Structural System Research Articles

Hybrid structural systems for timber high-rise buildings

Hybrid structural systems for timber high-rise buildings

Repeatability and reproducibility of artificial intelligence-acquired fetal brain measurements (SonoCNS) in the second and third trimesters of pregnancy

Artificial Intelligence (AI)-based algorithms are increasingly entering clinical practice, aiding in the assessment of fetal anatomy and biometry. One such tool for evaluating the fetal head and central nervous system structures is SonoCNS™, which delineates appropriate planes for measuring head circumference (HC), biparietal diameter (BPD), occipitofrontal diameter (OFD), transcerebellar diameter (TCD), width of the posterior horn of the lateral ventricle (Vp), and cisterna magna (CM) based on a 3D volume acquired at the level of the fetal head’s thalamic plane. This study aimed to evaluate the intra- and interobserver variability of measurements obtained using this software. The study included 381 patients, 270 in their second trimester of pregnancy (70%) and 111 in the third trimester. Each patient underwent manual biometric measurements of the aforementioned structures and twice using the SonoCNS software. We calculated the intraobserver variability between the manual measurements and the average of the automated measurements, as well as the interobserver variability for automated measurements. We also compared the median examination time for manual and automated measurements. The interclass correlation coefficients (ICC) for interobserver and intraobserver variability for parameters BPD, HC, and OFD ranged from good to excellent reproducibility in the general population and subgroups (> 0.75). CM and Vp measurements, both in the general population and subgroups, fell into the category of moderate (0.5–0.75) and poor reproducibility (< 0.5). TCD measurements showed moderate (> 0.5) to good reproducibility (0.75–0.9), and OFD showed good and excellent reproducibility. The assessment of the biometry of fetal head structures using SonoCNS took an average of 63 s compared to 14 s for manual measurement (p < 0.001). The SonoCNS™ software is characterized by good to excellent reproducibility and repeatability in the measurement of fetal skull biometry (BPD, HC, and OFD), with poorer performance in measurements of intracranial structures (CM, Vp, TCD). Apart from biometric parameters, the software is useful in clinical practice for delineating appropriate planes from the acquired volume of the fetal head and shortening examination time.

A novel optimization‐based modal pushover analysis procedure for estimating the response of structures

AbstractIn recent years, studies have focused on the seismic behavior of various structural systems, including single‐ and double‐layered spatial structures. While nonlinear dynamic analyses are common for these studies, they are time‐consuming and complex. To address this, many pushover procedures have been developed, but their effectiveness in spatial structures remains underexplored. This study introduces an optimized lateral loading profile for evaluating the seismic response of walled bilayer spatial structures. By combining dominant inertial forces and optimizing their corresponding coefficients with the particle swarm optimization (PSO) algorithm, an optimal loading profile is derived. The method's accuracy was tested on models with varying arch height‐to‐span ratios and a constant wall height‐to‐span ratio, as well as a 15‐story frame structure. The results obtained showed that the proposed method closely matches incremental dynamic analyses (IDAs) in predicting base shear, initial stiffness, and displacements, especially for higher arch height‐to‐span ratios. Additionally, the method accurately estimates drift profiles and nodal displacements on roofs and walls, and performs better than similar mode‐based methods for frame structures.

Application of pole allocation to optimize passive viscous dampers represented by the Maxwell model

The Maxwell model is used to understand the realistic effectiveness of vibration reduction in the building structures. The model consists of a dashpot and spring in series. The dashpot and spring represent a viscous damper and joint between the damper and the structural frame, respectively. However, few studies have investigated the optimal damper capacity and the corresponding spring stiffness in the practical parameter ranges. Additionally, the optimal damper derived using the fixed-point theory has no relationships with that derived via pole allocation. Therefore, in this study, to examine the effects of the joint spring, the pole allocation method was used to design a structural system wherein the Maxwell model was incorporated into a single-degree-of-freedom damped model. We introduced a closed-form expression, which explicitly described the relationships between the target structural damping ratio, damper capacity, and joint spring. The Maxwell model constrained the control effectiveness using damper parameters and simultaneously suggested an optimal and realistic joint spring for the damper. Pole allocation was also applied to a multi-degree-of-freedom (M-DOF) damped structural system employing multiple Maxwell models. The newly proposed optimized joint spring could easily control the additional damping effect on the M-DOF system. The Maxwell model can be optimized almost manually. The scheme is more useful in the preliminary design stage than the previous numerical optimizations. This study extended the mathematical equation governing the building vibrations to the Maxwell model. The extended equation served as a unified description for considering structural passive control.

Enhanced Multi‐Objective Optimization Model for Bridge Performance Assessment and Prediction, Based on Improved PCA, K‐Means Clustering, and Kaplan–Meier Survival Algorithm

ABSTRACTThe research proposes a hybrid algorithm model that combines model‐driven and data‐driven approaches for the direct application of bridge health monitoring technology in bridge management. This comprehensive study encompasses a series of analytical techniques and methodologies to build a multi‐objective optimization model for bridge performance assessment and prediction. It focuses on the processing of multi‐source heterogeneous data, selection of key sub‐parameters using Principal Component Analysis (PCA), enhanced K‐means clustering analysis, determination of structural component target thresholds, time‐dependent survival probability analysis, regression fitting, and timing prediction of the bridge system for both the components of double‐layer truss arch bridge and the bridge system. The initial phase of the study concentrates on the diversification and decentralization of monitored data from various sources, integrating and cleaning data obtained from different sources to ensure data quality and consistency. PCA technique is applied to identify key sub‐parameters that have significant impacts on the performance of structural components. Enhanced K‐means clustering analysis is carried out to effectively group and classify the identified key sub‐parameters. Numerical simulations, including structural nonlinear analysis, are conducted to determine the target thresholds of bridge structure, providing important benchmarks for performance evaluation. Finally, a multi‐parameter regression model is used to evaluate and update the performance of the bridge structure, taking into account survival probability (using the Kaplan–Meier method), maintenance history, and material deterioration to estimate the most critical time for the bridge system. A case study is conducted to validate the suggested comprehensive algorithms for a double‐layer truss arch combination bridge, which contributes to enhancing performance evaluation and predicting the most critical time for structural components and bridge system in the bridge management and maintenance practices. It should not be ignored that, the accuracy and reasonability of bridge structure system performance evaluation and prediction depend largely on the selection of target thresholds.

New orbital periods of high-inclination dwarf novae based on Gaia Alerts photometry

The orbital period of a cataclysmic variable stands as a crucial parameter for investigating the structure and physics of these binary systems, as well as understanding their evolution. We use photometric Gaia data for dwarf novae (DNe) in the quiescent state ---which are available for a number of years--- to determine new orbital periods and improve or modify previously suggested period values. Two approaches are implemented for selecting high-inclination targets, either eclipsing or with ellipsoidal variations. We determine new orbital periods for 75 DNe and improve ephemerides for 27 more (three of which change significantly), contributing 9.4&lt;!PCT!&gt; of the known DNe periods of between 0.05 and 2.0 days, and doubling the number of known periods exceeding 0.44 days. Their phase-folded light curves are presented and arranged by orbital period, illustrating the transition from short-period systems, dominated by radiation from the accretion disc and the hot spot, to longer-period DNe, where the Roche-lobe-filling secondary star is the primary visual flux source. This transition ---which occurs around the well-known period gap (between sim 2 and 3 hours)--- is expected, as DNe with larger orbital periods typically harbour more massive donors, which contribute to the visible flux. However, this transition is not abrupt. Within the same range of periods, we observe systems dominated by ellipsoidal variations, where the companion star is clearly visible, as well as others dominated by the disc and the hot spot. The presence of some DNe with ellipsoidal variations near the lower edge of the period gap is striking, as the companions in these systems are expected to be cool low-mass M-dwarfs not visible in the light curve. This could indicate that we are observing systems where the donor star was originally much more massive and underwent significant nuclear evolution before mass-transfer began, as has been suggested previously for QZ Ser.

Efficient fuzzy simulations for estimating the failure credibility of engineering structures under fuzzy environment

Efficiently and accurately solving the failure credibility of a structural system plays a significant role in the engineering field under fuzzy environment. A more precise failure credibility can help assess the safety degree of the system, and then reduce the occurrence of security accidents. At present, the extended fuzzy first-order and second-moment method (EFFOSM) is effective to analyze failure credibility for some occasions. However, when it comes to complicated performance functions and fuzzy inputs, the accuracy of EFFOSM is greatly reduced and its efficiency also needs to be improved. To overcome the above shortcomings, this paper proposes two types of novel fuzzy simulation algorithms, namely uniform discretization algorithm (UDA) and bisection simulation algorithm (BSA). For the system involving frequently-encountered continuous and strictly monotone performance functions of regular LR fuzzy interval inputs, these two algorithms are designed to estimate failure credibility with higher efficiency and accuracy. Subsequently, with the aid of the linearization and regularization procedures in EFFOSM, the application of UDA and BSA is extended to non-monotone performance functions of irregular LR fuzzy intervals. To evaluate and verify the performance of the proposed two algorithms, their comparisons with EFFOSM are conducted through some numerical examples and practical problems. The results show that the proposed two algorithms outperform EFFOSM in terms of accuracy and efficiency, and also have wider application range for estimating the failure credibility of strictly monotone performance functions involving regular LR fuzzy interval inputs. Meanwhile, BSA is slightly better than UDA for the less runtime.

Toric configuration spaces: the bipermutahedron and beyond

We establish faithful tropicalisation for point configurations on algebraic tori. Building on ideas from enumerative geometry, we introduce tropical scaffolds and use them to construct a system of modular fan structures on the tropical configuration spaces. The corresponding toric varieties provide modular compactifications of the algebraic configuration spaces, with boundary parametrising transverse configurations on tropical expansions. The rubber torus, used to identify equivalent configurations, plays a key role. As an application, we obtain a modular interpretation for the bipermutahedral variety.

“Meet the IUPAB councilor”—Thomas Gutsmann

AbstractAs one of the twelve newly elected councillors, it is my pleasure to provide a brief biographical sketch for the readers of Biophys. Rev. and the members of the Biophysical Societies. I have been actively involved in the German Biophysical Society (DGfB) since 2008, initially as the speaker for the “Membrane Biophysics” section and, since 2015, as the secretary. Within the IUPAB council I follow Prof. Hans-Joachim Galla, former Secretary and President of the German Biophysical Society, who served as a councillor for two terms from 2018 to 2024. Thus, a direct continuation of the German contribution to the IUPAB is guaranteed. My journey in biophysics began during my studies of physics at the University of Kiel, where I specialized in physiology and biophysics. After earning my doctorate in the lab of Ulrich Seydel at the Research Center Borstel, I spent two years at the University of California, Santa Barbara, working in Paul Hansma’s lab on the development and application of atomic force microscopy. During my time at UCSB, I also collaborated with Jacob Israelachvili’s lab on membrane properties. Since 2008, I have been leading the Biophysics Research Group at the Research Center Borstel, Leibniz Lung Center. In 2010, I was appointed as a professor at the University of Lübeck. Additionally, since 2023, I have been serving as an associate member at the Centre for Structural Systems Biology (CSSB) in Hamburg.

Strain distribution and failure modes of steel lattice tower gusset plates as a function of their geometry

Steel gusset plates (SGP) are structural elements that connect and transfer loads among various members, such as beams, columns, and trusses, in steel structures like buildings, bridges, and lattice towers. Their geometry significantly affects structural performance, requiring a thorough analysis of strain distribution and failure modes to ensure the integrity and safety of structural systems. However, the design and evaluation of lattice tower gusset plates (LTGP) in particular, present challenges due to complex geometries and the lack of universally accepted design methods. This paper presents a comprehensive comparative study of the strain distribution and failure modes of LTGP across different geometries. Experimental tests were conducted using Digital Image Correlation (DIC) on specimens with different configurations, each featuring a single row of bolts. The force–displacement curves and strain distributions were analyzed to determine the influence of gusset plate width, end-distance, and the number of bolts on their behavior. The study compares the experimental data with the prescriptions of design standards. Additionally, it presents numerical modeling of LTGP connections using finite element analysis in ANSYS®, with validation against experimental results confirming model accuracy. The research program is further complemented by a parametric study examining the effects of end-distance, plate width, and bolt spacing on the ultimate strength of LTGP.

Intersecting inequalities: (re)producing the marginalized other

ABSTRACT In their introduction, the editors of this Special Issue argue that critical discursive approaches which embrace an intersectional lens can, in combination, reveal the ways in which identities and social categories are shaped by power structures in society. Indeed, the case studies presented in the Special Issue demonstrate the key role of discourse analysis in revealing the mechanisms which create and reproduce inequality. They speak to the need for a critical intersectional analysis which highlights how structural systems of marginalization – such as racism and sexism – combine and interact. The articles illustrate, too, the ‘intra-categorical’ approach to intersectionality – whereby a person’s experience of one aspect of identity is understood to be fundamentally informed by its intersection with other factors – by showing us that we cannot analyse issues such as racism, or identities such as masculinity, in isolation.

ЛЕЧЕБНО-ВОССТАНОВИТЕЛЬНЫЕ И БИОТЕХНОЛОГИЧЕСКИЕ РЕСУРСЫ НАУЧНОЙ МУЗЫКОТЕРАПИИ В РЕШЕНИИ ПРОБЛЕМ БЕСПЛОДИЯ

Scientific music therapy is an advanced therapeutic and preventive direction, widely in demand in various areas of health care, psychological assistance, and social rehabilitation, but still underestimated in reproductive medicine. Complex scientific research conducted over thirty years has helped to better understand the nature of the main mechanisms of music's influence on the neuroendocrine system,vital organs, and cellular structures. On this basis, unique and effective methods of scientific music therapy and promising biotechnologies have been created, the possibilities of which in solving infertility problems are discussed in this article.

Dynamic Analysis of a 600-m-High Supertall Building Subjected to Long-Period Ground Motions, Ordinary Ground Motions and a Super Typhoon: A Comparative Study

Long-period ground motions pose potential risks to the safety and serviceability of supertall buildings, which was not paid sufficient attention in the past of structural seismic design. To address this issue, the comparative study presented in this paper systematically investigates the dynamic responses of a 600-m-high supertall building subjected to natural hazards including long-period ground motions, ordinary ground motions and a super typhoon with the same return periods of 50 years. The seismic responses and wind-induced responses of the supertall building are obtained based on the building’s finite element model under earthquake excitation records and structural health monitoring system installed in the skyscraper, respectively. The long-period ground motions cause larger dynamic responses of the supertall building than those resulted by the ordinary ground motions or the super typhoon. This combined study of numerical analysis and field measurement provides valuable insights into the dynamic responses of a supertall building under different natural hazards, especially the long-period ground motions. The findings are expected to be of interest and practical use to the design of supertall buildings.

Inverse-designed 3D sequential metamaterials achieving extreme stiffness

Mechanical metamaterials signify a groundbreaking leap in material science and engineering. The intricate and experience-dependent design process poses a challenge in uncovering architectural material sequences with exceptional mechanical properties. This study introduces inverse-designed 3D sequential metamaterials with outstanding mechanical attributes, achieved through a novel computational framework. The explored sequences based on Schoen's I-graph–wrapped package (IWP) and Schwarz Primitive (Schwarz P) surpass the Hashin-Shtrikman upper bound of Young's modulus at relative densities of 0.24 and 0.43, outperforming previous records. Optimized Body-Centered-Cubic (BCC) truss-based sets outperform traditional ones by 72.7%. This innovative approach can be extended for metamaterial customization, involving the optimization of multi-directional Young's modulus, total stiffness, and the addition of isotropy constraints. The paper explores the characteristics and implications of this innovation, emphasizing the impact of geometric and topological variations on mechanical performance. These metamaterial sequences offer unparalleled adaptability, and hold significant potential in structural engineering and adaptive mechanical systems, opening avenues for technological advancements.

Construction and Verification of Composite Intensity Measures for Multi-Storey Underground Structures Based on Partial Least Squares Regression Method

In the processes of seismic design of underground structures, selecting a reasonable input ground motion is very important, which can cause severe damage to underground structures. To quantitatively evaluate the seismic damage potential of ground motions on multi-storey underground structures and solve the problem that single intensity measures are inadequate in accurately indicating the seismic damage potential of ground motions, this paper taking the input ground motions in the seismic design of underground structures as the research object, and constructing some composite intensity measures that can effectively characterize the damage potential of input ground motion. Firstly, considering that the underground structures in different characteristic period-type sites will exhibit different seismic responses under the same excitation, the soil–structure system is divided into four-period bands. Then, four representative periods are selected from four-period bands respectively, and the corresponding four soil–structure system numerical models are established. Subsequently, 40 ground motions are selected for elastoplastic numerical analysis, and the results of the numerical analysis were used as sample data to construct composite intensity measures corresponding to soil–structure systems in each period band using the partial least squares regression method. Finally, 100 additional ground motions were used to verify the correlation between the composite intensity measures and the seismic damage of underground structures. The results show that the correlation coefficient between the composite intensity measures and the seismic damage of multi-storey underground structures is better than those of commonly used single intensity measures.

System fragility analysis of highway bridge using multi-output Gaussian process regression surrogate model

This study presents a multi-output Gaussian process regression (GPR) surrogate model for seismic-fragility analysis of bridge structural systems. Multi-output GPR can model the correlations among multiple outputs, accuracy and stability are achieved with fewer training data, which reduces the computational cost of fragility analysis. Furthermore, the explainability of the constructed surrogate model is implemented by adopting an automatic relevance-determination (ARD) kernel in the GPR. The estimated hyperparameters can provide the contribution of the uncertainty of each input parameter to the outputs. The fragility analysis using the multi-output GPR surrogate model was verified by applying it to a seismic isolation highway bridge with multiple spans and a curved geometry. The effectiveness of the multi-output GPR was demonstrated by the construction of an accurate and stable surrogate model with 46 inputs and 28 outputs. The relative contributions of the uncertainties to the structural properties and input earthquake loads could also be understood. The fragility curves, at both the component and system levels, were appropriately obtained using a sufficient number of samples in a Monte Carlo calculation. Furthermore, the failure modes were evaluated, identifying which structural components contributed to the system failure. This enabled discussions on structural system failures from the viewpoint of the structural dynamic characteristics of the bridge and earthquake-load properties.

Efficient seismic fragility analysis considering uncertainties in structural systems and ground motions

AbstractFragility plays a pivotal role in performance‐based earthquake engineering, which represents the seismic performance of structural systems. To comprehensively understand the structural performance under seismic events, it is necessary to consider uncertainties in the structural model, i.e., epistemic uncertainties. However, considering such uncertainties is challenging due to computational complexity, leading most fragility analyses only to consider the chaotic behavior of ground motions on structural responses, i.e., aleatoric uncertainties. To address this challenge, this study proposes an adaptive algorithm that intertwines with the conventional fragility analysis procedures to consider both aleatoric and epistemic uncertainties. The algorithm introduces Gaussian process‐based metamodels to efficiently consider epistemic uncertainties with a small number of time history analyses. Steel moment‐resisting frame structures and a reinforced concrete building are used to demonstrate the improved efficiency and wide applicability of the proposed method. In each case, the proposed method yields fragility curves consistent with reference solutions but with substantially lower computational effort. Comprehensive discussions are provided regarding ground motion sets, structural types, and definitions of limit‐states to demonstrate the robustness of the proposed approach.

Additively Manufactured Structures for Precise and Robust Mounting of Optical Elements

The design freedom of Additive Manufacturing offers new opportunities for the design of mounting structures of optical systems, which are not feasible for conventional manufacturing approaches, thus opening up new areas of application for optical systems. We use this to develop a fully monolithic mounting structure for precise positioning of the optical elements, while simultaneously increasing their robustness against harsh environmental conditions. We additively manufacture such a mounting structure for an imaging lens and evaluate its optical performance with interferometric measurement of its wavefront, before and after applying a mechanical shock to the entire system. The results indicate a centering accuracy better than 6~µm, both in the initial positioning as well as the subsequent repositioning after a mechanical shock of 15G.

Root traits of soybeans exposed to polyethylene films, polypropylene fragments, and biosolids

Biosolid use imports microplastics into the rhizosphere where they may interfere with root-soil-microbial interactions and cause morphological adaptations in crop root systems. Few studies have examined the response of crop roots to microplastics at documented soil concentrations, and many studies collect root traits using destructive techniques. Hence, there is little information on when and how microplastics effect the physical structure of root systems. Using the rhizobox method, soybeans (Glycine max) were grown in soil amended with biosolid microplastic mimics (polyethylene film or polypropylene fragments at 2,000 and 15,000 particles/kg dry soil) or biosolids and imaged weekly until maturity (11 weeks) using a custom scanner system. Plant biomass increased in the polyethylene treatments and decreased in the high concentration polypropylene treatment. Relative to the Control, polyethylene treatments had larger root length, reduced root diameters, reached maturity faster, had deeper root systems, and had a greater number of lateral roots. In contrast, polypropylene treatments had a mixed response, with high concentrations eliciting a lower root length, fewer laterals, and a more vertical root orientation. Segmented linear regression revealed that root growth in the Control and Biosolid treatments continued through the course of the experiment, while the microplastic treatments reached maturity up to two weeks earlier. Imagery revealed that microplastics elicited deeper rooting depth within the first week and differences in all root traits were evident by the development of the first trifoliate leaflets. Microplastic effects on root traits at early life stages suggest soil physiological drivers, while increased branching frequency and lower lateral elongation are suggestive of changes in soil nitrogen availability. The minimal difference in root traits in the biosolid treatment may be attributable to differences in microplastic properties or counteractive effects by other biosolid constituents.

Intersectional Identity and Representative Politics

Representation scholarship has drawn from intersectionality theory 0to examine how systemic structures of oppression and privilege have created social groups with distinct political needs. Derived from Black feminist theory that recognizes that identities are mutually constitutive and interconnected, intersectionality research is rooted in the lived experiences of marginalized groups who call attention to social (in)justice. Empirical scholarship building on the insights of Black feminist theorists such as Collins and Bilge (2016), Hill Collins (1990), Crenshaw (1989; 1991), and King (1988) has constituted nothing less than a paradigm shift in the study of gender and politics. Nevertheless, there remain an array of opportunities to expand upon the potential for intersectional frameworks and methods, as well as pressing new questions concerning the operationalization of intersectionality itself. This Critical Perspectives section offers a moment to take stock of these developments and debates, as well as to highlight new pathways for scholarship committed to centering the margins and considering the nexus of multiple power structures that frame our political lives.