Cross-sectional Dimensions Research Articles

ПРОБЛЕМЫ ПРИМЕНЕНИЯ СОВРЕМЕННЫХ НОРМАТИВНЫХ ДОКУМЕНТОВ ДЛЯ РАСЧЕТА ТРАНСПОРТНЫХ СООРУЖЕНИЙ

About 400 normative documents were developed in the field of transportation construction, but the correctness and relevance of some of them is questionable. The lack of a unified terminology, the presence of contradictions and the increasing volume of documentation significantly complicate its use. In addition to general disadvantages, there are a number of private problems. For example, the authors point out the incorrect use of the limit states methodology for the calculation of structures, since this methodology considers limit (extreme) loads, and the regularities of the real behavior of the structure at lower levels of loads are unknown. In addition, the calculation according to limit states methodology does not take into account durability (it is not defined). When calculating using this methodology for the action of only loads with other unknown operating influences, the limit state is realized by reaching a certain limit value by this load. In reality, the limit state may occur due to changes in the shape of the structure, dimensions of cross-sections of structural elements and, more often, due to degradation of its material properties under the influence of service conditions. For the calculation of structures, it is necessary to apply the deformation approach more widely. According to it, both strength and deformation problems of structural calculation are correctly interrelated, and their hypotheses do not conflict with each other.

SWENet: A Physics-Informed Deep Neural Network (PINN) for Shear Wave Elastography.

Shear wave elastography (SWE) enables the measurement of elastic properties of soft materials in a non-invasive manner and finds broad applications in various disciplines. The state-of-the-art SWE methods rely on the measurement of local shear wave speeds to infer material parameters and suffer from wave diffraction when applied to soft materials with strong heterogeneity. In the present study, we overcome this challenge by proposing a physics-informed neural network (PINN)-based SWE (SWENet) method. The spatial variation of elastic properties of inhomogeneous materials has been introduced in the governing equations, which are encoded in SWENet as loss functions. Snapshots of wave motions have been used to train neural networks, and during this course, the elastic properties within a region of interest illuminated by shear waves are inferred simultaneously. We performed finite element simulations, tissue-mimicking phantom experiments, and ex vivo experiments to validate the method. Our results show that the shear moduli of soft composites consisting of matrix and inclusions of several millimeters in cross-section dimensions with either regular or irregular geometries can be identified with excellent accuracy. The advantages of the SWENet over conventional SWE methods consist of using more features of the wave motions and enabling seamless integration of multi-source data in the inverse analysis. Given the advantages of SWENet, it may find broad applications where full wave fields get involved to infer heterogeneous mechanical properties, such as identifying small solid tumors with ultrasound SWE, and differentiating gray and white matters of the brain with magnetic resonance elastography.

THE EFFECT OF THE ANGLE AND DIMENSIONS OF A CROSS-SECTION SPECIMEN ON THE TORSIONAL STRENGTH OF AISI 1020 SQUARE STEEL SHAFT

The unknown torsional strength due to the inconsistency of the angles and dimensions of the square cross-section of AISI 1020 steel specimens in the torsion test is the problem encountered. The research method included: preparation of square AISI 1020 steel specimens measuring 6 mm x 6 mm x 160 mm, measurement of 2 diagonal angles of the cross section of the specimen and dimensions of the cross section at 5 observation points along the specimen receiving torsion loads, torsion testing of specimens, analysis of torsion test results data, and drawing conclusions. The results of the study affect the angle and dimensions of the specimen cross-section on the torsional strength of the AISI 1020 steel square shaft which has a greater value at the angles of 89o and 91o than 90o which with an angle of 89o at dimensions of 5.96 mm x 5.96 mm has a torsional strength of 412 MPa, while at an angle of 90o with dimensions of 5.96 mm x 5.96 mm it has a torsional strength of 359 MPa, and for an angle of 91o in dimensions of 5.95 mm x 5.95 mm has a torsional strength of 402 MPa. The average torsional strength is achieved in the range of 351 to 397 MPa, at an angle of 89o the torsional strength increases by 46 MPa or around 13.1 %, and at an angle of 91o the torsional strength increases by 43 MPa or around 12.3%.

Assessment of pharyngeal airway space in patients with different maxillofacial skeletal abnormalities using cone beam computed tomography

Background. The patency of the pharyngeal airway has a far-reaching impact on craniofacial development. Conversely, the position of the maxillofacial skeletal components in certain disorders may lead to a compromised airway. Therefore, the evaluation of the airway is an essential step in treatment planning. Objectives. The basic aim of this study was to measure the pharyngeal air space volume in the patients with maxillofacial skeletal abnormalities (like Class II, Class III malocclusion, TMJ Ankylosis, Condylar abnormalities and Syndromic cases) and those without any skeletal abnormalities. The objectives were to assess the Linear, Cross-sectional, and Volumetric dimensions of the pharyngeal airway in patients with and without maxillofacial skeletal abnormalities. (Study and Control group) Materials and methods. The Study group included 49 patients with maxillofacial Skeletal abnormalities like Class II and Class III malocclusion, Temporomandibular Joint Ankylosis, Condylar abnormalities, Syndromic cases. 49 Control group patients did not present with any skeletal abnormalities. The Linear, Cross-sectional, and Volumetric dimensions of the pharyngeal airway in the Study group and Control group were calculated and compared within the groups. Statistical Analysis: Unpaired t -test, ANOVA test and Tukey’s Post Hoc analysis test were for the data analysis of the above study. Outcomes. The Anteroposterior dimension of the airway at the Superiormost level was found to be significantly greater in Class II (p-value-0.039), Class III (p-value-0.002), and Control groups (p-value <0.001) when compared with the TMJ Ankylosis group. The Volume and Cross-sectional area of the airway at the most constricted level of the airway was found to be significantly greater in Class III (p-value <0.001) and Control group (p-value 0.013, 0.003) respectively when compared with the TMJ Ankylosis group. Conclusions. The pharyngeal airway was narrowest anteroposteriorly at all three levels (Superior-most, Most constricted, and Inferior-most levels) in the TMJ Ankylosis group and widest in the Class III group. The least cross-sectional area was found in the TMJ Ankylosis group whereas the greatest was found in the Class III group. The airway volume in the TMJ Ankylosis group and Class II group is significantly lesser than that of the Control group.

Unified machine-learning-based design method for normal and high strength steel I-section beam–columns

High strength steel is regarded as a promising construction material due to its superior mechanical properties. However, the codified failure load predictions for high strength steel welded I-section beam–columns are not accurate in some cases owing to the lack of relevant design codes for high strength steel structures. In addition, current design codes ignore the interaction effect of the cross-section plate elements, leading to the inaccuracy of codified predictive ultimate resistances for both normal and high strength steel beam–columns. In this paper, a unified and accurate design method was proposed based on machine learning for both normal and high strength steel welded I-section beam–columns failing by different failure modes. Firstly, a total of 812 experimental and numerical data on welded I-section beam–columns with various steel grades, geometric dimensions, including cross-section dimensions and member lengths, and failure modes, including global buckling, local buckling and local–global interactive buckling were collected to establish a database. Seven machine learning algorithms, including Decision Tree, Random Forest, Support Vector Machine, K-Nearest Neighbour, Adaptive Boosting, Extreme Gradient Boosting and Categorical Boosting were applied to develop regression models to predict failure loads. Based on the established database, each machine learning model was then trained and key hyperparameters were optimised. The model performance was evaluated through a series of statistical indicators and the feature importance analysis, and the evaluated results indicated that the XG-trained regression model had the highest level of accuracy. Finally, the predictions given by the XG-trained regression model were compared with those of the existing codified design provisions, as given in Eurocode and American codes. The evaluation results indicated that the codified predictive bearing capacities of I-section beam–columns were scattered and inaccurate, while the XG-trained regression model provided substantially improved failure load predictions.

Out-of-Plane Design Equations for Confined Masonry Walls

Nowadays there is still a lack of requirements for the out-of-plane design of confined masonry walls. Current code requirements are mainly based on the in-plane behavior of those walls. This research is divided into two parts. In the first part, two confined walls subjected to out-of-plane uniform loads were tested in the laboratory. Confining elements with minimum cross-section dimensions and wall aspect ratios smaller than one were considered. The variable studied was the wall length. Out-of-plane load—displacement curves of walls were obtained. In the second part, two design equations were developed to determine the out-of-plane strength of confined walls. A design equation was developed to determine the corresponding in-plane forces transferred to the confining elements. The out-of-plane strength of 6912 walls was determined using a computer program based on the bidirectional strut method. A parametric analysis was carried out for the out-of-plane strength considering different variables. Multiple linear regression analyses were carried out to propose out-of-plane strength design equations. It was concluded that the experimental out-of-plane strength increased, and the wall failure type changed as the wall length decreased. In addition, the experimental out-of-plane strength of walls was well predicted with both out-of-plane design equations.

Nanophotonic chalcogenide waveguides for supercontinuum generation pumped at 1550 nm

Nanophotonic chalcogenide waveguides (ChGs) fabricated from Ge28Sb12Se60 (GeSbSe) glass were designed and fabricated for efficient supercontinuum (SC) generation. Dispersion engineering and nonlinear optical simulations were used to optimize the cross-sectional dimensions of the strip waveguides for pumping at 1550 nm. The waveguides were fabricated using e-beam lithography and plasma etching to achieve submicron confinement and high optical quality. By pumping anomalous dispersion engineered waveguides with femtosecond pulses at 1550 nm wavelength, supercontinuum generation spanning over 750 nm was demonstrated on-chip. The findings provide experimental evidence of the potential applications of GeSbSe waveguides in nonlinear photonics, highlighting their advantages in terms of performance and spatial efficiency.

Data driven models for capacity prediction of CFS lipped channel flexural members

Cold-Formed Steel (CFS) is considered as a sustainable material and CFS members are becoming popular nowadays as primary or secondary load carrying structural elements. The increasing use of CFS members is owing to their other advantages like high strength to weight ratio, versatility in cross sectional shapes and dimensions, easy fabrication and mass production, uniform quality, good energy efficiency, easiness to handle and transport etc. The behaviour of cold-formed members under flexure is complex as it involves the occurrence of various buckling modes (Local, distortional or lateral-torsional buckling) and the possible interaction between them. Although, the moment carrying capacity of CFS beams can be estimated using existing codes and design standards, the present study is an attempt to introduce an alternate rapid capacity assessment tool based on machine learning for the same. Available data on experiments conducted on CFS lipped channel beams are collected to model and analyse in ABAQUS for validating the finite element model. The validated FE model is used for developing the input-output data set for training the Machine Learning (ML) models by sampling the geometric and strength related input parameters of the CFS beam. Recently introduced machine learning regression models like Linear Regression, Lasso regression, K-Nearest Neighbors, Decision Tree, Random Forest, Adaptive Boosting, Extreme Gradient Boosting, Light Gradient Boosting, Categorical Boosting, Gradient Boosting Regressor, Support Vector Machine and Artificial Neural Network are used to predict the ultimate flexural capacity of CFS beams. The CatBoost model is emerged as the best performing algorithm for predicting the flexural capacity, with 98.5% accuracy for the test data set. A SHAP (SHapley Additive exPlanations) analysis is also conducted for the global and local interpretation of the prediction of the best performing machine learning model. SHAP results not only indicate the influence of input parameters on output prediction, but also the influence of input parameters on each other in predicting the output.

Investigations on the fatigue loading of thin-walled and resource-efficient UHPFRC segmental bridges

Many reinforced concrete and prestressed concrete bridges are defective or can no longer withstand the increased traffic loads for a sufficiently long time. In the long term, they will have to be replaced by new structures. In previous reinforced concrete and prestressed concrete bridges, fatigue loading (e.g. traffic, wind) is rarely a problem with regard to the concrete, especially since the cyclic traffic loads are relatively low compared to the static dead loads due to a solid construction method. However, for reasons of sustainability and compliance with climate targets, future structures and bridges should be built in a resource-efficient and materials-compatible manner, while at the same time fast and durable. A target-oriented approach to this is segmental bridge construction with keyed dry joints made of ultra-high-performance fiber-reinforced concrete (UHPFRC). In these bridge structures the fatigue loads could become more relevant due to the slenderness of the thin-walled UHPFRC bridges superstructure and fatigue problems could occur. In order to investigate this in more detail, FE investigations on segmental box girder bridges under variation of the concrete strength (NSC, HSC and UHPFRC) were carried out, while optimising the cross-section dimensions. It was shown that due to the performance of UHPFRC and the associated cross-section optimisation, an exponential increase in the ratio of cyclic live loads to static dead loads and thus an exponential increase in fatigue loading occurs at thin-walled and resource-efficient UHPFRC segmental bridges compared to NSC and HSC bridges and that this can become relevant for the design of such bridges.

Experimental and numerical investigations of austenitic stainless steel semi-oval hollow sections under combined compression and bending

Semi-oval hollow section is an innovative cross-section profile, including one semi-circular flange, one flat flange and two flat webs. While the semi-circular flange (exposed to fluid or wind) offers a low level of hydrodynamic or aerodynamic drag, the flat elements facilitate connections with other members. This paper presents experimental and numerical investigations into the local buckling behaviour and resistances of austenitic stainless steel semi-oval hollow sections under combined compression and bending. A testing programme was firstly conducted and included initial local geometric imperfection measurements and ten eccentric compression tests. In conjunction with the testing programme, a numerical modelling programme was performed, where finite element models were developed to validate against the test results and conduct parametric studies for expanding the test data pool over a wider range of cross-section dimensions and loading combinations. The obtained test and numerical data were used to evaluate the applicability of the relevant design interaction curves for austenitic stainless steel rectangular hollow sections, as prescribed in the European code and American specification, to austenitic stainless steel semi-oval hollow sections. On the basis of the evaluation results, the codified design interaction curves were found to provide conservative resistance predictions. Finally, an improved design interaction curve, with more accurate end points and suitable shape, was developed and led to more accurate and consistent resistance predictions for austenitic stainless steel semi-oval hollow sections under combined compression and bending.

Experimental and numerical investigation of the hysteretic behavior of reinforced concrete column-steel beam interior joints under low seismic intensity levels

For the composite frame structure of concrete column and steel beam, a connection structure based on ribbed angle steel connector (RASC) is proposed, and the hysteresis performance and force transmission mechanism of this new type of composite joint are studied. Through quasi-static experimental research, the influence of beam and column cross-sectional dimensions on the bearing capacity, energy dissipation capacity, stiffness degradation, ductility, and failure form of the frame structure was analyzed. The results of experimental and finite element analysis show that the failure forms of this joint under low-cycle repeated loading are mainly manifested as the shear failure of concrete in the core area of beams and columns and sliding failure between angle steel connectors and steel beams, and the hysteresis curves of the joints are similar to those of frame beams and columns, respectively.

Redefining Radiation Metrics: Evaluating Actual Doses in Computed Tomography Scans.

Computed tomography (CT) contributes significantly to the collective dose from medical sources, raising concerns about potential health risks. However, existing radiation dose estimation tools, such as volume computed tomography dose index (CTDIvol), dose-length product (DLP), effective dose (ED), and size-specific dose estimate (SSDE), have limitations in accurately reflecting patient exposure. This study introduces a new parameter, size-specific dose-length product (DLPss), aiming to enhance the precision of radiation dose estimation in real-life scenarios. A retrospective analysis of 134 chest CT studies was conducted. Relationships between CTDIvol and anthropometric parameters were examined, and SSDE was calculated based on effective diameter. Additionally, the novel parameter, DLPss, was introduced, considering scan length and cross-sectional dimensions. Analysis reveals variations in scan length, effective diameter, and CTDIvol between genders. Strong correlations were observed between CTDIvol and effective diameter, particularly in men. The average CTDIvol for the entire group was 7.83 ± 2.92 mGy, with statistically significant differences between women (7.38 ± 3.23 mGy) and men (8.30 ± 2.49 mGy). SSDE values showed significant gender differences, with men exhibiting higher values. The average SSDE values for women and men were 9.15 ± 2.5 mGy and 9.6 ± 2.09 mGy, respectively, with a statistically significant difference (p = 0.03). The newly introduced DLPss values ranged around 343.90 ± 81.66 mGy·cm for the entire group, with statistically significant differences between women (323.53 ± 78.69 mGy·cm) and men (364.89 ± 79.87 mGy·cm) (p < 0.05), providing a comprehensive assessment of total radiation dose. The study highlights the need for accurate radiation dose estimation, emphasizing the impact of CT examination parameters on dose variability. The proposed DLPss parameter offers a promising approach to enhancing precision in assessing radiation risk during CT scans. Further research is warranted to explore additional parameters for a comprehensive understanding of radiation exposure and to optimize imaging protocols for patient safety.

Enhancing structural behaviour of polypropylene fibre concrete columns longitudinally reinforced with fibreglass bars

Abstract The research aims to study the behaviour of concrete columns reinforced with fibreglass as bars exposed to seawater. Firstly, hardened concrete properties as the compressive strength and the tensile strength were investigated at ages 14, 28, and 56 days. Secondly, the experimental testing also involved casting 18 short concrete columns that have a length of 300 mm with the cross-sectional dimensions of 100 mm × 100 mm. Six samples were plain concrete, six were reinforced with a diameter of 6 mm longitudinal fibreglass bars, and six polypropylene fibre concrete columns were reinforced with a diameter of 6 mm fibreglass bars. The results added useful information using fibreglass bars (anti-corrosion materials) as reinforced longitudinal concrete columns, so the ultimate load of the reinforced concrete column with fibreglass rod exposed to seawater was 174.8 kN that it was higher than that of the plain concrete column at 104.9 kN. Thus, the fibreglass reinforcement technology enhances the capacity of the columns. So, it could be used in non-impacting structural parts. Meanwhile, the ultimate load of the fibre-reinforced concrete column with fibreglass rod exposed to seawater was 201.8 kN. It is 15.4% higher than that of the ultimate axial load of the reinforced concrete column with fibreglass rods only. Also, the results achieved of this research were encouraging, as the maximum failure load for short columns reinforced with fibreglass rods reached approximately 84 to 87% of failure load relative to polypropylene fibre concrete columns containing reinforcing fibreglass bars. As a result, the structural behaviour bars have been enhanced using fibreglass rod and polypropylene fibre.

Heterogeneous integration of an on-chip Nd:YAG whispering gallery mode laser with a lithium-niobate-on-insulator platform.

The integration of heterogeneous optical components onto an optical platform is crucial for the advancement of photonic chips. To achieve this, efficient coupling of optical signals between components and the platform is essential. Here, we have successfully integrated a Nd:YAG microdisk laser with a lithium-niobate-on-insulator (LNOI) photonic platform by modulating the propagation modes of LNOI. Ridge waveguides are fabricated on the LNOI by carefully adjusting the cross-sectional dimensions to enable the propagation of higher-order propagation modes. This ridge waveguide ensures that the effective refractive index of the higher-order mode closely matches that of the fundamental mode of the Nd:YAG microdisk, ensuring efficient waveguide-microdisk coupling. This on-chip laser, consisting of an Nd:YAG microdisk and LNOI integration, achieves a maximum output power of 23 µW, and a mode suppression ratio of 53.6 dB. This research presents an efficient approach for constructing highly functional heterogeneous integrated optical chips.

Inequality and Asset Prices during Sudden Stops

This paper studies the cross-sectional dimension of Fisher’s debt-deflation mechanism that triggers Sudden Stop crises. Analyzing microdata from Mexico, we show that this dimension has macroeconomic implications that operate via opposing effects. We propose a small open economy, asset-pricing model with heterogeneous-agents and aggregate risk to measure the effects of inequality during crises. In contrast to a representative-agent model, heterogeneity generates persistent current account reversals with smaller drops in asset prices and larger drops in consumption driven by the leveraged households. Moreover, in a lower inequality calibration, we find that crises are less severe, as observed in the data.

Shear wave propagation in a fiber-laden viscoelastic waveguide under prestress: Inverse modeling challenges

The functional role of skeletal muscle and the hierarchal microstructure and arrangement of fibers within it results in anisotropy and inhomogeneity in both material properties and imposed stresses. Dynamic elastography reconstruction methods for estimating muscle tissue viscoelastic properties that are based on assumptions of homogeneity, isotropy and only bulk wave motion may produce inaccurate estimates. Biases may be introduced in reconstruction by homogenizing muscle with axially aligned fibers and approximating it as transversely isotropic. The significance of these biases, and their interplay with imposed stresses and confounding waveguide effects due to small cross-sectional dimensions, is quantified with a series of numerical finite element and experimental elastography studies on cylindrically-shaped fiber-laden muscle phantoms, with varying fiber dimensions. Specifically, numerical simulations of elastography are conducted on 4-, 60- and 113-fiber models with the aligned fiber cross-sectional area fixed (reduced fiber diameter as fiber count increases) and comprising approximately 40% of the cross-sectional area of the cylindrical phantom that is also undergoing tensile axial pre-loading. Fiber elastic moduli twice that of connective tissue are considered. Experimental studies of the 4-fiber model are used to validate the numerical model. [Funding support: NSF 1852691 and NIH AR071162]

Solving Saint Venant torsion problems for rectangular beams using single finite Fourier sine transform method

This research presents the single Fourier sine transform method (SFSTM) for solving the Saint Venant torsion problem of rectangular prismatic bars. The problem is a common theme in the theory of elasticity of unrestrained torsion which was previously expressed by Prandtl using Prandtl stress functions ϕ(x,y) as a Poisson type nonhomogeneous partial differential equation (PDE) called the stress compatibility equation. In this work the SFSTM was applied to the stress compatibility equation, converting the PDE to an easier to solve ordinary differential equation (ODE) in the transformed domain. The boundary conditions were used to find the integration constant and inversion was used to find the solution in the physical domain. The non vanishing stresses and torsional moments were thus found as a single series of infinite terms with rapid convergence. The maximum stresses and moments were found in standard form in terms of torsional parameters which were tabulated for various ratios of the cross-sectional dimensions. A comparison of the torsional parameters with previous results show that the present results are identical with previous results illustrating the accuracy of the SFSTM used. The sine kernel of the SFSTM satisfies the boundary conditions of the problem and contributed to the exact solution obtained. The SFSTM simplified the PDE to an ODE which is simpler to solve.

Ultimate bearing capacity of T-shaped retrofitting diagonal members for angle steel transmission towers

Collapse of steel latticed transmission towers under strong winds is a significant safety concern for power systems. Attaching additional members to the tower members can enhance the wind resistance of transmission towers. To establish systematic retrofitting schemes and methods for predicting the ultimate bearing capacity of T-shaped retrofitting diagonal members, static experiments and finite element analysis on various cross-sectional dimensions and member lengths were utilized in this study. The experimental results indicate that retrofitting can effectively increase the bearing capacity of diagonal members. Finite element models are developed and verified based on the discussion of load-displacement curves and failure modes. The finite element analysis reveals that the increase in capacity achieved by reducing connector spacing is relatively small when compared to the ultimate bearing capacity obtained with the spacing of two connectors, and the arrangement of connectors at both ends meets the requirement of connector spacing. The relationship between the retrofitting bearing capacity and the slenderness ratio of diagonal members can be divided into two linear stages, which correspond to different failure modes. Furthermore, a λk coefficient method based on the axial compression equation is proposed to predict the ultimate bearing capacity of T-shaped retrofitting members. The bearing capacity based on the λk method shows agreement with finite element analysis results.

Similarity quantification of soil spatial variability between two cross-sections using auto-correlation functions

In geotechnical engineering, an appreciation of local geological conditions from similar sites is beneficial and can support informed decision-making during site characterization. This practice is known as “site recognition”, which necessitates a rational quantification of site similarity. This paper proposes a data-driven method to quantify the similarity between two cross-sections based on the spatial variability of one soil property from a spectral perspective. Bayesian compressive sensing (BCS) is first used to obtain the discrete cosine transform (DCT) spectrum for a cross-section. Then DCT-based auto-correlation function (ACF) is calculated based on the obtained DCT spectrum using a set of newly derived ACF calculation equations. The cross-sectional similarity is subsequently reformulated as the cosine similarity of DCT-based ACFs between cross-sections. In contrast to the existing methods, the proposed method explicitly takes soil property spatial variability into account in an innovative way. The challenges of sparse investigation data, non-stationary and anisotropic spatial variability, and inconsistent spatial dimensions of different cross-sections are tackled effectively. Both numerical examples and real data examples from New Zealand are provided for illustration. Results show that the proposed method can rationally quantify cross-sectional similarity and associated statistical uncertainty from sparse investigation data. The proposed method advances data-driven site characterization, a core application area in data-centric geotechnics.

A Cross-Sectional and Longitudinal Integrated Study on Brain Functional Changes in a Neuropathic Pain Rat Model.

Human and animal imaging studies demonstrated that chronic pain profoundly alters the structure and the functionality of several brain regions and even causes mental dysfunctions such as depression and anxiety disorders. In this article, we conducted a multimodal study cross-sectionally and longitudinally, to evaluate how neuropathic pain affects the brain. Using the spared nerve injury (SNI) model which promotes long-lasting mechanical allodynia, results showed that neuropathic pain deeply modified the intrinsic organization of the brain functional network 2 weeks after injury. There are significant changes in the activity of the left thalamus (Th_L) and left olfactory bulb (OB_L) brain regions after SNI, as evidenced by both the blood oxygen level-dependent (BOLD) signal and c-Fos expression. Importantly, these changes were closely related to mechanical pain behavior of rats. However, it is worth noting that after morphine administration for analgesia, only the increased activity in the TH region is reversed, while the decreased activity in the OB region becomes more prominent. Functional connectivity (FC) and c-Fos correlation analysis further showed these two regions of interest (ROIs) exhibit different FC patterns with other brain regions. Our study comprehensively revealed the adaptive changes of brain neural networks induced by nerve injury in both cross-sectional and longitudinal dimensions and emphasized the abnormal activity and FC of Th_L and OB_L in the pathological condition. It provides reliable assistance in exploring the intricate mechanisms of diseases.