Simulation Methodology Research Articles

Influence of Simulation and Interactivity on Human Perceptions of a Robot During Navigation Tasks

In Human-Robot Interaction, researchers typically utilize in-person studies to collect subjective perceptions of a robot. In addition, videos of interactions and interactive simulations (where participants control an avatar that interacts with a robot in a virtual world) have been used to quickly collect human feedback at scale. How would human perceptions of robots compare between these methodologies? To investigate this question, we conducted a 2x2 between-subjects study (N=160), which evaluated the effect of the interaction environment (Real vs. Simulated environment) and participants’ interactivity during human-robot encounters (Interactive participation vs. Video observations) on perceptions about a robot (competence, discomfort, social presentation, and social information processing) for the task of navigating in concert with people. We also studied participants’ workload across the experimental conditions. Our results revealed a significant difference in the perceptions of the robot between the real environment and the simulated environment. Furthermore, our results showed differences in human perceptions when people watched a video of an encounter versus taking part in the encounter. Finally, we found that simulated interactions and videos of the simulated encounter resulted in a higher workload than real-world encounters and videos thereof. Our results suggest that findings from video and simulation methodologies may not always translate to real-world human-robot interactions. In order to allow practitioners to leverage learnings from this study and future researchers to expand our knowledge in this area, we provide guidelines for weighing the tradeoffs between different methodologies.

The application and algorithm of fabric simulation in game industry

fabric simulation has emerged as a crucial aspect of computer graphics, particularly in applications such as film production, video games, and design. This paper provides a comprehensive review of fabric simulation methodologies, implementation techniques, and its diverse applications within the game industry. The fabric simulation algorithms are broken down into Fabric Modeling, Dynamic Simulation, and Collision Handling. The three common modeling strategies of Elasticity-Based Models, Particle-Based Models, and Mass-Spring Damper Models, are discussed in detail. Additionally, dynamic simulation strategies such as Position-Based Dynamics (PBD) and Extended Position-Based Dynamics (XPBD) are explored for their role in real-time simulations, particularly in the game industry. The paper also delves into collision handling algorithms, exploring the strategies for accurate collision detection and response. The application of fabric simulation in the game industry is highlighted, showcasing how it enhances realism and immersion by simulating fabric movement and interactions with the environment. The paper introduced various fabric simulation tools and systems within popular game engines like Unity 3D and Unreal Engine 5. Furthermore, optimization strategies, such as view-dependent adaptive simulation, are discussed to improve performance providing insight for future work.

The application and algorithm of fabric simulation in game industry

fabric simulation has emerged as a crucial aspect of computer graphics, particularly in applications such as film production, video games, and design. This paper provides a comprehensive review of fabric simulation methodologies, implementation techniques, and its diverse applications within the game industry. The fabric simulation algorithms are broken down into Fabric Modeling, Dynamic Simulation, and Collision Handling. The three common modeling strategies of Elasticity-Based Models, Particle-Based Models, and Mass-Spring Damper Models, are discussed in detail. Additionally, dynamic simulation strategies such as Position-Based Dynamics (PBD) and Extended Position-Based Dynamics (XPBD) are explored for their role in real-time simulations, particularly in the game industry. The paper also delves into collision handling algorithms, exploring the strategies for accurate collision detection and response. The application of fabric simulation in the game industry is highlighted, showcasing how it enhances realism and immersion by simulating fabric movement and interactions with the environment. The paper introduced various fabric simulation tools and systems within popular game engines like Unity 3D and Unreal Engine 5. Furthermore, optimization strategies, such as view-dependent adaptive simulation, are discussed to improve performance providing insight for future work.

Comparison of modelling methodologies for large porous absorbers hanging in a volume

Porous material simulation methodologies are well established. However, most methods, like the Transfer-Matrix Method (TMM) make the assumption that there is a source side and a receiver side. In practice, this works for the majority of industrial noise control treatments. For architectural applications, this is not always the case. Hanging absorbers and curtains are common materials that add absorption to a space, but do not have a boundary condition at a wall or a well-defined source and receiver side. To evaluate the validity of existing simulation methods for this condition, a reverb room test was simulated with a large cube of melamine foam inside the volume. The effective absorption of the cube in the space was then calculated using various simulation methodologies, and compared to results from a measured reverb room absorption test.

An efficient procedure for the blood flow computer simulation of patient-specific aortic dissections

In this work we present a novel methodology for the numerical simulation of patient-specific aortic dissections. Our proposal, which targets the seamless virtual prototyping of customized scenarios, combines an innovative two-step segmentation procedure with a CutFEM technique capable of dealing with thin-walled bodies such as the intimal flap. First, we generate the fluid mesh from the outer aortic wall disregarding the intimal flap, similarly to what would be done in a healthy aorta. Second, we create a surface mesh from the approximate midline of the intimal flap. This approach allows us to decouple the segmentation of the fluid volume from that of the intimal flap, thereby bypassing the need to create a volumetric mesh around a thin-walled body, an operation widely known to be complex and error-prone. Once the two meshes are obtained, the original configuration of the dissection into true and false lumen is recovered by embedding the surface mesh into the volumetric one and calculating a level set function that implicitly represents the intimal flap in terms of the volumetric mesh entities. We then leverage the capabilities of unfitted mesh methods, specifically relying on a CutFEM technique tailored for thin-walled bodies, to impose the wall boundary conditions over the embedded intimal flap. We tested the method by simulating the flow in four patient-specific aortic dissections, all involving intricate geometrical patterns. In all cases, the preprocess is greatly simplified with no impact on the computational times. Additionally, the obtained results are consistent with clinical evidence and previous research.

CALPAGAN: Calorimetry for Particles Using Generative Adversarial Networks

Abstract In this study, a novel approach is demonstrated for converting calorimeter images from fast simulations to those akin to comprehensive full simulations, utilizing conditional Generative Adversarial Networks (GANs). The concept of Pix2pix is tailored for CALPAGAN, where images from fast simulations serve as the basis (condition) for generating outputs that closely resemble those from detailed simulations. The findings indicate a strong correlation between the generated images and those from full simulations, especially in terms of key observables like jet transverse momentum distribution, jet mass, jet subjettiness, and jet girth. Additionally, the paper explores the efficacy of this method and its intrinsic limitations. This research marks a significant step towards exploring more efficient simulation methodologies in high-energy particle physics.

Effect of Carbon on Void Nucleation in Iron.

The study reports the significance of carbon presence in affecting void nucleation in Fe. Without carbon, void nucleation rates decrease gradually at high temperatures but remain significantly high and almost saturated at low temperatures. With carbon present, even at 1 atomic parts per million, void nucleation rates show a low-temperature cutoff. With higher carbon levels, the nucleation temperature window becomes narrower, the maximum nucleation rate becomes lower, and the temperature of maximum void nucleation shifts to a higher temperature. Fundamentally, this is caused by the change in effective vacancy diffusivity due to the formation of carbon-vacancy complexes. The high sensitivity of void nucleation to carbon comes from the high sensitivity of void nucleation to the vacancy arrival rate in a void. The void nucleation is calculated by first obtaining the effective vacancy diffusivity considering the carbon effect, then calculating the defect concentration and defect flux change considering both carbon effects and pre-existing dislocations, and finally calculating the void nucleation rate based on the recently corrected homogeneous void nucleation theory. The study is important not only in the fundamental understanding of impurity effects in ion/neutron irradiation but also in alloy engineering for judiciously introducing impurities to increase swelling resistance, as well as in the development of simulation and modeling methodologies applicable to other metals.

Physics-based discrete models for magneto-mechanical metamaterials

Magneto-mechanical metamaterials are emerging smart materials whose mechanical responses can be tailored through structure architecture and magnetic interactions. The latter provides additional freedom in the material design space and leads to novel behaviors due to its nonlocal nature. The enriched functionalities open new possibilities in various applications, such as actuators, energy absorbers, and soft robots. However, the nonlinear and nonlocal coupling between elastic and magnetic forces poses a great challenge in the modeling and simulation of these systems, further hindering theory-based rational design strategies. Here, we focus on a class of magneto-mechanical metamaterials comprising elastic solids embedded with rigid permanent magnets. The clear separation between elastic and magnetic forces simplifies the design and fabrication process, yet their nonlocal interplay still allows for complex behaviors. We present a simulation framework for such magneto-mechanical metamaterials by combining a lattice spring model for the elastic solid with the dipole model for the magnetic interactions and implementing it in the LAMMPS molecular dynamics software. We demonstrate the capabilities of our framework by simulating a few representative structures, including shape-locking lattice metamaterials, a soft cellular solid with controllable buckling, and a metamaterial chain with phase-transforming behavior. For the shape-locking lattice metamaterials, we successfully capture the magnetic-actuation-driven reconfiguration and the nonlinear mechanical response of the curved lattices. For the soft cellular solid, we identify its buckling patterns under external non-uniform magnetic fields and simulate a buckling evolution process consistent with experiments. For the metamaterial chain, we include the strong long-range interactions among the embedded magnets and reproduce the controllable phase transitions in the experiments. Our work provides a simple yet versatile simulation methodology to investigate the nonlinear mechanical behaviors in the presence of strong external and internal magnetic forces, which will facilitate the design and analysis of magneto-mechanical materials. It can also be applied to other magnetically-driven smart structures, such as soft robots.

Stress Concentration Modelling on Resistance Spot Welding Lap Joint of Steel ASS316L and Titanium Ti-6Al-4V with Variable Weld Geometries

This research is a finite element simulation on resistance spot welding (RSW) process between dissimilar sheet metals consist of Titanium alloy, Ti-6Al-4V and Austenitic Stainless Steel (ASS) 316L. The problem statement was inability to visualize the stress concentration profile over weld nugget joint when Titanium alloy and steel welded with variable electrode geometry of circle, triangle, square and hexagon. To determine the best geometry for best weld with lowest maximum stress concentration. The methodology of simulation was tensile-shear test using SOLIDWORKS software. The tensile-stress load of 664.09 N was applied across all 4 different weld geometries. The result for the lowest magnitude of maximum stress 180.6 MPa was on circle weld geometry. Triangle geometry registered highest stress concentration of 219.6 MPa. This proves that most common weld geometry used in industry was circle. Even for dissimilar material joint the result supports that circle weld geometry as the best geometry. Keywords: Resistance spot welding (RSW), stress concentration, weld nugget, weld geometry.

Scaling effects on peak wind load estimation for low-rise buildings: An experimental and analytical study

Though scaling effects on estimation of peak wind loads are extensively documented in the literature, there is a lack of systematic comparison of such scaling effects across different model scales tested in wind tunnels. Moreover, the limited studies on large-scale physical models accepted the inadequacy of simulating the large turbulent eddies rather than addressing the missing low-frequency turbulence simulation inherent in such large-scale testing. This study provides an in-depth comparison of estimates of peak wind loads obtained using a range of experimental scaled models (1:100 and 1:6 model scales) of the Wind Engineering Research Field Laboratory (WERFL) building while applying a Partial Turbulence Simulation (PTS) methodology to incorporate the effects of turbulence. Large-scale wind tunnel testing of structures provides the advantage of achieving an improved Reynolds number (Re) similarity, more accurate geometric similarity, and enhanced resolution of flow details such as corner vortices, than is possible with the use of smaller model scales. However, as the model scale increases, achieving turbulence similarity becomes challenging due to limitations in simulating the low-frequency turbulent eddies in the wind tunnel. The PTS method has been used in the recent past to account for the low-frequency turbulence effects in the peak wind load estimation. The method is referred to as 1DPTS when considering longitudinal turbulence components only and 2DPTS when considering both longitudinal and lateral turbulence components in the analysis. The computationally intensive 2DPTS can be further simplified by using a weighted average method as described in this paper as “weighted average PTS.” The current study explores the effect of scaling on peak wind load estimation by using the 1DPTS, 2DPTS, and weighted average PTS methods. Results from the multi-scale experimental tests demonstrate that using larger model scales and compensating for the low-frequency turbulence deficit in the post-test analysis significantly improve the agreement with the prototype data owing to the simulation of a higher Reynolds number. Furthermore, comparing the results of the proposed weighted average method with full-scale data reveals its potential as a substitute for the original 2DPTS method, offering enhanced accuracy, particularly at the roof corner for oblique wind directions. While the effects of Re are well known, the findings of this study explore its impact in conjunction with the application of the PTS methods on peak Cp estimation across five different model scales with Re ranging from 3.65 × 104 to 2.43 × 106, the latter being closest to the full-scale (field) Re. The findings provide new insights into how large-scale physical model testing in high Re flows, supported by analytical PTS-based compensation, can enhance the accuracy of peak wind load estimations for critical scenarios including cornering winds that generate conical vortices.

Pharmaceutical care for patients with headaches: pharmacists' statements and pharmacy practice

Relevance. According to the World Health Organization, headaches are one of the most common symptoms of nervous system diseases. Pharmacists play an important role in communicating with headache patients, as well as in rationally directing self-treatment.Aim. Using the questionnaire and patient’s simulation method, comparing the results of these studies, to evaluate the quality of pharmaceutical care for patients with headaches.Material and methods. An anonymous survey was conducted among 153 pharmacists. Three different trained simulated patients (SP) allegedly suffering from headaches visited 101 pharmacies. The results were recorded visually and on a voice recorder. The commercial segment of the Russian pharmaceutical market for analgesics was analyzed.Results. The leaders in sales in ATC-subgroups were the following INN: Ibuprofen, Paracetamol+Naproxen+Caffeine+Drotaverine+ Pheniramine. Corresponding trade names are most often recommended based on the results of questionnaires and simulated patient methodology (SPM). Prescription drugs (13.1 %/14.9 % in SPM) that shouldn’t be recommended in the pharmacy and combination drugs (87.6 %/91.1 % in SPM) were frequently mentioned. A similar number of INN (20/23) and trade names (52/53) were named. The average number of trade names recommended by one pharmacist was higher in the SPM. In SPM the patient was asked very few questions and almost no information about the drug was specified.Conclusion. The real involvement of pharmacists in the provision of pharmaceutical care to patients with cephalgia appears to be much lower, in contrast to the stated results of the questionnaire. In real pharmacy practice, the approach to interaction with a patient with headache and counselling is formal and requires standardization: the development of protocols, standards and algorithms for interaction with patients with headache based on clinical guidelines.

Improvement of linearity in trap-rich substrates for radio frequency applications: Which of donor and acceptor trap is the best?

This paper investigates the effect of volume traps intentionally introduced into a silicon-on-insulator (SOI) substrate by inserting a layer of polysilicon beneath buried oxide. In radio frequency applications, this type of substrate, referred to as trap-rich, is known to considerably reduce the generation of harmonics resulting from the parasitic non-linear charge dynamics introduced by the substrate handler under the buried oxide. This analysis focuses on a test vehicle in the form of an integrated coplanar waveguide on two types of substrates, namely, high-resistivity SOI substrates with and without a trap-rich layer. From a modeling point of view, a simulation methodology is implemented in order to convert the 3D simulation of the coplanar waveguide into a 2D treatment that takes into account the wave propagation effect associated with the distributed nature of the transmission line. As a first step, this modeling strategy is implemented to reproduce the effect of increasing substrate resistivity on 2nd and 3rd harmonic reductions, leading to an excellent agreement with experimental data. Building on this validation of the simulation method, we have opted to simulate the non-linear response of the transmission line on the SOI trap-rich substrate by simplifying the trap distribution model. To avoid the adoption of unverified and strongly process-dependent trap distributions across the bandgap, a midgap monovalent trap density has been introduced, either acceptor or donor density. A monovalent density of acceptor traps with a concentration of 1016 cm−3 and a carrier lifetime of 0.1 ns has been shown to reproduce the experimental data very accurately with a substantial reduction in 2nd and 3rd harmonics. A detailed analysis of the displacement current waveforms explains the beneficial role of acceptor traps compared with donor traps.

IMMISCIBLE VISCOUS FINGERING MODELING OF TERTIARY POLYMER FLOODING BASED ON REAL CASE OF HEAVY OIL RESERVOIR MODEL

In immiscible displacements, lower viscosity injected fluids with higher mobility than crude oil can create viscous fingers, affecting displacement efficiency. The Buckley–Leverett approach for relative permeabilities (kr) may not represent accurately 2D features like increased water saturation in viscous fingering. Based on the physics issue, this work applies Sorbie's 4-Steps methodology to a 3D simulation of an offshore heavy oil reservoir focusing on waterflooding and tertiary polymer flooding, assessing their impact on oil production forecasts. It also explores the application of this methodology to coarse grid simulation models, employing pseudo kr functions by data assimilation. During tertiary polymer injection, two processes were identified in oil displacement: viscous crossflow mechanism and oil bank mobilization by a second finger. This combination resulted in earlier and increased oil production. For both strategies, refining the grid increased simulation runtime from minutes to days compared to coarse grids, making it impractical for intensive processes. From data assimilation, the best solution with matched field indicators reduced runtime from days to minutes. This study expanded the 4-Steps methodology for 3D reservoir simulation, proposing kr as uncertainties. Data assimilation enhances the methodology, generating pseudo kr for coarser grid simulations, reducing computational costs, and capturing small-scale phenomena.

Bio-based connections and hybrid planar truss: A parallel genetic algorithm approach for model updating

Bolted steel to laminated bio-based material connections experience significant performance challenges due to the nonlinear response and high stress concentrations at their joints. This paper introduces an innovative 3D plasticity-fracture continuum Finite Element (FE) model that significantly advances the simulation of such truss joints by integrating Hill's yielding criteria with an element removal methodology for fracture simulation. This novel approach captures both plastic and fracture behaviors simultaneously, a capability not sufficiently addressed in existing models. We detail the theoretical framework for these models, including the derivation of constitutive equations and the algorithms necessary for their implementation in ABAQUS. Additionally, it is provided a low-fidelity modeling of truss joints, offering a comprehensive analysis of connector elements, joint models, and parametric modeling via Python scripting. The model's efficacy is demonstrated through identification of connection and of hybrid planar trusses under cyclic loading, which validates the practical applicability of the method. To optimize computational efficiency, we developed a Parallel Genetic Algorithm (PGA) that integrates seamlessly with ABAQUS and Python to facilitate parameter calibration. This integration not only enhances the model's accuracy but also reduces computational load, making it feasible for complex engineering applications. Our findings illustrate a significant improvement in modeling accuracy and efficiency, establishing a robust methodology for analyzing truss joints in bio-based construction materials.

Energy optimization of a steel slab reheating furnace through the use of swirl and diffusion burners using a new mathematical simulation methodology

This study proposed a new methodology to optimize the fuel use in a walking beam reheating furnace that uses swirl burners in the soaking zone through mathematical simulation. Likewise, the radiative effect of the WSGGM model over the heating and thermal gradient of the slab was analyzed, as well as its thermal implications of using swirl and diffusion burners. The model was validated with experimental temperatures obtained inside the furnace by using 16 thermocouples, and they were compared with those in the simulation, reaching an average error of 3.19%. This methodology has allowed the proposal of new operating conditions in fuel management, making the combustion process more efficient with an average saving of 5,067,360 kg of methane annually, representing 9% of the plant’s current use. This optimization process would mean substantial economic savings for the industry and would also be reflected in a significant decrease of greenhouse gases with adverse effects on the planet.

Improving tension fatigue performance of gray cast iron by LSPwC-induced gradient structure and carbon diffusion

HT250 Gray cast iron (GCI) commonly utilized in diesel engine cylinders, is susceptible to fatigue failure under alternating stress conditions. To address this issue, the investigation involved the application of laser shock peening without coating (LSPwC) on HT250 GCI to assess its impact on the high cycle tension fatigue properties of the material. Both experimental and simulation methodologies were employed to analyze the effects of LSPwC on residual stress, microhardness, and microstructure in HT250 GCI. The LSPwC resulted in a substantial 29% enhancement in the high cycle tension fatigue limit of the HT250 GCI, which is attributed to a synergistic combination of factors induced by LSPwC, including high-amplitude compressive residual stresses, elevated microhardness, grain refinement, and carbon diffusion. This study contributes valuable insights into the reinforcement of complex cast components.

Uncertainty-Based Validation Methodology and Experimental Analysis for External Control Room Human Performance Simulation: Application to Fire Probabilistic Risk Assessment of Nuclear Power Plants

In probabilistic risk assessment (PRA) of nuclear power plants (NPPs), human reliability analysis (HRA) is conducted to identify potential human failure events that could contribute to risk scenarios and estimate human error probabilities. Lessons learned from the 2011 Fukushima Daiichi NPP accident underscored that for PRA, it is critical to model external control room (Ex-CR) human actions. The state-of-practice HRA methods, historically developed for the main control room HRA, are limited in capturing the unique nature of Ex-CR human actions, such as location dependence (in addition to the time dependence) of human actions and spatiotemporal interactions of human performance with the surrounding physical environments, for instance, hazard propagation. To advance the Ex-CR HRA in the context of the fire PRA for NPPs, the authors’ team developed a simulation-based fire crew performance model using an agent-based modeling (ABM) technique. The ABM fire crew simulation was coupled with a fire progression model through a spatiotemporal interface using a geographic information system. This paper focuses on the validation of the ABM simulation, which is the key requirement for the simulation-based Ex-CR human performance model to be utilized in PRA. The existing validation approach, initially developed for physical models in the fire PRA of NPPs, is extended for validation of the simulation-based Ex-CR human performance model. Model uncertainty is used as a measure of model validity, which facilitates the incorporation of the validation result into the PRA. The degree of the model uncertainty is characterized by a lognormal error model whose parameters are quantified based on a pairwise comparison between empirical data and model predictions. The proposed validation approach is demonstrated using a case study of the fire PRA of NPPs. This study makes two research contributions: (1) it is the first to validate the simulation-based Ex-CR human performance model against empirical human performance data and incorporate the validation result into the PRA of NPPs, and (2) this study, for the first time, conducts a controlled experimental test to collect empirical data for fire crew performance at NPPs.

Real-time vacuum plume flow field reconstruction during lunar landings based on deep learning

In space missions, the vacuum plume generated by rocket engines can negatively impact spacecraft. Therefore, researching the vacuum plume is crucial to guarantee the regular operation of spacecraft. The conventional numerical simulation methodology, the direct simulation Monte Carlo (DSMC) method, is time-consuming and lacks real-time calculation capabilities. Recently, deep learning (DL) methods have emerged in the field of fluid dynamics. In this study, a DL model trained by a convolutional neural network with multiple decoders is introduced to predict the vacuum plume flow field during lunar landings. The network processes shape topology information and boundary conditions as inputs, yielding flow field data including velocity and pressure fields as outputs. Meanwhile, the flow field prediction results under different conditions and training methods are discussed. The results show that the predicted flow field under different lunar surface conditions is in accord with the DSMC results. The maximum mean and standard deviation errors of the data distribution of each flow field do not exceed 9.72% and 9.07%, respectively. Different training methods with flat and inclined lunar surfaces also have an impact on the prediction results. Compared with the DSMC method, the DL method exhibits higher efficiency with a speedup of about four orders of magnitude, indicating that the DL-based flow field reconstruction method has strong application prospects in the real-time computation of vacuum plume flow fields.

A dynamic Pre-Darcy model and its application in the numerical simulation of enhanced geothermal system

Numerical simulations of Enhanced Geothermal Systems (EGS) currently primarily depend on the Darcy model, neglecting pre-Darcy flow in the matrix rock and the impact of temperature on pre-Darcy flow. This paper introduces a dynamic pre-Darcy model that accounts for the influence of temperature, deriving from the capillary flow model and boundary layer theory. This model is able to consider how temperature variations affect both the thickness of the boundary layer and the yield stress of the fluid. The reliability of the dynamic pre-Darcy model is validated through experimental data, and comparison with both static pre-Darcy and Darcy models demonstrates its superior ability to accurately capture the influence of temperature on pre-Darcy flow. Subsequently, a thermal-hydraulic simulation methodology incorporating the dynamic pre-Darcy model is developed to characterize mass and heat transfer between the matrix and fracture based on the framework of the embedded discrete fracture model (EDFM), which is further validated with analytical and numerical solutions. In the simulation of single-fracture case, we explore the impact of the dynamic pre-Darcy flow on mass and heat transfer between the matrix and fracture. Field-scale numerical simulations for EGS further demonstrate that the Darcy model tends to overestimate both production temperature and total extracted energy. In contrast, the static pre-Darcy model generally underestimates these metrics. The dynamic pre-Darcy model, however, provides more accurate and reasonable predictions.

Synchronous high-speed measurements of a flexible structure under wind gust load

Simultaneously measuring the fluid flow around a flexible structure and the resulting deformations during short-term yet highly dynamic flow events is the focus of this fluid–structure interaction (FSI) study. These scenarios occur when a wind gust impacts a flexible structure, leading to extreme loads and significant deflections. To mimic such gusts, a specifically designed wind gust generator is used within a wind tunnel featuring an open test section. A high-speed particle-image velocimetry system records the flow field, while the digital-image correlation technique captures the structural deformations. That allows us to perform synchronized coupled fluid–structure measurements for a T-structure under wind gust load. The time-resolved measurements are repeated up to 104 times, allowing for phase-averaging of both the flow and the structural data, and to examine the convergence of the statistics. A comprehensive analysis of the instantaneous and phase-averaged data reveals that the flow field in the vicinity of the structure undergoes noticeable changes during the gust impact. The recirculation region behind the T-structures perceptibly increases when the gust hits the structure. A maximum deformation of about 10% of its height is observed during the highly dynamic gust event. Given (1) the availability of synchronously recorded data for both the fluid flow and the structure deformation, (2) the simplicity of the structure's geometry, and (3) the moderate Reynolds number of about 4×104, this case also serves as a well-suited benchmark test case for evaluating simulation methodologies for strongly coupled, highly dynamic FSI problems.