Structural System Research Articles

Temperature-responsive metamaterials made of highly sensitive thermostat metal strips.

Temperature-responsive metamaterials have remarkable shape-morphing ability during thermal energy conversion. However, integrating the thermal shape programmability, wide-working temperature range, fast temperature response, and actuation into metamaterials remains challenging. Here, we introduce using thermostat metal strips to assemble metamaterials with desirable and balanced temperature-responsive properties, and we systematically investigate the thermal deformation performance. Achieving 70 to 80% of the designed strain requires only 5 seconds of heating. A thermal strain of around 30% is achieved for the assembled metamaterials, surpassing other bimetallic metamaterials by a magnitude of 100 to 200. The actuation capacity of thermostat metal strips exceeds 26 times their weight. Further, by leveraging the highly programmable thermal deformation, the tuneable bandgap range is 3847 to 40,000 hertz. These fully integrated mechanical performances in the multiphysics have great application potential, for example, as soft actuators and soft robots in intelligent structure systems, vibration isolation and noise reduction in hypersonic vehicles, and unique thermal deformation in precision instruments.

Structural Optimization of Chalcogenide Thin Films for Enhancing the Threshold Switching Performance.

This study conducts a comprehensive investigation into the physical properties of germanium telluride (GeTe, GT) thin films and their associated electronic devices to establish fundamental relationships that are essential for achieving reliable threshold switching (TS) characteristics. Chemical composition variations in GT thin films significantly influence their crystallinity, atomic vibration modes, chemical binding status, bandgap, and distribution of electronic traps. The increase in the tellurium (Te) content results in elevated Urbach energy, subsequently reducing the effective bandgap energy. Excluding GT8, trap energy increases proportionally with increasing Te content. Correlating electrical properties with physical characteristics reveals key conditions necessary for stable TS behavior: maintaining amorphous crystallinity, optimizing the chemical composition of the GT layer, and ensuring an appropriate bandgap and trap energy. These findings underscore the importance of precise chemical composition control for reliable TS performance. Insights from this study can guide nanoscale analyses of bonding structures in Te-based binary TS systems and present opportunities for material optimization across various applications.

Comparative Study of Cradle-to-Gate Carbon Emissions from Steel and Concrete Structures of Bangladeshi Industrial Projects

Sustainable practice is necessary for the construction industry's environmental impact, particularly carbon footprint. A "cradle-to-gate" Life Cycle Assessment of the embodied carbon emissions of two structural systems, steel and reinforced concrete, is presented for an industrial building in Bangladesh. By quantifying these emissions through BIM modeling and emission factor databases, the analysis shows that steel-framed structures have a significantly higher carbon footprint than their concrete alternatives, mainly because of the energy-intensive steel production processes. Emissions from raw material extraction, transportation, and manufacturing stages are detailed and assessed. The results show that steel structures produce 60% more embodied carbon than reinforced concrete counterparts, primarily due to raw material emissions, with other emissions from aluminum and rebar in both systems. These findings provide a basis for construction material selection and highlight the need for low-carbon approaches to reduce the sector's carbon footprint in rapidly urbanizing areas like Bangladesh. Further research should extend to the end-of-life impacts and more localized emission data to continue to refine sustainable construction strategies.

Time-division multiplexing cascaded active phase-locking method for an all-fiber coherent beam combining system

Coherent beam combining (CBC) is an effective approach to exceed the power limitation of fiber lasers by combining multiple laser sources. Phase-locking is one of the important steps in an active CBC system. Many phase-locking methods have already been developed and have effectively achieved phase control. Generally, the phase control bandwidth decreases accordingly as the number of combined lasers increases. This will hamper the development of CBC systems to larger scales. At the same time, the structure of traditional tiled-aperture CBC systems is also a potential limiting factor in the aspect of feedback configuration. An all-fiber CBC structure based on active phase control can avoid physical size limitations on traditional structures and greatly expand the scale of tiled-aperture CBC arrays to over tens of thousands of sub-beams. In such a large array scale, existing phase control methods will inevitably encounter the problem of bandwidth reduction. To solve this problem, we propose a time-division multiplexing cascaded (TDMC) active phase-locking method in this paper. Simulation studies on phase control of over 10,000 laser beams are conducted. The method shows huge bandwidth enhancement in control phases of a large number of lasers. This will lay the technological foundation for further expanding the number of an all-fiber tiled-aperture array.

Assessing the reliability of woody vegetation structural characterisation from UAV-LS in a tropical savanna

Terrestrial laser scanning (TLS) represents the gold standard in remote quantification of woody vegetation structure and volume, but is costly and time consuming to acquire. TLS data is typically collected at spatial scales of 1 ha or smaller, which limits its suitability for representing heterogeneous landscapes, and for training and validating satellite-based models which are needed for larger area monitoring. Advances in unoccupied aerial vehicle laser scanning (UAV-LS) sensors have recently narrowed the gap in quality between what TLS delivers and what can be acquired over larger areas from UAV platforms. We tested how well new nadir-forward–backward (NFB) UAV-LS technology can capture the structure of individual trees in a tropical savanna setting with a diversity of tree sizes and growth forms. UAV-LS data was acquired with a RIEGL VUX-120 LiDAR sensor mounted on a Acecore NOA hexacopter. Reference data was obtained with a RIEGL VZ-2000i TLS scanner using a multi-scan approach. Point clouds were segmented into individual trees and volumetrically reconstructed with RayCloudTools (RCT). We found no statistical difference between UAV-LS and TLS derived estimates of tree height, canopy cover, diameter, and wood volume. Mean tree height and DBH derived from UAV-LS were within 3% of the TLS estimate, and there was less than 1% deviation in stand wood volume. Our findings ease the advancements on the detailed monitoring of open forests, potentially achieving large-scale mapping and multi-temporal investigations. The open structure of savanna systems is well suited to UAV-LS sensing, but more research is needed across diverse ecosystems to understand the generality of these findings in landscapes with greater canopy closure or complex understorey conditions.

Structural insulation panel system (SIP) as an alternative for cooling energy saving, decarbonization, and energy cost reduction in hot and dry climates. A simulation-based approach

ABSTRACT During the last decades, the growing urban prospects represent a challenging condition to develop climate change adaptation solutions before the urban overheating effects and its challenges to the environment, human health, and building energy consumption, which is critical in hot arid climates with record-breaking heatwaves where society is turning to air conditioning instead of energy-efficient building envelopes. The primary aim of this study was to examine the influence of the Structural Insulation Panel (SIP) system heat transfer in energy-related aspects and contrast it with those of conventional construction systems. Therefore, a comparative study was carried out in low-income dwellings to measure the thermal transmittance of the building envelope and assess the thermal energy simulation allocated in Köppen-Geiger´s hot desert climate, characterized by typical maximum temperatures of 45°C in the summer season. The investigation ascertained the levels of energy consumption, the capacity of the air conditioning system, the associated energy costs, and the potential decrease in carbon footprint. The study shows SIP as a viable construction system alternative, the evidence shows a 20% heat gain reduction, the Heating, Ventilation, and Air Conditioning (HVAC) system capacity was reduced by 38%, and energy cost by 27%. The system also contributes to the decarbonization and carbon footprint by 20%. Likewise, to reduce the heat flow, a crucial element is evident, since transmittance in thermal bridges significantly affects the heat transfer in these low thermal conductivity systems with structural reinforcement elements.

Sequential transcranial electrical stimulation in patients with dyscirculatory encephalopathy associated with post-COVID syndrome

BACKGROUND: The primary hypothesis for the use of sequential transcranial electrical stimulation therapy in the rehabilitation of patients with dyscirculatory encephalopathy associated with post-COVID syndrome is the potential synergistic effect on the central nervous system. Specifically, the method combines brain micropolarization — involving neocortex neurons and diencephalic brain stimulation — affecting limbic system structures. This synergy is expected to improve connections between cortical and subcortical structures, as well as neurohumoral regulation. AIM: To study the effectiveness of complex medical rehabilitation involving sequential transcranial electrical stimulation therapy in patients with dyscirculatory encephalopathy associated with post-COVID syndrome. MATERIALS AND METHODS: An open, prospective, randomized comparative study included 142 patients with dyscirculatory encephalopathy: 79 female (55.6%) and 63 male (44.4%) patients, aged 59 (45–69] years. The average disease duration was 8.4 years, with a period after coronavirus infection of 3.6 months. After randomization, patients in Group 1 (comparison group 1, n=48) received brain micropolarization; Group 2 (comparison group 2, n=46) received diencephalic brain stimulation; and Group 3 (main group, n=48) received both therapies sequentially. Treatment outcomes were evaluated based on changes in clinical symptoms over time and a battery of neuropsychological tests. RESULTS: In Group 3, which received sequential transcranial electrical stimulation therapy, all symptoms of dyscirculatory encephalopathy showed a significant improvement (1.2–1.6 times) compared to baseline (p 0.05–0.001). For brain micropolarization alone (Group 1), there was an average reduction in the severity of symptoms such as cranialgia, memory and attention deficits, irritability, and sleep disturbances by 1.2–1.4 times. In Group 2, diencephalic brain stimulation resulted in an improvement in tinnitus, fatigue, work productivity, and dizziness by 1.3–1.4 times. In the main group, there was an overall alleviation of all psychophysiological issues (1.1–2.0 times; p 0.05–0.01); in comparison groups 1 and 2, improvement was 1.1–1.5 times and 1.2–1.8 times, respectively. CONCLUSION: Medical rehabilitation using a combined approach (sequential application of brain micropolarization and diencephalic brain stimulation) alongside pharmacological support in patients with dyscirculatory encephalopathy associated with post-COVID syndrome is shown to be the most effective due to the pronounced neurotropic effect of the physical factors involved, allowing for the correction of a whole range of neurological, neuropsychological, and motor disorders.

Asian adult sleep medicine fellowship training curriculum: one curriculum, many contexts.

To develop a comprehensive Asian adult sleep medicine fellowship training curriculum to address the significant disparities in sleep medicine training across Asia, guided by the principle of "One Curriculum, Many Contexts," providing a standardized yet adaptable framework for sleep medicine education across the diverse healthcare landscapes of Asian countries. The curriculum development process involved a gap analysis, comprehensive literature review, and expert consensus through a modified RAND appropriateness method (RAM)/Delphi survey. The curriculum offers two flexible tracks: a one-year program (Track A) and a two-year program (Track B), accommodating varied educational pathways and healthcare system structures across Asia. Key features of the curriculum include detailed learning outcomes, competency-based educational content, and recommendations for teaching and learning activities. The assessment strategy incorporates summative and formative methods, with standard setting and program evaluation guidelines. The curriculum also provides recommendations for program accreditation, fellow-faculty ratios, and funding considerations. The Asian adult sleep medicine fellowship training curriculum provides a standardized yet adaptable framework for sleep medicine education across diverse Asian healthcare landscapes. By emphasizing flexibility and customization while maintaining high training standards, the curriculum aims to bridge the gap in sleep medicine training across Asia, ultimately improving the quality of sleep healthcare and patient outcomes throughout the region.

The Subordinated Other: Exploring Gender and Environmental Subjugation in Barbara Kingsolver’s Prodigal Summer through Val Plumwood’s Theory of Master Model

ABSTRACT One of the fundamental issues in mankind’s pursuit of greater development is the protection of the environment and other subordinated groups, which has been a major concern of ecofeminists in recent decades. Claiming that environmental issues are feminist issues, ecofeminists argue that the domination of women correlates with the exploitation of nature and there are critical linkages between the two. Val Plumwood, one of the most distinguished environmental philosophers, describes the oppression of humans and nature as a phenomenon stemming from a system of dualistic structures. According to this notion, these structures are psychologically manifested through the identity of the Master Model in which the Self recognizes the Other not as a distinct center of agency but rather as either a hindrance to or a resource for its needs. Examining various forms of oppression, Barbara Kingsolver in Prodigal Summer illustrates the social inequalities and the destructive attitudes toward nature and argues that they stem from the existing hierarchical dualisms in society. Accordingly, the article aims to portray these dualistic structures, their consequences, and the ways through which they are manifested psychologically. The article concludes that the domination of women and nature are correlated and lie behind many environmental degradations and oppressive attitudes toward women.

Combining Effective Hamiltonians and Brillouin-Wigner Approach: A Perturbative Approach to Spectroscopy

Abstract The numerical cost of variational methods suggests using perturbative approaches to determine the electronic structure of molecular systems.
In this work, a sequential construction of effective Hamiltonians drives the definition of approximate model functions and energies in 
a multi-state Rayleigh-Schrödinger perturbative scheme. A second step takes advantage of an updated partitioning of the Hamiltonian
to perform a state-specific Brillouin-Wigner energy correction based on a well-tempered perturbation expansion. 
The multi-step RSBW method is exemplified on model-Hamiltonians to stress its robustness, efficiency 
and applicability to spectroscopy determination.

Full-field dynamic strain reconstruction of rotating compressor blades based on FBG sensors

Abstract Rotating compressor blades experience complex alternating loads during service, altering their stress–strain distributions and peak stress positions over time. Accurate measurement of these strains is crucial for identifying the areas of stress concentration. This paper presents a structural health monitoring system using fiber Bragg grating (FBG) sensors to record dynamic strains on laboratory-scale rotating blades, and a tailored full-field strain reconstruction methodology, which successfully identifies the magnitude of the strains and the areas of stress concentration of the blades at different rotational speeds. First, dynamic strain at selected blade points was monitored using FBG sensors, with raw signal data enhanced by the empirical wavelet transform method to reduce noise and clarify signals. An analytical framework was developed to relate blade rotational velocity to signal period, enabling precise speed calculation and accurate strain analysis. The improved-Kriging interpolation technique was then used to reconstruct comprehensive strain profiles. A comparative analysis showed an average strain relative error of 7.4% between predicted and actual values, demonstrating the methodology’s robustness and precision.

Research on the design of prefabricated curved structure production capacity residential energy system: a case study of an entry of 2022 China International Solar Decathlon Competition- 'Solar Ark 3.0'

Under the severe situation of global warming, the problem of high energy consumption and carbon emissions in the construction industry need to be addressed urgently, and the method to promote the development of the construction industry in the direction of low-carbon sustainability has become a problem to be solved. Taking ‘Solar Ark 3.0’, the entry of Southeast University United Team in the Third China International Solar Decathlon Competition (SDC2022), as an example. This study proposes the wind and solar complementary capacity design, multi-mode energy storage design, intelligent energy use design and production, storage and use of multi-energy complementary intelligent energy management methods through the exploration of the integrated design and construction of curved structure housing and energy system. These designs of ‘Solar Ark 3.0’ improve the utilization efficiency of renewable energy in buildings and also provide methods for the integrated design of curved structural housing and energy systems.

Impact of seismic demand on construction costs for buildings up to 8 storeys high

The legally binding earthquake performance requirements in New Zealand's Building Act and Building Code emphasise building collapse prevention, allowing for a certain degree of damage to resist the seismic load. However, societal expectations demand that buildings remain operational after an earthquake. This research aims to understand the true cost of up to 8 storeys high building structures that remain operational after an earthquake. Our assumptions are: 1) higher seismic demand is expected to have a limited impact in overall construction costs, and quite minimal impact on total development costs, and 2) the influence of seismic resilience on construction costs is different depending on the structural system. An extensive construction costs database was developed including the most typical structural and foundation systems. The main conclusions are that 1) the effect of location and floor type on construction costs is not critical, 2) the impact of a higher seismic demand on construction costs depends on the structural system, and 3) foundation type has a large influence on construction costs but seismic demand does not. Engineers should prioritise stiff lateral systems because the cost implications of having a stiffer structural system are minimal, especially when considering the development costs. The cost implications of having more resilient buildings that can be readily occupied after an earthquake are negligible, and New Zealand should move towards stiff, damage resisting structures using well understood structural systems like RC walls. Society expects this from our buildings, our engineers are trained and capable to design them, and the extra cost is minuscule.

On the hysteretic bending behavior of slack metallic cables

Short and slack stranded metallic cables are encountered in several technical applications to connect different structures or different parts of the same structural system. A couple of relevant examples are provided by flexible-bus conductors used in high-voltage electrical substations or passive damping devices installed on overhead electrical lines, such as Bretelle dampers. Bending behavior of metallic cables is nonlinear and non-holonomic due to the onset and propagation of relative sliding phenomena between the wires. While taut suspended cables have been widely studied in the literature under the classic assumptions of small sag and perfect flexibility, whenever dealing with short and slack cables, the aforementioned hypotheses typically cease to be valid, and the bending stiffness contribution plays a significative role in the determination of the overall structural response. In the present paper, two different modeling strategies for the description of the bending behavior of short and slack stranded cables are presented. The first (discrete bending model) describes the cable as a composite structural element made of wires, which are individually modeled as curved elastic thin rods interacting through normal and tangential contact forces. The second (phenomenological bending model), instead, relies on a description of the cable bending process based on an application of the well-known Bouc-Wen hysteresis model. Applications of the proposed models are presented both at the cross-sectional and at the structural levels. The systematic comparison between theoretical and experimental results allows to assess the performance of the two proposed bending models when used with “nominal” values of the model parameters, which are estimated only on the base of the knowledge of the material and geometric properties of the strand. Moreover, a back-analysis of the model parameters is carried out to get an insight on internal mechanical parameters of the cable and on the overall cross-sectional bending response (e.g. bending stiffness values).

The utility of homomorphism concepts in simulation: building families of models from base-lumped model pairs

In this tutorial review paper we explain the concept of homomorphism and identify some principles that justify homomorphism construction based on the homogeneity of structure and coupling in systems with multiple components. We discuss some simple examples to show how these underlying justifying conditions can arise. Examples include brain simulation, combat attrition, and the greatly reduced computational complexity represented by Pascal’s triangle. Homomorphism is also shown to be fundamental for constructing approximate low-resolution models. Models that simplify complex time-demanding simulation models are often used as surrogate or metamodels in system optimization. However, such models are fitted typically to computationally derived response surfaces and not structurally related directly to the originals using homomorphisms as described here. Along these lines, we show how homomorphism plays an essential role in a novel approach being developed to strongly control tree expansion in state space explorations of stochastic system simulation.

A fractional adaptive type-2 fuzzy structural control system: Theoretical/experimental study

A new modified sliding mode control (SMC) method based on type-2 fuzzy neural networks (T2FNNs) is introduced for the active mass damper (AMD) systems. An adaptive T2FNN is used in the switching part, and another adaptive T2FNN is used to estimate the uncertainty of the AMD system. T2FNNs are adopted to predict the system’s uncertainties and establish a dynamic model of the AMD system, independent of the mathematical model. The chattering phenomenon is also taken into account and analyzed. The stability is studied by using the Lyapunov approach to derive training rules for both T2FNNs in dynamic modeling and switching part. Numerical simulation and experimental verifications confirm the feasibility and effectiveness of the designed T2FNN based SMC. The results reveal that the designed controller outperforms the conventional controllers in reducing the vibration peak and reducing the root mean square (RMS) value of structural displacement and acceleration. It also exhibits good robustness against external disturbances and structural dynamic perturbations. The suggested algorithm combines the advantages of adaptive control and fuzzy logic, addressing the issue of chattering in control and overcoming the lack of self-learning capability in conventional SMCs.

Optimum Design of Hybrid Base Isolation and Tuned Liquid Damper Systems for Structures under Near-Fault Ground Motions

Optimum Design of Hybrid Base Isolation and Tuned Liquid Damper Systems for Structures under Near-Fault Ground Motions

Recursive Bayesian estimation of wind load on a monopile-supported offshore wind turbine using output-only measurements

Offshore wind turbine structures experience combined wind and wave loading during their lifetime, and the cyclic characteristics of these loads significantly impact the fatigue life of the support structure. Continuous monitoring of stress-related quantities, such as strain time histories at hotspot locations of the structure, can help to estimate the fatigue life. However, sparse measurements from the substructure necessitate using a digital twin as a tool for structural health monitoring by creating a virtual model. This virtual model relies on real-time input loads for virtual sensing and stress-related quantities prediction. However, the exact loading on these structural systems is often unknown or estimated with considerable uncertainty. This paper implements a recursive window-based Bayesian estimator for input load estimation and virtual sensing of acceleration and strain time history at unmeasured critical locations using output-only measurements. The estimator is numerically and experimentally validated in the context of input load estimation for an offshore wind turbine, and the results are compared with a traditional augmented Kalman filter and a linear regression approach for the quasi-static component of loading. The method is first demonstrated through a numerical study using a finite element model of a 6 MW offshore wind turbine, where input wind load time histories are accurately estimated. Then, the framework is applied to the real data measured from an offshore wind turbine in the North Sea. The study demonstrates the window-based Bayesian input estimator as a promising tool for the digital twinning of offshore wind turbines, demonstrating superior accuracy in input load estimations and full response predictions compared to the augmented Kalman filter and linear regression methods without the constraint of collocated measurements at input load locations.

Causality structures in nonlinear dynamical systems

Causality structures in nonlinear dynamical systems

A Neuro-Fuzzy Solution for Inverse Kinematics of Redundant Manipulators

Abstract: This paper presents a novel approach for solving the inverse kinematics (IK) problem of redundant robotic manipulators using an Adaptive Neuro-Fuzzy Inference System (ANFIS). Redundant manipulators, characterized by having more degrees of freedom (DOF) than necessary for a task, introduce complexity in their IK solutions due to their non-linear, time-varying, and transcendental nature. Traditional methods such as algebraic or geometric solutions are often computationally intensive and can suffer from issues such as singularities. This study leverages ANFIS, combining the learning capability of neural networks with the logic-based structure of fuzzy systems, to predict IK solutions for 5-DOF and 7-DOF manipulators. The Denavit-Hartenberg (D-H) notation is employed for the kinematic modeling of robot links. Comparative analysis of the predicted IK values using ANFIS demonstrates its high accuracy and efficiency, as validated by surface and residual plots. The results show that ANFIS can be effectively utilized for fast and reliable IK predictions, offering a robust alternative to traditional approaches. This method can be applied in robotic systems requiring high precision in constrained or dynamic environments.