The research, led by Azlan Adnan of Universiti Teknologi Malaysia together with Yuyun Tajunnisa and colleagues at Institut Teknologi Sepuluh Nopember in Surabaya, Indonesia, combines full-scale laboratory testing with advanced computer simulation to trace the entire chain of seismic damage, from the first hairline crack in a joint to the collapse of an entire frame. The work was funded by the Indonesian Endowment Fund for Education under the EQUITY Program and supported by Malaysia’s Public Works Department, which supplied technical data for the connection details studied.

At the heart of the study is a deceptively simple structural element. In many precast industrial buildings, particularly in Southeast Asia, beams are not cast monolithically with columns. Instead, they are supported on nibs, short cantilevered projections that carry the beam’s reaction through a combination of bearing pressure, dowel action of any projecting reinforcement, and friction. This arrangement speeds up construction enormously, but it also creates a discontinuity in the load path precisely where seismic forces concentrate. When a frame sways during an earthquake, the beam-to-column interface must transfer alternating moments and shears through a joint that was never designed as a continuous monolithic element.

To understand how such a joint actually deforms, the team built a full-scale specimen of a nib connection and subjected it to cyclic loading, the laboratory equivalent of the back-and-forth shaking an earthquake delivers. The test followed internationally recognized protocols for cyclic seismic testing of components, applying progressively larger displacement cycles while measuring the force resisted by the joint. The resulting load-deformation loops, known as hysteresis curves, revealed how stiffness degrades and energy is dissipated as cracking, bond slip, and concrete crushing accumulate at the nib. These experimental curves are the gold standard for characterizing connection behavior, but they describe only a single joint, not a whole building.

That is where the hybrid modeling strategy of the study becomes significant. The researchers first constructed a detailed three-dimensional nonlinear finite element model of the tested joint in ABAQUS, using plastic-damage constitutive models for concrete that capture the material’s degradation under cyclic loading. By calibrating this micro-scale model against the full-scale test data, they ensured the simulation reproduced the real joint’s stiffness, strength, and hysteretic shape. From the validated model, they extracted a moment-rotation relationship for the connection, a curve describing how much rotational resistance the joint provides as it is progressively damaged. Because this curve was synthesized from both experiment and simulation, the authors describe it as a hybrid moment-rotation curve, and it forms the critical bridge between component-level physics and building-level analysis.

The hybrid curve was then imported into SAP2000, a structural analysis platform widely used in engineering practice, as a custom nonlinear hinge placed at each beam-to-column interface of a complete precast frame. This allowed the global model to reproduce the complex, pinching hysteretic behavior observed in the laboratory rather than assuming an idealized elastic or perfectly plastic joint. With the frame model in place, the team ran two complementary forms of nonlinear analysis. The first, nonlinear static pushover analysis, pushes the structure laterally with a monotonically increasing force pattern to identify the sequence of damage states and the governing collapse mechanism. The second, incremental dynamic analysis, subjects the frame to a suite of earthquake ground motion records scaled to ever-higher intensities, tracking how drift demands and damage accumulate as shaking intensifies.

The output of these analyses is a set of fragility curves, probabilistic functions that express the likelihood of reaching a defined damage state at a given level of ground shaking, here quantified by peak ground acceleration. Fragility curves are the workhorses of modern seismic risk assessment: they allow engineers, insurers, and code writers to translate a hazard forecast into an expected probability of damage. For the precast frame with nib connections resting on rock sites, the results are encouraging. The probability of first cracking, corresponding to the Immediate Occupancy performance level at which a building remains safe to use without significant repair, begins to rise at a peak ground acceleration of about 0.20 g. More strikingly, the probability of reaching the Collapse Prevention threshold, the point beyond which the structure is on the verge of partial or total collapse, remains a negligible one percent even at 0.30 g, a level of shaking that would be destructive in many regions.

Those favorable numbers, however, come with an important caveat that the authors emphasize through parametric variation. When the same frame is assumed to stand on softer soils, local site amplification magnifies the ground motion transmitted to the structure, and the damage probabilities climb substantially. The finding underscores that soil-structure interaction is not a secondary refinement but a first-order control on seismic risk for precast buildings. Two identical frames on the same street can face materially different fragilities depending on what lies beneath their foundations, a fact with direct consequences for site selection, foundation design, and retrofit prioritization in moderate-seismicity zones.

The study’s broader significance lies in its methodology as much as its results. In regions of low to moderate seismicity, such as much of Malaysia and Indonesia outside the great subduction zones, large destructive earthquakes are rare enough that extensive experimental databases do not exist, yet frequent enough that vulnerability assessment matters for schools, hospitals, and industrial facilities built with precast technology. By anchoring a numerical model to a full-scale test and then propagating that validated connection behavior through pushover and incremental dynamic analyses to fragility curves, the researchers have demonstrated a transferable framework. Other connection types, from dapped-end beams to grouted duct and post-tensioned joints, could be assessed with the same pipeline, filling a persistent gap between idealized code assumptions and the idiosyncratic behavior of real precast interfaces.

For the precast industry, the message is cautiously optimistic. Nib connections, when properly detailed and founded on competent ground, appear capable of delivering adequate seismic safety in moderate seismic zones, with cracking initiating only at shaking levels that would already alarm occupants and collapse probabilities remaining vanishingly small at 0.30 g on rock. But the same analysis shows that the margin evaporates as soil softens, and that the connection, not the member, is the component that governs the whole frame’s fate. As cities across Southeast Asia and beyond continue to expand with factory-built construction, studies of this kind provide the quantitative evidence base that codes and practitioners need to ensure that speed of assembly never comes at the cost of resilience when the ground finally moves.

Subject of Research: Seismic fragility assessment of precast concrete frames with nib beam-to-column connections

Article Title: Seismic performance and fragility analysis of precast concrete frames with nib connections

Article References: Adnan, A., Tajunnisa, Y., Ramli, M. Z., Falahi Abdul Halim, N. H., Ab Kadir, M. A., Nurhadi, H., Yudoprasetyo, K., & Hariyanto, I. R. (2026). Seismic performance and fragility analysis of precast concrete frames with nib connections. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02700-9

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02700-9

Keywords: precast concrete, nib connections, seismic fragility, cyclic testing, incremental dynamic analysis, pushover analysis, soil-structure interaction, finite element modeling, earthquake engineering, beam-to-column joints, moment-rotation curves, ABAQUS

The research team, working across French institutions, built a coupled thermo-metallurgical-mechanical finite element model of tungsten inert gas (TIG) welding on S355J2N steel plates. What sets the work apart is its systematic decomposition of transformation-induced plasticity, or TRIP, the extra plastic strain that arises when steel changes its crystal structure while under stress. Previous simulations often ignored phase transformations entirely or included them only partially, treating the associated volumetric strains while neglecting TRIP altogether. The new study shows that this omission can inflate predicted residual stresses dramatically, potentially leading designers to underestimate the fatigue performance of real welded assemblies.

The experimental foundation of the study was meticulous. Six identical S355J2N specimens, each consisting of two plates measuring 100 by 50 by 15 millimeters joined in a butt configuration, were welded under identical conditions: 200 amperes of current, 14 volts of arc voltage, a travel speed of 2 millimeters per second, pure argon shielding, and no filler metal. Type-K thermocouples recorded the thermal cycles at 50 hertz, while optical microscopy and scanning electron microscopy mapped the microstructures of the fusion zone and the heat-affected zone. Three specimens had to be excluded from the thermal analysis because their thermocouples shifted during welding, a candid limitation the authors acknowledge, but the three retained welds showed cooling-time repeatability within one second.

On the modeling side, the arc’s heat input was represented by the Goldak double-ellipsoid model, whose parameters were calibrated from the measured fusion zone geometry: a half-width of 6 millimeters and a half-depth of 3 millimeters. Diffusive transformations among austenite, ferrite, pearlite, and bainite were described with the V. I. Machnienko model, while the diffusionless martensitic transformation followed the Koistinen-Marburger relation. The mechanical response used a temperature-dependent elastic-plastic von Mises formulation with isotropic hardening, implemented in Abaqus through custom subroutines handling the moving heat source, phase evolution, and stress integration. The mesh contained 67,650 elements, refined down to half a millimeter near the weld.

The thermal validation was convincing. Predicted peak temperatures matched the six thermocouple measurements with errors below 7 percent, and the cooling stage was reproduced with good accuracy, although the cooling time between 800 and 500 degrees Celsius was overestimated by roughly 12 to 14 percent at the two hottest measurement points. The metallurgical predictions fared well too: the model identified bainite as the dominant phase in both the fusion zone, at about 44 percent, and the heat-affected zone, at about 32 percent, exactly as the electron microscope images confirmed. Martensite remained a minor constituent, and the predicted hardness of roughly 240 Vickers in the heat-affected zone sits comfortably below the 380 HV10 limit recommended by the relevant ISO standard.

The heart of the paper lies in its comparison of seven mechanical modeling configurations. Approach A2, which neglects transformation strains entirely, predicted peak longitudinal residual stresses of 632 megapascals on the surface and 760 megapascals through the thickness, values approaching the steel’s yield strength. Adding only the volumetric strain of phase transformations, approach A1, trimmed those peaks by 21 to 35 percent. But the complete model, A4, which adds TRIP, cut the through-thickness peak to 473 megapascals and the region-averaged longitudinal stress from 641 to 280 megapascals, a reduction of more than half. Volumetric strain alone, in other words, tells only a fraction of the story.

Even more striking was the decomposition of TRIP itself into three distinct contributions: classical plasticity driven by stress variations, plasticity driven by temperature variations, and plasticity driven by the rate of change of phase fractions. When each term was isolated, the phase-fraction term emerged as the overwhelming driver of stress relaxation. On the surface path, it reduced the mean longitudinal stress by 51 percent, nearly matching the 53 percent achieved by the complete model, while the stress-only term managed just 9 percent. This finding is qualitatively consistent with the theoretical estimate of Leblond and colleagues, who calculated that plasticity from phase fraction variations could be roughly 25 times greater than that from temperature variations during martensitic transformation.

The study also quantified a subtler effect: the evolution of the effective yield stress during cooling, computed as a phase-weighted average of the individual phase yield stresses. Keeping the yield stress identical during heating and cooling, as many earlier simulations did, raised the predicted peak stress by about 8 to 24 percent compared with accounting for its evolution. Sensitivity analyses reinforced the robustness of the conclusions: plausible variations in high-temperature thermal properties, mesh refinement, and high-temperature mechanical assumptions shifted the mean longitudinal stress by at most a few percent, whereas the TRIP activation threshold proved to be the single most influential parameter, changing predicted stresses by up to 32 percent.

Transverse residual stresses, by contrast, remained much lower than the longitudinal ones, peaking at 178 megapascals on the surface and 384 megapascals through the thickness for the complete model. The authors attribute this asymmetry to the greater plastic deformation the plate undergoes in the transverse direction and to the narrow width of the weld bead relative to its length. The longitudinal dominance aligns with trends reported in earlier studies of arc-welded joints, including work showing that tensile residual stresses in tubular K-joints can drive fatigue cracks to half the chord thickness even under nominally compressive loading.

The practical implications are significant for anyone designing or fabricating welded steel structures. Models that ignore TRIP may substantially overestimate residual stresses and thereby underestimate fatigue performance, potentially triggering unnecessary post-weld treatments or overly conservative designs. Conversely, the finding that the phase-fraction term governs relaxation gives modelers a clear target: capturing transformation kinetics accurately matters more than refining thermal parameters. The authors caution that direct experimental validation of the residual stresses is still pending, with X-ray diffraction measurements on reserved specimens planned for a forthcoming study, along with Vickers microhardness validation and a dedicated investigation of the contact conductance between plate and welding table. Until those results arrive, this work stands as a compelling demonstration that the invisible drama of phase transformations inside cooling steel is not a modeling nicety but the decisive factor in predicting the stresses that determine whether welded structures endure.

Subject of Research: Thermo-mechanical modeling of residual stresses and transformation-induced plasticity in TIG-welded S355 structural steel joints

Article Title: Thermo-mechanical modeling of residual stresses in TIG-welded S355 steel joints

Article References: Niangaly, I., Abdennadher, M., Zouari, S., Leprêtre, E., & Dieng, L. (2026). Thermo-mechanical modeling of residual stresses in TIG-welded S355 steel joints. Results in Engineering, 32, Article 113233. https://doi.org/10.1016/j.rineng.2026.113233

Image Credits: AI Generated

DOI: 10.1016/j.rineng.2026.113233

Keywords: residual stress, TIG welding, S355 steel, phase transformations, transformation-induced plasticity, TRIP, finite element modeling, bainite, martensite, fatigue, heat-affected zone, structural steel

The physiological anchor of the review is the recognition that heart failure is, at its core, a disease of disturbed mechanics. Changes in myocardial stiffness, fiber architecture, wall stress distribution, and chamber geometry drive the maladaptive remodeling that precedes irreversible decline. The authors emphasize that conventional metrics such as ejection fraction and chamber dimensions often miss the regional biomechanical abnormalities that determine therapeutic response. This is particularly true for heart failure with preserved ejection fraction, a phenotype increasingly understood as a disorder of diastolic dysfunction, microvascular impairment, and ventricular–vascular uncoupling rather than simple pump failure. At the molecular level, dysregulation of calcium-handling proteins including SERCA2a, the ryanodine receptor RyR2, and the sodium–calcium exchanger produces distinct cellular signatures in reduced- versus preserved-ejection-fraction disease, linking subcellular dysfunction to the macroscopic stiffness and impaired relaxation that clinicians measure at the bedside.

Finite-element modeling is the computational backbone of this convergence. By combining imaging-derived geometry with constitutive laws describing myocardial tissue behavior and physiologically realistic boundary conditions, these models can quantify regional stress and strain that no global clinical index can capture. The review illustrates the power of this approach through bioprosthetic heart valves, whose durability limits remain a major clinical problem. Under cyclic loading, valve leaflets undergo progressive geometric remodeling: after roughly 50 million cycles, equivalent to about two years of in vivo function, leaflets show permanent deformation concentrated in the central belly region, accompanied by collagen redistribution rather than outright fiber rupture. Time-dependent finite-element frameworks that iteratively update material parameters and remesh geometry across loading cycles can now reproduce this staged evolution from early remodeling to stress redistribution and eventual failure.

Collagen architecture emerges as a decisive variable in these simulations. Comparative finite-element studies incorporating isotropic fiber distributions, exogenously crosslinked bovine pericardial architectures, and native porcine aortic valve fiber architectures reveal striking differences in deformation behavior. Valves with isotropic or pericardial fiber arrangements deform relatively uniformly, with maximum in-plane Green–Lagrange strains of approximately 0.2, whereas valves carrying native fiber alignment display pronounced spatial heterogeneity, particularly within the leaflet belly. The modeling also shows that stress concentrations localize precisely where calcification and structural failure are observed experimentally, providing compelling evidence for mechanobiological coupling between cyclic stress exposure, collagen organization, and mineral deposition. For heart failure care, the relevance is indirect but important: these valve studies supply validated methods for quantifying how loading conditions, device–tissue interactions, and ventricular–vascular coupling shape remodeling trajectories.

Computational predictions, however, are only as credible as their experimental validation, and this is where three-dimensional printing enters the pipeline. What began as static anatomical replication from computed tomography datasets has matured into functional phantoms that reproduce both anatomy and mechanical behavior. Multimaterial printing technologies such as PolyJet can combine compliant soft-tissue regions with rigid calcified components in a single model, a capability the review highlights as particularly valuable for replicating aortic stenosis. When such patient-specific phantoms are coupled to pulsatile flow loops, they reproduce echocardiographic features and hemodynamic profiles of severe disease, with experimental measurements of transvalvular gradients and effective orifice area closely matching patient Doppler data. Fluid–structure interaction simulations based on the immersed boundary method, validated against pulse-duplicator experiments, show good qualitative agreement in leaflet kinematics, with residual discrepancies attributed to geometric variability between leaflets, differences in collagen architecture, and turbulent flow effects at physiological Reynolds numbers on the order of 20,000.

The clinical footprint of printed models already extends well beyond the bench. In pediatric and congenital heart disease, where complex spatial relationships among chambers, great vessels, and airways defy two-dimensional imaging, printed models have improved surgical strategy selection, interdisciplinary communication, and trainee education. In structural heart interventions, patient-specific models allow bench-top rehearsal of transcatheter valve deployment, atrial septal defect closure, and ventricular assist device placement, with quantitative prediction of paravalvular leak demonstrated using tissue-mimicking aortic root phantoms and biomechanically informed parameters such as the maximum bulge index. For adults with congenital heart disease complicated by heart failure, printed models have visualized systemic right ventricles, Fontan pathways, and surgically constructed baffles, directly supporting planning for advanced therapies including ventricular assist device implantation. The review stresses a critical caveat: geometric fidelity alone is insufficient, and mechanical fidelity must be characterized under use-specific loading conditions for a printed model to serve as a meaningful biomechanical surrogate.

Artificial intelligence completes the triad by extracting clinically actionable patterns from high-dimensional data. The review surveys a hierarchy from machine learning to deep learning, noting that rigorous separation of training, validation, and testing datasets is essential to avoid information leakage and inflated performance claims. Concrete applications are already impressive: an AI-enabled electronic stethoscope detected left-sided valve disease from heart sounds with area under the receiver operating characteristic curve values of 0.76 for aortic stenosis, 0.79 for mitral regurgitation, and 0.85 for composite left-sided disease, supporting point-of-care screening. Automated software quantifies aortic annular dimensions dynamically across the cardiac cycle, and the fully automated 4TAVR pipeline performs segmentation, landmark identification, measurement extraction, and report generation from computed tomography without any user interaction. Machine learning models predicting in-hospital mortality after transcatheter aortic valve replacement achieved an area under the curve of 0.92, with logistic regression outperforming more complex architectures. Natural language processing has exposed discrepancies between quantitative measurements and narrative conclusions in echocardiographic reports, while acoustic analysis of ventricular assist device sounds identifies complications such as significant regurgitation through harmonic amplitude and rotational speed features.

The review’s most sobering contribution is its candid assessment of evidence maturity, which it finds strikingly heterogeneous across the three technologies. Finite-element approaches remain predominantly validated in retrospective or simulation-based studies with limited prospective clinical testing, earning a low-to-moderate clinical readiness rating. Three-dimensional printed phantoms are widely used for in vitro testing and procedural rehearsal, yet direct evidence linking their use to improved patient outcomes is minimal, yielding the lowest readiness score. Artificial intelligence has achieved the broadest clinical integration, particularly in imaging and risk stratification, but most models rest on retrospective datasets without robust external validation. Strikingly, the authors identified no prospective studies directly linking patient-specific finite-element descriptors or phantom testing to hard endpoints such as all-cause mortality or heart failure hospitalization. They also caution that pooling accuracy metrics across these approaches is inappropriate because endpoints, datasets, and validation standards differ so substantially.

To close this gap, the review proposes a concrete research agenda built around candidate mechanical descriptors for heart failure phenotyping, including peak regional von Mises stress, end-systolic principal strain, strain heterogeneity index, transmural strain gradient, myocardial work density, annular displacement, and peak leaflet stress. Each descriptor is paired with a minimum validation pathway running from bench calibration through phantom testing to retrospective association and, ultimately, prospective outcome-linked trials. The authors acknowledge that finite-element outputs are sensitive to imaging quality, segmentation, constitutive assumptions, boundary conditions, and mesh resolution, and that harmonized reporting standards are prerequisites for multicenter comparison. Ethical considerations, including data governance, transparency, and algorithmic bias, must be resolved in parallel to earn regulatory and clinical trust.

The vision that emerges is not of any single technology replacing clinical judgment, but of an integrated ecosystem in which computational mechanics, physical validation, and data-driven prediction are jointly optimized for each patient. Imaging feeds patient-specific finite-element models; those models guide the fabrication of functional phantoms that experimentally confirm predicted stresses and flows; machine learning accelerates segmentation, builds surrogate models, and maps heterogeneous phenotypes such as preserved-ejection-fraction subtypes onto mechanistic descriptors. The authors conclude that these technologies are best viewed today as complementary components of a developing translational ecosystem rather than standalone clinical tools, with their greatest impact contingent on rigorous validation, standardized reporting, and heart-failure-specific clinical targeting. If prospective multicenter trials confirm the framework’s promise, the digital–physical twin could shift heart failure management from reactive measurement of global indices toward predictive, personalized, and mechanistically grounded care.

Subject of Research: Integration of finite-element modeling, 3D printing, and artificial intelligence for heart failure diagnosis and prognosis

Article Title: Mechanical‐medical convergence in heart failure: Artificial intelligence, finite‐element modeling, and 3D printing for diagnosis and prognosis

Article References: Sabrina, Q. N. E., Zobaer Shah, Q. M., Sohela, Q. N. E., Mousum, M. M. H., Chisty, M. M. U., & Shah, Q. M. A. (2026). Mechanical‐medical convergence in heart failure: Artificial intelligence, finite‐element modeling, and 3D printing for diagnosis and prognosis. Bioengineering & Translational Medicine, 11(5), Article e70156. https://doi.org/10.1002/btm2.70156

Image Credits: AI Generated

DOI: 10.1002/btm2.70156

Keywords: heart failure, finite-element modeling, 3D printing, artificial intelligence, digital twin, cardiac biomechanics, bioprosthetic heart valves, ventricular remodeling, machine learning, patient-specific modeling, transcatheter valve replacement, precision medicine

The study, published in the Annals of Biomedical Engineering, was led by Juuso Tuppurainen and colleagues at the University of Eastern Finland and Kuopio University Hospital. The team obtained forty osteochondral plugs from the femoral condyles and tibial plateaus of five human knee joints donated through a commercial biobank, spanning a wide range of osteoarthritic severity graded on the Osteoarthritis Research Society International histological scale. Each plug, four millimeters in diameter with cartilage thickness averaging 1.85 millimeters, was subjected to rotational friction testing in a phosphate-buffered saline bath. The samples were compressed vertically at 0.05 millimeters per second until a target stress of 0.1 megapascals was reached, held for thirty seconds, and rotated at an effective sliding velocity of ten millimeters per second, with twenty such cycles performed in sequence.

The crucial twist in the protocol came between loading cycles. At the end of each compression phase, the glass counterface was lifted one hundred micrometers away from the cartilage surface for one second, allowing fluid to flow back into the tissue. This brief lift-off, seemingly a minor experimental detail, turned out to be the decisive factor in whether the interstitial fluid cushion survived the test at all. When the researchers modeled the experiment as a single continuous creep curve without lift-offs, the modeled fluid load support decayed to zero in thirty-six of the forty samples. When the lift-offs were included, fluid load support recovered between cycles and remained elevated throughout the entire experiment in every sample.

The reason lies in the physics of porous, water-rich tissue. Cartilage is a fibril-reinforced poroelastic material: a dense mesh of negatively charged proteoglycans draws water into the matrix, while a network of collagen fibrils, pre-stretched by tissue swelling, resists expansion and restricts fluid outflow. Under rapid compression, this architecture traps fluid and builds up internal pressure, shielding the solid matrix from stress and keeping the two sliding surfaces separated by a lubricating fluid layer. But pressure dissipates as fluid escapes. During the lift-off phase, the model showed that pore pressure inside the cartilage actually dropped below the external bath pressure, creating a negative pressure gradient that actively drove fluid back into the tissue. In other words, even a one-second reprieve allows the cartilage to rehydrate, resetting the fluid cushion for the next cycle.

To quantify these dynamics, the researchers built a sample-specific three-dimensional fibril-reinforced poroelastic finite element model for every plug, using measured cartilage thickness from micro-computed tomography and replicating the observed axial creep deformation through an optimization procedure. Three material parameters were fitted for each sample: the fibril network modulus, the non-fibrillar matrix modulus, and the permeability. From the optimized models, the team extracted interstitial fluid load support curves, defined as the average fluid pressure at the cartilage surface divided by the applied contact pressure, and tracked five variables including initial load support, equilibrium load support, the change between them, and the time needed to reach equilibrium.

One of the study’s most striking findings concerns osteoarthritis. Contrary to the researchers’ hypothesis, neither early-to-moderate osteoarthritis nor anatomical location significantly altered the average initial fluid load support or its long-term maintenance. A statistically significant difference did emerge in the drop of load support from initial to equilibrium values between healthy cartilage and severely degenerated samples, with a mean difference of 12.2 percentage points, but the broader pattern was far subtler than expected. Degenerated samples lost fluid support more rapidly within individual loading cycles, yet some severely degraded tissue paradoxically maintained high load support between cycles, likely because increased permeability allowed faster fluid re-entry during lift-offs even as pressurization collapsed under load.

The explanation came from the material parameters themselves. A linear mixed-effects model revealed that the non-fibrillar matrix modulus, commonly associated with proteoglycan content, was significantly linked to both initial and equilibrium fluid load support, with higher values corresponding to lower load support, possibly because stiffer matrices contain less free water and deform less under compression. The fibril network modulus showed the opposite effect: stiffer collagen networks produced higher fluid load support by resisting lateral expansion and promoting volumetric compression. Permeability governed both the equilibrium level and the time to reach it, with leakier tissue losing pressure faster. These results demonstrate that fluid load support is a complex, parameter-dependent phenomenon in which reduced structural integrity does not necessarily translate into reduced pressurization, helping to explain why osteoarthritis grade alone failed to predict the outcome.

The relationship between fluid load support and friction proved equally nuanced. Earlier studies had established a linear inverse relationship: as fluid load support decreases, the friction coefficient rises. Yet in this study, no significant correlation appeared at either the initial or equilibrium time points, likely because the lift-off phases kept pressurization elevated and friction remarkably stable, compressing the dynamic range needed to detect the relationship. However, when the researchers analyzed how friction changed within each sample relative to the change in fluid load support from start to finish, a clear inverse trend emerged, with a correlation coefficient of negative 0.45 and a linear fit closely resembling those reported for porcine and bovine cartilage in earlier work. The expected relationship does exist, but only when the cumulative effect of pressurization changes over time is taken into account.

The authors are careful to note the limitations of their approach. Because interstitial fluid pressure cannot be directly measured in this unconfined compression geometry without invasive instrumentation that would itself alter the tissue, the model-derived load support values should be interpreted as relative comparisons rather than absolute physiological estimates. The applied stress of 0.1 megapascals sits at or below the lower end of in vivo joint contact stresses, and the simplified model omitted depth-dependent inhomogeneity and realistic collagen architecture, choices made deliberately to allow consistent parameter fitting across a large sample set.

Nevertheless, the implications reach well beyond the laboratory. If brief unloading intervals allow cartilage to rehydrate and sustain its fluid cushion, then interrupting prolonged static loading, such as hours of standing, with short periods of movement might help preserve joint health over a lifetime, a hypothesis the authors flag for future testing under physiological conditions. The work also carries a direct message for engineers developing artificial cartilage: matching bulk mechanical stiffness is not enough, because the true protective mechanism depends on generating and sustaining interstitial fluid pressure. By providing a practical framework for estimating fluid load support from ordinary friction experiments, the study offers a functionally anchored benchmark for evaluating tissue degradation, repair strategies, and biomimetic materials, and a reminder that one of the body’s most elegant lubrication systems depends on water, pressure, and the brief pauses that let them recover.

Subject of Research: Interstitial fluid load support and friction in human articular cartilage under degeneration, loading protocols, and varying material properties

Article Title: Interstitial Fluid Load Support in Human Articular Cartilage: Effects of Degeneration, Loading, and Material Properties via Combined Experimental Testing and Computational Modeling

Article References: Interstitial Fluid Load Support in Human Articular Cartilage: Effects of Degeneration, Loading, and Material Properties via Combined Experimental Testing and Computational Modeling. (n.d.). https://doi.org/10.1007/s10439-026-04374-5

Image Credits: AI Generated

DOI: 10.1007/s10439-026-04374-5

Keywords: articular cartilage, interstitial fluid load support, osteoarthritis, finite element modeling, friction, biomechanics, fibril-reinforced poroelastic model, permeability, collagen network, proteoglycans, joint lubrication, biomaterials

The research, conducted by Hessam Atghaee and Farhang Farahbod of Islamic Azad University’s West Tehran Branch together with Fayaz R. Rofooei of Sharif University of Technology, was published in the Bulletin of Earthquake Engineering. The team set out to answer a deceptively simple question: what happens to the in-plane seismic behavior of a concrete-filled steel deck diaphragm when it is simultaneously squeezed by out-of-plane gravity loading? Despite decades of use in commercial and industrial construction around the world, the coupled influence of sustained gravity loads and connection detailing on diaphragm response has remained insufficiently quantified, leaving a gap between how these systems are tested in laboratories and how they actually perform in buildings.

To close that gap, the researchers built and tested three full-scale diaphragm specimens, each measuring 2.5 by 5.0 meters, under reversed cyclic in-plane loading that mimics the back-and-forth shearing an earthquake imposes. The first specimen served as a control, carrying no gravity load and containing no mechanical connectors between the steel deck and the concrete. The second was subjected to a sustained gravity load of 600 kilograms per square meter, a realistic service-level loading, but likewise lacked mechanical connectors. The third combined the same gravity loading with self-drilling screws installed to enforce composite action between the steel deck and the concrete fill. This three-way comparison allowed the team to isolate the effect of gravity loading alone and then to evaluate whether mechanical fasteners could compensate for the degradation it causes.

The experimental program captured a rich set of response measurements, including hysteretic load-displacement loops, stiffness degradation from cycle to cycle, slip at the steel-concrete interface, and the progression of visible damage through to failure. The results were striking. Sustained gravity loading reduced the in-plane diaphragm capacity by approximately 20 percent compared with the unloaded control specimen. Just as importantly, gravity loading accelerated the development of damage under cyclic loading, meaning the diaphragm not only lost strength but also deteriorated faster as the simulated earthquake continued. In seismic terms, that combination is doubly concerning: a weaker diaphragm that degrades more quickly offers less protection precisely during the strongest and longest phases of ground shaking.

The third specimen told a more encouraging story. Adding self-drilling screws to enforce composite action between the deck and the concrete effectively suppressed interface slip, the relative sliding that undermines the ability of the two materials to work as a single structural unit. With slip controlled, the fastened diaphragm exhibited significantly reduced in-plane deformations and enhanced post-elastic stiffness, retaining its shape and load path integrity at displacement levels where the unfastened specimens had softened considerably. Interestingly, however, the mechanical fasteners did not raise the ultimate in-plane capacity. Their benefit lies in deformation control and stiffness preservation rather than in raw strength, a distinction that matters for performance-based seismic design, where limiting drift and damage is often as important as preventing collapse.

Complementing the laboratory work, the researchers developed a detailed three-dimensional finite element model of the diaphragms and validated it against the experimental measurements. With the model proven reliable, they used monotonic numerical analyses to reproduce the seismic backbone, or envelope, response of the specimens and to run parametric investigations that would have been impractical experimentally. One parameter stood out: reducing the concrete compressive strength decreased both diaphragm stiffness and strength, though it did not alter the underlying failure modes. In other words, weaker concrete produces a weaker, more flexible diaphragm, but the same mechanisms govern its failure. By contrast, the orientation of the applied in-plane loading relative to the deck corrugations had only a minor influence on seismic diaphragm response, a finding that simplifies design considerations for decks loaded in different directions.

The implications ripple through seismic design practice. Modern codes and design guides, including documents from the American Concrete Institute, the American Institute of Steel Construction, and the Steel Deck Institute, provide procedures for diaphragm design, but the new results highlight the importance of explicitly considering sustained gravity effects rather than treating in-plane and out-of-plane demands as independent. A diaphragm designed without accounting for gravity-induced degradation could enter an earthquake with substantially less reserve capacity than its calculations suggest. The 20 percent capacity reduction measured here is not a marginal correction; it is the kind of systematic bias that can erode safety margins across an entire building stock, particularly in regions where composite steel deck floors dominate mid-rise construction.

The study also carries a practical prescription. Because self-drilling screws suppressed interface slip and dramatically reduced in-plane deformations without adding ultimate capacity, they represent a relatively inexpensive retrofit and detailing measure that improves seismic performance where it often matters most: controlling damage and maintaining functional stiffness during shaking. For new construction, specifying mechanical fasteners to enforce composite action offers a straightforward way to build in that resilience. For existing buildings, the findings give engineers a quantitative basis for assessing whether unreinforced diaphragms under significant gravity load warrant strengthening, especially in seismic retrofit projects evaluated under standards such as ASCE 41.

Methodologically, the work demonstrates the value of pairing full-scale cyclic testing with validated finite element simulation. Physical tests of 2.5 by 5.0 meter diaphragms under simultaneous gravity and cyclic in-plane loading are expensive and logistically demanding, and only a handful of configurations can realistically be examined. The validated numerical model extends the reach of the three experiments, allowing the team to explore how material properties and loading orientations shape the backbone response across a much broader design space. The researchers note that the experimental measurements and simulation results are available from the corresponding author upon reasonable request, given the large volume of data and the project-specific nature of the models.

Ultimately, the study delivers new quantitative insight into gravity-influenced diaphragm behavior at a moment when earthquake engineering is increasingly focused on realistic, coupled loading conditions rather than idealized single-demand tests. Buildings do not experience earthquakes in isolation from the loads they carry every day, and the structures that connect those loads to the lateral system should not be designed as if they did. By showing exactly how much capacity sustained gravity loading can consume, and by demonstrating a simple fastening strategy that claw back much of the lost performance, the researchers have given the seismic engineering community both a warning and a workable solution. For the countless composite steel deck floors overhead in offices, hospitals, and warehouses worldwide, the message is clear: the weight they carry shapes how well they can protect the people below when the ground begins to move.

Subject of Research: Experimental and numerical investigation of gravity load effects on the in-plane seismic behavior of composite steel deck diaphragms.

Article Title: Investigation of gravity load effects on in-plane behavior of composite steel decks

Article References: Atghaee, H., Farahbod, F., & Rofooei, F. R. (2026). Investigation of gravity load effects on in-plane behavior of composite steel decks. Bulletin of Earthquake Engineering. https://doi.org/10.1007/s10518-026-02692-6

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DOI: 10.1007/s10518-026-02692-6

Keywords: composite steel deck, seismic diaphragm behavior, gravity load effects, cyclic loading, self-drilling screws, interface slip, finite element modeling, stiffness degradation, in-plane shear, earthquake engineering, concrete-filled steel deck, structural design