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Ice Shell-Steel Truss Composite Structure Ice and Snow Venue in High-Altitude Cold Regions: Thermal Performance and Structural Feasibility Study
Hulunbuir experiences long, severe winters, with significant wind-chill effects at outdoor ski resorts that pose a high risk of frostbite for children. Traditional indoor ski resorts require substantial investment and high operational energy consumption, making them difficult to promote in less developed high-altitude cold regions. This paper proposes a composite ice and snow venue model combining a compacted snow shell, steel truss load-bearing structure, inner protective layer, and insulated glass zoning, and systematically analyzes its regional adaptability, structural design, and thermal performance. The research demonstrates that the venue, relying on natural cold sources without mechanical refrigeration units, can maintain a stable low-temperature range of -8°C to -5°C indoors (wind speed ≤ 0.2 m/s, temperature fluctuation ≤ ±1°C), eliminating wind-chill effects. The arched load-bearing design and layered compaction ensure snow shell stability, while safety nets and waterproof breathable membranes provide dual protection. Insulated glass zoning achieves the integration of hot beverage service and ice body protection. The venue construction cost is approximately 800–1000 RMB/m², with monthly operating electricity costs of approximately 11,000 RMB, representing a reduction of over 70% compared to traditional indoor ski resorts in both construction (3000–5000 RMB/m²) and operational costs. This model combines structural safety, operational economy, and child-friendliness, providing a feasible technical pathway for ice and snow venue construction in high-altitude cold regions.
Ice and snow venue Snow shell structure Steel truss Composite structure High-altitude cold regions Thermal performance Child frostbite prevention Hulunbuir
Engineering Structural Engineering Civil Engineering Building Technology Cold Regions Engineering
Copyright (c) 2026 Hong-sheng Liu https://creativecommons.org/licenses/by/4.0
Reservoir Operational Planning of Irrigation Dams for Micro-Hydropower Development
Modern forms of energy are simply not available in rural areas of Ethiopia, while traditional sources such as fuel wood, cow dung, and crop residue are being depleted rapidly thereby deepening the rural energy crisis. Compared with other new and renewable sources of energy, micro-hydropower has been recognized as being a viable and mature technology. It can be applied immediately on an economic scale in a flexible manner and can comparatively easily bring benefits to the population in isolated areas, who are so far not covered by national electricity supply grid. About 84 percent of the Ethiopian people reside in rural areas and less than one percent of this population has access to electricity. However, a number of micro- irrigation dams have been constructed and planned for implementation, especially in Tigray and Amhara Regional States which could generate and provide electricity to the local population. A case study regarding reservoir operational planning had been conducted on Haiba dam, which is one of the fully implemented micro-irrigation earth dams in Tigray Regional State so as to integrate it with micro-hydropower. Accordingly a number of objectives were accomplished like formulation of discrete dynamic programming model, collecting, processing and analyzing meteorological data, collecting and preparing input data for the DP model. A Visual Basic Program was written to solve the DP model. The main results obtained were monthly energy output, energy output duration curve and optimal reservoir operation guide curve. The optimal power output of Haiba reservoir has an electrification capacity of 50 to 650 households each using one light bulb of 40w each. The results of this study showed that it is possible to produce a valuable amount of electric energy that is very useful in electrifying the rural community, from micro-irrigation dams without affecting its irrigation service by applying systems engineering as a planning tool. Based on the findings, conclusions and recommendations for further studies are drawn.
Copyright (c) 2026 Mulatu Kassa, Zelalem Hailu, Michael Abebe https://creativecommons.org/licenses/by/4.0
Dynamic Cascade Reactor (DCR): A Segmented Micro-Fusion Design with Cascading Chamber Cycles for Enhanced Stability and Control
The Dynamic Cascade Reactor (DCR) is a conceptual micro-fusion system employing a modular architecture of segmented plasma chambers with phased magnetic compression and synchronization, intended to mitigate large-scale plasma instabilities. By dividing the plasma volume into smaller, orchestrated units, the DCR aims to reduce the amplitude and effect of tearing modes, edge-localized modes (ELMs), and other magnetohydrodynamic (MHD) disruptions common in current fusion reactor designs. The concept draws on resonant magnetic perturbation (RMP) control and deep reinforcement learning (DRL) for instability suppression, both validated in experiments at facilities including DIII-D and TCV (see References). This document addresses confinement, wall erosion, and control latency challenges, but does not yet resolve — and explicitly flags — whether the segmentation strategy itself helps or hurts the reactor's net energy balance. That question is the central open problem in this draft.
Copyright (c) 2026 Sebastian Woodhouse https://creativecommons.org/licenses/by/4.0
Investigations into the substitutability of conventional coatings with coatings based on renewable raw materials in graphic printing
The substitutability of conventional coating systems with (“green”) coating systems based on renewable raw materials is being investigated with regard to the properties of graphic printing. In addition to color and rheological properties, the main focus is on technical printing properties such as abrasion resistance, static and dynamic friction, and wet block resistance. The four “green” coating systems tested show differing performance on three different substrates. Only the matte coating system proved to be fully acceptable as a substitute, while the glossy coatings tested showed only limited performance.
Copyright (c) 2026 Insa-Marie Wickel, Philipp Wüst, Edgar Dörsam, Andreas Blaeser https://creativecommons.org/licenses/by/4.0
Analyzing the Impact of DVFS and System Noise on Merge Sort Benchmarking Through System Quiescing
Accurate performance evaluation of computer programs requires reliable execution time measurements. However, modern computer systems contain various hardware and software mechanisms that introduce variability into timing measurements, making the observed performance differ from the algorithm's actual behavior. In this study, the execution time of the Merge Sort algorithm was measured for different input sizes under two experimental conditions: normal system operation and a quiesced system. The results demonstrate that system noise produces noticeable fluctuations in execution time, while reducing these sources of interference significantly improves the stability and repeatability of the measurements. These findings highlight the importance of controlling system noise when conducting performance benchmarking and demonstrate that system quiescing provides a more reliable environment for performance evaluation.
Copyright (c) 2026 Mohammad-Moein Arabi https://creativecommons.org/licenses/by/4.0
Limitations of Fourier Neural Operators for Nonlinear Structural Response Prediction under Earthquake Excitation
Neural operators provide a promising framework for mapping earthquake ground motions directly to structural response histories, but their accuracy for nonlinear dynamics and out-of-distribution conditions remains poorly understood. We systematically evaluate a fixed Fourier Neural Operator architecture using single- and five-degree-of-freedom systems with linear-elastic, cubic-hardening, and bilinear-hysteretic restoring forces. Our numerical tests isolate the effects of restoring-force nonlinearity, structural period, excitation frequency content, and ground-motion amplitude. Within the training regime, the mean perrecord relative L2 error increases from 0.02 for the linear system to 0.28 and 0.38 for the cubic-hardening and bilinear-hysteretic systems, respectively; corresponding five-degree-of-freedom tests confirm the deterioration for hysteretic response. Generalization degrades more severely under distribution shifts. When structural periods fall outside the 0.5–1.0s training interval, relative L2 errors exceed 1 for both single- and multi-degree-of-freedom systems. Broader excitation frequency content further reduces nonlinear prediction accuracy, even within otherwise interpolative conditions. In addition, when models trained on records with peak ground accelerations up to about 0.19 g are evaluated at amplitudes up to about 1.0 g, they underpredict the root-mean-square bilinear-hysteretic response by approximately 17%. Error decomposition further shows that residual mean offsets account for approximately 22% of the bilinear-hysteretic error, compared with 3% for the cubic-hardening system, whereas amplitude-scaling errors remain small. These results demonstrate that strong interpolation performance does not ensure accurate prediction of nonlinear structural response under changes in structural or excitation regimes.
Copyright (c) 2026 Kexun Li, Luis Ceferino https://creativecommons.org/licenses/by/4.0
Consolidation of Sinking Infrastructures by Pore Pressure using XYY' Calculus
The consolidation of sinking infrastructures on soft soils is characterized by unknown initial conditions () and ambiguous boundary conditions (type, shape, and size of drainage). Under these forensic conditions, classical Newton-Leibniz chronological frameworks and traditional consolidation methodologies fail, triggering the "Missing Time" problem. This paper introduces the application of the XYY' Calculus framework—originating from complex soil mechanics in the mid-1990s—to model infrastructural consolidation using exclusively localized pore pressure measurements, completely bypassing the need for physical settlement data. By transforming the process from the chronological time domain into a geometric state-space, pore water pressure is mapped directly against its instantaneous dissipation rate. This proves that late-stage consolidation converges into an invariant linear phase-space trajectory known as the Master Decay Asymptote. This linearity encapsulates the universal Central Operator (), allowing for the flawless extraction of the coefficient of consolidation () irrespective of initial loading times. The technique isolates pure hydrodynamic diffusion from secondary structural creep, rendering it a robust mechanism for 3D underground mapping. Optimal piezometer placement strategies permit the determination of vertical at 30% to 40% consolidation, while radial consolidation parameters can be extracted at just 5% to 10% consolidation. This framework simplifies complex partial differential equations into linear algebraic relationships, providing ideal normalized feature sets for AI and Machine Learning applications in modern computational geomechanics. This is particularly useful for global infrastructure challenges like the Mexico City's subsidence, Kansai Airport, Jakarta City, the MOSE project Venice etc
Copyright (c) 2026 Prof Sudhir Kumar Tewatia, Mr Kanishck Tewatia, Mr Anttriksh Tewatia https://creativecommons.org/licenses/by/4.0
Pair-valued bi-matrix games and lexicographic equilibrium strategy profiles
For pair-valued bi-matrix games we show that a necessary and sufficient condition for a strategy profile to be a lexicographic equilibrium strategy profile is that the strategy profile must be an equilibrium strategy profile for the bi-matrix game corresponding to the first coordinates and if the expected value of an action for a player in this bi-matrix game is equal to the expected value of this bi-matrix game for the player, then the expected value of the same action for the same player in the bi-matrix game corresponding to the second coordinates is less than or equal to its expected value in this second bi-matrix game. This result is used in an example of a pair-valued bi-matrix game to show that it has no lexicographic equilibrium strategy profile. Subsequently we prove a necessary and sufficient condition in terms of a bi-linear programming problem with a real-valued objective function and constraints which are also real-valued. We show that a possible resolution of the coordination problem in 2X2 coordination games could be achieved by introducing the concept of a dominant player, thereby embedding the coordination game in a pair-valued bi-matrix game and then choosing the lexicographic equilibrium strategy profile of the pair-valued bi-matrix game.
lexicographic equilibrium strategy profile
Copyright (c) 2026 Somdeb Lahiri https://creativecommons.org/licenses/by/4.0
Sediment-Related Problems in the Nile Basin: Emphasis on Sudan/South Sudan's Experience
The growing awareness of the important role of alluvial sediment in water resources management has accentuated the need for better and more consistent information, yet such information still lags. In the Nile Basin, the problem of sediment management represents quite a challenge. In this paper, brief information on sediment transport and watershed management is reported. The difficulties and constraints in this field are reflected and discussed. Comments on sediment modelling in general and on the Nile Basin in particular are highlighted. Among several sediment modelling software packages, the SMS model has been selected for data analysis in the Nile Basin. The experience of Sudan/South Sudan (67% of the Nile Basin area-wise) in sediment management, which is very rich, is examined and explained. Management of sediment should work with nature, not against it, for ecological and economic sustainability. The paper concludes that sediment supply, transport and deposition are spatially and temporally variable; therefore, integrated sediment transport management in the Nile Basin requires a policy aimed at decreasing the adverse impacts of sedimentation for both U/S and D/S countries across the entire basin.
Copyright (c) 2026 Abdalla A. Ahmed https://creativecommons.org/licenses/by/4.0
Crumple: An Empirical Crush and Force Envelope for the Modern Australian Vehicle Fleet
Designers of vehicle barriers face a gap between two regimes. At the low end, AS/NZS 1170.1 prescribes fixed car-park barrier forces whose assumed crumple zones (0.10–0.15 m) have no stated empirical derivation and do not scale with vehicle mass or speed. At the high end, hostile-vehicle-mitigation standards certify specific barrier products at 48–80 km/h but publish no calculation method. In between, for impacts at 30–60 km/h or by vehicles heavier than a passenger car, the designer has no empirically grounded estimate of vehicle crush or average impact force. This paper offers that basis: an empirical research envelope. From 10,876 crash-test records of the United States National Highway Traffic Safety Administration (NHTSA), a documented quality-control chain yields a modern cohort, model year 2004 on, age-matched to the Australian passenger fleet. The 614 tests with directly derived dynamic crush supply the primary fit, a non-crossing quantile envelope in speed and mass, with average force following from the energy identity F_avg = mv²/(2d), checked independently against barrier load cells. The result is a rigid-barrier crush and force envelope supported over 1,007–3,448 kg and 33–57 km/h, read in both directions: the stiff-vehicle 5th percentile bounds force demand, the soft-vehicle 95th percentile bounds penetration. The load cells locate the height at which the force acts. Beyond the tested speeds, external evidence bounds a crush ceiling the data alone cannot locate, keeping the high-speed force treatment conservative. It is offered as a candidate basis for future calibration, not as characteristic design actions.
Copyright (c) 2026 Daniel Vaughan https://creativecommons.org/licenses/by/4.0
Behavior-rule dependence of capacity gains and hysteresis suppression in autonomous/human mixed cellular-automaton traffic
The dependence of capacity gains and hysteresis suppression on the choice of autonomous-vehicle (AV) behavior rule is investigated using a Nagel--Schreckenberg-type cellular-automaton model of mixed AV/human-vehicle (HV) traffic. Four AV following rules---naive (deterministic Nagel--Schreckenberg), IDM, ACC, and CACC---are implemented under a common collision-safety architecture, in which each vehicle computes a desired speed from its own rule and is subject to the same hard safety floor. Slow-to-start (VDR) dynamics are retained for HVs to induce hysteresis, and two independent detection methods are used to quantify the hysteresis loop width as a function of AV penetration rate $r$. The framework is validated against an exact two-species disordered-TASEP solution at $v_{¥max}=1$, showing agreement to within 0.53¥%. The capacity gain from AV penetration is found to be highly sensitive to the calibration of the AV following rule rather than being an intrinsic property of the rule itself: under human-calibrated IDM parameters, AV penetration lowers capacity below the human-only baseline at every penetration rate tested, whereas doubling the acceleration/deceleration capability reverses this shortfall into a capacity gain. CACC, in contrast, saturates the common safety floor and becomes indistinguishable from the naive rule at high $r$, while ACC remains distinct owing to its longer effective headway. Furthermore, hysteresis suppression is shown to be threshold-like rather than proportional to $r$: the loop width remains largely unchanged up to $r¥approx0.4$ and vanishes only as $r¥to1$, indicating that AVs must dominate the population of stopped vehicles before slow-to-start asymmetry is eliminated. These results demonstrate that the widely assumed benefit of AV penetration for traffic flow is not a model-independent conclusion, but instead depends sensitively on the specific behavior rule and its calibration.
Copyright (c) 2026 Mitsuyoshi Yagyu https://creativecommons.org/licenses/by/4.0
Identification of the Determinants of Severity for Pedestrian Injuries on Brazilian Federal Highways between 2017 and 2019: A Multinomial Logistic Regression Analysis
Walking is one of the main forms of mobility among the Brazilian population, representing 41% of the trips made in the country in 2016. However, the sharing of space between pedestrians and motor vehicles in locations lacking adequate infrastructure has created conflict situations, increasing the risk of injuries and fatalities among pedestrians. This study analysed the determinants of injury severity among pedestrians on Brazilian federal highways between 2017 and 2019. Official data from the Brazilian Federal Highway Police were used to create a multinomial logistic regression model that classified the injury severity of pedestrians involved in highway crashes based on a set of explanatory variables. The results indicate that pedestrians struck by large vehicles, such as trucks, buses, and utility vehicles, have higher odds of death; periods of the day with lower natural light, such as night, dawn, and dusk, are associated with a higher risk of severe injuries and fatalities; urban road segments are less prone to fatalities than those located in rural areas; male pedestrians have higher odds of severe injury or death; and multi-carriageway roads and weekends are associated with higher odds of pedestrian death or severe injury. Finally, an annual upward trend was identified in the odds of severe injury (9.9% per year) and death (3.3% per year) among Brazilian pedestrians, alongside a higher risk of pedestrian injuries in the North, Northeast, and Central-West regions.
Copyright (c) 2026 Rian Miranda, Walber Paschoal da Silva, Steven Dutt-Ross https://creativecommons.org/licenses/by/4.0
ActionABI: Turning Undocumented Action Tensors into Verified Converters or Honest Refusals
Robot learning datasets and deployments routinely carry action tensors whose meaning—which channel drives which degree of freedom, its sign, scale, whether targets are absolute or delta, in which frame, with what pipeline lag, and whether the gripper is inverted—is undocumented, untrusted, or missing. Existing tools either check declared metadata against a specification or define new schemas going forward; neither retrofits legacy or adversarial data carrying no metadata at all. We present ActionABI, a C++20 evidence-first CLI that scores a finite, declared action-interface grammar against timestamped trajectories, retains a calibrated observational-equivalence set instead of breaking ties, and emits a converter only when every required field is supported by evidence—abstaining rather than forcing a unique answer. On a 100-case synthetic ambiguity gate, ActionABI eliminates all 25 false unique certifications a forced-argmin baseline makes, at full coverage. Against ground-truth latent contracts from real ManiSkill GPU simulation (90 traces, 45 contracts), structural fields (permutation, sign) recover to 0.80/0.84 overall after a lag-observable fix, while scale is confounded by the physical controller, not the grammar. A 35-dataset Hugging Face Hub audit scores recovered conventions against documented ones over 139 field-labels with 0 contradictions and 0 false uniques, finding that “OXE” is not one action convention and that ≥ 5 gripper-polarity conventions coexist. Three measurement-driven defects were found, root-caused, fixed, and regression-tested; ActionABI’s C++ core runs load-bearing in a sibling adaptation benchmark at 5.7 × 10⁻¹⁴ parity and a ~13× CPU-regime speedup, while its CUDA path honestly fails a preregistered 5× gate. We make no “first” claims and no hardware claims; every number traces to a committed report.
Engineering › Computer Engineering › Robotics (primary)
Physical Sciences and Mathematics › Computer Sciences › Artificial Intelligence and Robotics
Physical Sciences and Mathematics › Computer Sciences › Software Engineering
Copyright (c) 2026 Krishi Attri https://creativecommons.org/licenses/by/4.0
Calibrated Per-Carrier Confidence and Certified Pruning for Gaussian-Splat Assets
A 3D Gaussian-splatting asset ships millions of primitives, each carrying a per-primitive confidence — a view count, an opacity — that downstream pruning, streaming, and level-of-detail decisions consume as if it meant something. It does not: these numbers are heuristics with no operational meaning and no guarantee, so a consumer that drops “low-confidence” primitives is guessing. We ask what it takes to give a splat asset a per-carrier confidence a consumer can actually trust, and report AURA, a preview-stage library (v1.0.0) that attaches one. The method has three parts, each pure-CPU post-processing over the exported carrier array. First, a held-out per-carrier reliability label from multi-view re-projection agreement: a carrier is reliable to the degree its stored colour matches what independent held-out views observe where it projects, computed under both an occlusion-blind colour label and a stricter occlusion-aware depth label. Second, isotonic (PAVA) calibration of an export-time feature — train-view colour agreement, computable without held-out ground truth — into a calibrated confidence. Third, a distribution-free split-conformal pruning certificate: prune every carrier below a threshold (\tau) and the retained set’s mean unreliability is at most (\epsilon) with confidence (1-\alpha). On four real scenes (Tanks-and-Temples Truck; Mip-NeRF-360 Garden, Kitchen, Room), the export-time feature predicts held-out reliability at correlation 0.91–0.98 (colour label) while the shipped view-count heuristic ((|r| \leq 0.13)) and opacity (−0.18 to +0.16) do not; isotonic calibration cuts expected calibration error from 0.46–0.59 to 0.0006–0.0016 (~300–900×); and confidence-guided selection recovers 0.58–0.72 mean retained reliability, within 1–4% of an oracle ceiling and above opacity (0.37–0.53, at or below random) at every budget — keeping only 10% of carriers it retains 0.77–0.90 reliability versus opacity’s 0.31–0.49. The properties survive the stricter occlusion-aware label; they further persist at native full resolution under a corrected, genuinely held-out split (which lowers one over-optimistic per-scene certificate from 1.00 to 0.77), transfer across scenes for selection (AUC within ±0.0004) with a small per-scene conformal set restoring the certificate, and survive a stricter render-loss label read from the actual alpha composite with honestly weaker margins. We extend the single pruning certificate into a certified level-of-detail ladder — a consumer streams carriers in descending calibrated confidence and may stop at any published level with a distribution-free, family-wise bound on the unreliability mass it thereby discards (all 16 bounds hold across four scenes and four levels). We deliver the calibrated confidence through the KHR_gaussian_splatting_AURA_CONFIDENCE channel, the OpenUSD 26.03 UsdVolParticleField3DGaussianSplat schema, and a sidecar for Niantic’s SPZ v4 container whose writer is cross-validated bit-exact against the reference implementation. We are deliberate about scope: AURA is a preview-stage system; the reliability labels are self-computed re-projection proxies, not human ground truth; the evaluation gates, while content-checked against the committed artifacts, are our own and run locally; the scenes are single captures; the typed-carrier backend result we report (+0.33 dB on Truck) is a reproduction of Deformable Beta Splatting, not a contribution of this paper. What we do claim is narrow and, we believe, new: a calibrated, certified, exportable per-carrier confidence is a capability a bare Gaussian splat does not have, and this paper measures it honestly on real scenes.
Physical Sciences and Mathematics › Computer Sciences › Graphics and Human Computer Interfaces (primary)
Physical Sciences and Mathematics › Computer Sciences › Numerical Analysis and Scientific Computing
ActionShift: A Benchmark for Hidden Compositional Action-Interface Adaptation in Manipulation
Robot-learning benchmarks that hide dynamics parameters—mass, friction, payload—have driven a mature line of adaptation methods: online system identification, meta-RL, and rapid motor adaptation. A distinct, software-level failure mode is equally real and structurally different. The mapping from a policy’s action tensor to controller behavior—which channel drives which axis (or mutation), each channel’s sign and scale, whether the target is a delta or an absolute pose, its reference frame, its pipeline lag, and the gripper convention—can itself be wrong, undeclared, or silently changed, and we are not aware of a prior benchmark that isolates this action-interface contract as the object of study while holding task dynamics fixed. We introduce ActionShift, a real-simulation benchmark on frozen, competent ManiSkill PPO and Diffusion Policy backbones (PickCube, PushCube, PullCube, StackCube) in which a discrete, compositional interface contract is hidden behind a leakage-safe wrapper across preregistered seen, unseen-composition, and long-lag splits, with a privileged oracle and preregistered promotion gates. A competent policy that is near-perfect under a known interface (up to 1.000) collapses to a 0.000–0.007 floor when it is hidden—identically for RL and imitation policies—and the same policy-agnostic belief adapters restore both. Across a matched-privilege tournament, entropy-guided probing clears our promotion gate over fixed probing on 2 of 4 tasks (+5.8 points, 3-seed paired-significant on PickCube), and our controller, DualABI, matches the champion’s success at roughly half the probe cost on all four tasks. Grammar-only belief, with no privileged pool, converts the learned-identifier tier’s ~0.0 into 0.36–0.67 and—via a hold-probe excitation schedule—breaches the all-absolute wall (0.005→0.722, 0.000→0.790). We report the load-bearing negatives in equal detail: passive learned identification fails outright (0.0), every reactive method including the oracle collapses under lag, and a delay-aware backbone solves the long-lag split by planning through delay (~20×/~2.7×)—evidence the two adaptation problems are not interchangeable in practice. We make no literature-priority (“first”) claims: every novelty statement is an explicit “we are not aware of” backed by a direct literature check.
Engineering › Electrical and Computer Engineering
Probabilistic Background of Eurocode Ship Impact Forces and a Remaining-Life-Based Reduction Rule for Existing Bridges
Ship impact on bridges represents a highly complex load case due to its dynamic and probabilistic nature. Experimental research gained momentum in the mid-20th century, with seminal studies laying the foundation for understanding of impact mechanics. The key influencing parameters include the vessel’s mass, geometry, stiffness, and velocity. This variability makes it difficult to derive representative impact forces for design and analysis. The load models in the Eurocode have been derived from probabilistic analyses; however, verifications are typically carried out deterministically. This paper reconstructs the probabilistic framework underlying the Eurocode ship impact provisions and clarifies the link between collision models, impact force distributions and return periods. Building on this framework, a rational approach is presented that allows ship impact loads for existing bridges to be adapted depending on the remaining working life of the structure. The proposed approach is also, in principle, applicable to other types of accidental actions. The method enables impact-action levels to be related to a finite remaining assessment period while preserving the nominal cumulative exceedance probability assigned to the reference action, thereby fostering more efficient and sustainable use of resources.
Civil Engineering, Structural Engineering
Copyright (c) 2026 Christian Gasser, Claus Kunz, Vazul Boros, Ralph Holst https://creativecommons.org/licenses/by/4.0
Automated Multi-Class Structural Damage Detection and Segmentation for Unmanned Aerial Vehicle-Based Infrastructure Inspection Using Deep Learning
This study presents a three-stage deep learning framework for automated structural damage classification, segmentation, and unmanned aerial vehicle (UAV)-based inspection simulation targeting bridges, offshore platforms, and other civil infrastructure. Stage 1 fine-tunes ResNet50 with differential learning rates and class weighting to classify crack, corrosion, spalling, and intact surfaces, achieving 85.69% accuracy on a held-out test set of 1,600 images drawn from multi-source public datasets, with the differential learning rate strategy contributing an 8.25% improvement over the frozen-backbone baseline. A targeted augmentation strategy addresses minority-class imbalance and yields a spalling F1-score of 0.886 under the balanced evaluation protocol. Stage 2 applies DeepLabV3+ with a partially unfrozen ResNet50 backbone for pixel-level damage localization, achieving mean intersection over union (mIoU) values of 0.7890 for three-class segmentation and 0.6446 for four-class segmentation, the latter incorporating 315 real UAV crack images to extend the training distribution to the aerial perspective absent from most public crack datasets. Stage 3 integrates frame-level inference into a boustrophedon UAV grid inspection simulation that produces a severity-coded damage map and a structured JSON inspection report, identifying 16 of the 20 damaged zones. Average CPU inference time is 16.29 ms per frame (61 frames per second), consistent with near-real-time deployment on modest hardware. Ablation studies of backbone unfreezing depth and Grad-CAM visualizations provide additional support for the robustness and interpretability of the proposed pipeline. The framework demonstrates that multi-class damage recognition, pixel-level localization, and inspection workflow integration can be combined in a single reproducible system built entirely on open data.
Copyright (c) 2026 Seyed Farhad Abtahi https://creativecommons.org/licenses/by/4.0
Multi-Scale Mapping of Diaphyseal Stresses Across Gait Modalities Using Femoral Digital Twins
Bone health decreases with age and can culminate in fractures with particularly devastating consequences in the femur. Exercise-induced mechanical loading can be prescribed as preventative care, but clinical recommendations are hindered by a lack of clarity regarding the mechanical stresses experienced during habitual locomotive tasks such as walking, stair descent, and stair ascent. We used subject-specific, muscle-driven finite element digital twins of post-menopausal women to conduct a multi-scale analysis of the spatiotemporal distribution of femoral principal stresses during each task. At the macroscopic level, stresses peaked during both the early and late stance phases of the gait cycle and the femur was subjected to a combination of bending and torsional loads for all tasks. Mesoscale analyses revealed a noticeable regional partition: stress distributions were highly consistent across tasks and timepoints in the proximal and mid-diaphysis, but deviated in the distal diaphysis. At the tissue level, peak stresses during stair ascent were lower in the proximal region but higher in the distal region compared to walking and stair descent; meanwhile, in the mid-diaphysis, peak stresses during stair descent exceeded those during walking. Together, these findings indicate that while the global femoral loading environments were similar across tasks, there was heterogeneity in the spatial and temporal mechanical response. Incorporating stair activity into daily routines can diversify bone remodeling stimulation throughout the diaphysis.
Copyright (c) 2026 Mikayla Hoyle, Saulo Martelli, Marcus Pandy, Mariana Kersh https://creativecommons.org/licenses/by/4.0
We present a phase-domain method for generating multi-input synthetic vibration signals that match a prescribed cross-spectral density (CSD) together with a user-selected set of higher-order diagonal and cross moments. The CSD is enforced structurally by pre-multiplying random-phase, unit-modulus, frequency-domain signals with a Cholesky factor of the target CSD, following the frequency-domain synthesis of Shinozuka and Jan (1972) and its extensions to partially coherent and non-Gaussian MIMO outputs (Smallwood and Paez 1993; Smallwood 1997; Cui et al. 2011); this leaves the remaining phase degrees of freedom unconstrained. We show that this freedom is enough to shape the channelwise moments – extending the IFFT phase-manipulation idea of Steinwolf (1993, 2011, 2012) – and, in addition, the joint cross-moments (co-skewness, co-kurtosis) that govern coincident-peak excursions and hence multi-axial fatigue damage (Saathoff et al. 2006). The key result is a single Fourier-domain identity: the gradient of any differentiable memoryless functional of the synthesized signal, with respect to the free phases, reduces to one forward Fourier transform of its pointwise derivative, projected through the conjugated unit-modulus source spectrum u* and the conjugated frequency response H*. Every target used in this paper – diagonal and cross moments, endpoint values, a crest-factor surrogate – is an instance of this one identity, at a cost of at most m FFTs per gradient evaluation for a target of order m, independent of the number of channels; the MIMO case therefore requires no machinery beyond the single-channel one. The resulting problem is smooth and is solved with SciPy's L-BFGS-B (Byrd et al. 1995; Virtanen et al. 2020) using the analytic gradient directly, found in a head-to-head comparison to need an order of magnitude fewer loss evaluations than NLopt's CCSAQ (Svanberg 2002; Johnson 2007–present) on the warm-started continuation used for crest minimization, while matching or improving the achieved optimum. When the target statistics are estimated from a measured multi-axial record the targets are realizable by construction – the record itself is a witness – which is the primary operating regime for the method; we demonstrate it on a 12-channel wheel-hub force/moment record measured on a test track, reproducing all 30 moment targets alongside the full CSD, and show empirically that the per-evaluation cost scales tractably to 32 channels and 560 simultaneous targets. A complete, unit-tested reference implementation – including Slepian multitaper CSD estimation and analytic-gradient verification against central differences – is open-sourced at https://github.com/luchp/mimoshape; every figure and table in this paper is regenerated from it with fixed seeds.
Copyright (c) 2026 Luc Holtkamp https://creativecommons.org/licenses/by/4.0
Statistical Attribution of In-Service Specific Fuel Oil Consumption Deviation to Bunker Fuel Combustion Quality
Specific fuel oil consumption (SFOC) deviation in service is routinely attributed, without formal separation, to some combination of bunker fuel quality, engine mechanical condition, ambient operating conditions, and load profile. Existing correction practice — net calorific value (NCV) normalisation to an ISO reference and ambient correction under ISO 3046-1/15550 — removes the deterministic component of fuel-quality effects but leaves the combustion-quality component (incomplete combustion, ignition delay, afterburning associated with poor ignition characteristics) unseparated from genuine engine degradation. This paper proposes a regression-based framework that reconstructs bunker-batch boundaries from tank remaining-on-board (ROB) records, applies deterministic NCV correction, and then estimates a fixed-effects model in which each bunker batch enters as a categorical variable alongside engine load and a continuous time-drift term representing mechanical degradation. The batch coefficients recovered by this model are interpreted as the combustion-quality penalty of each bunker batch, net of energy content, load, and engine wear, with confidence intervals derived from heteroskedasticity- and autocorrelation-consistent standard errors. Three identification threats — confounding with maintenance events, confounding with load profile, and confounding with ambient conditions — are formalised as automatic diagnostic checks, and a placebo test using randomised batch boundaries is proposed to guard against spurious attribution. The framework is demonstrated on a synthetic twelve-month operating dataset for a representative handysize bulk carrier with injected ground-truth effects; the batch with the largest injected effect is recovered within its estimated confidence interval, while smaller and sequentially later batches show attenuated identification consistent with a formally diagnosed collinearity between batch timing and the continuous degradation term — a limitation the paper reports explicitly rather than obscures. The paper situates this contribution against the existing literature, which addresses fuel ignition quality (CCAI, CII, EFN) and in-service SFOC monitoring as separate bodies of work; to the authors' knowledge, no published methodology jointly estimates bunker-batch-specific combustion penalties from routine in-service reporting data under an explicit identification framework. Implications for bunker procurement, fuel quality dispute resolution, and vessel performance monitoring practice are discussed, along with the method's data and instrumentation requirements and its limitations.
Copyright (c) 2026 Tanmoy Dey https://creativecommons.org/licenses/by/4.0
Acoustic Emission Signatures of Flow Boiling in a Microchannel Heat Sink
Flow boiling in microchannel heat sinks is a promising route for next-generation electronics cooling, but its implementation is limited by interfacial instabilities, flow oscillations, vapor choking, and local dryout. Conventional diagnostics based on optical visualization, temperature, pressure, and flow-rate measurements are valuable, but they can be difficult to apply for real-time monitoring in compact or visually inaccessible cooling hardware. This work evaluates contact acoustic emission (AE) sensing as a nonintrusive diagnostic for identifying phase-change events and characterizing transient two-phase flow behavior in a microchannel heat sink. A synchronized multimodal facility was developed that combines contact AE sensing, airborne microphone measurements, thermofluidic measurements, and high-speed optical imaging under controlled heating conditions. Representative tests comparing a single-phase baseline at P = 2.2 W with a boiling case at P = 45.3 W show that boiling onset produces pronounced increases in AE amplitude and AE hit rate. The AE count-duration distribution also broadens during boiling and includes short-duration, high-count transients that are consistent with rapid interfacial motion and abrupt vapor-fraction changes. In contrast, microphone spectrograms show weaker separation between single-phase and two-phase conditions, indicating that solid-borne AE is more sensitive to confined boiling events under the tested conditions. These results establish a baseline framework for physics-informed acoustic diagnostics and machine-learning-assisted monitoring of two-phase thermal management systems.
Copyright (c) 2026 Stephen Pierson, Hari Pandey, Ben Xu, Han Hu https://creativecommons.org/licenses/by/4.0
Dual-Constrained Diffusion Model for Nonlinear Microstructure Inverse Design with Direct Evaluation
Diffusion models have emerged as powerful tools for inverse design, yet their stochastic nature typically requires surrogate models or additional numerical simulations to verify target-condition satisfaction. To address this bottleneck, we propose a dual-constrained diffusion framework that jointly generates structural designs and solution fields under both physical and conditional constraints. The framework combines a dual-constrained diffusion model (DCDM) for training-stage constraint enforcement with dual-guided diffusion sampling (DGS) for sampling-stage guidance, enabling direct evaluation without additional numerical simulations. We demonstrate the framework through the inverse design of hyperelastic microstructures conditioned on prescribed strain energy under uniaxial extension. Compared with a conventional diffusion model, DCDM with DGS reduces physics residual errors by more than an order of magnitude. In addition, 1,000 generated candidates can be screened directly in approximately 0.27 seconds. Importantly, because the dual constraints are incorporated during training, a single DCDM supports target-aligned unguided generation and can be combined with DGS for guided generation. For high-density in-distribution targets, unguided generation produces structurally diverse candidates with reliable direct evaluation at one-fifth the sampling time of guided generation. When higher target fidelity is desired or out-of-distribution targets are considered, DGS can be activated on the same trained model to increase the number of valid candidates and maintain reliable target satisfaction beyond the training distribution. The proposed framework provides a general and practical approach to inverse design for systems governed by physical laws, requiring only the definition of physics and condition residuals.
Copyright (c) 2026 Jecheon Yu, Jinun Byun, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu https://creativecommons.org/licenses/by/4.0
Industrial Use of Steam in Sustainable Oil Recovery
The enhanced oil recovery operation refers to an industrial process within the oil sector for producing crude oil from reservoirs that have been exploited to the point that ordinary lifting technologies prove to be inadequate. This enhanced oil recovery operation aims to change the characteristics of the crude oil such that it becomes more flowable. The present study considers solar-based thermal enhanced oil recovery systems in Oman at the oil field “Amal” that is located in Dhofar, which is the country’s largest governorate (state). In these systems, reflective trough concentrator surfaces are utilized for producing hot water vapor in a steam generator for the thermal recovery of crude oil. Three systems were established, which are “Amal I”, “Amal II”, and “Miraah”. If these systems are combined together, they can provide approximately two trillion British thermal units of heat annually while producing a peak of 2.1 kilotonnes of steam daily and avoiding the annual release of carbon dioxide, preventing annual emissions that exceed 100 kilotonnes. The three unconventional systems of oil recovery are briefly discussed here as examples of sustainability transformation practices in business and engineering under the oil sector.
Copyright (c) 2026 Osama Marzouk https://creativecommons.org/licenses/by/4.0
Comparison, Evaluation and Development of Bio-Based Screen-Printing Inks
Screen printing is a well-established printing technique that typically uses petrochemical inks, which can be problematic both for the environment and recycling. This study investigates the development and characterization of bio-based screen-printing inks as a sustainable alternative. Various bio-based inks using materials such as starch, chitosan and cellulose were formulated, and their viscosity was analyzed using a rotational rheometer. The print quality was examined by screen printing tests on various substrates and subsequent visual and color density assessment. Rubbing fastness and light fastness were determined using a crockmeter resp. xenon light. The results show that the print quality is only slightly dependent on the viscosity, although there is an optimum viscosity range. A higher polymer concentration in the ink led to a slightly improved resistance to rubbing, while the light fastness was exclusively influenced by the pigment used. Several bio-based formulations showed equivalent or better print quality than the petrochemical reference ink, especially in terms of edge sharpness. These findings highlight the potential of bio-based screen-printing inks for a more environmentally friendly printing industry. The study shows that sustainable formulations with renewable raw materials are a promising alternative to conventional inks.
Copyright (c) 2026 Philipp Wüst, Thorsten Euler, Marcus Bischoff, Dieter Spiehl, Edgar Dörsam, Andreas Blaeser https://creativecommons.org/licenses/by/4.0
Determination of the Volume of Trucks from the Data of Annual Average Growth Rate from 2005 to 2030, Cost, Operational Issues, and Economical Condition on National Highways
The primary intention of the goal of the study is to find out the volume of trucks from the data of annual average daily traffic on national highways. The objective of the survey was to find out the number of trucks that entered and left the truck terminals within 15 minutes. The study also helps to identify the cost and operational issues for observing the present financial and economic condition of the truck industry in our country. The annual average growth rates of trucks from 2005 to 2030 are also included in this study. Besides, a field survey was performed in the truck terminals of Dhaka city to identify the flow of trucks. Our report also includes a breakdown of the findings of the 2008 investigation into the two most popular truck makes. The percentage of trucks by type can also be obtained from the annual average traffic volume data. This is an important factor in calculating the depreciation expenses attributed to various types of vehicles, which is emphasized in our study. The overhead cost consists of office administration and rental charges, garaging, insurance, vehicle excise duty/ VAT, and tolls/route permit fees. Road safety is an essential consideration in urban traffic planning and safety. Globally up to two-thirds of all traffic injuries occur in urban areas, and trucks are significant in the overall context of road accidents. Accident characteristics were examined in terms of severity level, locations, accident rates, time of accidents, casualty class, etc. However, this study will help to understand the current situation of truck movement in our country.
Copyright (c) 2026 Asif Al Adnan, Tahamina Fariya Supty, Zeba Tahsin https://creativecommons.org/licenses/by/4.0