Search Results (1,645)

Multibody dynamics (MBD) simulations involving hundreds to thousands of bodies give rise to large-scale, sparse, and structurally indefinite linear systems. Traditional direct solvers incur prohibitive memory and computational costs, while iterative methods suffer from slow convergence due to severe ill-conditioning. This paper proposes HPI-MBD, a hybrid preconditioned iterative framework. It combines an algebraic multigrid (AMG) for global error smoothing with a block Jacobi preconditioner tailored to the kinematic constraint graph. The framework exploits graph topology to construct a block-diagonal Schur complement approximation, incorporates Tikhonov regularisation for redundant constraints, and maintains $\mathcal{O}\left(n\right)$ work per iteration, where n is the number of degrees of freedom. A rigorous spectral analysis supports the problem-size independent convergence of the Minimal Residual (MINRES) solver. Evaluated on five benchmark systems with ${10}^4$ to ${10}^6$ degrees of freedom, the HPI-MBD achieves speedups up to $12.7\times$ and memory reductions up to 68% against MA57, with comparable gains against PARDISO. All solutions maintain relative residuals below ${10}^{-6}$. Comparisons against ILU(0)-preconditioned Generalised Minimal Residual (GMRES), Finite Element Tearing and Interconnecting method (FETI-1), and a block-Jacobi-only variant confirm the essential role of AMG. The framework exhibits near-linear scalability and strong parallel efficiency on up to 32 processors, along with robust performance under redundant constraints and varying time step sizes. These results position HPI-MBD as a scalable, memory-efficient alternative for real-time simulation in virtual prototyping, robotics, and biomechanics. Full article

This study presents a reusable adjoint-octree multilevel fast multipole algorithm (MLFMA) for full-wave radar scattering analysis of multi-state unmanned aerial vehicle (UAV) formations. The method is motivated by remote-sensing applications in which dense angular sampling or long motion sequences are required for physically reliable signature generation. Instead of rebuilding a global octree for the full formation at every motion state, the proposed approach assigns each sub-target an independent target-attached local octree that translates and rotates with the rigid body. This preserves mesh–cell affiliation in the body-fixed frame and separates the system operator into a state-invariant intra-target near-field component and a state-dependent inter-target far-field component. Consequently, near-field matrices and sparse approximate inverse preconditioners are assembled once and reused throughout the state sequence, while only inter-target far-field coupling terms are updated. The method is evaluated for six representative UAV formations at 3.5 GHz using monostatic radar cross section (RCS) over a full azimuth sweep. Across all tested formations, the proposed solver reproduces the RCS behavior of conventional MLFMA while substantially reducing computational cost. For Formation A, the center-state total time decreases from 251.4 s to 66.06 s; for Formation C, it decreases from 470.95 s to 76.06 s. Over 100-state sequences, the resulting acceleration reaches approximately 11.8-fold and 15.2-fold, respectively. Jitter-envelope analysis further shows that orientation perturbation produces stronger signature uncertainty than planar displacement. The proposed framework therefore provides an efficient and physically consistent forward solver for radar remote-sensing studies of cooperative UAV formations. Full article

Suspended ceiling systems are among the most seismically vulnerable non-structural components in buildings, posing significant life-safety risks and economic losses, yet understanding their full-field kinematic behavior under seismic loading remains a major experimental challenge. Conventional contact sensors offer limited spatial coverage and can alter the dynamic properties of lightweight panels due to mass loading. In contrast, non-contact optical alternatives are rarely feasible in shake-table environments due to restricted viewing angles, extensive areal coverage requirements, and the risk of equipment damage from falling panels. This study proposes an end-to-end three-dimensional displacement measurement framework for large-scale shake-table testing of suspended ceiling systems, employing consumer-grade cameras with purpose-built tools that cover the complete experimental workflow, including motion-based video trimming, semi-automated calibration, a robust multi-stage image-tracking pipeline that maintains trajectory continuity under extreme inter-frame displacements, and a ceiling system motion visualization and analysis tool. The framework was validated through a full-scale shake-table experiment continuously tracking 324 spatial nodes across 81 ceiling panels, achieving an RMSE below 3 mm in all spatial directions and exact peak-frequency agreement in 9 out of 10 test cases. A parallel processing architecture reduced total processing time from over 27 h to under 10 min without GPU acceleration, and six-degree-of-freedom rigid-body analysis resolved the complete panel failure sequence from constrained oscillation through multi-axis rotation to gravitational free fall, a level of kinematic detail unattainable with conventional instrumentation. This framework establishes a practical, scalable foundation for full-field seismic performance assessment of non-structural systems where conventional instrumentation is physically or logistically infeasible. Full article

The Absolute Nodal Coordinate Formulation (ANCF) is extensively utilized in the field of flexible multibody dynamics because it offers a constant mass matrix and inherently eliminates Coriolis forces. However, ANCF requires the computation of complex nonlinear elastic internal forces and thermal deformation forces at each time step, which imposes a significant computational burden. To alleviate this burden, researchers have developed local linearization (LL) methods. The local linearization method constructs constant elastic and thermal stiffness matrices within a small range by means of Taylor expansion, effectively reducing the number of stiffness matrix updates. But the method suffers from error accumulation and relies on displacement-based update criteria that are inefficient for systems with large rigid-body motion. This paper proposes an improved local linearization (I-LL) method to address these issues. Two key enhancements are introduced: (1) the update criterion for the elastic and thermal stiffness matrices is modified from displacement-based to total strain-based, enabling more accurate and size-independent updates; (2) accurate elastic or thermal deformation force calculations are inserted within the local linearization iteration cycle to mitigate error accumulation. These two improvements reduce the number of calculations of the nonlinear internal forces and, at the same time, lessen the error accumulation in the simplified model. The accuracy and effectiveness of the I-LL algorithm are demonstrated through three numerical examples. Full article

This study investigates a polymorphic underwater vehicle designed to combine long-range cruising with stable underwater operation, reducing dependence on surface support vessels. By introducing a foldable polymorphic structure, the vehicle can switch configurations, including serial and parallel. However, underwater environments often contain obstacles, and the vehicle may collide with them during the folding process. To prevent collisions between the vehicle and surrounding obstacles during the folding process, this paper investigates the motion envelope of the vehicle and examines how motion parameters and mass distribution influence the motion envelope. In this work, the polymorphic underwater vehicle is modeled as a multibody system operating under a neutrally buoyant condition. Based on space robot modeling methodologies and the linear and angular momentum theorems, the equations of motion of the polymorphic underwater vehicle are derived and verified using the Adams software 2020. In summary, the present study establishes a clear relationship between motion parameters, mass distribution, hydrodynamic effects, and the resulting motion envelope of a polymorphic underwater vehicle. The results show that the attitude of the vehicle during the folding process is uniquely determined by the joint angles, and a larger relative speed between the outer and inner folding motions produces a more compact attitude during the folding process. Mass distribution further influences the motion envelope of the vehicle: concentrating mass toward the center of the vehicle shifts the overall motion envelope upward, whereas concentrating mass toward both ends of the vehicle shifts it downward. In addition, hydrodynamic forces introduce an upward velocity component of the vehicle in the vertical direction during the folding process, which leads to an upward shift in the overall center of mass of the vehicle. Full article

Emerging sustainability demands and calls for lowering materials’ environmental impact have directed authors to examine a class of polymers characterised as covalent adaptable networks and referred to as vitrimers. In this study, composite plates were made using vitrimer resin as the matrix material and continuous unidirectional flax fibre fabrics as the reinforcement. A specific early-stage composite part production method is proposed to make the multi-ply flax/vitrimer composite plate. The development of natural fibre–reinforced vitrimer composites is of clear research interest as a promising approach towards sustainable and recyclable novel material systems. Specimens prepared with all the plies oriented 0° exhibited a 129.4 MPa tensile strength and a 12.4 GPa tensile modulus, indicating a 334% increase in tensile strength when compared to the average value of 29.8 MPa obtained for neat vitrimer specimens and a 1140% improvement in the tensile modulus compared to the 1.0 GPa reached for neat vitrimer. The specimens whose plies were oriented 90° are found to deliver a tensile strength of 12.2 MPa and a 1.3 GPa tensile modulus. Applying the classical composite material micromechanics equation to calculate the 0°-direction tensile modulus demonstrated a good agreement with the experimentally obtained value—a 9.6% difference was discovered. Proper fibre/matrix interfacial adhesion was detected when the flax/vitrimer specimens’ surfaces after fracture were examined under scanning electron microscope. The research findings on tensile mechanical properties reveal that the observed flax/vitrimer composites may be potential candidates for replacing typical synthetic fibre–reinforced materials rated for automotive applications and intended for in-plane loaded parts, particularly some inner-body vehicle elements. Full article

With the advancement of systematic ecological protection and restoration, ecosystem coordination assessment and multi-scale differentiation analysis have become increasingly important for regional ecological governance. In this context, this study develops a multi-scale coupling coordination evaluation framework for the mountain–water–forest–farmland–lake (MWFFL) system in Dangtu County, Anhui Province. The framework integrates 14 indicators across five subsystems, uses a combined weighting method based on the Entropy Weight Method and Analytic Hierarchy Process, and applies the coupling coordination degree (CCD) model and trend analysis to characterize inter-system coordination and its spatiotemporal patterns at the regional and ecosystem scales. The results indicate that land use is dominated by arable land, with water bodies forming the structural backbone and construction land distributed in clusters. From 2020 to 2024, the mean CCD remained stable around 0.675, indicating that the overall coupling coordination level was relatively stable. Spatially, the CCD pattern remained higher in the southwest and lower in the northwest, with a new high-value clustering zone emerging in the south. At the ecosystem scale, the four ecological restoration units showed distinct spatiotemporal patterns of coupling coordination. This multi-scale MWFFL evaluation framework supports regional ecological monitoring and provides a reference for restoration effectiveness assessment in similar regions under the life community concept. Full article

Ionizing radiation induces reactive oxygen species (ROS) and inflammatory signaling that contribute to both therapeutic efficacy and normal tissue toxicity. While the effects of high-dose radiation are well characterized, responses to low-dose-rate radiation (LDRR) remain inconsistent and are not adequately explained by conventional linear dose–response models. To address this gap, we conducted a narrative review of recent experimental studies across multiple biological systems, including body fluids, joint microenvironments, and reproductive tissues, focusing on redox and immune-related responses under LDRR conditions (dose rates: 0.39–3.49 mGy/h). Literature was identified through PubMed/MEDLINE, Web of Science, and Google Scholar, with emphasis on studies published between 2015 and 2026. These studies demonstrate that LDRR elicits nonlinear, dose-dependent effects that vary across biological compartments and involve coordinated changes in oxidative stress, immune signaling, and metabolic regulation. Based on this synthesis, we propose a unifying framework of nonlinear redox–immune coupling, in which oxidative stress functions as a threshold-dependent regulator and immune responses follow a biphasic trajectory characterized by activation at lower dose rates and attenuation or adaptation at higher levels. These responses are strongly influenced by the local microenvironment, resulting in compartment-specific variability. This integrated perspective supports a shift from dose-centric to systems-level interpretations of radiation biology and provides a basis for improving biomarker development, risk assessment, and therapeutic strategies in chronic low-dose radiation exposure settings. Future research priorities include time-resolved mechanistic studies to define compartment-specific redox thresholds, validation of candidate biomarkers under identical multi-compartment experimental conditions (e.g., GSH/GSSG ratio, 8-OHdG, circulating cytokine panels including IL-10/TNF-α ratio), and integration of subject-specific biological variables (e.g., age, sex, and baseline redox capacity) into predictive models of LDRR response. Full article

Mucopolysaccharidosis (MPS) are a group of inherited lysosomal storage genetic disorders that affect the body’s ability to break down glycosaminoglycans (GAGs) due to the deficiency of required enzymes. This leads to depositions of these GAGs in various tissues and organs resulting in multi-systemic manifestations including pulmonary and sleep related issues. In recent years, there have been significant advancements in therapeutic options and supportive management which have led to the overall improvement in respiratory care, culminating in improved quality of life for MPS patients. Management of pulmonary and sleep disorders in mucopolysaccharidosis requires a multidisciplinary approach due to the multi-systemic affectation of the genetic disorders. Therapeutic options such as enzyme replacement therapy (ERT) and hematopoietic stem cell transplantation (HSCT) have yielded varying success in mitigating respiratory complications. Emerging treatments such as gene therapies have shown exciting and promising results thus far. Supportive therapies such as airway clearance, regular vaccination and use of positive airway pressure devices are also essential. Pre-operative airway and anesthesia planning is critical to mitigate peri-operative and post-operative complications. Early diagnosis, close monitoring and a patient focused individualized approach are essential for respiratory optimization and overall improvement in clinical outcomes. This review article aims to discuss these advancements in a comprehensive format, making it accessible to medical providers who care for this subset of patients. Full article

Background/Objectives: Patient-specific subperiosteal implants are increasingly used to treat severely atrophic ridges due to advances in digital planning and additive manufacturing. This study aimed to evaluate the effects of material type and implant configuration on stress distribution in subperiosteal implant systems and to compare their overall biomechanical performance using a multi-criteria decision framework. Methods: A three-dimensional model of a severely atrophic maxilla was reconstructed to simulate four clinical scenarios combining two configurations (one-piece and two-piece) and two materials (titanium and 60% carbon fiber-reinforced polyetheretherketone). Finite element analysis was conducted to assess stress distribution within the implant body, fixation screws, prosthetic framework, and surrounding bone under vertical and oblique loading conditions. Maximum and minimum principal stresses were evaluated in bone, whereas von Mises stresses were calculated for implant components. The resulting biomechanical indicators were subsequently integrated using an entropy weight–TOPSIS multi-criteria decision analysis. Results: Principal stresses in the surrounding bone showed minimal variation between titanium and 60% carbon fiber-reinforced polyetheretherketone across all configurations. Implant configuration had a more pronounced effect on implant body stress. Under oblique loading, the two-piece configuration demonstrated substantially higher implant stresses than the one-piece design, whereas under vertical loading, lower implant stresses were observed in the two-piece configuration. The multi-criteria analysis ranked the one-piece titanium model highest under oblique loading and the two-piece titanium model highest under vertical loading. Conclusions: Implant configuration and loading direction influenced biomechanical behavior more than material selection in patient-specific subperiosteal implants. Full article

Wireless Body Area Networks (WBANs) have become an essential component of modern Internet of Medical Things (IoMT) healthcare systems, enabling continuous monitoring of patient physiological signals through wearable sensors. Despite their advantages, WBAN environments remain highly prone to cyber threats, privacy breaches, and single points of failure. To address these risks, this work proposes a Hybrid Multi-Metric Anomaly Detection (HM-MAD) framework deployed on the NodeMCU-32S platform with BLE 5.0 connectivity for secure continuous glucose monitoring (CGM) data transmission. The detection model simultaneously analyses physiological signals, system-level parameters, and network-level communication metrics, enabling the reliable identification of multiple cyberattacks. The proposed system focuses on securing data transmission against relay attacks, where attackers induce communication delay without modifying payloads, potentially leading to false glucose readings, improper insulin dosage delivery, unauthorized control or denial-of-service. The Convolutional Neural Network (CNN) and Bi-Directional Long Short Term Memory (BiLSTM) model classifies attack types including timing manipulation, replay attacks, power glitches, firmware tampering, and sensor spoofing. Experimental evaluation demonstrates that the proposed CNN + BiLSTM framework achieves 94.6% detection accuracy with an average inference latency of 15 ms, representing a 50% latency reduction compared to Transformer-based intrusion detection models (30 ms), while simultaneously reducing computational overhead by 28% in terms of floating-point operations and memory utilization. These results indicate that the HM-MAD framework provides an effective and scalable solution for protecting resource-constrained IoMT healthcare systems against emerging cyber threats. Full article

Global shifts in energy policy have contributed to an increase in electricity generation from renewable sources, which introduces unique issues with volatility and grid reliability. Robust grid-scale energy storage methods must fill the gap between generation and consumption. Flywheel energy storage (FES) is a mechanical technology that utilizes the stored kinetic energy of a rotating body, but is typically only suited for shorter-term frequency regulation due to significant windage losses. In this work, a novel Python 3.13-based simulation and optimization tool is presented and used to optimize geometric design parameters for efficiency, energy density, and other metrics. The simulation utilizes a 1 degree-of-freedom, multi-regime fluid friction model with a time-marching algorithm. The optimization functionality utilizes pyswarms, a particle swarm optimization package, with adjustable search parameters and cost functions to evaluate simulation results. Optimization parameters include geometric parameters of rotor radius, shaft radius, airgap width, and airgap height; material properties of mass and moment of inertia; and initial angular velocity. An optimal initial angular velocity is found for a particular geometry, lasting 30 times longer until self-discharge versus the worst values. This work can inform the design of flywheel systems to minimize windage losses and promote the technology’s utility for longer-term energy storage. Full article

LIFE REVIVE aims to restore ecological status and ecosystem services in the Lima and Vouga river basins (NW Iberian Peninsula), where hydromorphological alteration and hydropower-driven flow regulation are major causes of water bodies failing to reach Good Ecological Status under the EU WFD. The project targets key pressures such as longitudinal fragmentation by weirs and dams, artificial flow regimes, degradation of spawning substrates, and the spread of invasive aquatic plants, which strongly affect fish communities, including sea lamprey, salmonids, and other diadromous species. Technically, the project combines barrier removal or eco-adaptation, nature-like fish passes, and spawning-habitat renaturalisation with optimized environmental flow regimes (EFR) downstream of important hydropower systems, explicitly accounting for present and future hydroclimatic scenarios. Multi-scale ecohydrological modelling (species distribution models, habitat suitability models, GLM/GAM approaches) will quantify fish–flow–habitat relationships and support the definition of operational EFR guidelines that balance ecological requirements with hydropower and agricultural constraints through joint work with the main Portuguese hydropower operator, EDP. Impact evaluation is structured around a rigorous BACI monitoring design in intervention and control tributaries, using standard WFD biological indices for fish and aquatic/riparian vegetation, hydromorphological indices (HQA, HMS, RHS), and project-specific Key Performance Indicators for water quality, biodiversity, and habitat. Expected outcomes include the restoration of at least 51 km of rivers towards free-flowing conditions, reduced hydromorphological pressure in more than 20 km of heavily modified river stretches, and measurable increases in the distribution and abundance of fish species and native vegetation. A strong communication and capacity-building programme underpins public engagement, while a decision matrix for barrier prioritization, technical workshops, and pilot replications in additional basins (e.g., Alva, Mouro, Deva, and Tea in Galicia) are designed to maximize transferability, policy uptake, and long-term sustainability of the solutions beyond the project lifetime. Full article

As a core component for restraining cab roll, the lateral stabilizer bar bears continuous complex alternating loads during vehicle operation, making it highly susceptible to fatigue failure that may trigger severe traffic accidents. Therefore, fatigue analysis of the lateral stabilizer bar is of great significance. To address the drawbacks of conventional direct load testing, such as difficult sensor arrangement and long test cycles, this paper proposes a fatigue-load decomposition and life evaluation method, combining multi-body dynamics and virtual iteration. Firstly, target signal spectra of the frame are obtained via real-vehicle road tests, and a high-precision system dynamic model is established with key suspension parameters. Subsequently, virtual iteration technology is adopted to accurately inverse-solve load spectra at critical points of the lateral stabilizer bar. Finally, the finite element model of the lateral stabilizer bar is validated through modal tests, and the fatigue life and vulnerable regions of the lateral stabilizer bar are predicted using the material S-N curve. Compared with traditional physical testing methods, the proposed method effectively avoids barriers to direct testing under complex operating conditions. It not only greatly reduces testing difficulty and time costs but also ensures the accuracy of load extraction and system analysis. Full article

Whole-body dynamic positron emission tomography/computed tomography (WBD-PET/CT) has transformed medical imaging, enabling the fusion between (i) detailed anatomical maps of the human body and (ii) quantitative multi-parametric functional maps of specific biochemical and physiological processes across the human body beyond the semi-quantitative limitations of static PET/CT imaging. Latest developments in systems hardware, particularly with the introduction of long-axial-field-of-view (LAFOV) and Time-of-Flight (TOF) PET scanners and low-dose CT scanners, and in data analysis, primarily with direct parametric PET image reconstruction and Artificial Intelligence, offer unprecedented opportunities towards the wide clinical adoption of the superior quantitative accuracy and precision of WBD-PET/CT imaging overcoming current challenges, such as data acquisition complexity and long scan durations. This review aims to summarize the latest developments, current challenges, and emerging opportunities in WBD-PET/CT, emphasizing its potential to broaden the diagnostic and theranostic role of PET/CT in clinical practice. Full article