Blind Prediction Research Articles

Shake-Table Testing of a Brick Masonry Groin Vault: Overview of Blind Predictions and Postdictions and Comparison with Experimental Results

Shake-Table Testing of a Brick Masonry Groin Vault: Overview of Blind Predictions and Postdictions and Comparison with Experimental Results

Blind prediction and post-experimental analysis of RC core wall’s cyclic flexural response using MVLEM-FD

AbstractBlind prediction and post-experimental studies of the flexural cyclic response of a U-shaped core wall, tested at UCLouvain, Belgium, are presented. The tested specimen (referred to as UW1) was modelled using a relatively simple 3D force–displacement-based version of the beam–column multiple-vertical-line-element (MVLEM-FD), developed at the University of Ljubljana (UL), using standard element parameters. The blind prediction accurately identified critical failure points within the specimen. However, the predicted type of failure, attributed to the rupture of longitudinal bars in the boundary region of flanges was somewhat different from that observed in the experiment. These bars were indeed ruptured, but their rupture was preceded by their buckling and the spalling of the surrounding concrete core. Moreover, the predicted force–displacement hysteretic loop exhibited a slight shift compared to experimental observations. Post-experimental studies revealed that this discrepancy was primarily due to the modelling of the loading at the top of the wall rather than the modelling of the wall itself. Specifically, an additional bending moment induced by the eccentricity of the vertical load applied using three actuators, which was overlooked in the blind prediction. Upon correcting the loading, the agreement between the numerical studies and experiment was considerably improved in terms of both the global and local response quantities. Additionally, minor improvements in modelling the boundary regions of the wall’s flanges, considering the relatively large unconfined concrete cover, were introduced, leading to enhanced estimations of near-collapse response.

Test and sensitivity analysis of base‐isolated steel frame with low‐friction spherical sliding bearings

AbstractIn Japan, spherical sliding bearings with low friction coefficients are gaining popularity for base‐isolating low‐rise frames that are relatively lightweight. However, the complete dataset of isolators and a base‐isolated frame for evaluating the model sensitivity and response uncertainty are limited. This study first presents the design process, isolation unit‐ and frame‐level testing, and a blind prediction contest conducted on the occasion of full‐scale shaking table testing of a three‐story base‐isolated hospital specimen. The design process utilizes a numerical model that accounts for the velocity and contact pressure dependencies and requires soft‐ and hard‐case simulations with nominal friction coefficients plus and minus standard deviation to consider the uncertainties associated with the bearing behavior. The pre‐shipment isolation unit and frame shake table testing yielded an invaluable dataset for bearings under normal and low contact pressures, low and high velocities, and constant and varying axial loads. The accompanying blind prediction contest provided a valuable dataset for rethinking the impact of modeling uncertainty. In‐depth data analysis and sensitivity analysis were conducted. The sliding coefficient increased under low‐contact pressure and low‐velocity conditions. The static friction coefficient was 1.9 to 4.5 times higher than the dynamic coefficient, but this had little impact on the residual displacement, cumulative travel, and maximum story shear force. The axial force fluctuation, vertical motion, and two‐directional input did not significantly affect the bearing behavior in the test. The test and the following simulations confirmed that the low friction coefficient helped the building contents, that is, medical equipment in this study, remain in order under near‐fault and long‐period ground motions.

Simulation of fatigue crack growth in aluminium alloy 7075-T7351 under spike overload and aircraft spectrum loading

The trend towards virtual testing and digital-twin assisted management means that the accurate and reliable simulation of fatigue crack propagation behaviour is more important than ever. Reliable but conservative approaches to support this are in widespread use in the aerospace industry. Nevertheless, the conservatism comes at a significant cost in terms of reduced structural life and an increased ongoing inspection requirement and, as such leads to questions about the economic burden of these approaches. Recent comparisons between blind predictions and test results revealed the extent of the issue for cracking in aluminium alloy 7075-T7351 coupons with configuration and loading representative of military transport aircraft wing skins. The current models were generally conservative by a factor of two or more in terms of crack propagation life. This suggested that there was significant scope to improve the modelling to better reflect all the complex contributing factors. The current work has investigated the issue of changes in the crack front constraint as the crack progresses from a state of high constraint (close to plane strain) to a lower constraint (approaching plane stress). This issue was investigated both experimentally and with the development of an improved analytical model. A test program was conducted on several specimens, loaded under constant-amplitude, constant-amplitude with spike-overloads and a variable amplitude spectrum. Crack-opening stress levels were measured at key points in the tests and the results were used to develop and evaluate improved modelling approaches. The improved model was generally able to predict crack growth within about ± 30 % of that demonstrated along with the correct form of the crack growth, which is a significant advance and will lead to reduced costs and increased safety.

Improving fluid identification in well logging using Continuous Wavelet Transform and Vision Transformers: An innovative approach

Well logging fluid prediction is one of the key steps in assessing oil and gas reserves. By analyzing downhole logging data, different types of fluids contained in underground rocks, such as crude oil, natural gas, and water, can be determined. This information is crucial for assessing the abundance and recoverable reserves of oil and gas resources and helps guide oil and gas exploration and development work. We have introduced a novel model called CWT (Continuous Wavelet Transform)-ViT (Vision Transformer). CWT can simultaneously provide frequency information at different scales, enabling the model to analyze downhole logging data more comprehensively and accurately at different scales. Underground rock structures often exhibit features at multiple scales, and CWT can effectively capture these features, aiding in better differentiation of different types of fluids. The ViT model utilizes the Transformer architecture, allowing for global attention over input sequences without being limited by sequence length. This enables the model to comprehensively understand the overall information of downhole logging data and extract richer features. For complex geological structures and fluid distributions in geological exploration, the global attention mechanism helps the model better grasp the overall situation, thereby improving the accuracy of fluid prediction. When we used the CWT-ViT method for well logging fluid prediction, we achieved a high accuracy rate of 97.50% in the first dataset, which further improved to 97.77% in the second dataset. These results demonstrate the significant robustness and efficiency of the CWT-ViT method in lithology prediction using well logging data. We also conducted blind well experiments, and our CWT-ViT model outperformed other models, achieving a blind well prediction accuracy of 97.36%. Therefore, the experiments indicate that the key to improving accuracy in well logging fluid prediction with CWT lies in its multiscale analysis capability, effectively capturing different fluid characteristic frequencies. Additionally, CWT enhances signal features and removes noise, increasing the precision of fluid identification. Finally, the integration with ViT further optimizes fluid prediction performance, making it outstanding in complex geological environments. The advantages of ViT in fluid prediction include its excellent sequence modeling capability, effective handling of long-distance dependencies, and enhanced ability to capture fluid characteristics in complex well logging data.

An evaluation of the consistency of data and models for performance assessment: Divalent metal sorption on montmorillonite

A detailed analysis of literature data on the retention of divalent metal by purified montmorillonite or montmorillonite-rich material (e.g. bentonite) was conducted. Data for which sufficient experimental conditions were available were modeled with the 2SPNE SC/CE model available in the literature, and with a “minimalist” model, which uses a minimum number of parameters to reproduce the data.A successful data modeling could only be achieved if considering (i) cation exchange competition with aqueous Ca2+ and Mg2+, originating from the dissolution of the clay mineral itself or accessory minerals and (ii) precipitation, at high pH, of phases incorporating the divalent metal of interest. However, in many studies, the concentration of aqueous Ca2+ and Mg2+ and, more generally, a full characterization of solution composition (e.g., Si, Al, dissolved organic carbon, alkalinity) is not provided, thus impeding accurate data modeling. Further difficulties stem from uncertainties related to the nature of the solids precipitating at high pH and missing or inaccurate thermodynamic data related to mineral solubility.Log KD values cannot be predicted from available literature data with an accuracy better than ±1 log unit, without sorption data obtained on a material representative of in situ conditions. In addition, the most reactive sites, commonly referred to as strong sites, which have been characterized only on some, but not all, reference clay materials, should not be considered in blind predictions based on the mineralogical composition of clay materials.

Foreword to the special issue “Adjacent Interacting Masonry Structures”

This special issue focuses on the seismic performance of adjacent interacting masonry structures, particularly in historical European city centers. The AIMS project provided unique data on interacting masonry structures through large-scale shake table tests on two adjacent half-scale stone masonry buildings. The experimental campaign was accomapgnied by a blind prediction study where participants modeled the aggregate’s seismic response. Findings highlight challenges in accurately predicting displacement demands and failure modes, providing critical insights for improving future modeling techniques for masonry buildings.

Combined loading of unreinforced and Z-pin reinforced composite pi joints: An experimental and numerical study

Blind predictions of experimental responses of non-reinforced and z-pin reinforced composite pi joints were established using a progressive damage and failure model. The finite element model used a novel mixed-mode cohesive formulation to model intra-laminar and inter-laminar damage. A deliberate meshing strategy was used for cohesive interlayers to capture the interaction between intra- and inter-laminar damage modes. A smeared cohesive zone modeling approach was implemented to efficiently include the effects of z-pinning for the z-pin reinforced specimens. Using material properties obtained through experimental correlation of simpler joint configurations, blind predictions for large element specimens subjected to combined loading (axial compression and push-off loading) were established. To assess the predictive capabilities of the model, experimental and numerical comparisons were made in terms of load-displacement response, critical loads, and failure progression. Comparisons between the experimental results and predictions for the unreinforced joints were found to be in good agreement across the range of compressive loads tested. For the z-pin reinforced joints, initial responses were accurately predicted; however, ultimate loads and the toughening effect of the z-pin reinforcement was overpredicted.

Regularities and Anomalies in Neon Matrix Shifts of Hydrogen-Bonded O-H Stretching Fundamentals.

O-H bond stretching vibrations in hydrogen-bonded complexes embedded into cryogenic neon matrices are subtly downshifted from cold gas phase reference wavenumbers. To the extent that this shift is systematic, it enables neon matrices as more universally applicable spectroscopic benchmark environments for quantum chemical predictions. Outliers are indicative of either an assignment problem in one of the two cryogenic experiments or they reveal interesting dynamics or structural effects on the complexes as a function of the environment. We compile 6 literature-known pairs of experimental data in jet and neon matrix expansions and realize a 6-fold expansion of that number through targeted matrix isolation and/or slit jet expansion spectroscopy presented in this work. In many cases, the neon matrix shift is less than the uncertainty of the currently best-performing blind quantum chemical predictions for the gas phase, but in specific cases, it may exceed the currently achievable theoretical accuracy. Some evidence for a positive correlation of the matrix shift with the hydrogen bond shift is found, similar to observations for helium nanodroplets. Outliers in particular for water acting as a donor are discussed, and in a few cases they call for a future reinvestigation. Substantial improvement in the correlation of the matrix shift with the hydrogen bond shift is achieved for ketone monohydrates by removing a vibrational resonance. New insights into nitrile hydration isomerism are obtained, and the linear OH stretching spectrum of the jet-cooled ammonia-water complex is presented for the first time. Vibrational spectroscopy in weakly perturbing solid rare gas quantum matrices for the benchmarking of gas phase theory and future explicit theoretical treatments of the quantum matrix environment to better understand the outliers are both encouraged.

Empirical approaches for non-linear site response: results for the ESG6-blind test

As a contribution to step 3 of the ESG6 blind prediction exercise, we present an application of two different, purely empirical approaches to estimate the strong ground motion at a soft site ("KUMA") from the observed ground motion at a reference rock site ("SEVO") for the two largest shocks of the Kumamoto 2016 sequence. The two methods estimate the non-linear transfer function between a reference rock and a sedimentary site by modifying the linear transfer function derived from weak motion recordings. The modification is based either on a machine learning tool based on a wide collection of Japanese weak and strong motion recordings and the associated site metadata (method 1), or on an estimate of a site-specific parameter related to an average non-linear site response (method 2). The acceleration time series are then derived at the sedimentary site of interest using an estimation of the time delay between wave arrivals at the rock and site stations, and a minimum phase assumption for the site transfer function. These predictions were made blindly, but after the ESG6 conference they could be compared both with the actual ground motion recorded at KUMA during the two shocks, and the average and range of all other predictions preformed for this benchmark. Both of these purely empirical methods provide an honorable prediction of usual engineering ground motion parameters of the two target events. The performance of these two purely empirical approaches is at least comparable to those of the numerical simulation methods for the foreshock—if not better—and slightly worse for the (largest) mainshock. As the methods required only recordings of weak motions at the target and a referent sites and very simple description of the soil profile. The use of moderate motions to constrain the frequency shift prediction for the second method and the consideration of an alternative phase modification are possible ways to improvement.Graphical

Discontinuum Micromodelling of Unstrengthened and FRCM-Strengthened Masonry Cross-Vaults Subjected to Seismic Excitation

ABSTRACT Many historical buildings employ masonry cross-vaults as flooring systems. The structural response of such cross-vaults to seismic excitation still needs to be fully understood and requires investigation through experimental studies or accurate numerical simulations. This article presents a finite element discontinuum micromodelling technique to simulate a full-scale mortared masonry cross-vault (unstrengthened and subsequently strengthened with textile-reinforced mortar) recently tested on a shake table as part of a blind prediction competition. The numerical technique uses shell elements to model the brick and mortar geometry explicitly within the STKO+OpenSees finite element framework. Both brick and mortar materials are modeled using an advanced damage-plasticity constitutive model, addressing potential convergence issues associated with strain-softening materials through a novel implicit-explicit integration algorithm. The numerical models predicted the failure mechanisms and crack patterns in close agreement with the experimental results. The strengthened model displayed severe cracks spreading across a larger part of the cross-vault, whereas the unstrengthened model exhibited in-plane shear failure along the groin lines. The strengthened vault showed an almost twofold increase in peak ground acceleration capacity, demonstrating the effectiveness of textile-reinforced mortar. The proposed numerical technique will be helpful in the design of effective retrofit measures for heritage structures.

Reconstructing flexible body vortex-induced vibrations using machine-vision and predicting the motions using semi-empirical models informed with transfer learned hydrodynamic coefficients

This work assesses the validity of transfer learning the hydrodynamic coefficient database, consisting of the added mass and lift coefficients, applicable to flexible bodies undergoing vortex-induced vibrations. Specifically, the hydrodynamic coefficient database learned on data collected by Braaten and Lie (2005) are used to predict the motions observed during in house bare riser model experiments at the MIT Towing Tank. A fully immersed vertical flexible riser model with a length-to-diameter ratio of 145 is towed at different flow speeds and top tensions. Motion is tracked using underwater cameras and the motions are reconstructed using a machine-vision framework eliminating the need for expensive sensing hardware. The vibration amplitude, frequency, and mode shape are determined and the results are compared with those in the literature. Finally, blind predictions of the in-house observed experiments are made using the software VIVA informed with transfer learned hydrodynamic coefficients learned on the experiments by Braaten and Lie (2005).

Blind prediction of fracture in an additively manufactured geomaterial using the finite discrete element method

Modeling fracture and damage processes is a challenging, yet critical capability for promoting safe and sustainable design in geotechnical, energy, and hydrological applications. Numerical methods capable of modeling fracture processes are rarely asked to make blind predictions against experimental observations. Here, we report results from a numerical study of blind fracture prediction in an additively manufactured, three-point bend specimen. We record a number of physical mechanisms associated with the fracture of the specimen and make a blind prediction against experimental results that were unknown when the numerical study was performed. We then compare results from our model to the blind data set. We find that the combined finite discrete element method performs exceptionally well in the simulation and prediction of fracture processes.

Blind prediction of curved fracture surfaces in gypsum samples under three-point bending using the Discontinuous Galerkin Cohesive Zone method

A computational framework based on a Discontinuous Galerkin (DG)/Cohesive Zone formulation is utilized to simulate the experiments of the Purdue Damage Mechanics Modeling Challenge. The inelastic response of the additively-manufactured gypsum material used in the experimental tests is modeled via a dilatational plasticity model. The constitutive and fracture model parameters are calibrated using the load–displacement curves corresponding to three-point bending tests initially provided by the Challenge organizers. The test samples contained initial notches especially designed to force specific types of mixed fracture modes. The calibrated computational modeling framework is used to blindly simulate the more complex configuration of the Challenge experiments. The numerical predictions of the load–displacement curve and the shape of the curved fracture surface are compared to the experimental data provided a posteriori. It is found that the computational method is able to quantitatively describe the fracture response of the material including crack propagation, plastic wake, and the curved geometry of the fracture surface that results from the evolving fracture mode mixity with significant fidelity.

Structural and non‐structural numerical blind prediction of shaking table experimental tests on fixed‐base and base‐isolated hospitals

AbstractBase‐isolated hospitals are frequently preferred to fixed‐base ones because of their improved seismic structural performance. Despite this, the question remains open on the advisability of using this modern seismic protection technology in preference to other conventional solutions, on the grounds of a holistic approach based on limiting non‐structural damage as well as continuity of service to the community in the aftermath of an earthquake. Two full‐scale four‐storey (fixed‐base) and three‐storey (base‐isolated) hospital buildings have been recently built and subjected to three‐dimensional shaking table tests at the National Research Institute for Earth Science and Disaster Prevention (Japan), with particular attention to evaluating and classifying functionality of non‐structural components and vital medical equipment. A two‐phase experimental campaign was carried out considering two earthquakes scaled at different intensity levels and applied along the horizontal and vertical directions. The current study aims to provide results of a numerical structural and non‐structural blind prediction of these hospital settings. A homemade numerical code is developed to account for lumped plasticity modelling of steel frame members and variability of the friction coefficient of spherical sliding bearings. Moreover, three non‐structural components are modelled in the fixed‐base structure: that is, elastic single degree of freedom systems representing two tanks filled with sand at the top floor; elastic beam elements for piping at the third floor; five‐element macro‐model for the in‐plane‐out‐of‐plane nonlinear response of partition walls at the first floor. The identification of predominant vibration periods of the fixed‐base structure is carried out using a homemade numerical code based on the continuous wavelet transforms in combination with the complex Morlet wavelet. Finally, the sliding and rocking motion of three items of medical equipment (i.e., incubator at third floor, dialysis machine at second floor and surgical bed at first floor) are analysed by means of a homemade numerical code, considering acceleration time histories of selected structural nodes of the fixed‐base structure.

A model for the response of unreinforced and z-pin reinforced composite pi joints

Experimental data obtained from Narrow Element and Wide Element pi joints was used to motivate the development of a mechanics-based model to predict the quasi-static response of non-reinforced and z-pin reinforced composite pi joints. The progressive failure modeling approach used a novel cohesive formulation to include intra- and inter-laminar damage modes and their interactions. A smeared cohesive zone modeling approach was implemented in which effective fracture toughness and cohesive strength values were defined in the areas corresponding to the z-pin fields in the reinforced joints. Properties defining the cohesive responses were calibrated at the narrow element level and subsequently used in the wide element model to establish blind predictions prior to experimental testing. Unreinforced (unpinned) and z-pin reinforced pi joint specimens were tested in pull-off loading. Experimental and numerical comparisons were made in terms of load–displacement response, critical loads, damage modes, and failure progression. Comparisons between the experimental results and blind predictions for the unpinned joints were found to be in good agreement; however, discrepancies for the z-pin reinforced joint emphasize the challenges associated with physics-based simplified modeling techniques intended to capture complex z-pin behavior.

Investigation of the subsurface structure at the target site in Kumamoto, Japan, and the distributed data of the blind prediction exercise: report for the experiments for the 6th international symposium on effects of surface geology on seismic motion

This technical report explains details on the results of the investigation to build a subsurface structural model and a selection of earthquake data at the target site of the blind prediction exercise for “The 6th International Association of Seismology and Physics of the Earth’s Interior/International Association of Earthquake Engineering International Symposium on the Effect of Surface Geology on Seismic Motion (ESG6).” The selection process of the target site in the Kumamoto Plain, Japan, in ESG6 was explained with a historical review of the blind prediction tests in the previous ESG conferences. We have collected existing subsurface structural and earthquake data and conducted geophysical and geotechnical surveys in and around the target site to generate important velocity structure and the earthquake data used in the blind test. Microtremor data were obtained in triangular arrays ranging in side lengths from 1 to 962 m, and active surface wave data were derived along a 36-m line at the site. These data were provided for the prediction of a subsurface structural model in the first step of the blind prediction exercise. We also conducted a velocity logging in a borehole to a bottom depth of 39 m at the site and laboratory tests of soil samples from the borehole. We constructed a velocity profile of the shallow and deep sedimentary layers from a combination of the geophysical and geotechnical data at the site, and validated it by comparing the characteristics of the ground motion data from the moderate event. This “preferred velocity model” was provided as a standard model to the participants in the second and third steps of the blind prediction test to predict the earthquake ground motions of a moderate event and the mainshock of the 2016 Kumamoto earthquake.Graphical

Efficient AI-Physics hybrid model with productive capabilities to reduce the time of history matching and scenario assessment; a case study: Minagish oil field

This paper proposes a novel approach that combines physics-based numerical simulation with deep-learning neural networks to create an AI-Physics hybrid model for reservoir simulation. Our primary objective is to reduce the time of history match and achieve the best match between model and observation data using our hybrid model. We trained our model using historical data and created a reliable forecasting model that predicts field behavior and proposes new scenarios to improve production in the upcoming years. To test our model, we combined AI physics history training with blind test prediction calculations of the remaining oil map, and the AI physics model created a forecast scenario definition based on this map. Our proposed simulation method can reduce the time of history matching and scenario evaluation by 90-95%. We created three improved forecast scenarios based on predefined scenarios that can produce millions of standard barrels more oil over three years than the original development scenario. The results demonstrate the potential of our AI-Physics hybrid model in revolutionizing reservoir simulation in the oil and gas industry. Our approach can significantly reduce simulation time, improve forecasting accuracy, and optimize production strategies, leading to significant economic benefits.

Compositional balance analysis: A novel method for tectono-geochemical anomaly identification and blind ore deposit prediction

Tectono-geochemical exploration always involves the study of tectono-geochemical primary halos. From the perspective of compositional data analysis, this study introduced how to use compositional balance analysis (CoBA) method to recognize tectono-geochemical anomalies and infer blind ore deposits in the deep. A case study for prediction of concealed Pb–Zn ore deposits based on tectono-geochemical data in the Huangzhuguan ore cluster, Gansu Province, China, was employed to demonstrate the potential applications of the CoBA method. First, an optimal element combination (i.e., Pb–Zn –Cd) related to near-ore halo was determined by means of CoBA method and receiver operating characteristic curve analysis. Then, according to the element zonation sequences of the primary halo in the hydrothermal deposit, the front halo element combination (i.e., As–Sb–Hg) and the tail halo element combination (i.e., W–Sn–Mo–Bi) were selected for compositional balance analysis. Finally, based on knowledge-driven CoBA method, three types of tectono-geochemical primary halos were customized to evaluate blind Pb–Zn deposits in the Huangzhuguan ore cluster. The results indicate that the CoBA method combined with the superimposed characteristics of tectono-geochemical primary haloes, proves to be effective and straightforward in interpreting Pb–Zn mineralization-related anomalies and predicting hidden Pb–Zn targets.

Combined Finite-Discrete Element Model Simulations of Shake-Table Tests on a Full-Scale Masonry Cross Vault

ABSTRACT This work presents the numerical simulations of shaking table tests of a full-scale masonry cross vault. The boundary conditions simulate the presence of a continuous lateral wall and of a colonnade-between-naves condition. The seismic action is applied along the longitudinal direction of the specimen, with increasing amplitude. The model used for the simulations allows for the elastic finite element modelling of masonry units and the discrete element modelling of the interfaces between them. A tension cut-off governs the interface: no tensile stress can be transmitted once this strength is exceeded. The shear response is defined by cohesion and friction: once the former is exceeded the interface reacts according to Coulomb’s behaviour. The simulations are related to the blind predictions, according to the scheduled tests, and the post-dictions, according to the actual testing sequence. The prediction model overestimates displacements and does not catch the actual crack distribution. Therefore, a post-simulation model was implemented, revising the masonry elastic modulus as well as the stiffness and boundary conditions of the supporting piers. Simulations are improved both in terms of displacement predictions and damage mechanism. Finally, the sensitivity to finite-element size, damping ratio and block discretisation was explored.