Displacement Reconstruction Research Articles

Holocene shoreline displacement, land‐cover change and human settlement distribution on the southeast coast of Sweden

ABSTRACTIn this study, we investigate the interplay between relative sea‐level changes, the development of human settlements and land‐cover changes in the Västervik–Gamlebyviken region on the southeast coast of Sweden, an important archaeological area from the Mesolithic until recent times. The reconstruction of shore displacement was based on diatom analysis of radiocarbon‐dated sediment cores from three lake basins combined with previously published lake isolation data. The resulting curve was used to construct palaeogeographical maps for selected time windows. Land‐cover changes were inferred from pollen data from three lakes using the Landscape Reconstruction Algorithm with its two models REVEALS and LOVE. Our data suggest that people took advantage of the land gained due to an overall fall in relative sea level from ~35 to ~3 metres above sea level (m a.s.l.) over the last 10 000 years, interrupted by periods of transgression and highstands. A sea‐level regression of ~16 m occurred between 10 000 and 8500 cal a bp followed by an ~3–4‐m sea‐level rise, reaching ~22 m a.s.l. at ~7500 cal a bp, which corresponds to the maximum Littorina Sea shoreline in the area. The available archaeological findings for the Mesolithic and Early Neolithic (8950–5450 cal a bp) agree well with the shore displacement curve showing that settlements and human activities were concentrated along or above the shorelines as defined from our study. During the transgression after 8500 cal a bp, however, seasonal settlements were submerged (as shown by findings of polished stone tools and hearths buried in sand) and used again during the subsequent regression after 4600 cal a bp. The Iron Age (2450–900 cal a bp) corresponds partly to a highstand at ~11 m a.s.l. between 3600 and 2000 cal a bp and partly to a rapid regression of ~8 m between 2000 and 1500 cal a bp, and both periods coincide with known human activities along the contemporaneous shoreline. The rapid regression after 2000 cal a bp corresponds to an increase of both regional and local landscape openness and the beginning of a continuous record of crop cultivation.

Dynamic strain field estimation of fixed offshore support structures using limited acceleration measurements

The strain history affecting the fatigue life of fixed offshore support structures is one of the most important topics in structural monitoring. However, some critical fatigue locations are located below the seabed, and the installation of strain gauges at these locations entails significant maintenance costs. In contrast, acceleration which reflects the vibration characteristics of the structure is an easily accessible and more stable physical parameter. Therefore, this study presents a strain estimation scheme that uses limited acceleration measurements to estimate the dynamic strain field of the fixed offshore support structures. An adaptive displacement reconstruction method is used to obtain the displacements at the master degrees of freedom, then the global displacements are obtained by the evolutionary orthogonal response expansion method, and finally, these displacements are implemented into the numerical software by redefining the boundary conditions to obtain the dynamic strain field. The advantage of the proposed method over the traditional strain-solving forward problem is that it relies solely on measured acceleration and structural geometry information, without requiring displacement, strain, or modal information. The correctness of the proposed method is verified by a numerical jacket platform model with multi-harmonic and non-stationary random excitations. Furthermore, physical experiments under eccentric rotation and hammering excitations are performed to assess the applicability of the proposed method on a wind turbine model equipped with laser displacement and fibre bragg grating sensors as reference measurements. The results show that the proposed method can accurately predict the dynamic strains of jacket platform and wind turbine support structures, while the appropriate agreement between the estimated strains and the numerical results, and the optical measured response is observed, with maximum estimation errors of 1.80% and 4.63%, respectively. Summarily, the application of the approach enables a new type of strain monitoring applicable to fixed offshore support structures.

A High-Precision Inverse Finite Element Method for Shape Sensing and Structural Health Monitoring

In the contemporary era, the further exploitation of deep-sea resources has led to a significant expansion of the role of ships in numerous domains, such as in oil and gas extraction. However, the harsh marine environments to which ships are frequently subjected can result in structural failures. In order to ensure the safety of the crew and the ship, and to reduce the costs associated with such failures, it is imperative to utilise a structural health monitoring (SHM) system to monitor the ship in real time. Displacement reconstruction is one of the main objectives of SHM, and the inverse finite element method (iFEM) is a powerful SHM method for the full-field displacement reconstruction of plate and shell structures. However, existing inverse shell elements applied to curved shell structures with irregular geometry or large curvature may result in element distortion. This paper proposes a high-precision iFEM for curved shell structures that does not alter the displacement mode of the element or increase the mesh and node quantities. In reality, it just modifies the methods of calculation. This method is based on the establishment of a local coordinate system on the Gaussian integration point and the subsequent alteration of the stiffness integration. The results of numerical examples demonstrate that the high-precision iFEM is capable of effectively reducing the displacement difference resulting from inverse finite element method reconstruction. Furthermore, it performs well in practical engineering applications.

Is Oncoplastic Surgery Safe in High-Risk Breast Cancer Phenotypes?

Oncoplastic surgery (OPS) has increased in popularity over the recent years. It is a form of breast conservation surgery allowing for larger partial mastectomy (PM) resections followed by either volume displacement or volume replacement reconstruction techniques. However, there is a lack of evidence on the effectiveness and safety of OPS with radiotherapy (OPS + RT) in high-risk breast cancer phenotypes, such as triple negative breast cancer (TNBC) and HER2 positive (HER2+) patients. Our aim was to compare the breast cancer-specific survival (BCSS) and postoperative surgical complications in OPS + RT compared to PM alone with radiation (PM + RT) and total mastectomy (MTX) without radiotherapy (MTX-RT). Patient data were analyzed from the Surveillance, Epidemiology, and End Results (SEER) cancer registries from January 1, 2012 to December 31, 2020. Patients were stratified according to the type of surgery. Cox regression analysis was performed to assess prognostic factors of BCSS. A total of 24 621 patients with high-risk breast cancer phenotypes were identified, 180 underwent OPS + RT; 13 402, PM + RT; and 11 039 MTX-RT. OPS + RT was more frequently performed in younger (mean age of 65.53 years, SD: 9.29, p < 0.001), non-Hispanic White (90.5% vs. 77.7% vs. 76.3%) and single women (17.9% vs. 12.1% vs. 13.3%). MTX-RT was usually performed in patients with high histological grade, TNBC, and higher stages. Overall complication rates were higher in the MTX-RT, compared to OPS + RT and PM + RT, 2%, 1.1%, and 0.7%, respectively, p < 0.001. Rates of hematoma and surgical site infections were higher in the MTX-RT group. With a median follow-up of 46 months, OPS + RT had better BCSS rates at 5 years compared to PM + RT and MTX-RT (97.1% vs. 94.7% vs. 89.8%, p < 0.001). MTX-RT was found to be an independent prognostic factor of worse BCSS compared to OPS + RT (hazard ratio [HR] = 2.584; 95% confidence interval [CI]: 1.005-7.171), while PM + RT had no difference compared to OPS + RT (HR = 1.670, 95% CI: 0.624-4.469). OPS is a safe breast surgical option in patients with HER2+ and TNBC. Patients with high-risk phenotypes who underwent OPS + RT and have similar BCSS and complication rates compared to standard breast surgical options. As such, OPS should be considered as an option whenever breast conservation surgery is being discussed.

A novel shape sensing approach based on the coupling of Modal Virtual Sensor Expansion and iFEM: Numerical and experimental assessment on composite stiffened structures

Shape sensing, i.e. the reconstruction of the displacement field of a structure from discrete strain measurements, is becoming crucial for the development of a modern Structural Health Monitoring framework. Nevertheless, an obstacle to the affirmation of shape sensing as an efficient monitoring system for existing structures is represented by its requirement for a significant amount of sensors. Two shape sensing methods have proven to exhibit complementary characteristics in terms of accuracy and required sensors that make them suitable for different applications, the inverse Finite Element Method (iFEM) and the Modal Method (MM). In this work, the formulations of these two methods are coupled to obtain an accurate shape sensing approach that only requires a few strain sensors. In the proposed procedure, the MM is used to virtually expand the strains coming from a reduced number of strain measurement locations. The expanded set of strains is then used to perform the shape sensing with the iFEM. The proposed approach is numerically and experimentally tested on the displacement reconstruction of composite stiffened structures. The results of these analyses show that the formulation is able to strongly reduce the number of required sensors for the iFEM and achieve an extremely accurate displacement reconstruction.

Dynamic analysis and shape sensing of pipes subjected to water hammer by the inverse finite element method

Pipe structures are commonly employed in modern industries. However, the transient pressure induced by water hammer leads to a high risk of structural damage, highlighting the importance of Structural Health Monitoring (SHM). The inverse Finite Element Method (iFEM) offers a way to reverse structural deformations based on a set of discrete strain data. In this paper, the water hammer phenomenon in a Reservoir-Pipe-Valve (RPV) system is investigated. The element iQS4 is adopted to reconstruct dynamic deformations for the pipe using iFEM. The water hammer resulting from an instantaneous closure of the valve can generate significant fluid pressure, leading to severe pipe vibrations. The vibration deformations can be monitored by iFEM. The maximum error of the pipe nodal displacement is below 3 % and the average error is below 2 % in the proposed several sensor location cases, even the mesh of iFEM is coarser than the FE model. Among the sparse sensor location cases, the X path which is suitable for Fiber Bragg Grating (FBG) sensors has the highest accuracy of the displacement reconstruction. The results reveal a promising prospect in the real-time monitoring based on iFEM for pipes.

DIPHORM: An Innovative DIgital PHOtogrammetRic Monitoring Technique for Detecting Surficial Displacements of Landslides

Monitoring surface displacements of landslides is essential for evaluating their evolution and the effectiveness of mitigation works. Traditional methods like robotic total stations (RTSs) and GNSS provide high-accuracy measurements but are limited to discrete points, potentially missing the broader landslide’s behavior. On the contrary, laser scanner surveys offer accurate 3D representations of slopes and the possibility of inferring their movements, but they are often limited to infrequent, high-cost surveys. Monitoring techniques based on ground-based digital photogrammetry may represent a new, robust, and cost-effective alternative. This study demonstrates the use of multi-temporal images from fixed and calibrated cameras to achieve the 3D reconstruction of landslide displacements. The method presented offers the important benefit of obtaining spatially dense displacement data across the entire camera view and quasi-continuous temporal measurement. This paper outlines the framework for this prototyping technique, along with a description of the necessary hardware and procedural steps. Furthermore, strengths and weaknesses are discussed based on the activities carried out in a landslide case study in northeastern Italy. The results from the photo-monitoring are reported, discussed, and compared with traditional topographical data, validating the reliability of this new approach in monitoring the time evolution of surface displacements across the entire landslide area.

Accelerometer-aided millimeter-wave radar interferometry for uninterrupted bridge displacement estimation considering intermittent radar target occlusion

Monitoring bridge displacement is necessary to detect early signs of damage, prevent catastrophic failures, and maintain public confidence in the safety of critical transportation infrastructure. Radar interferometry is attractive for long-term continuous monitoring of bridge displacements, given its resilience to weather and lighting conditions. However, intermittent radar target occlusions caused by moving vehicles beneath bridges pose challenges during extended continuous monitoring periods. In this study, accelerometer-aided millimeter-wave radar interferometry was explored with an explicit consideration of intermittent radar target occlusion. Radar and accelerometer measurements were first recorded over a short period. Multiple good targets were selected among all radar-detected targets, and their direction-converting factors were estimated using short-period measurements. Subsequently, bridge displacement was continuously estimated by overcoming intermittent radar target occlusions. A displacement reconstruction algorithm was proposed for target occlusion periods, and a multitarget-based phase-unwrapping algorithm was proposed to remove the displacement drift caused by radar target occlusion. The proposed technique was experimentally validated through laboratory tests on a 10-meter-long bridge structure and field tests on two different spans of a footbridge. The technique accurately estimated displacements with overall errors below 0.1 mm, allowing it to be widely applied to bridges with millimeter-scale displacements.

A Similarity Clustering Deformation Prediction Model Based on GNSS/Accelerometer Time-Frequency Analysis

Structural monitoring is crucial for assessing structural health, and high-precision deformation prediction can provide early warnings for safety monitoring. To address the issue of low prediction accuracy caused by the non-stationary and nonlinear characteristics of deformation sequences, this paper proposes a similarity clustering (SC) deformation prediction model based on GNSS/accelerometer time-frequency analysis. First, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm is used to decompose the original monitoring data, and the time-frequency characteristic correlations of the deformation data are established. Then, similarity clustering is conducted for the monitoring sub-sequences based on their frequency domain characteristics, and clustered sequences are combined subsequently. Finally, the Long Short-Term Memory (LSTM) model is used to separately predict GNSS displacement and acceleration with clustered time series, and the overall deformation displacement is reconstructed based on the predicted GNSS displacement and acceleration-derived displacement. A shake table simulation experiment was conducted to validate the feasibility and performance of the proposed CEEMDAN-SC-LSTM model. A duration of 5 s displacement prediction is analyzed after 153 s of monitoring data training. The results demonstrate that the root mean square error (RMSE) of predicted displacement is 0.011 m with the proposed model, which achieves an improvement of 64.45% and 61.51% in comparison to the CEEMDAN-LSTM and LSTM models, respectively. The acceleration predictions also show an improvement of 96.49% and 95.58%, respectively, the RMSE of the predicted acceleration-reconstructed displacement is less than 1 mm, with a reconstruction similarity of over 99%. The overall displacement reconstruction similarity can reach over 95%.

A full-field structural displacement reconstruction method for large-scale floating rafts in marine propulsion systems

Large-scale floating rafts have been widely applied to marine propulsion. Due to the presence of elastic supports, it belongs to the elastic constraints rather than the fixed constraints found in aerospace and bridge structures. This leads to displacement is no longer just elastic deformation, but also includes some rigid-body displacement. However, the existing displacement reconstruction methods are all based on fixed constraints. To address this issue, an improved modal method (IMM) is proposed. The boundary conditions are extended from fixed constraints to elastic constraints and the displacement field is uniformly described. Firstly, by analyzing the modal characteristics of three types of constraints, the reasons for the failure of the current modal method under elastic constraints are presented. Secondly, the IMM is established based on a dimensionless error function between the discrete strain, finite displacement measurements, and their theoretical values. Finally, the feasibility of the IMM is verified by numerical analysis and experiment tests on an elastic support plate structure with high precision and excellent suitability. This method can be applied to the full-filled displacement reconstruction in large-scale floating rafts of marine propulsion systems, which provides significant engineering value for improving the shafting alignment and the raft attitude balance.

Displacement Sensing for Laser Self-Mixing Interferometry by Amplitude Modulation and Integral Reconstruction.

To robustly and adaptively reconstruct displacement, we propose the amplitude modulation integral reconstruction method (AM-IRM) for displacement sensing in a self-mixing interferometry (SMI) system. By algebraically multiplying the SMI signal with a high-frequency sinusoidal carrier, the frequency spectrum of the signal is shifted to that of the carrier. This operation overcomes the issue of frequency blurring in low-frequency signals associated with continuous wavelet transform (CWT), enabling the precise extraction of the Doppler frequency of the SMI signal. Furthermore, the synchrosqueezing wavelet transform (SSWT) is utilized to enhance the frequency resolution of the Doppler signal. Our experimental results demonstrate that the proposed method achieves a displacement reconstruction accuracy of 21.1 nm (0.89%). Additionally, our simulations demonstrated that this method can accurately reconstruct target displacement under the conditions of time-varying optical feedback intensity or a signal-to-noise ratio (SNR) of 0 dB, with a maximum root mean square (RMS) error of 22.2 nm. These results highlight its applicability in real-world environments. This method eliminates the need to manually determine the window length for time-frequency conversion, calculate the parameters of the SMI system, or add additional optical devices, making it easy to implement.

Experimental investigation on fluid-induced vibration of a semi-submerged flexible pipe in oncoming flows

Fluid-induced vibration (FIV) features of the semi-submerged flexible pipe in an oncoming flow are experimentally investigated in this paper. The flexible pipe is towed to simulate the equivalent uniform oncoming flow with a Froude number (Fr) ranging from 0.2 to 2.5. The overtopping states are determined and divided into three regions by the Fr numbers, including non-overtopping, intermitting overtopping, and continuous overtopping regions. Through the displacement reconstruction and wavelet transform methods, the displacement response, frequency, trajectory, and the chaotic characteristics of the semi-submerged pipe are studied. The results show that the FIV displacement responses are evidently affected by the intensity of the overtopping phenomenon. A significant mean displacement in the cross flow (CF) direction can be seen and a maximum value of 0.88D can be reached. The unexpectedly larger FIVs with standard deviation values of around 0.52D can be witnessed in the in-line (IL) direction than those for a fully submerged pipe. Moreover, the FIV frequency response in the IL direction is found to be consistent with that in the CF direction under intermitting overtopping and continuous overtopping state, and the corresponding Strouhal numbers are 0.24 and 0.28, respectively. The FIV response is found to be chaotic in non-overtopping states, while it behaves periodic and quasiperiodic features as overtopping occurs. The “O” shape of the motion trajectory is observed at such overtopping regions. The present work improves the basic understanding of the FIV features of the semi-submerged flexible pipe in the oncoming flow and can provide useful references for designing the relevant marine structures.

Isogeometric mindlin-reissner inverse-shell element formulation for complex stiffened shell structures

Structural health monitoring (SHM) is a technology that is used to improve the safety, stability, and availability of large engineering structures. One important aspect of SHM is the ability to perform real-time reconstruction of the full-field structural displacements, also known as shape sensing. The inverse Finite Element Method (iFEM) is a technique that has been used for three-dimensional shape sensing of structures using strain data. On the other hand, Isogeometric Analysis (IGA) is a method that utilizes smooth spaces of functions, such as non-uniform rational B-splines, to solve structural problems and has gained significant attention in recent times. In this study, the authors propose a new method for shape sensing of complex stiffened shell structures by combining IGA with the iFEM method. The goal of this research is to accurately reconstruct the complex geometry of the structure without the need for a fine numerical discretization or mesh. To achieve this, the authors have developed an isogeometric Mindlin-Reissner inverse-shell element (IgaiMin) to implement the coupling between IGA and iFEM. The proposed method is validated by solving problems involving simple plates, tee junctions, and partly clamped stiffened panels representing ship structures.

Distributed strain monitoring method for structural vibration based on multi-point acceleration measurement

Fiber Bragg Grating (FBG) has been widely used in vibration monitoring due to its advantages of high sensitivity, resistance to electromagnetic interference and ease of networking. This paper proposes a method of distributed strain monitoring for vibrating structures where the surface is unsuitable for attaching FBG. This method utilizes measured multi-point acceleration to calculate dynamic displacement, and subsequently reconstructs distributed strain based on displacement matching and a displacement–strain function. Finite element simulation results demonstrate that the displacement matching scheme has higher strain reconstruction accuracy and broader adaptability. An FBG accelerometer with an equal-strength beam is designed, fabricated, and tested, exhibiting a resonant frequency of 56 Hz and an average sensitivity of 70 pm·g−1 in the flat frequency band. The proposed method is experimentally validated using a 12 m steel pipeline. It’s demonstrated that the displacement reconstruction error is less than 8 %, and the strain reconstruction error is less than 11 %.

Displacement Reconstruction Based on Physics-Informed DeepONet Regularizing Geometric Differential Equations of Beam or Plate

Physics-informed DeepONet (PI_DeepONet) is utilized for the reconstruction task of structural displacement based on measured strain. For beam and plate structures, the PI_DeepONet is built by regularizing the strain–displacement relation and boundary conditions, referred to as geometric differential equations (GDEs) in this paper, and the training datasets are constructed by modeling strain functions with mean-zero Gaussian random fields. For the GDEs with more than one Neumann boundary condition, an algorithm is proposed to balance the interplay between different loss terms. The algorithm updates the weight of each loss term adaptively using the back-propagated gradient statistics during the training process. The trained network essentially serves as a solution operator of GDEs, which directly maps the strain function to the displacement function. We demonstrate the application of the proposed method in the displacement reconstruction of Euler–Bernoulli beams and Kirchhoff plates, without any paired strain–displacement observations. The PI_DeepONet exhibits remarkable precision in the displacement reconstruction, with the reconstructed results achieving a close proximity, surpassing 99%, to the finite element calculations.

Damage detection based on accelerometers and computer vision measurements of moving load-induced structural responses

Damage identification is an important and challenging issue in structural health monitoring to prevent sudden structural failures. This study introduces a novel damage detection method for beams associated with the cross-correlation function of the moving load-induced full-field displacements. Firstly, through theoretical derivation, the structural responses of a single-span beam under arbitrary boundary conditions subjected to a moving concentrated force were investigated, both before and after damage occurred. The changes in structural responses due to local stiffness damage were analyzed from a theoretical perspective. Then, a method is introduced to extract high-resolution mode shapes, which represent the true state of the structure, from the computer vision-based displacements and accelerations measured at limited locations. These mode shapes were then used for full-field displacement reconstruction, and the changes in the cross-correlation function of these reconstructed displacements were employed for damage detection. The proposed method can obtain the higher-order responses compared to the traditional vision-based methods, and the displacements at the acceleration-unmeasured locations can be improved compared to the conventional data fusion method. Finally, the proposed method was validated both in numerical simulations and experimental tests on a beam model with multiple damage scenarios. The results have demonstrated the capability of the proposed method in mode shape extraction, full-field displacement reconstruction, and damage detection.

A technique for enhancing tight oil recovery by multi-field reconstruction and combined displacement and imbibition

A seepage-geomechanical coupled embedded fracture flow model has been established for multi-field coupled simulation in tight oil reservoirs, revealing the patterns of change in pressure field, seepage field, and stress field after long-term water injection in tight oil reservoirs. Based on this, a technique for enhanced oil recovery (EOR) combining multi-field reconstruction and combination of displacement and imbibition in tight oil reservoirs has been proposed. The study shows that after long-term water flooding for tight oil development, the pressure diffusion range is limited, making it difficult to establish an effective displacement system. The variation in geostress exhibits diversity, with the change in horizontal minimum principal stress being greater than that in horizontal maximum principal stress, and the variation around the injection wells being more significant than that around the production wells. The deflection of geostress direction around injection wells is also large. The technology for EOR through multi-field reconstruction and combination of displacement and imbibition employs water injection wells converted to production and large-scale fracturing techniques to restructure the artificial fracture network system. Through a full lifecycle energy replenishment method of pre-fracturing energy supplementation, energy increase during fracturing, well soaking for energy storage, and combination of displacement and imbibition, it effectively addresses the issue of easy channeling of the injection medium and difficult energy replenishment after large-scale fracturing. By intensifying the imbibition effect through the coordination of multiple wells, it reconstructs the combined system of displacement and imbibition under a complex fracture network, transitioning from avoiding fractures to utilizing them, thereby improving microscopic sweep and oil displacement efficiencies. Field application in Block Yuan 284 of the Huaqing Oilfield in the Ordos Basin has demonstrated that this technology increases the recovery factor by 12 percentage points, enabling large scale and efficient development of tight oil.

Global Displacement Reconstruction of Lattice Tower Using Limited Acceleration and Strain Sensors

Displacement is an important parameter for evaluating structural performance. However, the accurate measurement of global dynamic displacement remains a challenging task. To solve this problem, this paper proposes a global dynamic displacement reconstruction method for lattice tower structures, fusing limited acceleration and strain data. First, the strain-displacement mapping method for cantilever beams with variable cross-sections is presented and then extended to lattice towers. Thereafter, a modified multi-rate data fusion algorithm incorporating Kalman filtering and the proposed strain-displacement mapping methods is developed to fuse the acceleration and strain data to reconstruct the global dynamic displacement of the tower. The numerical simulation, model test and full-scale test demonstrate that the reconstructed dynamic displacements using the proposed method agree well with the reference values in both the time and frequency domains, and the parametric analysis has also been carried out, exhibiting great robustness and high reconstruction accuracy.

Focus on sub-nanometer measurement accuracy: distortion and reconstruction of dynamic displacement in a fiber-optic microprobe sensor

Focus on sub-nanometer measurement accuracy: distortion and reconstruction of dynamic displacement in a fiber-optic microprobe sensor

Inverse analysis of deformation moduli for high arch dams using the displacement reconstruction technique and multi‐objective optimization

AbstractThe inverse analysis of the deformation moduli of high arch dams based on displacement monitoring data is essential for structural safety assessment. In traditional inverse analysis methods, the deformation moduli are identified based on the single‐objective optimization and the hydrostatic component derived from the statistical model. This type of method has two main shortcomings: First, it treats the essential multi‐objective optimization problem as a single‐objective problem; second, the extracted hydrostatic component may be biased due to the multicollinearity of variables in the statistical model. This paper presents a methodology for the inverse analysis of the deformation moduli of high arch dams under a multi‐objective optimization strategy. The methodology employs empirical mode decomposition to extract the aging component from displacement monitoring data. Then, thermomechanical analysis is used to reconstruct the remaining hydrostatic and temperature components, thereby avoiding the biases encountered in solving the statistical model. The adaptive polynomial chaos expansion method is embedded in the NSGA‐III algorithm to establish and solve multi‐objective functions in the inverse analysis. Additionally, a composite decision index considering errors and test information is proposed to determine acceptable deformation moduli from the Pareto solution set. A high arch dam is selected to illustrate this methodology with static and dynamic monitoring data. The results show that the identified deformation moduli have errors of 3.8% and 7.2% in displacement and acceleration, respectively. The proposed methodology can yield deformation modulus values that are more consistent with the physical implications than those of the single‐objective optimization method.