Properties Of Substructures Research Articles

Dynamic Behaviors of Composite-Laminated Concentrically Stiffened Rectangular Plates by Substructure Modal Synthesis

Existing numerical analysis methods often incur high computational costs when directly solving multi-degree-of-freedom systems due to computer capacity limitations. To address this issue, this paper took the composite laminated concentrically stiffened rectangular plate as the research object. The modal synthesis method was employed to reduce the degrees of freedom of the model, enabling the solution of complex dynamic characteristics. In the research process, the domain decomposition theory was used to divide the research object into plate and rib substructures. Based on the spectral Chebyshev method, the substructure dynamic model of the composite laminated rectangular plate was constructed. Subsequently, the function expressions of the complex load excitation on each substructure were derived, and the fixed modal synthesis method was introduced to construct the spectral Chebyshev reduced model of the substructures. According to the artificial spring theory equivalent, the interface force, and the whole reduction model of the composite laminated concentrically stiffened rectangular plate were obtained by assembling the substructure models. The time–domain and frequency–domain dynamic behaviors of composite laminated concentrically stiffened rectangular plates are yielded by solving the whole reduced model. The novelty of this work lies in combining the spectral Chebyshev method with the modal synthesis method. The established reduced model no longer depended on mesh quality and required fewer matrix dimensions and computation time compared to the whole model, while still achieving sufficiently accurate results. Additionally, based on the reduced model, an effective parametric study scheme was proposed to analyze the impact of dimensions and material properties of rib substructures on the dynamic behaviors of the composite laminated concentrically stiffened rectangular plate. These findings can be used to guide the optimal design of laminated concentrically stiffened rectangular plates in engineering practice.

A Knowledge-Driven Self-Supervised Approach for Molecular Generation.

Due to the great successes of Graph Neural Networks (GNN) in numerous fields, growing research interests have been devoted to applying GNN to molecular learning tasks. The molecule structure can be naturally represented as graphs where atoms and bonds refer to nodes and edges respectively. However, the atoms are not haphazardly stacked together but combined into various spatial geometries. Meanwhile, since chemical reactions mainly occur in substructures such as functional groups, the substructure plays a decisive role in the molecule's properties. Therefore, directly applying GNN to molecular representation learning could ignore the molecular spatial structure and the substructure properties which in turn degrades the performance of downstream tasks. In this paper, we propose Knowledge-Driven Self-Supervised Model for Molecular Representation Learning (KSMRL) to address above problems. The KSMRL consists of two major pathways: (1) the Spatial Information (SI) based pathway which preserves the spatial information of molecular structure, (2) the Subgraph Constraint (SC) based pathway which retains the properties of substructures into the molecular representation. In this manner, both the atomic level and substructure level information can be included in modeling. According to the experimental results on multiple datasets, the proposed KSMRL can generate discriminative molecular representations. In molecular generation tasks, KSMRL combined with Autoregressive Flow (AF) models or Discrete Flow (DF) models outperforms the state-of-the-art baselines over all datasets. In addition, we demonstrate the effectiveness of KSMRL with property optimization experiments. To indicate the ability of predicting specified potential Drug-Target Interactions (DTIs), a case study for discriminating the interactions between molecule generated by KSMRL and targets is also given.

AuriDESI: mock catalogues for the DESI Milky Way Survey

ABSTRACT The Dark Energy Spectroscopic Instrument Milky Way Survey (DESI MWS) will explore the assembly history of the Milky Way by characterizing remnants of ancient dwarf galaxy accretion events and improving constraints on the distribution of dark matter in the outer halo. We present mock catalogues that reproduce the selection criteria of MWS and the format of the final MWS data set. These catalogues can be used to test methods for quantifying the properties of stellar halo substructure and reconstructing the Milky Way’s accretion history with the MWS data, including the effects of halo-to-halo variance. The mock catalogues are based on a phase-space kernel expansion technique applied to star particles in the Auriga suite of six high-resolution lambda-cold dark matter magnetohydrodynamic zoom-in simulations. They include photometric properties (and associated errors) used in DESI target selection and the outputs of the MWS spectral analysis pipeline (radial velocity, metallicity, surface gravity, and temperature). They also include information from the underlying simulation, such as the total gravitational potential and information on the progenitors of accreted halo stars. We discuss how the subset of halo stars observable by MWS in these simulations corresponds to their true content and properties. These mock Milky Ways have rich accretion histories, resulting in a large number of substructures that span the whole stellar halo out to large distances and have substantial overlap in the space of orbital energy and angular momentum.

Synthesis of Defective Wheel‐Shaped Nanographdiynes

AbstractThe synthesis and optical properties of wheel‐shaped nanographdiynes that has lost some butadiyne spokes were reported. These defective wheel‐shaped nanographdiynes possess butadiyne‐bridged metacyclophanes with para‐bis(phenylbutadiynyl)‐benzene units as the axis. The optimized geometries of the defective wheel‐shaped nanographdiynes along with their vibrational spectra, HOMO and LUMO orbitals were calculated at B3LYP/6‐311G(d,p) level. HOMO and LUMO orbitals are delocalized mainly over the para‐bis(phenylbutadiynyl)‐benzene axis, with weak contribution from the attached ethynyl units. The π‐conjugation extension and quantity increase of the para axis influenced the optical properties of these graphdiyne substructures, leading to the change of bandgap from 2.88 eV to 2.56 eV as reflected by optical spectroscopy. The defective wheel‐shaped nanographdiynes lost the characteristic intensive sharp absorption peak at low energy region, which indicated that the fusion of adjacent dehydrobenzo [18] annulenes are crucial for the bulk properties of graphdiyne.

Mesoscale Modeling of Polymer Concrete Dynamic Properties.

There is a constant need to predict the dynamic properties of composite materials already at the design stage. A particularly attractive tool for achieving this goal is mesoscale finite element modeling. This paper presents the mesoscale modeling of the dynamic properties of polymer concrete. The method is based on finite element modeling and substructural identification. Substructural identification is a model updating technique based on frequency response functions. It enables the identification of model dynamic properties considering damping. The presented method is used to model the dynamic properties of a polymer concrete beam. In the first step, the mesoscale finite element model is built and then it is decoupled into substructures: a polymer matrix, aggregates, and an interfacial transition zone (ITZ). Next, the dynamic properties of the polymer matrix substructure are updated, and the model is reassembled. Then, second-stage updating takes place, which consists of determining the parameters of the aggregates and the ITZ. The use of substructural identification made it possible to determine the parameters of substructures that do not exist in an independent, isolated form like the ITZ. Moreover, it allows for determining the amount of damping that ITZ brings to the structure.

The effect of the perturber population on subhalo measurements in strong gravitational lenses

ABSTRACT Analyses of extended arcs in strong gravitational lensing images to date have constrained the properties of dark matter by measuring the parameters of one or two individual subhaloes. However, since such analyses are reliant on likelihood-based methods like Markov-chain Monte Carlo or nested sampling, they require various compromises to the realism of lensing models for the sake of computational tractability, such as ignoring the numerous other subhaloes and line-of-sight haloes in the system, assuming a particular form for the source model and requiring the noise to have a known likelihood function. Here, we show that a simulation-based inference method called truncated marginal neural ratio estimation (TMNRE) makes it possible to relax these requirements by training neural networks to directly compute marginal posteriors for subhalo parameters from lensing images. By performing a set of inference tasks on mock data, we verify the accuracy of TMNRE and show it can compute posteriors for subhalo parameters marginalized over populations of hundreds of substructures, as well as lens and source uncertainties. We also find that the multilayer perceptron (MLP) mixer network works far better for such tasks than the convolutional architectures explored in other lensing analyses. Furthermore, we show that since TMNRE learns a posterior function it enables direct statistical checks that would be extremely expensive with likelihood-based methods. Our results show that TMNRE is well-suited for analysing complex lensing data, and that the full subhalo and line-of-sight halo population must be included when measuring the properties of individual dark matter substructures with this technique.

L-fuzzy algebraic substructure

This article aims to provide a method for defining L-fuzzy algebraic substructures on general algebras. Concretely, the properties of L-fuzzy sets are first reviewed, and their representations are then provided. Next, algebraic substructures are generalised as the closure systems on the power set of the algebra, and the properties of the prime and maximal elements in the above closure system are investigated. Based on these facts, L-fuzzy algebraic substructures with respect to the closure system are defined and studied. Two equivalence characterisations of the sup property of the ordered set L are provided using L-fuzzy substructures. Similarly, some properties of L-fuzzy prime and maximal substructures with respect to the closure system are discussed. Finally, to demonstrate the broad applicability of the theory of L-fuzzy algebraic substructures, the theory is applied to some specific algebraic structures, such as groups and pseudo MV-algebras.

Clumpiness of lens galaxies as a window on dark matter

AbstractWhile the direct detection of the dark-matter particle remains very challenging, the physical properties of dark matter could potentially be constrained indirectly – by comparing the population characteristics of substructures in real galaxies with predictions from the phenomenological dark-matter models, such as cold, warm or self-interacting dark matter. Whereas these models are practically indistinguishable with respect to the expected abundance and statistical properties of massive galactic substructures, the critical difference lies in the low-mass regime ≲ 108M⊙. Galaxy-galaxy strong gravitational lensing provides a unique opportunity to search for gravitational signatures of such low-mass substructures in galaxies acting as a strong gravitational lens on a more distant background galaxy, serendipitously located along the same line of sight. In [Bayer et∼al.(2023)Bayer, Chatterjee, Koopmans, Vegetti, McKean, Treu, Fassnacht, and Glazebrook, Bayer et∼al.(2023)Bayer, Koopmans, McKean, Vegetti, Treu, Fassnacht, and Glazebrook, Bayer et∼al.(2023)Bayer, Vernardos, and Koopmans], we have recently introduced a novel approach to investigate the collective perturbative effect of low-mass substructures in the inner regions of massive elliptical lens galaxies and observationally constrain their power spectrum (on 1-10 kpc scales) based on the Fourier analysis of the associated surface-brightness anomalies in the lensed images (i.e., Einstein rings and gravitational arcs) observed with the Hubble Space Telescope. Here, we present a concise summary of the methodology, the encountered modelling challenges and the inferred observational constraints on the sub-galactic matter power spectrum. The future comparison of these results with predictions from hydrodynamical simulations might either verify the cold-dark-matter paradigm or require its substantial revision. Moreover, we demonstrate that the grid-based smooth lens modelling might model away surface-brightness anomalies caused by the presence of substructures in the lens galaxy and incorrectly interpret them as surface-brightness structure in the lensed background galaxy itself. If not properly understood and accounted for, such signal suppression might lead to severely biased constraints on the properties of substructures in galactic haloes.

Chemically characterising the Milky Way’s stellar halo

AbstractGalactic haloes in a Λ-CDM universe are predicted to host today a swarm of debris resulting from cannibalised dwarf galaxies. The chemo-dynamical information recorded in their stellar populations helps elucidate their nature, constraining the assembly history of the Galaxy. Using data from APOGEE and Gaia, we examine the chemical properties of various halo substructures, considering elements that sample various nucleosynthetic pathways. The systems studied are Heracles, Gaia-Enceladus/Sausage (GES), the Helmi stream, Sequoia, Thamnos, Aleph, LMS1, Arjuna, I’itoi, Nyx, Icarus, and Pontus. Abundance patterns of all substructures are cross-compared in a statistically robust fashion. Our results show that many halo substructures conjectured to be debris from individual accretions likely belong to either the omnipresent GES or to in situ populations, and that the Milky Way likely underwent three major mergers so far: Heracles, GES, Sagittarius dSph.

The chemical characterization of halo substructure in the Milky Way based on APOGEE

ABSTRACT Galactic haloes in a Λ-CDM universe are predicted to host today a swarm of debris resulting from cannibalized dwarf galaxies. The chemodynamical information recorded in their stellar populations helps elucidate their nature, constraining the assembly history of the Galaxy. Using data from APOGEE and Gaia, we examine the chemical properties of various halo substructures, considering elements that sample various nucleosynthetic pathways. The systems studied are Heracles, Gaia-Enceladus/Sausage (GES), the Helmi stream, Sequoia, Thamnos, Aleph, LMS-1, Arjuna, I’itoi, Nyx, Icarus, and Pontus. Abundance patterns of all substructures are cross-compared in a statistically robust fashion. Our main findings include: (i) the chemical properties of most substructures studied match qualitatively those of dwarf Milky Way satellites, such as the Sagittarius dSph. Exceptions are Nyx and Aleph, which are chemically similar to disc stars, implying that these substructures were likely formed in situ; (ii) Heracles differs chemically from in situ populations such as Aurora and its inner halo counterparts in a statistically significant way. The differences suggest that the star formation rate was lower in Heracles than in the early Milky Way; (iii) the chemistry of Arjuna, LMS-1, and I’itoi is indistinguishable from that of GES, suggesting a possible common origin; (iv) all three Sequoia samples studied are qualitatively similar. However, only two of those samples present chemistry that is consistent with GES in a statistically significant fashion; (v) the abundance patterns of the Helmi stream and Thamnos are different from all other halo substructures.

Data-driven uncertainty quantification in computational human head models

Computational models of the human head are promising tools for estimating the impact-induced response of the brain, and thus play an important role in the prediction of traumatic brain injury. The basic constituents of these models (i.e., model geometry, material properties, and boundary conditions) are often associated with significant uncertainty and variability. As a result, uncertainty quantification (UQ), which involves quantification of the effect of this uncertainty and variability on the simulated response, becomes critical to ensure reliability of model predictions. Modern biofidelic head model simulations are associated with very high computational cost and high-dimensional inputs and outputs, which limits the applicability of traditional UQ methods on these systems. In this study, a two-stage, data-driven manifold learning-based framework is proposed for UQ of computational head models. This framework is demonstrated on a 2D subject-specific head model, where the goal is to quantify uncertainty in the simulated strain fields (i.e., output), given variability in the material properties of different brain substructures (i.e., input). In the first stage, a data-driven method based on multi-dimensional Gaussian kernel-density estimation and diffusion maps is used to generate realizations of the input random vector directly from the available data. Computational simulations of a small number of realizations provide input–output pairs for training data-driven surrogate models in the second stage. The surrogate models employ nonlinear dimensionality reduction using Grassmannian diffusion maps, Gaussian process regression to create a low-cost mapping between the input random vector and the reduced solution space, and geometric harmonics models for mapping between the reduced space and the Grassmann manifold. It is demonstrated that the surrogate models provide highly accurate approximations of the computational model while significantly reducing the computational cost. Monte Carlo simulations of the surrogate models are used for uncertainty propagation. UQ of the strain fields highlights significant spatial variation in model uncertainty, and reveals key differences in uncertainty among commonly used strain-based brain injury predictor variables.

On a new kind of ordered fuzzy group

This paper aims to further study the new kind of ordered fuzzy group named ordered L-group, which is put forward in literature [20]. Some algebraic properties of ordered L-groups, such as the relationship between elements, the equivalent characterizations and the products of these groups are discussed. Following that, the properties of substructures including characterization theorems, the convexity, the products of (normal) subgroups maintain the original substructure, along with the properties of ordered L-group homomorphisms are explored. The discussion of ordered fuzzy groups in this paper is from the perspective of fuzzy binary operation, which is different from the commonly method that just discuss the fuzzification of substructures in the research of fuzzy algebra. It can better reflect the essence of fuzzy groups logically just like that of classical groups.

Gas Disk Sizes from CO Line Observations: A Test of Angular Momentum Evolution

The size of a disk encodes important information about its evolution. Combining new Submillimeter Array observations with archival Atacama Large Millimeter/submillimeter Array data, we analyze millimeter continuum and CO emission line sizes for a sample of 44 protoplanetary disks around stars with masses of 0.15–2 M ⊙ in several nearby star-forming regions. Sizes measured from 12CO line emission span from 50 to 1000 au. This range could be explained by viscous evolution models with different α values (mostly of 10−4–10−3) and/or a spread of initial conditions. The CO sizes for most disks are also consistent with MHD wind models that directly remove disk angular momentum, but very large initial disk sizes would be required to account for the very extended CO disks in the sample. As no CO size evolution is observed across stellar ages of 0.5–20 Myr in this sample, determining the dominant mechanism of disk evolution will require a more complete sample for both younger and more evolved systems. We find that the CO emission is universally more extended than the continuum emission by an average factor of 2.9 ± 1.2. The ratio of the CO to continuum sizes does not show any trend with stellar mass, millimeter continuum luminosity, or the properties of substructures. The GO Tau disk has the most extended CO emission in this sample, with an extreme CO-to-continuum size ratio of 7.6. Seven additional disks in the sample show high size ratios (≳4) that we interpret as clear signs of substantial radial drift.

Seismic reliability evaluation of a tall concrete‐timber hybrid structural system

SummarySeismic reliability analysis is important for performance evaluation and structure design of novel structural systems since it can consider inherent uncertainties in seismic actions and structural properties. In this paper, seismic reliability analyses were performed on an innovative high‐rise concrete‐timber (FaB) hybrid structural system. The FaB system combines a concrete frame‐tube structure with large story height as the main structure and multi‐story timber structures on each concrete slab as substructures. To better assess the seismic reliability of the FaB system, response surface methods with either the Lasso regression approach or the machine‐learning‐based symbolic regression approach were conducted and compared. Uncertainties, including ground motions, elastic properties and ductility factor of the concrete main structure, mechanical properties of timber substructures and connections (i.e., rubber bearings), mass ratios, and fitting errors, were considered in formulating the limit‐state performance functions. Tens of thousands of non‐linear time‐history analyses were run to establish the response database of the FaB system, and the reliability indexes of both the concrete main structure and timber substructures were calculated. The results show that the symbolic regression approach can formulate simpler response surface functions with similar results compared to the Lasso regression approach. The maximum difference of reliability indexes between the two approaches is less than 8.3%. For the concrete main structure, the seismic reliability indexes are in a range of 1.068 to 4.223 under different performance objectives and hazard levels, while those of timber substructures are in a range of 0.892 to 2.28. The corresponding non‐exceedance probabilities of failure are between 81% and 99%, which reveals the safety and robustness of the FaB system. Meanwhile, the adoption of rubber bearings in the FaB system can enhance the seismic reliability indexes of timber substructures by 9% to 28% but has little influence on those of the concrete main structure. Outcomes of this study can serve as efficient tools to quantify the seismic performance and evaluate the performance‐based seismic design methodology for the proposed tall concrete‐timber hybrid structural system.

Periodically alternated elastic support induced topological phase transition in phononic crystal beam systems

Determining strong robustness in flexural wave propagation in beam systems has always been a promising achievement with various real-life applications such as energy harvesting and waveguiding. In this manuscript, the bending characteristics of a phononic crystal beam on periodically alternated linear elastic support systems with topologically protected wave propagation are proposed. Based on the Timoshenko beam theory, general solutions of this periodic beam-foundation topological system are obtained. Subsequently, by applying the Bloch theory, the dispersion relation is obtained using the transfer matrix method. Comparing with finite element numerical solutions, excellent agreement is observed with only a minor difference due to the assumptions in the Timoshenko beam theory. Generally, any breaking of spatial symmetry in beam systems can be achieved by changing geometry of beam cross-sections or tuning the material properties of substructures. We herein propose a new approach to break the spatial symmetry, i.e., tuning the elastic stiffnesses of the periodically alternated elastic supports. It is found that beam bending on an infinite continuously distributed elastic foundation leads to a band-crossing point. After tuning the elastic support stiffness in a periodic manner, the band-crossing point is broken and a new bandgap appears due to the breaking of structural symmetry. Further, a mode shape inversion and Zak phase transition are captured. Based on a unit cell analysis, we examine the topologically protected interface modes in an array constructed with periodically arranged unit cells with two corresponding phase states. Furthermore, several numerical examples are used to demonstrate the defect- and disorder-immune properties in this one-dimensional topological system. This new proposed general mechanism can be extended to establish topological phase transitions in other mechanical and dynamic systems.

An accurate comprehensive approach to substructure: III. Masses and formation times of the host haloes

ABSTRACT With this paper, we complete a comprehensive study of substructure in dark matter haloes. In Paper I, we derived the radial distribution and mass function (MF) of accreted subhaloes (scaled to the radius and mass of the host halo) and showed that they are essentially universal. This is not the case, however, for those of stripped subhaloes, which depend on halo mass and assembly history. In Paper II, we derived these latter properties in the simplest case of purely accreting haloes. Here, we extend the study to ordinary haloes having suffered major mergers. After showing that all the properties of substructure are encoded in the mean truncated-to-original subhalo mass ratio profile, we demonstrate that the dependence of the subhalo MF on halo mass arises from their mass-dependent concentration, while the shape of the subhalo radial distribution depends on the time of the last major merger of the host halo. In this sense, the latter property is a better probe of halo formation time than the former. Unfortunately, this is not the case for the radial distribution of satellites as this profile is essentially disconnected from subhalo stripping and the properties of accreted subhaloes are independent of the halo formation time.

Effect of 1.5-T and 3.0-T magnetic resonance imaging on the ceramic adhesion and physical properties of prosthetic substructures

Statement of problemMagnetic resonance imaging (MRI) is a cross-sectional imaging technique that is widely used in the detection of pathologies in the head and neck region. However, information is lacking about the effect of MRI imaging on the clinical success of fixed partial dentures (FPDs). PurposeThe purpose of this in vitro study was to analyze the effect of MRI on the physical properties and ceramic adhesion of FPD substructure materials. Material and methodsThree hundred disk (12×1 mm) and 255 rectangular (4×2×2 mm) specimens were prepared with different fabrication techniques for 5 experimental groups: direct metal laser sintering (DMLS) with Co-Cr and Ti; casting with Co-Cr and Ni-Cr; and milling with ZrO2. After ceramic application, the disk specimens were subjected to aging and divided into 3 subgroups (n=20) with exposure to 1.5-T and 3.0-T MRI brain scans for 30 minutes and no exposure (control). The shear bond strength (SBS) of the specimens was measured by using a universal testing machine. The rectangular specimens were exposed to MRI with the same procedure, and the nanostructure of the specimens was analyzed with the small-angle X-ray scattering (SAXS) method to detect the nanoscale structural effects of MRI. The average surface roughness (Ra) and Vickers microhardness (Vh) were also measured for complementary analyses. SBS, Ra, and Vh values were statistically analyzed by 1-way ANOVA and the Tukey honestly significant difference test (α=.05). ResultsThe SBS (MPa) of casting groups (P<.001) and DMLS with the Co-Cr group (P<.05) were significantly affected by MRI exposures. The significant differences were seen on the Ra of casting (P<.001) and DMLS with Co-Cr (P<.05) and Ti (P<.01) groups. Also, the Vh of the casting with Co-Cr (P<.001) and Ni-Cr (P<.01) groups showed significant differences. The SAXS analysis indicated that the physical properties of materials were influenced by MRI exposure. ConclusionsThe results indicated that MRI applications affected the metal-ceramic adhesion of Co-Cr and Ni-Cr dental alloys produced by casting and the DMLS technique.

Engineering Hierarchical‐Dimensional Co(OH)F into CoP Superstructure for Electrocatalytic Water Splitting

AbstractMulti‐dimensional materials can combine the advantages of fast mass diffusion of high dimensional structures and advanced intrinsic properties of low dimensional substructures. In specific, superstructures are widely prepared from assembling low dimensional materials into arrays by complicated methods. We recently proposed the concept of hierarchical‐dimensional material (HDM), in which superstructure is composed of low dimensional substructures from simple wet chemical method. Herein, we report the synthesis of a CoP HDM from the engineering of the hierarchical‐dimensional Co(OH)F precursor by successive phosphorization and acid etching. The resulting CoP superstructure is built by porous CoP rod substructure. The rods weave together to form 2D mesh plates and the 2D mesh plates stack together to form the 3D superstructure. Thus, a very interesting structure is generated with 0D, 1D, 2D and 3D features. The CoP material displayed outstanding electrocatalytic activity for both HER and OER in alkaline solutions. The overpotentials required to drive a HER and OER current density of 10 mA/cm2 were 94 mV and 295 mV, respectively. The superior performance is believed to be associated with the unique structure from phosphorus‐based engineering of nanostructure.

Power of halometry

Astrometric weak gravitational lensing is a powerful probe of the distribution of matter on sub-Galactic scales, which harbor important information about the fundamental nature of dark matter. We propose a novel method that utilizes angular power spectra to search for the correlated pattern of apparent motions of celestial objects induced from time-dependent lensing by a population of Galactic subhalos. Application of this method to upcoming astrometric datasets will allow for the direct measurement of the properties of Galactic substructure, with implications for the underlying particle physics. We show that, with near-future astrometric observations, it may be possible to statistically detect populations of cold dark matter subhalos, compact objects, as well as density fluctuations sourced by scalar field dark matter. Currently-unconstrained parameter space will already be accessible using upcoming data from the ongoing Gaia mission.

Experimental study on viscoelastic dampers for structural seismic response control using a user-programmable hybrid simulation platform

To truly reflect the influence on structural seismic response control using viscoelastic dampers with strong nonlinear properties and reduce the cost and difficulty of experimental research, a new user-programmable hybrid simulation platform is developed. The core implementation details of this platform, including the core architecture, software system, and testing setup, are described. To better realize accuracy and stability of the hybrid simulation experiment, methods for solving the equivalent force equilibrium equation for hybrid simulation experiments on viscoelastically damped structures are proposed. Then, the mechanical properties of the experimental substructure (viscoelastic damper) are tested under different temperatures, amplitudes and frequencies, and the mathematical model parameters of the experimental substructure are identified. A seismic response comparison of viscoelastically damped structures obtained by the hybrid simulation experiment and the time history analysis verifies the robustness and reliability of the hybrid simulation platform to test nonlinear systems. Lastly, a series of hybrid simulation experiments for viscoelastically damped structures under different temperatures, seismic intensities and seismic waves are implemented using this hybrid simulation platform for the first time. The experimental results reveal the influence on structural seismic response control by viscoelastic damper under different temperatures, seismic intensities and seismic waves.