Scale Model Research Articles

Experimental and numerical analysis of seismic performance of jacket platforms subjected to onshore and offshore earthquakes

Offshore platforms located in seismically active areas may be subjected to different seismic effects during service. The seismic performance of offshore platforms under different earthquakes was studied using shaking table tests and finite element analysis (FEA). The dynamic properties, acceleration, displacement and strain responses of the scale model under near-field, far-field and offshore earthquakes were studied. On this basis, more consideration was given to soil-pile-structure interactions (SPSIs), and this finite element (FE) model was analyzed for seismic fragility using incremental dynamic analysis (IDA). By combining the results of the tests and FEA, it was found that the dynamic response of the platform was significantly larger under offshore earthquakes than under onshore earthquakes. The collapse resistance of offshore platform under offshore earthquakes was inferior to that under onshore earthquakes. Therefore, seismic performance assessment of long-period offshore platforms based on onshore earthquakes may overestimate its seismic capacity and pose potential risks to platforms in service.

Continuum insight into the effects of electrode design parameters on the electrochemical performance of lithium-ion batteries

Lithium-ion batteries energy and power density strongly depend on the type of active material and the electrode design parameters. An in-depth understanding of the effect of battery design parameters on their electrochemical performance is experimentally expensive and hence requires the utilization of cheaper continuum scale models. Here, using a lithium-ion cell composed of LiFePO4 cathode, Li4Ti5O12 anode and a porous separator filled with a liquid electrolyte as an example, we demonstrate the use of an experimentally validated pseudo-two-dimensional (P2D) model in one-dimension to explore the effects of different cell design parameters on the discharge capacity at different current rates. The model is simulated in two-dimensional to instantly visualize the concentration distribution of Li ions in the electrode at high discharge current rates. The continuum model unravels that the solution phase diffusion limitation is the main factor inhibiting the performance of thick electrodes at high current rates and the Li4Ti5O12 anode is the limiting electrode. These findings using continuum models provide guidance for and accelerate the optimization of electrode architecture for enhancing the performance of lithium-ion batteries.

Experimental validation of a Kalman observer using linearized OpenFAST and a fully instrumented 1:70 model

AbstractTo enable real‐time monitoring and control strategies for floating offshore wind turbines, accurate information about the state of the system is needed. This paper details the application of a Kalman filter to the UMaine VolturnUS‐S floating wind platform to provide accurate state estimates in real time using minimal system measurements. The midfidelity nonlinear simulation tool OpenFAST was used to generate the underlying linear state‐space model for the Kalman filter. This linear model and its limitations are demonstrated through comparison with experimental data collected on a 1:70 froude‐scaled model of the floating platform and tower. Using a selection of five measurements from the real system, a Kalman filter was developed to provide estimates for the remaining system states and measurements. These estimates were then validated against the experimental values collected from testing of the scale model. Validation of the Kalman filter produced accurate estimates of surge, heave, and tower base bending moment, measurements of which were not available to the Kalman filter. Performance of the Kalman filter was tested and validated over a range of sea conditions from rated wind speed to storm events and demonstrated robustness in the Kalman filter to maintain accuracy across all operating conditions despite significant error in the underlying linear model for extreme conditions.

Scaling laws for the modelling of energy geostructures

Among the different solutions to meet the increasing need for renewable energies, energy geostructures, and particularly energy piles, are very promising. However, their dual role (structural support and energy harvester) raises design questions and safety issues. In addition, they are often placed within a groundwater flow and the influence of seepage on thermal loadings and mechanical response is still to be characterised. In this perspective, centrifuge modelling can play a significant role as in lots of geotechnical problems. In the present case, reduced scale models present a supplementary advantage since diffusion timescales are highly reduced. Scaling factor for time is 1/N² if scaling factor for lengths is 1/N. Nevertheless, the numerous phenomena to consider make it difficult to ensure the similarity between model and prototype. The present document derives and gathers all the scaling laws and attention points to keep in mind when centrifuge modelling energy piles.

A pore scale model study of mass transfer and electrochemical reaction in cathode catalytic layer of high-temperature polymer electrolyte membrane fuel cells

The mass transfer and related electrochemical reactions in the catalytic layer (CL) are crucial for the performance of high-temperature polymer electrolyte membrane fuel cells (HT-PEMFCs), but there is a lack of understanding of the optimal phosphoric acid content and Pt/C catalyst loading in the CL. In this work, we investigate the influences of Pt/C catalyst numbers (NPt/C) and phosphoric acid film thickness (δPA) on mass transfer and electrochemical reactions of the cathode CL using a pore-scale model (300 × 300 × 300 nm3). The results reveal that larger NPt/C and δPA can impede oxygen diffusion, while lower NPt/C and δPA lead to fewer reaction active sites and lower conductivity, both of which result in lower current density. Therefore, the balance of three-phase transport is extremely important for CL. There is a 3D volcanic relationship between current density, Pt/C catalysts, and phosphoric acid film. At NPt/C = 200 (7407 per μm3) and δPA = 4 nm (the volume fractions of 37.22 % and 17.87 %), the highest current density can be achieved at a potential of 0.5 V (vs. RHE), which increased with the decrease of potential. This work is valuable for understanding the optimizing the microstructure and three-phase transport pathway of the CL to improve the performance of HT-PEMFCs.

Predicting Antimicrobial Peptides Using ESMFold-Predicted Structures and ESM-2-Based Amino Acid Features with Graph Deep Learning.

Currently, antimicrobial resistance constitutes a serious threat to human health. Drugs based on antimicrobial peptides (AMPs) constitute one of the alternatives to address it. Shallow and deep learning (DL)-based models have mainly been built from amino acid sequences to predict AMPs. Recent advances in tertiary (3D) structure prediction have opened new opportunities in this field. In this sense, models based on graphs derived from predicted peptide structures have recently been proposed. However, these models are not in correspondence with state-of-the-art approaches to codify evolutionary information, and, in addition, they are memory- and time-consuming because depend on multiple sequence alignment. Herein, we presented a framework to create alignment-free models based on graph representations generated from ESMFold-predicted peptide structures, whose nodes are characterized with amino acid-level evolutionary information derived from the Evolutionary Scale Modeling (ESM-2) models. A graph attention network (GAT) was implemented to assess the usefulness of the framework in the AMP classification. To this end, a set comprised of 67,058 peptides was used. It was demonstrated that the proposed methodology allowed to build GAT models with generalization abilities consistently better than 20 state-of-the-art non-DL-based and DL-based models. The best GAT models were developed using evolutionary information derived from the 36- and 33-layer ESM-2 models. Similarity studies showed that the best-built GAT models codified different chemical spaces, and thus they were fused to significantly improve the classification. In general, the results suggest that esm-AxP-GDL is a promissory tool to develop good, structure-dependent, and alignment-free models that can be successfully applied in the screening of large data sets. This framework should not only be useful to classify AMPs but also for modeling other peptide and protein activities.

A scale model study of an engine test facility for alleviating low-frequency howl

A scale model experimental study is conducted addressing howl occurring during engine tests in the Propulsion Systems Laboratory (PSL) of NASA Glenn Research Center. The aim is to understand the sources of the howling noise and find possible remedies. It is shown that a jet discharged into the model of the PSL entrance duct gives rise to high levels of low frequency noise. This occurs apparently due to duct acoustic modes randomly excited by the jet. Wire-mesh screens of various mesh size and configuration as well as tabs, placed at the end of the model duct, are shown to affect the noise. Comparative effects of these configurations are studied, and some are found to alleviate the low-frequency noise significantly. Based on these results, the equivalent of a 4-mesh screen is recommended as the end treatment for the duct of the PSL facility.

Planing Hull Hydrodynamic Performance Prediction Using LincoSim Virtual Towing Tank

This work shows the performance of LincoSim, a web-based virtual towing tank enabling automated and standardized calm water computational fluid dynamics (CFD) data sampling, extending previous published applications to the case of a high-speed hull. The calculations are performed for a 1:10 scale model of a 43 ft powerboat hull form in the Froude number range from 0.3 to 2.0. The counterpart physical model is the experimental fluid dynamics (EFD) campaign performed at the University of Naples Federico II, where the resistance, sinkage and trim data have been measured. The EFD/CFD data comparison is performed and shown with a discussion of the spotted differences. The average percentage differences between the EFD and CFD data for the whole speed range are 1.84, 6.87 and 6.94 for the resistance, dynamic trim, and sinkage, respectively. These results confirm the maturity of the standardized and automated CFD modeling for calm water hydrodynamic analysis included in LincoSim, even at very high Froude numbers. The wetted length of the keel and chine and the wetted surface are calculated from numerical data using the advanced post-processing. Finally, as a work in progress, we test a first comparison for the same hull of the EFD and CFD data, considering two seakeeping conditions for head waves at a given wavelength for two velocity conditions. Also, this kind of analysis confirms the tight correlation between the measured and computed outcomes. This synergic interplay of EFD and CFD can link the advantages of both methods to support hull design but also requires experiment planning and final data analysis to obtain physical parameters not easily measurable in laboratory, such as the wetted surface, wetted lengths, proper viscous contribution, and pressure distribution both in calm water and in waves.

Efficiency and sustainability: Evaluating and optimizing energy use and environmental impact in cucumber production

This study assesses the energy-economic-environmental aspects of cucumber production in the face of environmental issues and resource scarcity, which threaten global food security and demand sustainable agriculture solutions. Data were collected by questionnaire and analyzed for inputs from planting to harvesting. The results indicated that diesel fuel (37.41%) and nitrate fertilizer (37.22%) constitute the primary inputs. The energy ratio, energy efficiency and net energy gain were 0.43, 0.54 kgMJ−1 and -30,153.31 MJha−1, respectively. Input optimization by Data Envelopment Analysis (DEA) reduced the carbon footprint from 178.433 to 168.900 kg CO2 per ton, the abiotic depletion from 1228.291 to 964.305 MJ and the acidification from 0.838 to 0.749 kg SO2 eq. Also, the results of DEA showed that 52.5% and 35% of the units were fully efficient under Variable Return to Scale (VRS) and Constant Return to Scale (CRS) models, respectively, while the others were inefficient to varying degrees. The average of technical, pure technical and scale efficiencies were 92.88%, 97.64%, and 95.07%, respectively. The results of economic evaluation showed that production cost is 6058.84 $ha−1 with a benefit-cost ratio of 1.71. Based on the primary results, it is suggested to use precision agriculture techniques and the exploration of alternative energy sources, such as biofuel for machinery. Additionally, using slow-release fertilizers or organic substitutes can decrease nitrogen fertilizer dependency while maintaining crop yields and improve the sustainability in this production.

International Trauma Questionnaire and Posttraumatic Cognitions Inventory-9: validity evidence and measurement invariance of their Brazilian versions

BackgroundThe International Trauma Questionnaire (ITQ) is used to measure posttraumatic stress disorder (PTSD) and complex posttraumatic stress disorder (CPTSD) symptoms, and the Posttraumatic Cognitions Inventory-9 (PTCI-9) is used to measure posttraumatic cognitions. Both tools have been translated for use in Brazil. However, the psychometric properties of the Brazilian versions were not investigated, and no study has verified the invariance of these tools for many traumatic event types.ObjectiveThis study examined the validity, reliability, and measurement invariance of the Brazilian versions of the ITQ and the PTCI-9 for trauma type, gender, race, age group, education level, and geographical region.MethodsA total of 2,111 people (67.74% women) participated in an online survey. The scale models were tested via confirmatory factor analyses and measurement invariance through multigroup analyses. Pearson’s correlation analyses were used to examine the relationships between PTSD, CPTSD, posttraumatic cognitions, and depressive symptoms.ResultsExcept for the affective dysregulation factor, the reliabilities of the ITQ and PTCI-9 dimensions were adequate. Models with six correlated dimensions for the ITQ and three correlated dimensions for the PTCI-9 showed adequate fit to the data. The ITQ and PTCI-9 exhibited scalar invariance for gender, race, age group, education level, and geographical region. The ITQ also demonstrated full invariance for trauma type. The factors of both instruments were related to each other and to depressive symptoms, with higher effect sizes for posttraumatic cognitions and complex posttraumatic stress disorder symptoms.ConclusionWe recommend using the Brazilian versions of the ITQ and PTCI-9, which are crucial tools for assessing and treating trauma-related disorders.

Evaluation Of The Accuracy Of The Generated Wave Fields In The Coastal & Ocean Basin (Cob)

The Coastal & Ocean Basin (COB) wave tank facility is located in the Flanders Maritime Laboratory at the Ostend Science Park, Belgium. The COB and its associated testing services are designed (Troch et al. 2016) to facilitate the needs of the offshore renewable energy sector, coastal and offshore engineering community and offer the opportunity to academia, companies and government agencies, to test scale models under combined action of waves and currents in any relative direction, to develop innovative designs. The exploitation is managed by the consortium Ghent University, KU Leuven and Flanders Hydraulics. The COB is operational since March 2023 and has since then successfully completed its first projects on wave energy converters (WECFarm), wave diffraction study around a monopile (PhairywinD) and floating offshore photovoltaic islands (MarineSpots).

Effects of mimicking manure removal strategies on ammonia and greenhouse gas emissions in sow pen scale models

With growing concerns about air pollution and global warming effects, the emissions of NH3 and greenhouse gases (GHGs) have become significant issues in the pig production industry. In order to discover whether optimizing manure removal strategies could alter the manure decomposition process and benefit the reduction of gas emissions, a scale model approach was used to quantify the gas emissions under controlled conditions. This study compared the gas emission reduction potential of two classic manure removal systems (scraper and pull-plug system) in three manure removal strategies: scraper-I (retaining manure for 24 h), scraper-II (retaining manure for 8 and 16 h) and pull-plug (retaining manure for 44 days). Fresh urine and faeces collected from a gestation sow house were applied to the scale models and then removed through the manure removal systems. The concentrations of gases (NH3, CH4, CO2, and N2O) within the scale model and removed slurry samples were collected and analysed (pH, electric conductivity, dry matter, total nitrogen, total ammonium nitrogen and total carbon). The results showed that emissions of CH4, CO2, and N2O from scraper-I were on average 54%, 56% and 25% lower than those from scraper-II, and 71%, 67% and 6% lower than those from pull-plug treatment, respectively. The GHGs emission rates (as CO2-equivalents) of scraper-I and scraper-II were 52% and 26.3% lower than that of pull-plug treatment respectively (P < 0.01). The emissions of NH3 displayed a temporary peak during each application of urine and removal of manure. In pull-plug treatment, the concentrations of NH3, CH4, and CO2 exponentially increased between Day 39 and Day 41. The nitrogen content, both total nitrogen and total ammonium nitrogen, within the slurry under the scraper system exhibited lower values compared to those from the pull-plug system. Conversely, the total carbon content was higher in the former system. Caution is warranted in extrapolating results to full-scale pig housing, given study limitations (e.g. small scale, mimicked scraper activity, no animals, etc.). Nevertheless, the conclusions and findings of this study provide fundamental data for understanding gas emissions from pig house manure management. This insight can guide the design and daily operations of low-emission manure removal systems in gestation sow houses.

Development of mobile CAT for patient feedback on pediatric consultations based on Rasch analysis of online techniques.

The Rasch Rating Scale Model (RSM) is widely used in questionnaire analysis, providing insights into how individuals respond to item-level stimuli. Existing software for Rasch RSM parameter estimation, while powerful, often presents a steep learning curve. An accessible online tool can greatly benefit novice users, particularly students and clinicians, by simplifying the analytical process. This study introduces an online tool, an intuitive online RSM analysis tool designed to facilitate questionnaire data analysis for applied researchers, students, and clinicians. The online tool employs the joint maximum likelihood method for estimation, yielding estimates, standard errors (SE), and fit statistics iteratively. A unique feature of the tool is its ability to visualize estimates on Google Maps with an opacity setting of 0, enhancing data interpretation through a user-friendly interface. This study outlines the estimation process and key features, employing data from 200 proxy participants who answered 20 5-point questions regarding doctor-patient and doctor-family interactions in pediatric consultations. Mobile computerized adaptive testing (CAT) was employed. The online tool offers 5 essential visual displays often utilized in Rasch analyses, including the Wright Map, KIDMAP, category probability curve, performance plot, and differential item functioning (DIF) graph. DIF analysis revealed that 2 items, concerning the doctor attentiveness and empathy toward the child illness, exhibited differences in female proxy participants' responses, indicating lower satisfaction with pediatricians. The online tool emerges as a user-friendly and efficient RSM analysis tool with notable advantages for newcomers, improving data visualization and comprehension. Its capacity to pinpoint key areas of concern, such as gender-related satisfaction disparities among proxy participants, enhances its utility in questionnaire analysis. The online tool holds promise as a valuable resource for researchers, students, and clinicians seeking accessible Rasch analysis solutions.

Physical Modelling Of Propeller Jet Induced Scour Near Quay Walls

Ship propellers cause high flow velocities near quay walls, jetties, locks and other hydraulic structures which can lead to scour of the bed near these structures and potentially result in instabilities of the construction. Bed protection is commonly applied as a measure to prevent damage and increase the life span of such hydraulic structures. When designing bed protection, the existing guidelines e.g. (PIANC 2015, BAW 2010) may not always result in optimal designs due to simplifications made in jet-flow schematizations and uncertainty of propeller-induced loads. To improve these design guidelines and optimize bed protection, a working group led by CROW and the Dutch Government was formed, and a joint research programme was initiated aiming at developing knowledge on propeller jet-induced scour by combining field measurements (Tukker 2021), scale model tests (Deltares 2023), and numerical modelling. The objective of the presentation during the Coastlab24 conference is to provide an overview of the various measurement techniques applied in the present research.

Routing optimisation for towing a floating offshore wind turbine under weather constraints

This paper presents a methodology for optimising routing for towing of fully assembled Floating Offshore Wind Turbines using a purpose-built ship simulator to generate datasets describing dynamics for a towing arrangement together with the engine data of the ship, and using such dataset and historical metocean data to perform multi-objective route optimisation for the tow using NSGA-II evolutionary algorithm. The work introduces the new ship simulator and the modelling of the platform VolturnUS-S, including the discussion of a comparative experiment between the model in the ship simulator and a 1:70 scale model in a wave tank. This is then followed by a presentation of the towing experiments, the characteristics of the data obtained from them, and the methodology for the optimisation of the towing routes with the following minimisation objectives: the duration of the tow, the maximum tension in the towing line, and the carbon emissions. Results are presented and discussed together with the limitations. The methodology has the potential to offer rapid and accurate results, providing a framework for safe, fast, and economical experimental process that could enhance visibility for operations before high maturity level is achieved or they can be physically performed, and contribute to improve marine operations.

Accuracy analysis of hydrogen leakage scale modeling based on similarity theory

The scale modeling is widely used in the study of hydrogen leakage diffusion, however the similarity between the hydrogen leakage scale modeling and the full-scale model remains incomplete. This article established a full-scale and a 1/5th scale model and verify the accuracy relationship between the two models. Firstly, by comparing the full-scale model with only changing the size simulation, it was found that the accuracy of the two models was poor. However, after using the similarity theory to change the initial leakage conditions, the overall overlap between the full-scale and the scale modeling was improved apparently. Under the initial conditions of this study, the combustible cloud maps of the two models that only changed in size exhibit poor coincidence. The results show that the equivalent performance of a scale modeling instead of a full-scale model can be greatly improved by using the similarity theory. The findings of this study can provide a valuable reference for experimental results based on the scale models to the full-scale models.

Turning The Tide: Live-Bed Scale Experiments Of Bar-Dominated Estuaries And Effects Of Dredging On Intertidal Habitat

Many large sand-dominated estuaries and tidal basins have complex channel and bar patterns, wherein a continuous deep channel suitable for shipping is rarely naturally present, which requires dredging. The intertidal area has important, often protected habitats for macro-benthic species, wader birds and other species. The question is to what degree channel and shoal dimensions and the amount of intertidal area are affected by dredging and disposal for access to ports. While numerical modelling is conducted for these systems with some success, complementary scale experiments with live beds have challenged the fields of coastal engineering and coastal morphodynamics for over a century. Compared to scale models for rivers, the scale issues in tidal experiments are more complicated and very few attempts have been pursued. For example, Reynolds (1889) conducted the first scale experiments of an estuary by a periodic sea level fluctuation, but found that even fine sand was hard to mobilize, while the bed surface was dominated by ripples rather than bars. Similarly, Tambroni et al. (2005) carefully scaled sediment mobility in a converging channel and obtained large-scale morphological patterns with gentle bars nearly overwhelmed by ripples. Stefanon et al. (2010) present a careful attempt at erosive tidal channel network development in a scale model with low-density sediment, which showed unexplained, over-large scour holes at channel junctions. The key issues for tidal experiments are to obtain sufficient sediment mobility (expressed as Shields or Rouse number) and to avoid over-large ripples and scours, and to this end classic river scale modelling is inadequate. Here we assess whether our recent innovation solves these scale issues. The objective of this abstract is to elucidate the scaling of experiments that enable study of morphodynamic estuaries in many aspects including effects of sediment management by dredging.

Turbulence modeling of stratified turbulence using a constrained artificial neural network

For large eddy simulations (LES) of stratified turbulence in the strongly stratified regime, an artificial neural network (ANN) with five hidden layers is used to construct a sub-grid scale (SGS) model. The ANN is assessed by comparing it to the Smagorinsky model, the dynamic Smagorinsky model, the gradient model, and filtered direct numerical simulation data. In the a priori test, the SGS model using ANN performed better than the Smagorinsky model and the gradient model in terms of the correlation coefficient and relative error of the energy transfer rate. However, the ANN does not provide sufficient energy dissipation when it is applied to LES with a larger filter width because it overpredicts backscatter. To address this problem, we also trained a constrained ANN using a custom loss function that penalizes excessive backscatter. It is shown that the constrained ANN successfully predicts less backscatter, maintaining the high correlation coefficient without ad hoc clipping. These results show that ANN is a promising tool for realizing a highly accurate and stable SGS model for stratified turbulence.

Analysis of the shear-driven flow in a scale model of a phase separator: Validation of a coupled CFD approach using experimental data from a physical model

The effects of shear stress at the interface between a flowing gaseous phase and a liquid-filled cavity, a scenario commonly found in flue gas/slag phase separators are investigated in this study. This effect is frequently disregarded in computational fluid dynamics (CFD) simulations within metallurgy, primarily due to its limited influence on the motion of liquids (e.g., slag, liquid metal) when compared to other factors such as stirring by natural convection or bubbling. This study was undertaken to investigate shear-driven flow in a 1:4 scale model of a phase separator in which a flue gas stream coming from a furnace is mobilizing the flow of a slag melt. To cover a wide range of operating conditions, silicone oil with varying viscosities (20, 50, and 70 cSt) was considered for mimicking viscous slag. Additionally, different volumetric airflow rates (18, 27, and 36 m3/h) were considered to simulate the flue gas flow. Particle image velocimetry (PIV) measurements were conducted on the model. The experimental results were utilized to validate computationally efficient, coupled steady-state simulations of the system. Notably, the steady-state simulations, requiring approximately one hour of CPU time, demonstrated a computation time decrease of two magnitudes compared to conventional Volume of Fluid (VOF) modeling. A stable, laminar flow pattern of the liquid phase with surface velocities of up to approximately 30 mm/s was observed for the case with the lowest oil viscosity and the highest airflow rate, while a steady, turbulent flow was observed in the gas phase. Conversely, the lowest surface velocities, measuring around 5 mm/s, were recorded and calculated for the scenario with the highest oil viscosity and the lowest airflow rate. It was noted that velocities increased proportionally with the airflow rate but exhibited a disproportionate relationship with oil viscosity. The prediction of velocity magnitudes by the steady-state CFD model was highly accurate, with only minor discrepancies observed between the measured and calculated flow patterns. In summary, valuable insights into the often-overlooked shear stress effects at the phase boundary in gaseous-liquid flow over a cavity are provided by our study.

Estimating nonlinear wind-induced response of roof cable nets by aeroelastic experiments and ML modeling

The paper examines the structural engineering challenges related to the assessment of the wind-induced vertical displacements of lightweight, hyperbolic-paraboloid cable-supported membrane roofs. Analysis and comparisons are conducted using three distinct methods for calculating the roof vertical, out-of-plane displacements. Finite element method (FEM) analysis is employed using: (i) estimated static nodal forces obtained from wind pressure coefficients determined by aerodynamic wind tunnel tests on a rigid building model, and (ii) loads found from wind pressure coefficients, estimated through machine learning (ML) methods, and (iii) measured roof response found from aeroelastic wind tunnel tests on a flexible model. The study examines three different roof geometries (square, rectangular and circular) and two distinct membrane curvatures for each geometry. Furthermore, wind directionality (three mean-wind incidence angles) and Reynolds number effects (seven mean wind velocities) are studied. Comparisons show that the non-linear FEM analysis, based on estimated static wind loads, underestimates the roof displacements at the roof center, compared to the direct measurements on the aeroelastic model. The main contribution of the study consists of a novel application of ML models, and Artificial Neural Networks (ANNs) in particular, which are employed to correct roof displacement estimations, found by simplified aerodynamic test pressure measurements on rigid roof models. The goal is to better describe the complex fluid-structure interaction of the roof membranes, which can only be achieved by direct aeroelastic tests that are difficult to design and execute. Finally, the study demonstrates that ANNs can be used not only for the preliminary design of the full-scale structure but also for construction of wind tunnel scale models.