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Non-stationary flood frequency analysis in the Guachicono River (Colombian Andes): trend detection, GAMLSS modeling and design quantiles
Background and motivation. Flood frequency analysis is the cornerstone of hydraulic infrastructure design. The classical paradigm assumes statistical stationarity of peak-discharge series, an assumption increasingly challenged by anthropogenic climate change and land-use modification. In the upper Guachicono River basin (Cauca, Colombia), an Andean river with 31 years of continuous record (1993–2023), the stationarity hypothesis cannot be taken for granted without rigorous scrutiny. Objective. To present CFE-Colombia v1.0.0, an open-source R computational framework for non-stationary flood frequency analysis, integrating: (i) formal detection of trends and structural breaks via a battery of six complementary tests, (ii) multi-scale wavelet analysis with Monte Carlo simulation (n = 1 000), (iii) stationary fitting with AICc-based model selection and parametric bootstrap confidence intervals, and (iv) non-stationary modeling via GAMLSS with Cox-Snell residual validation. Methods. The test battery comprises Mann-Kendall (MK), Pettitt, sequential Sneyers, moving-window MK, White (heteroscedasticity), and augmented Dickey-Fuller (ADF). The stationary analysis fits six distributions (GEV, Gumbel, Log-Normal, Pearson III, LP3, and Normal) with AICc selection. The non-stationary analysis evaluates six GAMLSS models with P-splines and Gumbel, Log-Normal, and Gamma families. Uncertainty is quantified via parametric bootstrap (B = 1 000) for GEV quantiles and residual bootstrap (B = 500) for GAMLSS quantiles. Results. A significant increasing trend (τ = 0.316, Sen slope = 2.48 m3/s/yr, p = 0.013) and an abrupt structural break in 2010 (∆ = 37.5%, p = 0.020) were detected, classifying the series as non-stationary. The best GAMLSS model (M4: Log-Normal with time varying μ and σ via P-splines) yields AIC = 360.78 and adequate validation (KS p = 0.744, Filliben r = 0.976; edfμ = 4.59, df.fit = 9.80). For the year 2023, the 100-year design discharge is 542.9 m3/s (95% CI: 455.2–2 435.2 m3/s), compared with 1 160.8 m3/s from the stationary GEV model (−53.2%). Conclusions. The integrated framework reveals a stationary/non-stationary crossover paradox at Tr ≈ 5–7 yr: the stationarity assumption dangerously underestimates frequent floods with short return periods (Tr ≤ 5 yr) by up to +37.7%, and significantly overestimates major floods with long return periods (Tr ≥ 10 yr) under current basin conditions. Ignoring non-stationarity produces systematically incorrect hydrological designs, with direct implications for the engineering safety of water infrastructure in the Colombian Macizo Colombiano region under accelerated land-use transformation and climate chang.
Copyright (c) 2026 Mauricio Victoria https://creativecommons.org/licenses/by/4.0
Seamless Camera Handoff Between QNX and Android in Automotive Mixed-OS Architectures
Automotive systems increasingly deploy QNX for safety-critical early boot functions and Android for rich infotainment features on the same hardware. Camera systems face a timing challenge: QNX can display the rearview camera within 2--3 seconds to meet regulatory requirements, but Android eventually needs control for advanced features like surround view and parking assistance. This paper presents a handoff protocol that transfers camera ownership from QNX to Android without frame drops or visual discontinuity. The protocol uses heartbeat-based liveness monitoring, readyall synchronization barriers, and double-buffered frame handoff. Tests on automotive-grade hardware show handoff completion in 89ms average (p95: 142ms) with zero frame drops across 200 trials. The approach requires no hardware modification and integrates with standard Android EVS and QNX Screen frameworks.
Copyright (c) 2026 Duc-Trung HOANG https://creativecommons.org/licenses/by/4.0
A DAE Solver for Coordination of Force-Controlled Hybrid Testing
Hybrid testing couples numerical simulation with physical experiments by enforcing compatibility and equilibrium at the interface between numerical and physical substructures. This paper presents a force-controlled hybrid-testing formulation for stiff physical substructures coupled to nonlinear numerical substructures. Displacement compatibility is imposed directly on the numerical equations of motion to form a differential-algebraic equation. The interface force is obtained using Baumgarte-stabilized Lagrange multipliers. Physical-substructure velocity and acceleration, which are not measured in pseudo-dynamic testing, are estimated from displacement feedback using cubic regression. A linear illustrative system is used to assess convergence, stability, numerical damping, and period distortion for explicit time-integration schemes. The formulation is then demonstrated experimentally by coupling a stiff axially loaded steel-bar physical substructure to a nonlinear two-degree-of-freedom numerical substructure with a Duffing-type spring. The hybrid test remains stable, reproduces the dominant simulated dynamics, and maintains displacement compatibility despite noisy camera-based displacement feedback. These results show that Baumgarte-stabilized constraint dynamics provide a practical strategy for force-controlled hybrid testing of stiff physical substructures.
Copyright (c) 2026 Frederik Nordtorp, Giuseppe Abbiati https://creativecommons.org/licenses/by/4.0
Diagnosing the Airflow Mechanism of Blowhole Cave, Edwards County, Texas
In late summer 1976, I recorded outside air temperature and signed entrance airflow at hourly intervals during five consecutive days at Blowhole Cave, Edwards County, Texas, with a return visit two weeks later that captured a continuous overnight cycle. The dataset comprises 96 hourly samples taken with a vane anemometer at a 0.139 m. (1.5 ft.) entrance restriction, with cave-air temperature independently measured at 22.2 °C (72 °F). I test the two dominant cave-ventilation hypotheses against these data. The buoyancy-driven thermal-chimney model fits the signed flow with a Pearson correlation of r = +0.55 against sign(ΔT) ∣ΔT∣ , with negligible correlation against dT/dt, and yields an effective chimney height Δh ≈ 49 m (159 ft) from a single-parameter regression. The flow reverses sign precisely when outside temperature crosses cave temperature, a parameter-free prediction of the chimney model that no other mechanism reproduces. The 102 m (336 ft) of vertical relief surveyed inside the cave is more than sufficient to account for the observed flow. The barometric / large-volume hypothesis is rejected on six independent grounds, including a hidden-volume requirement of 1.6 Å~ 107 m., or roughly 1,100 times the surveyed cave volume. The result confirms the qualitative field interpretation recorded by the 1976 Project Deep survey team. The analysis extends the original treatment in Passmore (2023) with signed-flow analysis, USGS 3DEP topographic verification, and contextualization against the post-2020 cave-ventilation literature.
Copyright (c) 2026 Greg Passmore https://creativecommons.org/licenses/by/4.0
Thermoelectric (TE) materials have emerged as promising candidates for addressing the global energy crisis by enabling waste heat recovery and sustainable cooling technologies. The performance of TE materials is governed by the dimensionless figure of merit ZT = α² σ T / κ, which depends on three key interrelated parameters: the Seebeck coefficient (α), electrical conductivity (σ), and thermal conductivity (κ). Due to the conflicting nature of these interconnected variables, simultaneous optimization of all three parameters remains elusive. Two main strategies have been introduced to improve ZT: phonon engineering and band engineering. The ultimate goal of these approaches is to develop phonon-glass and electron-crystal materials. Among the well-studied families of thermoelectric materials are chalcogenides (e.g., Bi₂Te₃, PbTe, and SnSe), skutterudites (e.g., CoSb₃), Zintl phases (e.g., Yb₁₄MnSb₁₁), and half-Heuslers (e.g., ZrNiSn), each offering distinct advantages across different temperature regimes. Despite considerable progress, a unified understanding of structure-property relationships remains elusive, motivating growing interest in computational methods. The design, prediction, and discovery of new and improved thermoelectric materials increasingly rely on density functional theory and machine learning, which complement experimental efforts by accelerating the identification of high-performance candidates. In this overview, we revisit the fundamental concepts and theories underlying these materials along with their key design strategies and applications.
Copyright (c) 2026 Hadis Behjat Gharetape https://creativecommons.org/licenses/by/4.0
Evaluating the performance of oyster shells as sustainable coarse aggregate in concrete grade 25 (C25) production
This study assesses concrete using crushed granite (CC) and oyster shells (OS) as aggregates. Grading analysis confirmed well-graded distributions, with sand's fineness modulus (2.52) meeting British Standard (BS 812-103.1). OS concrete exhibited a higher water-cement ratio (0.67 vs. 0.55 design) due to greater water absorption (1.8% vs. 0.4% for CC). However, it was still within the BS 8500:1 limit. Crushed granite achieved a 70 mm slump, while OS recorded zero. This is attributed to its semi-elliptical shape, reducing grout availability. Both materials met the aggregate impact value (AIV), Los Angeles Abrasion value (LAAV), and specific gravity standards. At 28 days, compressive strength was 25.7 MPa for CC and 17.3 MPa for OS. The oyster shell failed to meet the 25 MPa design strength even after 36 days of curing. This could be attributed to the geometry and water-cement ratio limiting its performance, and optimization of the concrete is required.
Copyright (c) 2026 Gabriel Kwame Sipi Takyi, John Kwame Tawiah, Laudina Gloria Mends, Emmanuel Adu-Afari, Charles Vicku, Maxwell Selase Akple, Franklin Liggie-Kudono https://creativecommons.org/licenses/by/4.0
Stability Guided Neural Network For Hybrid Eulerian-Lagrangian Solvers
Solver coupling induced instabilities is the primary problem faced by hybrid Eulerian-Langrangian solvers in vortex dominated flows. Current ML CFD methods target accuracy or speed, but numerical stability is handled by traditional correction methods which are typically threshold based or apply continuous corrections. This project proposes a Sta bility Guided Neural Network, a lightweight LSTM controller trained only on native solver failure trajectories, requiring no external DNS reference data. The SGNN monitors a 12-scalar diagnostic feature vector over a rolling 10-step window and predicts imminent numerical blow-up, enabling preemptive and intermittent application of classical stabilisation techniques only when necessary. Trained across four 2D periodic flow topologies (Kelvin–Helmholtz, Kolmogorov, Tay lor–Green, and random vortex blobs), the controller achieves 0.98 AUC in blow-up prediction and extends stable simu lation time by 1.56× to 2.24× across Reynolds numbers from 10,000 to 30,000, where the uncontrolled baseline solver fails deterministically. Because corrections are applied only when a risk threshold is crossed, the hybrid solver’s con servation properties and spectral cascade are preserved during all stable phases. This proof-of-concept demonstrates that prediction of solver-specific instabilities is a tractable and computationally lightweight objective, complementary to existing accuracy-focused ML-CFD methods.
Copyright (c) 2026 Parshad Sawant https://creativecommons.org/licenses/by/4.0
Assessing climate change impacts on flood frequency and magnitude using CMIP6 GCMs: a case study of the Likhu River in eastern Nepal
Floods are becoming more severe with climate change disrupting the hydrological cycle, undermining the reliability of the historical flood records for future projections. Despite considerable research on large river basins, small to medium-sized basins like Nepal’s Likhu River remain under-researched, particularly in integrating CMIP6 climate models and Shared Socioeconomic Pathways (SSPs). To the best of the authors’ knowledge, this is the first study to apply the CMIP6/SSP framework to a medium-sized Himalayan basin in eastern Nepal, addressing a critical gap in regional climate-hydrology research. This study aims to quantify the future changes in flood magnitude and frequency of the Likhu River basin by linking CMIP6 climate models with an integrated hydrological-statistical approach. Five selected CMIP6 Global Climate Models (GCMs) under SSP245 and SSP585 scenarios were incorporated to drive a calibrated and validated Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) model, with flood frequency analysis performed using Log-Pearson Type III and Generalized Extreme Value (GEV) distributions. The future floods for each GCM and an ensemble model were evaluated for the three time periods: Near Future (2025–2050), Mid Future (2051–2075), and Far Future (2076–2100). Our findings suggest that a 100-year return-period flood estimated using the historical data may occur more frequently, with recurrence intervals shortening to 5–25 years under future climate change scenarios, highlighting the impact of climate change. Results also point out the variability among the different GCMs and necessitate the use of multiple GCMs to capture the range of uncertainties in flood predictions. These findings demonstrate that current design standards and practices for water-related structures need further modifications and improvements to provide safeguards against future flow conditions as monsoon extremes intensify.
Copyright (c) 2026 Sabina Budhathoki https://creativecommons.org/licenses/by/4.0
Methodology for Material Selection in Mechanical Design
This work develops a structured methodology for material selection in mechanical engineering design, aiming to guide engineers in choosing materials that meet the technical, economic, and environmental requirements of the projects. Based on a detailed literature review, this study proposes a rigorous and well-founded selection methodology based on five fundamental steps: identification of needs, collection of information on materials, analysis and comparison of properties, use of auxiliary tools, and justified decision-making. The main results indicate that the use of a systematic approach improves the accuracy in material selection and increases efficiency in project development. The proposed methodology facilitates informed decision-making and reduces the risk of failures, making the project more sustainable and economical. It is concluded that the adoption of this approach significantly contributes to improving the quality and durability of products in mechanical engineering projects.
Copyright (c) 2026 Bruno Seixas https://creativecommons.org/licenses/by/4.0
Wireless Flood Early Warning System for High-Density Population Areas by Combining Ultrasonic and Water Level Sensors
We introduce an innovative solution that integrates ultrasonic sonar systems and water level sensors for real-time monitoring of flood conditions. Utilising wireless communication, it transmits data and issues timely alerts when water levels reach critical thresholds. Designed for densely populated regions, this system enhances community preparedness and safety by providing accurate information to help mitigate risks of floods.
Copyright (c) 2026 Muhammad Fadhael Izzil Haq https://creativecommons.org/licenses/by/4.0
Fast lift and drag estimates along airfoil polars matter for design sweeps, but high-fidelity tools are slow at scale. We show that a causal sequence model with only 6394 trainable param- eters can match or beat two public NeuralFoil checkpoints (xxsmall and xxxlarge) on the same withheld BigFoil-derived test rows when each method sees identical preprocessing and the decoder is fed ground-truth past coefficients along the polar (teacher forcing). On the first 4096 rows of that split, pooled mean Cl MAE is 0.051 54 and Cd MAE is 0.002 99, below both baselines at much smaller width. FoilCORE walks the polar in angle-of-attack order. Geometry and (α, Re, M, Cl, Cd) tokens embed at width d=8. A masked causal trunk, path nonlinearities, gated outer products, and a two-output head predict the next step, so the curve is an ordered sweep rather than unrelated (α, Re) samples. Greedy decoding with K=0 raises validation MAE versus teacher forcing; Section 7.4 describes a NeuralFoil xxxlarge warmstart for open-loop use. Scope and caveats are in Section 9.
Copyright (c) 2026 Avneh Bhatia, Joshua Selvaraj https://creativecommons.org/licenses/by/4.0
Experimental Characterisation of an Optical Tracking Sensor for Capsule Localisation in the Small Intestine
This study reports the first systematic characterization of a miniature laser-based optical tracking sensor for smart capsule odometry in the small intestine in controlled and biologically relevant conditions. Data was collected by attaching the sensor to a CNC milling machine, allowing sensor measurements to be validated against ground-truth displacement data. A series of experiments were performed to probe the effects of biological tissue, interface material, material thickness, and environmental illumination on sensor performance. The findings suggest that the sensor exhibits consistent, repeatable results in identical conditions. Additionally, the effect of intestinal digesta content on the localisation performance of the sensor is investigated for the first time. Results show a 40% underestimation of distance travelled when traversing over high levels of digesta, indicating the importance of patients’ fasting before any in-vitro application. Despite this underestimation, the near-linear performance of the sensor indicates its feasibility for capsule odometry applications given suitable calibration.
Copyright (c) 2026 Farzaneh Baserisalehi, Ebubekir Avci, Ciaran Moore, David Thomas, Christopher Hann, Muhammad Rehan, Volker Nock https://creativecommons.org/licenses/by/4.0
Seismic Analysis and Probabilistic Risk Assessment of Reinforced Concrete Buildings: A Review and Integrated Framework
Reinforced concrete (RC) buildings form a major share of the building stock in seismic regions, yet their earthquake performance remains strongly influenced by analysis method, modelling assumptions, hazard characterization, and fragility formulation. This review synthesizes evidence from 130 studies on seismic analysis and probabilistic risk assessment of RC buildings. The literature is examined in five main areas: seismic analysis approaches, structural modelling and simulation techniques, seismic hazard representation and ground motion selection, performance evaluation metrics, and fragility curve development with probabilistic risk assessment. The review shows a clear shift from deterministic, code-based evaluation toward nonlinear, probabilistic, and consequence-oriented frameworks. Simplified procedures remain useful for screening and class-based studies, while nonlinear dynamic methods dominate collapse-sensitive and risk-oriented assessment. The findings also show that modelling choices, site effects, hazard representation, intensity-measure selection, and uncertainty treatment can significantly alter fragility and risk estimates. Although recent studies increasingly connect structural response with damage, collapse, loss, downtime, and recovery, important gaps remain in regional calibration, realistic modelling of existing building stock, and scalable risk-assessment frameworks. Based on these findings, an integrated framework is proposed to systematically link hazard characterization, structural modelling, seismic analysis, performance evaluation, fragility development, and decision-oriented risk assessment within a coherent workflow for existing RC buildings.
performance-based earthquake engineering
Copyright (c) 2026 Muhammad Abubakar, Muhammad Awaib https://creativecommons.org/licenses/by-nc/4.0/
Pseudo-Critical Inlet State Mapping of an sCO₂-Water Printed Circuit Heat Exchanger Pre-Cooler for Brayton Cycles
A design-oriented inlet state mapping methodology is presented for a printed circuit heat exchanger (PCHE) operating as a supercritical carbon dioxide (sCO₂) water pre-cooler in a Brayton-cycle application. The objective is to quantify how the thermal and hydraulic response of a fixed straight-channel PCHE core changes as the sCO₂ inlet state moves relative to the pseudo-critical region. A one-dimensional distributed counterflow model is formulated for a representative hot-side and cold-side channel pair. Real-fluid thermophysical properties are evaluated locally from pressure and specific enthalpy, and local heat-transfer and friction models are coupled with a wall conduction resistance represented through a two-dimensional conduction shape factor. The boundary-value problem is solved using a shooting method. The model is assessed against straight channel sCO₂-water PCHE data from the literature. For four outlet temperature comparison cases, the mean absolute error is approximately 0.6 K for the CO₂ outlet temperature and 1.28 K for the water outlet temperature. An additional comparison with digitized near critical axial temperature profiles is treated as a profile shape consistency check. The assessed model is applied to a fixed semicircular channel PCHE geometry over maps of hot side inlet pressure and temperature for three cooling water inlet temperatures. The maps show heat duty, effectiveness, straight core pressure drop, mean overall heat-transfer coefficient, minimum temperature approach, and hot outlet temperature. The results demonstrate the competing influence of pseudo-critical heat transfer enhancement, heat sink temperature, pinch margin, and hydraulic penalty, providing a compact preliminary design tool for sCO₂ Brayton cycle pre-cooler assessment.
Copyright (c) 2026 Ory Haimovitz https://creativecommons.org/licenses/by/4.0
Graph Attention Networks for Modeling Multi-Agent Decision Dynamics at Unsignalized Intersections
Gap acceptance at unsignalized intersections is a safety-critical decision in which a driver on a stop-controlled approach must judge whether the available time headway in a conflicting traffic stream is sufficient to cross safely. Conventional models treat this as a single-vehicle problem, estimating a critical gap threshold from ego-vehicle kinematics alone---an approach that ignores the multi-agent reality of intersection negotiation. This paper reframes gap acceptance as a multi-agent interaction problem and applies a Spatiotemporal Graph Attention Network (ST-GAT) to model it. Using the INTERACTION Dataset v1.2 across four unsignalized intersection scenarios, we extract 24,627 labeled gap acceptance events and construct per-event scene graphs where nodes represent agents encoded with ego-relative spatiotemporal features and edges connect agents within a 10-meter spatial threshold. ST-GAT achieves AUC values between 0.793 and 0.911 across scenarios, outperforming GCN in all four and remaining competitive with logistic regression. Critically, attention weight analysis reveals three behavioral patterns consistent across scenarios: proximity drives attention allocation, non-motorized road users are disproportionately attended during gap rejections relative to acceptances, and accepted gaps are associated with faster-moving attended agents. These findings generalize across two intersection geometries and three class balance conditions, demonstrating that graph attention mechanisms can surface interpretable behavioral structure in human gap acceptance decisions that single-agent and non-attentive graph models cannot.
Copyright (c) 2026 Insan Arafat Jahan https://creativecommons.org/licenses/by/4.0
ACPL: A Coordinate-System Prior for Topology-Aware Directed Trajectory Inference on Cyclic Biological Manifolds
Directed trajectory inference from single-cell RNA sequencing data requires graph construction algorithms that respect the geometric structure of cyclical biological processes. Minimum spanning tree approaches systematically produce backward edges across cyclical manifolds through Euclidean shortcuts at the loop closure, inverting the inferred direction of division at its most biologically consequential transition. We introduce ACPL (Arc+LOESS Polar-Linearization), a coordinate-system prior that transforms two-dimensional UMAP embeddings into polar coordinates aligned with the manifold's angular structure and admits only forward edges along LOESS-smoothed cumulative arc length. We prove that the resulting directed graph is acyclic by construction at O(N log N) cost and that LOESS smoothing is mathematically necessary to avoid a trivial accuracy artefact. Empirical evaluation across five biological datasets is reported in full: ACPL achieves 97.0% structural accuracy on Spellman yeast and 75.9% on Nestorowa haematopoietic stem cells, with all pairwise bootstrap confidence intervals crossing zero. The method is robust to UMAP hyperparameter choice (SD = 0.77 pp across 25 configurations) and survives spatial autocorrelation correction by hundreds of orders of magnitude. An R implementation is available at https://github.com/shreyosecret/ACPL under the MIT License.
Copyright (c) 2026 Shreyo Ghosh https://creativecommons.org/licenses/by/4.0
Quantity and Quality: A Proposed Exergy-Based Reporting Framework for Energy Systems
First-law scalar energy accounting, expressed in joules, kilowatt-hours, megawatt-hours, quads, barrels-of-oil-equivalent, and related quantities, does not encode the second-law distinction between energy magnitude and accessible work potential unless an additional quality field is provided. Classical exergy analysis restores that distinction, but routine adoption has been limited by reference-state dependence, carrier-specific terminology, data requirements, and the perceived burden of full thermodynamic accounting. The result is a persistent operational gap between thermodynamic rigor and the low-overhead reporting interfaces used by plant engineers, utility managers, regulators, market designers, and investors. This paper proposes a dual-layer framework for closing that gap. The physics layer preserves carrier-level thermodynamics. It defines the intensive carrier potential as the exergy voltage, ∆Φ(C) A =dXA/dC, and uses it to recover the carrier-current relation ̇XA = ̇C∆Φ(C) A , which can be written at a reporting boundary as ̇XA = fX ̇E. The interface layer compresses that physics into a practical reporting token, (Ecarrier,fX), where Ecarrier is a first-law energy quantity with explicit carrier and basis context, such as MWh_e, MWh_th, or MWh_HHV_CH4, and fX is the Exergy Factor, the accessible work potential per unit reported energy at the declared boundary. Five Fidelity Tiers, F0 through F4, allow the notation to scale from conventional scalar reporting, through presumptive lookup factors, asset-specific metadata, dynamic interval com putation, and full state-vector engineering analysis without changing the public interface. The paper also defines optional diagnostics: Exergy Capital Efficiency for capital screening, and the Exergy Loss Angle, θloss = atan2(Xlost,Xuseful,out), as a bounded display coordinate derived from second-law efficiency. The angle is not a new thermodynamic property; it is a visualization of retained versus lost useful work potential over a declared boundary and interval. The framework is demonstrated with public XAI4HEAT district-heating telemetry. Four pro cessed substations, covering 51,592 synchronized 15-minute intervals from the 2024–2025 heating season, are converted into dynamic F3 Exergy Factor records using measured primary supply temperature, measured ambient temperature, and the reported thermal-delivery field as an inter val weight. The delivery-weighted portfolio Exergy Factor is 0.216 with a dynamic ambient sink and 0.173 with a fixed 20◦C sink. A supply-return sensitivity check shows that an integrated primary water-stream model gives 0.172, while a secondary-side proxy gives 0.125, reinforcing that the public token must carry method and tier metadata. The empirical demonstration is limited to thermal district-heating telemetry and does not validate the chemical-carrier registry or optional diagnostic metrics. The central practical claim is therefore narrow and operational: every reported energy quantity should carry an Exergy Factor, and supply, demand, storage, and conversion pathways should be matched by both quantity and quality.
Copyright (c) 2026 Christopher DiMurro https://creativecommons.org/licenses/by/4.0
A Finite Volume-based Unified Transient Deterministic Framework for Lubrication Modelling
A transient deterministic unified lubrication model is developed for the analysis of rough, starved, and coated contacts within a single, fully coupled numerical framework capable of resolving boundary, mixed, and full‐film lubrication regimes. The model is formulated with the finite volume method on a curvilinear grid and extends conventional full‐film formulations through the introduction of a semi‐system methodology, enabling robust treatment of complex multi‐regime conditions. A key distinguishing feature of the framework is the direct resolution of thermal effects within both the lubricant and solid domains through solution of the energy equation. Unlike many existing mixed lubrication models that rely on analytical temperature approximations, the present approach captures transient, asperity‐scale temperature evolution explicitly, allowing accurate representation of local thermo‐mechanical interactions. Two case studies are presented to demonstrate the capabilities of the model. The first examines transient starvation in rough contacts with isotropic sinusoidal topographies of varying wavelength, revealing a strong dependence of lubricant entrainment, asperity interaction, and localised heating on surface morphology. Certain wavelengths promote hydrodynamic film recovery, whereas others lead to pronounced asperity contact and elevated thermal gradients. The second study investigates the role of coating thermal properties under transient starved conditions, demonstrating a strong coupling between heat transport, viscosity variations, and frictional response. Overall, the proposed framework provides a robust and physically consistent platform for the simulation of transient lubrication phenomena under realistic operating conditions, enabling detailed insight into roughness, starvation, and thermal effects across regimes using a fully coupled approach.
Copyright (c) 2026 Filimonas Kaliafetis, Daniele Dini, James P. Ewen, Suhaib Ardah https://creativecommons.org/licenses/by/4.0
Bounded Event-Time Execution Architecture
Contemporary cyber-physical and system-of-systems environments maintain sensing, synchronisation, coordination, and distributed processing capabilities across heterogeneous operational domains. Existing representational architectures define mechanisms for observation, modelling, and state coordination; however, operational state resolution remains externalised, deferred, or distributed across independent systems. Therefore, state formation proceeds through reconciliation, eventual consistency, or retrospective reconstruction rather than through bounded event-time execution. Bounded operational state-resolution semantics are not maintained within the execution domain itself. This paper defines a bounded event-time execution architecture and an integrated Concept of Operations (CONOPS) in which admissible actions resolve into operational system state within bounded domains. The architecture is defined at both functional and operational levels. Internal implementation constructs, deployment-specific mechanisms, and parameterisation remain abstracted from the architectural definition. Representational Digital Twin systems constitute one operational context but do not define the architectural scope of the contribution. The architecture defines bounded event-time execution semantics and operational state-resolution behaviour for cyber-physical and system-of-systems environments. The architecture is defined as a specification-stage operational execution architecture intended to support subsequent implementation, deployment, and empirical evaluation.
Copyright (c) 2026 Martina King https://creativecommons.org/licenses/by/4.0
A Data-Driven Design Framework for Wind Turbines via Design-by-Morphing and Bayesian Optimization
This study presents a data-driven design optimization framework the integrates Design-by-Morphing (DbM) with Bayesian optimization (BO) to facilitate the discovery of novel, high-performance aerodynamic geometries. Applied to vertical-axis wind turbines (VAWTs), the DbM approach enables the generation of novel shapes that go beyond the conventional constraints of lift-based (Darrieus) and drag-based (Savonius) geometries. Candidate designs were evaluated via expensive high-fidelity Unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations under representative urban wind conditions, with the design space systematically explored to maximize the power coefficient, Cp. From a design space of 6.28 million configurations, the BO-driven framework identified a high-performance design within a remarkably low number of iterations. The optimal configuration achieved a 21.26% increase in power extraction efficiency over existing benchmark designs, while simultaneously maintaining a stable torque profile and structural robustness across a range of Reynolds numbers. Ultimately, this research establishes the DbM-BO architecture as a scalable and computationally efficient pipeline for addressing complex aerodynamic challenges where the derivation of non-intuitive, high-performing surfaces is critical.
Copyright (c) 2026 Hamza Latif Mehr, Imran Akhtar, Haris Moazam Sheikh https://creativecommons.org/licenses/by/4.0
﻿Experimental Demonstration of Elastic-Plastic Wave Propagation in a Discrete Metamaterial
We fabricate a discrete phononic crystal with hysteretic force–deflection behavior analogous to elastic–plastic material response, and then measure its response to harmonic excitation. Slider (or Jenkins) elements are introduced to mimic plastic deformation and a ten-cell phononic crystal is constructed from modular unit cells. Modular construction enables calibration and validation of individual components prior to full integration, which is particularly important for the sliding elements. Subsequent frequency-sweep experiments at both elastic and plastic excitation amplitudes demonstrate pronounced wave attenuation aligned with bandgap frequencies arising from Bragg scattering. The presence of this strong attenuation, even at plastic amplitudes, reveals experimentally that bandgaps can continue to block frequencies into the strongly nonlinear, plastic regime. The fabricated system is expected to facilitate future experimental studies of large-amplitude, elastic–plastic wave propagation.
Copyright (c) 2026 Greg Dorgant, Michael Leamy https://creativecommons.org/licenses/by/4.0
Research on automobile whistling and suction sounds has been conducted in the past. For cavity resonance, a type of whistling sound, the cavity resonance frequency has been determined using Rossiter's empirical equation. Therefore, we limited our study to the three-dimensional case and clarified the physical phenomena that arise by solving a set of partial differential equations that explain the phenomenon. As a result, we were able to determine the frequency at which resonance increases, taking into account three-dimensional space. Finally, we were able to confirm the conditions under which resonance increases through numerical calculations.
Copyright (c) 2026 Takuya Yabu https://creativecommons.org/licenses/by/4.0
Why we need more showers in the aircraft
High levels of complexity in modern commercial aircraft and flight operations feature new accident types featuring a brittle flight crew response to increasingly frequent ambiguous and opaque non-normal situations. Previous work from the author proposes the Airmanship 2.0 concept to mitigate this brittleness by harmonizing the existing compliance-centred safety paradigm with an adaptive, sensemaking function in the flight deck. This article explores the neurocognitive sensemaking mechanisms that may enable this compound role, including related training considerations. A case study in mindfulness training is discussed as an initial practical exploration into such neurocognitive training of pilots. There are tentative indications of a positive impact of mindfulness on flight crew response to ambiguous situations, alongside key reflections on aviation cultural biases and (lack of) readiness for such advanced training.
Copyright (c) 2026 Frederik Mohrmann https://creativecommons.org/licenses/by-nc/4.0/
PhyGRU: a Physics-Biased Variant for Gated Recurrent Unit
The modeling of dynamical systems often takes place in regimes where data are limited and physical knowledge is only partially available. In such conditions, simplified physical models are often insufficient, while fully data-driven recurrent networks struggle to generalize. Moreover, many existing hybrid solutions require substantial architectural modifications or intervention, making them difficult to integrate into existing models or pipelines without major restructuring. To address this, PhyGRU is introduced, a physics-biased variant of the Gated Recurrent Unit in which the learned candidate state is replaced by an explicit time integration of a parametric physical model, optionally augmented by low-dimensional latent dynamics. The standard GRU gating mechanism is preserved, enabling interpolation between the previous state and a physics-informed candidate. PhyGRU targets scenarios with limited data and partial physical knowledge, where neither simplified physical models nor fully data-driven recurrent networks are sufficient. The approach requires only minimal architectural modifications relative to a standard GRU, at the cost of increased per-step computational time due to explicit state integration. Experiments, on three controlled dynamical systems of increasing complexity, under time-invariant and time-varying parameter regimes, indicate that PhyGRU can yield more physically coherent predicted trajectories when the assumed physical prior is reasonably aligned with the true dynamics, while performance degrade as the mismatch between the prior and the true system increases.
Copyright (c) 2026 Girolamo Oddo https://creativecommons.org/licenses/by/4.0
Impact of TiO2 on the Physical and Mechanical Characteristics of Cement-Based Materials: A Review
This paper reviews the effects of titanium dioxide (TiO2) as a photocatalytic additive on the physical and mechanical properties of various types of concrete and cement mortars. It emphasizes changes in strength, durability, workability, and structural integrity under both standard conditions and adverse environments, including temperature variations, exposure to CO2, gamma radiation, and electromagnetic waves. The findings indicate that TiO2 in cementitious composites acts as a filler due to its fine particle size and promotes hydration. It aids in the formation of C-S-H gel through its catalytic effects, which help fill voids, increase density, improve both strength and durability, and reduce workability. Furthermore, it enhances electrical resistivity and bolsters resistance to acid and chloride attacks, while also increasing the material's capacity to absorb gamma rays and electromagnetic waves. The amount of TiO2 used as a cement substitute should be kept to a minimum. The optimal range typically falls below 10%, specifically between 0.5% and 5%, because higher concentrations can reduce strength and durability. This paper offers valuable insights for civil engineers on the optimal proportions of TiO2 and its effective use in conjunction with other additives. Moreover, researchers can use this study to explore potential future research directions.
Copyright (c) 2026 Abbas Maniseresht https://creativecommons.org/licenses/by/4.0