Search Results (3,610)

Value factorization methods have become a standard tool for cooperative multi-agent reinforcement learning (MARL) in the centralized-training, decentralized-execution (CTDE) setting. QMIX (a monotonic mixing network for value factorization), in particular, constrains the joint action–value function to be a monotonic mixing of per-agent utilities, which guarantees consistency with individual greedy policies but can severely limit expressiveness on tasks with non-monotonic agent interactions. This work revisits this design choice and proposes Relaxed Monotonic QMIX (R-QMIX), a simple regularized variant of QMIX that encourages but does not strictly enforce the monotonicity constraint. R-QMIX removes the sign constraints on the mixing network weights and introduces a differentiable penalty on negative partial derivatives of the joint value with respect to each agent’s utility. This preserves the computational benefits of value factorization while allowing the joint value to deviate from strict monotonicity when beneficial. R-QMIX is implemented in a standard PyMARL (an open-source MARL codebase) and evaluated on the StarCraft Multi-Agent Challenge (SMAC). On a simple map (3m), R-QMIX matches the asymptotic performance of QMIX while learning substantially faster. On more challenging maps (MMM2, 6h vs. 8z, and 27m vs. 30m), R-QMIX significantly improves both sample efficiency and final win rate (WR), for example increasing the final-quarter mean win rate from $42.3\%$ to $97.1\%$ on MMM2, from $0.0\%$ to $57.5\%$ on 6h vs. 8z, and from $58.0\%$ to $96.6\%$ on 27m vs. 30m. These results suggest that soft monotonicity regularization is a practical way to bridge the gap between strictly monotonic value factorization and fully unconstrained joint value functions. A further comparison against QTRAN (Q-value transformation), a more expressive value factorization method, shows that R-QMIX achieves higher and more reliably convergent win rates on the challenging SMAC maps considered. Full article

Top-and-seat angle connections (TSACs) exhibit inherently asymmetric and nonlinear moment–rotation behavior, which can significantly influence the global response of steel frames subjected to combined gravity and lateral loading. In this study, a three-dimensional finite element model of an unstiffened TSAC is developed and validated against experimental moment–rotation data from the literature under monotonic loading conditions. The validated model is then used to investigate the influence of key geometric parameters, including top angle thickness, bolt diameter, and beam depth, on the connection’s moment–rotation response in both positive and negative bending directions. Subsequently, the monotonic connection behavior is incorporated into nonlinear static analyses of steel portal frames to examine the effects of asymmetric connection response and moment reversal on frame-level stiffness degradation and capacity. A practical SAP2000 modeling workflow is proposed in which the finite element-derived monotonic moment–rotation curves are implemented using zero-length rotational link elements, allowing combined consideration of material, geometric, and connection nonlinearities at the structural level. The comparisons between Abaqus and SAP2000 results demonstrate consistent frame-level responses when identical monotonic connection characteristics are employed, highlighting the ability of the proposed workflow to reproduce detailed finite element predictions at the structural analysis level. The results indicate that increasing top angle thickness, bolt diameter, and beam depth enhances the lateral stiffness and base shear resistance of steel frames. Positive and negative bending directions are defined consistently with the applied gravity-plus-lateral loading sequence. Full article

To clarify how flow-channel configuration and wall spacing govern the hydrodynamic performance of an oscillating-hydrofoil biomimetic pumping device, this study conducted a systematic numerical investigation under confined-flow conditions. Using a finite-volume solver with an overset-grid technique, we compared pumping performance across three channel configurations and a range of channel–wall distances. The results showed that bidirectional-channel confinement suppresses wake deflection and irregular vorticity evolution, enabling symmetric and periodic vortex organization and thereby improving pumping efficiency by approximately 33.6% relative to the single-channel case and by 62.7% relative to the no-channel condition. Wall spacing exhibited a distinctly non-monotonic influence on performance, revealing two high-performance regimes: under extreme confinement (gap ratio $h/c=$ 1.4), the device attains peak pumping and thrust efficiencies of 19.9% and 30.7%, respectively, associated with a strongly guided jet-like transport mode; and under moderate spacing ($h/c=$ 2.2–2.6), both efficiencies remain high due to an improved balance between directional momentum transport and reduced vortex-evolution losses. These findings identify key confinement-driven mechanisms and provide practical guidance for optimizing flow-channel design in ultralow-head oscillating-hydrofoil pumping applications. Full article

The passage of a premixed stoichiometric methane-air flame through a hole in an internal barrier in a Hele-Shaw channel with one end closed was studied experimentally. It was found that for the same initial conditions, a flame propagating from the closed channel end can either pass through the hole in the barrier or be extinguished. The passage probability dependence on the hole width was found to be non-monotonic, with a sharp maximum at small hole sizes, followed by a minimum at intermediate sizes and a gradual increase as the blockage ratio tends to zero. The nature of this non-monotonic behavior of flame passage probability was analyzed by analyzing the flame front histories leading to flame passage or extinction at the same experimental parameters. A likely cause of this behavior is the development of an alternating-direction gas jet blowing from the hole due to the pressure difference between the channel compartments. Cooling of hot combustion products with cold channel walls can cause a pressure drop in the closed channel part and development of a reverse (open-to-closed compartment) gas jet affecting the approaching flame. Therefore, flame passage or extinguishment is a feature of the whole two-chamber system, rather than an intrinsic flame property. Full article

This work presents a time-domain analog-to-digital conversion method in which the amplitude of a sensor signal is encoded through its crossing instants with a periodic ramp. The proposed architecture departs from conventional ADC and PWM demodulation approaches by shifting quantization entirely to the time domain, enabling waveform reconstruction using only a ramp generator, an analog comparator, and a timer capture module. A theoretical framework is developed to formalize the voltage-to-time mapping, derive expressions for resolution and error, and identify the conditions ensuring monotonicity and single-crossing behavior. Simulation results demonstrate high-fidelity reconstruction for both periodic and non-periodic signals, including real photoplethysmographic (PPG) waveforms, with errors approaching the theoretical quantization limit. A hardware implementation on a PSoC 5LP microcontroller confirms the practicality of the method under realistic operating conditions. Despite ramp nonlinearity, comparator delay, and sensor noise, the system achieves effective resolutions above 12 bits using only native mixed-signal peripherals and no conventional ADC. These results show that accurate waveform reconstruction can be obtained from purely temporal information, positioning time-encoded sensing as a viable alternative to traditional amplitude-based conversion. The minimal analog front end, low power consumption, and scalability of timer-based processing highlight the potential of the proposed approach for embedded instrumentation, distributed sensor nodes, and biomedical monitoring applications. Full article

Urban heat and hardscapes increase cooling electricity demand, stressing power grids and disproportionately burdening deprived neighborhoods. While previous studies have documented the cooling benefits of urban tree canopy, most analyses remain at coarse spatial scales and do not isolate the canopy’s marginal effect from built surfaces, limiting their utility for equitable neighborhood-level planning. We introduce a novel neighborhood-scale (census block-group, CBG) model to estimate cooling-season energy demand across Baltimore City and Baltimore County, Maryland. We quantify demand drivers and actionable tree-canopy targets while controlling for built surfaces. Correlation analysis shows demand increases with developed fraction and imperviousness, and decreases with tree canopy and other vegetated or water cover. Using an explainable monotone gradient-boosted tree model (SHAP) with controls for imperviousness and development, we isolate the canopy’s marginal effect. Demand reductions begin once the canopy exceeds ~11% in Baltimore City and ~23% in Baltimore County, with diminishing returns beyond ~18% (City) and ~24% (County). This flattening is strongest in highly impervious CBGs, while low-impervious county areas show renewed reductions at very high canopy (>55–60%), consistent with forest-dominated microclimates. Spatial hotspots cluster in Baltimore City and southern Baltimore County, where low canopy and high hardscapes coincide with elevated demand; 61% of City CBGs fall below the 18% threshold. We translate these findings into priority intervention tiers combining demand, hardscapes, jurisdiction-specific canopy thresholds, and an equity overlay, identifying 21% of City and 1.2% of County CBGs as high-priority targets for greening and energy-relief interventions. Full article

Multipartite Gaussian Einstein–Podolsky–Rosen (EPR) steering is a key resource for quantum networks, but in practice it is strongly degraded by channel loss and excess noise. This motivates the need to distill multipartite Gaussian EPR steering across all relevant mode partitions. Here we propose and analyze a measurement-based noiseless linear amplification (NLA) protocol that distills Gaussian EPR steering in a four-mode square cluster state transmitted through lossy and noisy channels. Starting from a CV cluster shared by a transmitted node A and three local nodes (B, C, and D), we reconstruct the covariance matrix of the Gaussian cluster state and evaluate Gaussian steering monotones for all $(1+1)$, $(1+2)$, and $(1+3)$ bipartitions before and after applying measurement-based NLA. We show that appropriate conditioning on the noisy mode or on selected relay nodes systematically restores and enhances directional steering, extends both one-way and two-way steerable regions, and preserves the monogamy constraints characteristic of Gaussian graph states. Taken together, these results show that measurement-based NLA provides a practical route to distributing robust multipartite steering in CV cluster architectures, thereby strengthening the foundations for continuous-variable quantum information processing. Full article

This paper is a theoretical contribution that introduces a new reasoning framework for SAT solving based on resolvable networks (RNs). RNs provide a graph-based representation of propositional satisfiability in which clauses are interpreted as directed reaches between disjoint subsets of Boolean variables (nodes). Building on this framework, we introduce a novel RN-based SAT solver, called RN-Solver, which replaces local assignment-driven branching by global reasoning over token distributions. Token distributions, interpreted as truth assignments, are generated by monotone CNF–DNF dualization applied to white (all-positive) clauses. New white clauses are derived via resolution along private-pivot chains, and the solver’s progression is governed by a taxonomy of token distributions (black-blocked, terminal, active, resolved, and non-resolved). The main results establish the soundness and completeness of the RN-Solver. Experimentally, the solver performs very well on pigeonhole formulas, where the separation between white and black clauses enables effective global reasoning. In contrast, its current implementation performs poorly on random 3-SAT instances, highlighting both practical limitations and significant opportunities for optimization and theoretical refinement. The presented RN-Solver implementation is a proof-of-concept which validates the underlying theory rather than a state-of-the-art competitive solver. One promising direction is the generalization of strongly connected components from directed graphs to resolvable networks. Finally, the token-based perspective naturally suggests a connection to token-superposition Petri net models. Full article

Recovery of the stratospheric ozone layer following the ban on ozone-depleting substances represents one of the most successful examples of international environmental policy. However, the long-term fate of ozone under continuing climate change remains uncertain. We present the first multi-century projections of ozone evolution to 2200 using emission-driven CMIP7 scenarios in the SOCOL-MPIOM chemistry-climate model. Our results show that despite the elimination of halogenated compounds, total column ozone exhibits non-monotonic evolution, with an initial increase of 8–12% by 2080–2100, followed by a decline to 2200, remaining 4.5–7% above the 2020 baseline. Stratospheric ozone at 50 hPa shows a monotonic decline of 2–11% by 2200 across all scenarios, with no recovery despite ongoing Montreal Protocol implementation. Critically, even in the high-overshoot scenario where CO₂ concentrations decline from 830 to 350 ppm between 2100 and 2200, stratospheric ozone continues to decrease. Intensification of the Brewer-Dobson circulation in warmer climates reduces ozone residence time in the tropical stratosphere, decreasing photochemical production efficiency. This dynamic effect outweighs the reduction in ozone-depleting substances, leading to persistent stratospheric ozone depletion despite total column ozone enhancements in polar regions. Spatial analysis reveals pronounced regional differentiation: Antarctic regions show sustained total column enhancement of +18–26% by 2190–2200, while tropical regions decline to levels below baseline (−4 to −5%). Our results reveal fundamental asymmetry between climate forcing and ozone response, with characteristic adjustment timescales of 100–200 years, and have critical implications for long-term atmospheric protection policy. Full article

Numerical simulation of the electrical conductivity of carbon fiber-reinforced asphalt concrete is essential for understanding its electrical behavior, yet research in this area remains limited. This study prepared six groups of Marshall specimens with carbon fiber (CF) contents of 0.1 wt%, 0.2 wt%, 0.3 wt%, 0.4 wt%, 0.5 wt%, and 0.6 wt%. The resistivity and asphalt concrete (AC) impedance spectra were measured to analyze the effect of fiber content on electrical performance. Nyquist diagrams were fitted to establish an equivalent circuit model, and a representative volume element (RVE) finite element model was developed. The Generalized Effective Medium (GEM) equation was employed to fit the resistivity data. The results show that the resistivity exhibits a two-stage characteristic—an abrupt decrease followed by stabilization, with an optimal CF content range of 0.2–0.4 wt%. Among the equivalent circuit parameters, the contact resistance (R₁) and tunneling resistance (R₂) significantly decreased, the growth of interface capacitance (C₁) slowed, the constant phase element Z_Q increased, and the non-monotonic change of volume resistance (R₃) reflected the heterogeneity of the internal void distribution of the material. The finite element numerical solution for resistivity, derived from the GEM equation, aligns well with experimental values, validating the proposed simulation approach. Full article

A knowledge of the process–structure–property correlation and underlying deformation mechanisms of material under a coupled electro-thermal–mechanical field is crucial for developing novel electrically assisted forming techniques. In this work, numerical simulation and experimental analyses were carried out to study the non-uniform deformation behaviors and microstructure evolution of Ti₂AlNb-based alloy stiffened panels in different characteristic deformation regions during electrically assisted press bending (EAPB). The quantitative relationships between electro-thermal–mechanical routes, microstructural features, and mechanical properties of EAPBed stiffened panels were initially established, and the underlying mechanisms of electrically induced phase transformation and morphological transformation were unveiled. Results show that the temperature of the panel first increases then deceases with forming time in most regions, but it increases monotonically and reaches its peak value of 720.1 °C in the web region close to the central transverse rib. The higher accumulated strain and precipitation of the acicular O phase at mild temperature leads to strengthening of the longitudinal ribs at near blank holder regions, resulting in an ideal microstructure of 3~4% blocky α₂ phase + a dual-scale O structure in a B2 matrix with a maximal hardness of 389.4 ± 7.2 HV_0.3. While the dissolution of the α₂ phase and the spheroidization and coarsening of the O phase bring about softening (up to 9.29%) of the lateral ribs and web near the center region, the differentiated evolution of microstructure and the mechanical property in EAPB results in better deformation coordination and resistance to wrinkling and thickness variation in the rib–web structure. The present work will provide valuable references for achieving shape-performance coordinated manufacturing of Ti₂AlNb-based stiffened panels. Full article

Accurate prediction of the shear strength of rock discontinuities requires accounting for surface roughness, which is a factor neglected in the classical Mohr–Coulomb criterion. This study proposes a fractal-enhanced Mohr–Coulomb model that incorporates the surface fractal dimension Ds as a geometric state variable governing both the cohesion and internal friction angle. The fractal dimension is treated as an objective, scale-invariant descriptor, computable via established methods, such as box-counting and power spectral density analysis, which are known to yield consistent results when applied to joint topography. The model predicts a nonlinear increase in shear strength with Ds, producing a dynamically adjustable failure envelope that can exceed the classical Mohr–Coulomb estimates by 25–40% for rough joints, which is consistent with trends observed in experimental shear tests. By linking strength parameters directly to measurable surface geometry, the framework provides a physically interpretable bridge between micro-scale roughness and macro-scale mechanical response. Although the current formulation assumes monotonic, dry, and quasi-static conditions, the explicit dependence on Ds offers a foundation for future extensions that incorporate anisotropy, damage evolution, and hydro-mechanical coupling. Full article

Carbon fiber reinforced polymer (CFRP) is prone to delamination damage during drilling, which seriously affects the processing quality. This study focuses on the use of variable parameter drilling technology. Firstly, an anisotropic constitutive model and a Hashin failure model for CFRP were constructed. Then, based on ABAQUS and VUMAT user subroutines, the influence laws of cutting parameters (spindle speed and feed rate) on delamination damage were explored. For the two methods of conventional fixed parameter drilling and variable parameter drilling (dynamic adjustment of feed rate when the drill reaches the exit plane), comparative simulation experiments were conducted. Subsequently, the genetic algorithm was introduced to optimize the spindle speed and feed rate under the variable parameter mode, and the results were verified through hole-making experiments. The results show that: under a constant spindle speed, the delamination damage factor increases monotonically with the increase in feed rate; under a constant feed rate, the delamination damage factor decreases first and then increases with the increase in spindle speed, presenting a nonlinear change characteristic. Among them, the variable parameter strategy of “first high feed, then low feed” can significantly reduce the delamination damage; the obtained optimal parameters can effectively balance the drilling quality and processing efficiency. This research provides theoretical and experimental support for optimizing CFRP hole-making parameters, addressing delamination control challenges in traditional drilling, and facilitating CFRP applications in aerospace and intelligent manufacturing. Full article

Langasite (LGS)-based surface acoustic wave (SAW) sensors are promising for high-temperature pressure detection. However, their performance is limited by the low pressure sensitivity of conventional sealed-cavity packaging and temperature-induced measurement drift. To address these issues, this study introduces a novel LGS SAW pressure sensor featuring two key innovations: a Kovar alloy point-force packaging structure to amplify pressure-induced LGS substrate deformation, enhancing sensitivity compared to traditional designs, and SAW resonators fabricated on an LGS (0°, 138.5°, 26.7°) cut, selected based on electromechanical simulations for its superior intrinsic pressure sensitivity and monotonic frequency–temperature response, effectively mitigating temperature interference on pressure measurements. Experimental characterizations show the resonator achieves a high Q-value of ~3000 at ~357 MHz. Tested under conditions of 250 °C and 0–0.4 MPa, the sensor exhibits a pressure sensitivity of 0.1866 MHz/MPa with a relative error of only 4.8% versus the finite element method (FEM)-simulated 0.196 MHz/MPa, demonstrating the proposed design’s effectiveness for accurate, stable pressure monitoring in harsh high-temperature environments such as turbine engines and high-temperature manufacturing lines. Full article

Ammonia (NH₃) is a zero-carbon fuel and an attractive hydrogen (H₂) carrier for gas turbine power generation due to its high energy density, ease of storage, and transportation. This study numerically investigates NH₃/air combustion using a hybrid Well-Stirred Reactor (WSR) and Plug Flow Reactor (PFR) model in Cantera at pressures of 1–20 atm, temperatures of 1850–2150 K, and equivalence ratios (ϕ) of 0.7–1.2. The effects of pressure, equivalence ratio, and temperature on NH₃ conversion and NO formation are examined. Results show that NH₃ exhibits a non-monotonic conversion curve with pressure after the WSR, reaching a minimum near 5 atm, whereas NO formation decreases monotonically from 1 to 20 atm. Equivalence ratio sweeps show that NO decreases steeply as ϕ increases from 0.7 to ~1.1 as nitrogen is redirected toward N₂ and oxidizer availability declines; residual NH₃ increases rapidly for ϕ > 1.0, especially at high pressure. Increasing temperature accelerates NH₃ oxidation and raises NO formation, most strongly at low pressure where thermal and NH/OH pathways are least inhibited. These results indicate that co-tuning pressure and equivalence ratio near rich operation enables low-NO_x ammonia combustion suitable for advanced gas turbine applications. Full article