunnel crown.This study developed an analytical method for the failure mechanism that occurs in deep-buried tunnel roofs,taking into account the influence of geostress.The limit analysis theory was utilized for deriving analytical solutions about the geometry of the collapsing surface and the limit supporting pressure.The collapsing surface obtained by the analytical solution was validated by the findings of the physical model test,which shows a high level of agreement with the actual one.An extensive investigation was done to explore the effects of the lateral pressure coefficients,the tunnel buried depth,the geological conditions of the surrounding rock,the long-short axis ratio,and the size of the tunnel profile.The findings indicate that an increase in the lateral pressure coefficient from 0.5 to 1.5 results in a reduction in the height of the collapsing zone by 2.08 m and the width of the collapsing zone by 1.15 m,while simultaneously increases the limit supporting pressure by 18.9%.The proposed upper bound method accurately determines the limit supporting pressure and the geometry of the collapsing surface,which aligns well with the results acquired through numerical modelling and on-site monitoring in actual engineering applications.The proposed analytical method can serve as a reference for similar crown failure issues of deep-buried tunnels.

Rockburst criterion and evaluation method for potential rockburst pit depth considering excavation damage effect

Excavation-induced disturbances in deep tunnels will lead to deterioration of rock properties and formation of excavation damaged zone(EDZ).This excavation damage effect may affect the potential rockburst pit depth.Taking two diversion tunnels of Jinping II hydropower station for example,the relationship between rockburst pit depth and excavation damage effect is first surveyed.The results indicate that the rockburst pit depth in tunnels with severe damage to rock masses is relatively large.Subsequently,the excavation-induced damage effect is characterized by disturbance factor D based on the Hoek-Brown criterion and wave velocity method.It is found that the EDZ could be further divided into a high-damage zone(HDZ)with D=1 and weak-damage zone(WDZ),and D decays from one to zero linearly.For this,a quantitative evaluation method for potential rockburst pit depth is established by presenting a three-element rockburst criterion considering rock strength,geostress and disturbance factor.The evaluation results obtained by this method match well with actual observations.In addition,the weakening of rock mass strength promotes the formation and expansion of potential rockburst pits.The potential rockburst pit depth is positively correlated with HDZ and WDZ depths,and the HDZ depth has a significant contribution to the potential rockburst pit depth.

Inverting the rock mass P-wave velocity field ahead of deep buried tunnel face while borehole drilling

Imaging the wave velocity field surrounding a borehole while drilling is a promising and urgently needed approach for extending the exploration range of the borehole point.This paper develops a drilling process detection(DPD)system consisting of a multifunctional sensor and a pilot geophone installed at the top of the drilling rod,geophones at the tunnel face,a laser rangefinder,and an onsite computer.A weighted adjoint-state first arrival travel time tomography method is used to invert the P-wave velocity field of rock mass while borehole drilling.A field experiment in the ongoing construction of a deep buried tunnel in southwestern China demonstrated the DPD system and the tomography method.Time-frequency analysis of typical borehole drilling detection data shows that the impact drilling source is a pulse-like seismic exploration wavelet.A velocity field of the rock mass in a triangular area defined by the borehole trajectory and geophone receiving line can be obtained.Both the borehole core and optical image validate the inverted P-wave velocity field.A numerical simulation of a checkerboard benchmark model is used to test the tomography method.The rapid convergence of the misfits and consistent agreement between the inverted and observed travel times validate the P-wave velocity imaging.

Bimodal growth of Fe islands on graphene

Magnetic metals deposited on graphene hold the key to applications in spintronics. Here, we present the results of Fe islands grown on graphene/Si C(0001) by molecular beam epitaxy, which are investigated by scanning tunneling microscopy. The two types of islands distinguished by flat or round tops are revealed, indicating bimodal growth of Fe. The atomic structures on the top surfaces of flat islands are also clearly resolved. Our results may improve the understanding of the mechanisms of metals deposited on graphene and pave the way for future spintronic applications of Fe/graphene systems.

Supposition of graphene stacks to estimate the contact resistance and conductivity of nanocomposites

In this study,the effects of stacked nanosheets and the surrounding interphase zone on the resistance of the contact region between nanosheets and the tunneling conductivity of samples are evaluated with developed equations superior to those previously reported.The contact resistance and nanocomposite conductivity are modeled by several influencing factors,including stack properties,interphase depth,tunneling size,and contact diameter.The developed model's accuracy is verified through numerous experimental measurements.To further validate the models and establish correlations between parameters,the effects of all the variables on contact resistance and nanocomposite conductivity are analyzed.Notably,the contact resistance is primarily dependent on the polymer tunnel resistivity,contact area,and tunneling size.The dimensions of the graphene nanosheets significantly influence the conductivity,which ranges from 0 S/m to90 S/m.An increased number of nanosheets in stacks and a larger gap between them enhance the nanocomposite's conductivity.Furthermore,the thicker interphase and smaller tunneling size can lead to higher sample conductivity due to their optimistic effects on the percolation threshold and network efficacy.

Mechanism of high-preload support based on the NPR anchor cable in layered soft rock tunnels

The control of large deformation problems in layered soft rock tunnels needs to solve urgently.The roof problem is particularly severe among the deformation issues in tunnels.This study first analyzes the asymmetric deformation modes in layered soft rock tunnels with large deformations.Subsequently,we construct a mechanical model under ideal conditions for controlling the roof of layered soft rock tunnels through high preload with the support of NPR anchor cables.The prominent roles of long and short NPR anchor cables in the support system are also analyzed.The results indicate the significance of high preload in controlling the roof of layered soft rock tunnels.The short NPR anchor cables effectively improve the integrity of the stratified soft rock layers,while the long NPR anchor cables effectively mobilize the self-bearing capacity of deep-stable rock layers.Finally,the high-preload support method with NPR anchor cables is validated to have a good effect on controlling large deformations in layered soft rock tunnels through field monitoring data.

Effects of wind speed,underlying surface,and seed morphological traits on the secondary seed dispersal in the Tengger Desert,China

The maintenance of sand-fixing vegetation is important for the stability of artificial sand-fixing systems in which seed dispersal plays a key role.Based on field wind tunnel experiments using 11 common plant species on the southeastern edge of the Tengger Desert,China,we studied the secondary seed dispersal in the fixed and semi-fixed sand dunes as well as in the mobile dunes in order to understand the limitations of vegetation regeneration and the maintenance of its stability.Our results indicated that there were significant variations among the selected 11 plant species in the threshold of wind speed(TWS).The TWS of Caragana korshinskii was the highest among the 11 plant species,whereas that of Echinops gmelinii was the lowest.Seed morphological traits and underlying surface could generally explain the TWS.During the secondary seed dispersal processes,the proportions of seeds that did not disperse(no dispersal)and only dispersed over short distance(short-distance dispersal within the wind tunnel test section)were significantly higher than those of seeds that were buried(including lost seeds)and dispersed over long distance(long-distance dispersal beyond the wind tunnel test section).Compared with other habitats,the mobile dunes were the most difficult places for secondary seed dispersal.Buried seeds were the easiest to be found in the semi-fixed sand dunes,whereas fixed sand dunes were the best sites for seeds that dispersed over long distance.The results of linear mixed models showed that after controlling the dispersal distance,smaller and rounder seeds dispersed farther.Shape index and wind speed were the two significant influencing factors on the burial of seeds.The explanatory power of wind speed,underlying surface,and seed morphological traits on the seeds that did not disperse and dispersed over short distance was far greater than that on the seeds that were buried and dispersed over long distance,implying that the processes and mechanisms of burial and long-distance dispersal are more complex.In summary,most seeds in the study area either did not move,were buried,or dispersed over short distance,promoting local vegetation regeneration.

Dynamic Response of Foundations during Startup of High-Frequency Tunnel Equipment

The specialized equipment utilized in long-line tunnel engineering is evolving towards large-scale,multifunctional,and complex orientations.The vibration caused by the high-frequency units during regular operation is supported by the foundation of the units,and the magnitude of vibration and the operating frequency fluctuate in different engineering contexts,leading to variations in the dynamic response of the foundation.The high-frequency units yield significantly diverse outcomes under different startup conditions and times,resulting in failure to meet operational requirements,influencing the normal function of the tunnel,and causing harm to the foundation structure,personnel,and property in severe cases.This article formulates a finite element numerical computation model for solid elements using three-dimensional elastic body theory and integrates field measurements to substantiate and ascertain the crucial parameter configurations of the finite element model.By proposing a comprehensive startup timing function for high-frequency dynamic machines under different startup conditions,simulating the frequency andmagnitude variations during the startup process,and suggesting functions for changes in frequency and magnitude,a simulated startup schedule function for high-frequency machines is created through coupling.Taking into account the selection of the transient dynamic analysis step length,the dynamic response results for the lower dynamic foundation during its fundamental frequency crossing process are obtained.The validation checks if the structural magnitude surpasses the safety threshold during the critical phase of unit startup traversing the structural resonance region.The design recommendations for high-frequency units’dynamic foundations are provided,taking into account the startup process of the machine and ensuring the safe operation of the tunnel.

Terahertz high-sensitivity SIS mixer based on Nb–AlN–NbN hybrid superconducting tunnel junctions

The terahertz band,a unique segment of the electromagnetic spectrum,is crucial for observing the cold,dark universe and plays a pivotal role in cutting-edge scientific research,including the study of cosmic environments that support life and imaging black holes.High-sensitivity superconductor–insulator–superconductor(SIS)mixers are essential detectors for terahertz astronomical telescopes and interferometric arrays.Compared to the commonly used classical Nb/AlO_(x)/Nb superconducting tunnel junction,the Nb/AlN/NbN hybrid superconducting tunnel junction has a higher energy gap voltage and can achieve a higher critical current density.This makes it particularly promising for the development of ultra-wideband,high-sensitivity coherent detectors or mixers in various scientific research fields.In this paper,we present a superconducting SIS mixer based on Nb/AlN/NbN parallel-connected twin junctions(PCTJ),which has a bandwidth extending up to490 GHz–720 GHz.The best achieved double-sideband(DSB)noise temperature(sensitivity)is below three times the quantum noise level.

Thermodynamics in a quantum corrected Reissner-Nordstr?m-AdS black hole and its GUP-corrections

We calculate the thermodynamic quantities in the quantum corrected Reissner-Nordstr?m-AdS(RN-AdS)black hole,and examine their quantum corrections.By analyzing the mass and heat capacity,we give the critical state and the remnant state,respectively,and discuss their consistency.Then,we investigate the quantum tunneling from the event horizon of massless scalar particle by using the null geodesic method,and charged massive boson W^(±)and fermions by using the Hamilton-Jacob method.It is shown that the same Hawking temperature can be obtained from these tunneling processes of different particles and methods.Next,by using the generalized uncertainty principle(GUP),we study the quantum corrections to the tunneling and the temperature.Then the logarithmic correction to the black hole entropy is obtained.

Inverse reliability analysis and design for tunnel face stability considering soil spatial variability

The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of random variables usually fails to account for soil spatial variability.To overcome these limitations,this study proposes an efficient framework for conducting reliability analysis and reliability-based design(RBD)of tunnel face stability in spatially variable soil strata.The three-dimensional(3D)rotational failure mechanism of the tunnel face is extended to account for the soil spatial variability,and a probabilistic framework is established by coupling the extended mechanism with the improved Hasofer-Lind-Rackwits-Fiessler recursive algorithm(iHLRF)as well as its inverse analysis formulation.The proposed framework allows for rapid and precise reliability analysis and RBD of tunnel face stability.To demonstrate the feasibility and efficacy of the proposed framework,an illustrative case of tunnelling in frictional soils is presented,where the soil's cohesion and friction angle are modelled as two anisotropic cross-correlated lognormal random fields.The results show that the proposed method can accurately estimate the failure probability(or reliability index)regarding the tunnel face stability and can efficiently determine the required supporting pressure for a target reliability index with soil spatial variability being taken into account.Furthermore,this study reveals the impact of various factors on the support pressure,including coefficient of variation,cross-correlation between cohesion and friction angle,as well as autocorrelation distance of spatially variable soil strata.The results also demonstrate the feasibility of using the forward and/or inverse first-order reliability method(FORM)in high-dimensional stochastic problems.It is hoped that this study may provide a practical and reliable framework for determining the stability of tunnels in complex soil strata.

An Optimized System of Random Forest Model by Global Harmony Search with Generalized Opposition-Based Learning for Forecasting TBM Advance Rate

As massive underground projects have become popular in dense urban cities,a problem has arisen:which model predicts the best for Tunnel Boring Machine(TBM)performance in these tunneling projects?However,performance level of TBMs in complex geological conditions is still a great challenge for practitioners and researchers.On the other hand,a reliable and accurate prediction of TBM performance is essential to planning an applicable tunnel construction schedule.The performance of TBM is very difficult to estimate due to various geotechnical and geological factors and machine specifications.The previously-proposed intelligent techniques in this field are mostly based on a single or base model with a low level of accuracy.Hence,this study aims to introduce a hybrid randomforest(RF)technique optimized by global harmony search with generalized oppositionbased learning(GOGHS)for forecasting TBM advance rate(AR).Optimizing the RF hyper-parameters in terms of,e.g.,tree number and maximum tree depth is the main objective of using the GOGHS-RF model.In the modelling of this study,a comprehensive databasewith themost influential parameters onTBMtogetherwithTBM AR were used as input and output variables,respectively.To examine the capability and power of the GOGHSRF model,three more hybrid models of particle swarm optimization-RF,genetic algorithm-RF and artificial bee colony-RF were also constructed to forecast TBM AR.Evaluation of the developed models was performed by calculating several performance indices,including determination coefficient(R2),root-mean-square-error(RMSE),and mean-absolute-percentage-error(MAPE).The results showed that theGOGHS-RF is a more accurate technique for estimatingTBMAR compared to the other applied models.The newly-developedGOGHS-RFmodel enjoyed R2=0.9937 and 0.9844,respectively,for train and test stages,which are higher than a pre-developed RF.Also,the importance of the input parameters was interpreted through the SHapley Additive exPlanations(SHAP)method,and it was found that thrust force per cutter is the most important variable on TBMAR.The GOGHS-RF model can be used in mechanized tunnel projects for predicting and checking performance.

Rock mass quality prediction on tunnel faces with incomplete multi-source dataset via tree-augmented naive Bayesian network

Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantitative parameters.However,due to the harsh on-site construction conditions,it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality prediction.In this study,a novel improved Swin Transformer is proposed to detect,segment,and quantify rock mass characteristic parameters such as water leakage,fractures,weak interlayers.The site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%,81%,and 86%for water leakage,fractures,and weak interlayers,respectively.A multisource rock tunnel face characteristic(RTFC)dataset includes 11 parameters for predicting rock mass quality is established.Considering the limitations in predictive performance of incomplete evaluation parameters exist in this dataset,a novel tree-augmented naive Bayesian network(BN)is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%.In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete dataset.By utilizing the established BN,a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters,results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.

Comparative Analysis of ARIMA and LSTM Model-Based Anomaly Detection for Unannotated Structural Health Monitoring Data in an Immersed Tunnel

Structural Health Monitoring(SHM)systems have become a crucial tool for the operational management of long tunnels.For immersed tunnels exposed to both traffic loads and the effects of the marine environment,efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge.This study proposed amodel-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel.Firstly,a dynamic predictive model-based anomaly detectionmethod is proposed,which utilizes a rolling time window for modeling to achieve dynamic prediction.Leveraging the assumption of temporal data similarity,an interval prediction value deviation was employed to determine the abnormality of the data.Subsequently,dynamic predictive models were constructed based on the Autoregressive Integrated Moving Average(ARIMA)and Long Short-Term Memory(LSTM)models.The hyperparameters of these models were optimized and selected using monitoring data from the immersed tunnel,yielding viable static and dynamic predictive models.Finally,the models were applied within the same segment of SHM data,to validate the effectiveness of the anomaly detection approach based on dynamic predictive modeling.A detailed comparative analysis discusses the discrepancies in temporal anomaly detection between the ARIMA-and LSTM-based models.The results demonstrated that the dynamic predictive modelbased anomaly detection approach was effective for dealing with unannotated SHM data.In a comparison between ARIMA and LSTM,it was found that ARIMA demonstrated higher modeling efficiency,rendering it suitable for short-term predictions.In contrast,the LSTM model exhibited greater capacity to capture long-term performance trends and enhanced early warning capabilities,thereby resulting in superior overall performance.

A Simplified Method for the Stress Analysis of Underground Transfer Structures Crossing Multiple Subway Tunnels

According to the design specifications,the construction of extended piles involves traversing the tunnel’s upper region and extending to the underlying rock layer.To address this challenge,a subterranean transfer structure spanning multiple subway tunnels was proposed.Deliberating on the function of piles in the transfer structure as springs with axial and bending stiffness,and taking into account the force balance and deformation coordination conditions of beams and plates within the transfer structure,we established a simplified mechanical model that incorporates soil stratification by combining it with the Winkler elastic foundation beam model.The resolved established simplifiedmechanicalmodel employed finite difference technology and the Newton-Simpsonmethod,elucidating the mechanical mechanism of the transfer structure.The research findings suggest that the load carried by the upper structural columns can be transferred to the pile foundation beneath the beams through the transfer structure,subsequently reaching the deep soil layer and ensuring minimal impact on adjacent tunnels.The established simplified analysis method can be used for stress analysis of the transfer structure,concurrently considering soil stratification,pile foundation behavior,and plate action.The pile length,pile section size,and beam section size within the transfer structure should account for the characteristics of the upper load,ensuring an even distribution of the beam bending moment.