Search Results (550)

A retrospective ozone simulation was conducted with the Microscale Forward and Adjoint Chemical Transport (MicroFACT) model for an industrialized area of Detroit, Michigan, USA, using a 24 km × 24 km horizontal × 1.5 km vertical grid. The domain encompassed a regulatory monitoring station at East 7 Mile Rd at the northern edge of the grid. The episode day was 30 June 2022, when the station-measured 8 h ozone reached 76 ppb during predominantly southwesterly wind. The ozone impacts of mobile, point, nonpoint, and biogenic emissions were simulated at 400 m horizontal resolution. Simulation results were compared against station measurements of ozone, nitrogen oxides, and total reactive nitrogen. Local nitrogen oxide sources were found to titrate ozone, while ozone turbulently entrained to the surface from ~500 m aloft enhanced surface Ozone Production Efficiency and led to extended periods of high ozone concentrations very similar to observations. Volatile Organic Compound emission reductions produced only weak decreases in maximum 8 h ozone, suggesting that radicals were enhanced mostly by photolysis of subsiding ozone. Entrainment of ozone layers aloft may thus be critical in explaining historical ozone exceedances of the United States National Ambient Air Quality Standard at the East 7 Mile Rd station. Full article

Urban populations are exposed to elevated local temperatures compared to surrounding rural areas due to the urban heat island (UHI) effect, which increases health risks and energy demand. The literature highlights that accurately quantifying UHIs at broader territorial scales remains challenging because of limited microscale climate data availability and, at the same time, the difficulty of increasing the spatial coverage of the outcomes. Within the PRIN2022-PNRR CRiStAll (Climate Resilient Strategies by Archetype-based Urban Energy Modeling) project, this work addresses these limitations by coupling Urban Building Energy Modeling with archetype-based representation of urban form and high-resolution climatic data. Urban archetypes are defined as representative microscale configurations derived from combinations of urban canyon geometries and building typologies, accounting for different climatic zones, use categories, and construction periods. The proposed methodology was applied to the city of Turin (Italy), where representative urban blocks were identified and modeled to evaluate key urban context metrics under short-, medium-, and long-term climate scenarios. The UHI effect was assessed using Urban Weather Generator, while energy simulations were performed with CitySim. The urban archetype approach enables both fine spatial resolution and extensive spatial coverage, supporting urban-scale mapping. Full article

Silicon nitride (Si₃N₄) ceramic bearings inevitably contain crack-like defects, yet their compressive capacity degradation and crack-driven failure mechanisms remain unclear. This study proposes a discrete element method (DEM) numerical framework within PFC2D to simulate a bearing containing a single prefabricated crack. First, a bearing DEM model was established and calibrated to reproduce the compressive mechanical response. Then, particle deletion introduced controllable central cracks in the ball and raceway with prescribed inclination angles. Finally, displacement-controlled compression-splitting simulations, serving as a surrogate for a quasi-static overload scenario relevant to quality screening, tracked crack initiation, propagation, and failure modes; under a fixed raceway-crack inclination, crack length was varied to quantify size effects. Results show that a single crack markedly reduces compressive strength. Failure progresses through elastic deformation, crack propagation, and final fracture, with cracks initiating at stress concentrators near crack tips. Crack inclination significantly regulates capacity: raceway cracks are most detrimental near 45°, while ball cracks exhibit an overall decrease in initiation and peak stresses with increasing inclination (with local non-monotonicity). Crack length has a stronger weakening effect than inclination, with accelerated capacity loss beyond 0.3 mm and a pronounced drop in initiation stress beyond 0.6 mm. The framework enables controllable defect parametrization and micro-scale failure interpretation for defect sensitivity assessment under compressive overload. Thus, this study focuses on simulating monotonic fracture events to elucidate fundamental defect–property relationships, which provides a foundation distinct from the prediction of rolling contact fatigue life under cyclic service conditions. Full article

This study addresses a key limitation in meso-scale discrete element modeling (DEM) of ultra-high performance concrete (UHPC). Most existing DEM frameworks rely on extensive macroscopic calibration and do not provide a clear, transferable pathway to derive contact law parameters from measurable micro-scale properties, limiting reproducibility and physical interpretability. To bridge this gap, we develop and validate a micro-indentation-informed, poromechanics-consistent calibration framework that links UHPC phase-level micromechanical measurements to a flat-joint DEM contact model for predicting uniaxial compression, direct tension, and flexural response. Elastic moduli and Poisson’s ratios of the constituent phases are obtained from micro-indentation and homogenization relations, while cohesion (c) and friction angle (α) are inferred through a statistical treatment of the indentation modulus and hardness distributions. The tensile strength limit (σₜ) is identified by matching the simulated flexural stress–strain peak and post-peak trends using a parametric set of (c, α, σₜ) combinations. The resulting DEM model reproduces the measured UHPC responses with strong agreement, capturing (i) compressive stress–strain response, (ii) flexural stress–strain response, and (iii) tensile stress–strain response, while also recovering the experimentally observed failure modes and damage localization patterns. These results demonstrate that physically grounded micro-scale measurements can be systematically upscaled to meso-scale DEM parameters, providing a more efficient and interpretable route for simulating UHPC and other porous cementitious composites from indentation-based inputs. Full article

In the context of fifth-generation (5G) communications and the dawn of sixth-generation (6G) networks, a surged societal demand on bandwidth and data rate and more stringent commercial requirements on transmission efficiency, cost, and reliability are increasingly evident and, hence, driving the maturity of reconfigurable millimeter-wave (mmW) and terahertz (THz) devices and systems, in particular, liquid crystal (LC)-based tunable solutions for delay line phase shifters (DLPSs). However, the field of LC-combined electronics has witnessed only incremental developments in the past decade. First, the tuning principle has largely been unchanged (leveraging the shape anisotropy of LC molecules in microscale and continuum mechanics in macroscale for variable polarizability). Second, LC-enabled devices’ performance has yet to be standardized (suboptimal case by case at different frequency domains). In this context, this work points out three underestimated knowledge gaps as drawn from our theoretical designs, computational simulations, and experimental prototypes, respectively. The first gap reports previously overlooked physical constraints from the analytical model of an LC-embedded coaxial DLPS. A new geometry-dielectric bound is identified. The second gap deals with the lack of consideration in the suboptimal dispersion behavior in differential delay time (DDT) and differential delay length (DDL) for LC phase-shifting devices. A new figure of merit (FoM) is proposed and defined at the V-band (60 GHz) to comprehensively evaluate the ratios of the DDT and DDL over their standard deviations across the 54 to 66 GHz spectrum. The third identified gap deals with the in-depth explanation of our recent experimental results and outlook for partial leakage attack analysis of LC phase shifters in modern eavesdropping. Full article

Powder bed fusion (PBF) is a widely adopted additive manufacturing (AM) process category that enables high-resolution fabrication across metals, polymers, ceramics, and composites. However, its inherent process complexity demands robust modeling to ensure quality, reliability, and scalability. This review provides a critical synthesis of advances in physics-based simulations, machine learning, and digital twin frameworks for PBF. We analyze progress across scales—from micro-scale melt pool dynamics and mesoscale track stability to part-scale residual stress predictions—while highlighting the growing role of hybrid physics–data-driven approaches in capturing process–structure–property (PSP) relationships. Special emphasis is given to the integration of real-time sensing, multi-scale modeling, and AI-enhanced optimization, which together form the foundation of emerging PBF digital twins. Key challenges—including computational cost, data scarcity, and model interoperability—are critically examined, alongside opportunities for scalable, interpretable, and industry-ready digital twin platforms. By outlining both the current state-of-the-art and future research priorities, this review positions digital twins as a transformative paradigm for advancing PBF toward reliable, high-quality, and industrially scalable manufacturing. Full article

Numerical simulations of the forming limit diagram (FLD) for SUS430/Al1050/TA1 laminated metal composites (LMCs) are conducted through the crystal plasticity finite element (CPFE) model integrated with the Marciniak–Kuczyński (M–K) theory. Representative volume elements (RVEs) that reconstruct the measured crystallographic texture, as characterized by electron backscatter diffraction (EBSD), are developed. The optimal grain number and mesh density for the RVE are calibrated through convergence analysis by curve-fitting simulated stress–strain responses to the uniaxial tensile data. The established multi-scale model successfully predicts the FLDs of the SUS430/Al1050/TA1 laminated sheet under two stacking sequences, namely, the SUS layer or the TA1 layer in contact with the die. The Nakazima test results validate the effectiveness of the proposed model as an efficient and accurate predictive tool. This study extends the CPFE–MK framework to multi-layer LMCs, overcoming the limitations of conventional single-layer models, which incorporate FCC, BCC, and HCP crystalline structures. Furthermore, the deformation-induced texture evolution under different loading paths is analyzed, establishing the relationship between micro-scale deformation mechanisms and the macro-scale forming behavior. Full article

A portable and integrated monitoring device was developed to digitally assess both water levels and surrounding fire-related conditions in forest firefighting water buckets using multi-sensor fusion. The system integrates a hydrostatic liquid-level sensor with temperature–humidity and smoke sensors. Validation was performed through field-oriented experiments conducted under semi-controlled conditions. Water-level measurements were collected over a three-month period under simulated forest conditions and benchmarked against conventional steel-ruler readings. Early-stage fire monitoring experiments were carried out using dry wood and leaf litter under varying wind speeds, wind directions, and representative extreme weather conditions. The device achieved a mean water-level bias of −0.60%, a root-mean-square error of 0.64%, and an overall accuracy of 99.36%. Fire monitoring reached a maximum detection distance of 7.30 m under calm conditions and extended to 16.50 m under strong downwind conditions, with performance decreasing toward crosswind directions. Stable operation was observed during periods of strong winds associated with typhoon events, as well as prolonged high-temperature exposure. The primary novelty of this work lies in the conceptualization of a Collaborative Forest Resource–Hazard Monitoring Architecture. Unlike traditional isolated sensors, our proposed framework utilizes a dual-domain decision-making model that simultaneously assesses water-bucket storage stability and micro-scale fire threats. By implementing a robust ‘sensing–logic–alert’ framework tailored for rugged environments, this study offers a new methodological reference for the intelligent management of forest firefighting resources. Full article

Due to its high energy density, liquid Hydrogen is an essential fuel for both terrestrial energy systems and space propulsion. However, uncontrolled evaporation poses a challenge for cryogenic storage and transport technologies. Accurate modeling of evaporation remains difficult due to the multiscale menisci formed by the wetting liquid phase. Thin liquid films form near the walls of containers, ranging from millimeters to nanometers in thickness. Heat conduction through the solid walls enables high evaporation rates in this region. Discrepancies in the reported values of the accommodation coefficients (necessary inputs to models) further complicate evaporation calculations. In this study, we present a novel multiscale model for CFD simulations of evaporating Hydrogen menisci. Film profiles below 10 $\mu$m are computed by a subgrid model using a lubrication-type thin film equation. The microscale model is combined with a macroscale model above 10 $\mu$m. Evaporation rates are computed using a kinetic phase change model combined with in situ calculations of the accommodation coefficient using transition state theory. The submodels are implemented in Ansys Fluent^TM using User-Defined Functions (UDFs), and a method to establish two-way coupling is detailed. The modeling results are in good agreement with cryo-neutron experiments and show improvement over prior models. The model, including UDFs, is made available through a public repository. Full article

High rock slopes are extensively distributed in areas of major engineering constructions, such as transportation infrastructure, hydraulic projects, and mining operations. The stability and failure evolution mechanism during their multi-stage excavation process have consistently been a crucial research topic in geotechnical engineering. In this paper, a series of two-dimensional rock slope models, incorporating various combinations of slope height and slope angle, were established utilizing the Discrete Element Method (DEM) software PFC2D. This systematic investigation delves into the meso-mechanical response of the slopes during multi-stage excavation. The Parallel Bond Model (PBM) was employed to simulate the contact and fracture behavior between particles. Parameter calibration was performed to ensure that the simulation results align with the actual mechanical properties of the rock mass. The research primarily focuses on analyzing the evolution of displacement, the failure modes, and the changing characteristics of the force chain structure under different geometric conditions. The results indicate that as both the slope height and slope angle increase, the inter-particle deformation of the slope intensifies significantly, and the shear band progressively extends deeper into the slope mass. The failure mode transitions from shallow localized sliding to deep-seated overall failure. Prior to instability, the force chain system exhibits an evolutionary pattern characterized by “bundling–reconfiguration–fracturing,” serving as a critical indicator for characterizing the micro-scale failure mechanism of the slope body. Full article

Traditional settlements exhibit remarkable climatic adaptability, representing a form of “Morphological Intelligence” developed over centuries. However, this inherent, physics-based wisdom remains underutilized in contemporary urban planning and design. This systematic review aims to decode such intelligence by analyzing the relationship between the morphological characteristics of traditional settlements and their thermal performance. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, literature retrieval and evaluation were conducted via the databases of Web of Science, Scopus, and China National Knowledge Infrastructure (CNKI) for articles published during 2004~2024. A total of 82 related articles with available full texts were selected from 1227 records for in-depth analysis, including peer-reviewed journal articles and reputable conference publications. This study first presents an overview of bibliometric and methodological landscapes, revealing that research is increasingly concentrated in Asia’s tropical and subtropical climates, predominantly employing case studies and computational simulations. Secondly, we synthesize a few key climate-adaptive morphological features across macro- (e.g., settlement layout), meso- (e.g., street canyon geometry), and microscales (e.g., courtyards). The findings illustrate a reliance on methods and metrics developed for modern urban contexts, which could not fully capture the specific morphological characteristics of traditional settlements. Most importantly, this study summarizes four core principles of “Morphological Intelligence” in traditional settlements, i.e., strategic solar control, facilitated natural ventilation, use of thermal mass, and integration of natural elements and creation of thermal buffer zones. By identifying the limitations of existing investigations, this study highlights a few directions for future studies, including conducting more systematic multi-scalar integrated analysis, focusing on the development of dedicated quantitative metrics and analytical frameworks, delving into more mechanism-oriented investigation, assessing morphological resilience under urbanization, and translating principles into contemporary design guidelines. This study provides a foundational framework for translating the “Morphological Intelligence” of traditional settlements into actionable, evidence-based strategies for resilient and energy-efficient urban planning and design amidst climate change. Full article

Microfluidics has emerged as a powerful enabling technology in plant science, offering unprecedented control over microscale environments for the cultivation, manipulation, and analysis of plant cells, tissues, and organs. This review provides a comprehensive overview of the development and application of microfluidic systems in plant physiology and development studies. We categorize the platforms based on their structural designs and biological targets—from single-cell trapping devices and droplet-based screening systems to organ-on-a-chip and root–microbe interaction modules. Key applications include live-cell imaging, real-time monitoring of stress responses, microenvironment simulation, and high-throughput phenotyping. Particular attention is given to microfluidic investigations of plant mechanobiology, chemotropism, and cell-to-cell communication, as well as their integration with biosensors, electrophysiological tools, and environmental control systems. We also examine current limitations related to material compatibility, device scalability, and biological complexity, and highlight emerging solutions such as modular design, interdisciplinary integration, and soil-on-a-chip systems. By addressing both fundamental research needs and practical agricultural challenges, microfluidic technologies offer a transformative path toward precision plant science and sustainable crop innovation. Full article

As a critical parameter for describing oil–water two-phase flow behavior, relative permeability curves are widely applied in field development, dynamic forecasting, and reservoir numerical simulation. This study addresses the issue of relative permeability anisotropy, focusing on the seepage characteristics of two typical bedding structures in sandstone reservoirs—tabular cross-bedding and parallel bedding—through multi-directional displacement experiments. A novel anisotropic relative permeability testing apparatus was employed to conduct displacement experiments on cubic core samples, comparing the performance of the explicit Johnson–Bossler–Naumann (JBN) method, based on Buckley–Leverett theory, with the implicit Automatic History Matching (AHM) method, which demonstrated superior accuracy. The results indicate that displacement direction significantly influences seepage efficiency. For cross-bedded cores, displacement perpendicular to bedding (Z-direction) achieved the highest displacement efficiency (75.09%) and the lowest residual oil saturation (22%), primarily due to uniform fluid distribution and efficient pore utilization. In contrast, horizontal displacement exhibited lower efficiency and higher residual oil saturation due to preferential flow path effects. In parallel-bedded cores, vertical displacement improved efficiency by 18.06%, approaching ideal piston-like displacement. Microscale analysis using Nuclear Magnetic Resonance (NMR) and Computed Tomography (CT) scanning further revealed that vertical displacement effectively reduces capillary resistance and promotes uniform fluid distribution, thereby minimizing residual oil formation. This study underscores the strong interplay between displacement direction and bedding structure, validating AHM’s advantages in characterizing anisotropic reservoirs. By integrating experimental innovation with advanced computational techniques, this work provides critical theoretical insights and practical guidance for optimizing reservoir development strategies and enhancing the accuracy of numerical simulations in complex sandstone reservoirs. Full article

Local Climate Zones (LCZs) have become a foundational framework for urban climate modeling, yet their use across model families has not been systematically evaluated. Crucially, the LCZ framework itself has served as a developmental basis, revealing the progression of urban canopy parameterizations (UCP) from early models to the diverse model families currently in use. This evolution is exemplified by systems like the Weather Research and Forecasting (WRF) model, where the application of LCZ has fundamentally shifted from an experimental add-on to a basic, built-in feature of its urban-modeling capabilities. This review synthesizes a decade of LCZ-based studies to clarify how LCZ improves surface representation, enhances comparability, and supports multiscale modeling workflows. It provides a comprehensive overview of peer-reviewed work up to the end of 2024, offering a baseline for understanding the field’s rapid recent growth. Using a structured evidence-mapping approach, we categorize applications into three maturity stages: testing and measurement, operational and planning-oriented applications, and expansions beyond urban climate to chemistry, hydrology, and Earth-system modeling. The assessment covers various iterations of mesoscale systems (WRF, SURFEX/TEB, COSMO), local-scale climatologies (MUKLIMO-3, UrbClim), microscale models (ENVI-met, CFD), and supporting tools including SUEWS, SOLWEIG, RayMan, VCWG, and CESM-CLMU. Results show clear divisions of labor: WRF and SURFEX/TEB anchor process-rich regional simulations; MUKLIMO-3 and UrbClim offer computationally efficient long-horizon or multi-city assessments; ENVI-met and CFD provide design-scale insight when parameterized with LCZ archetypes. Across all families, model skill is strongly constrained by LCZ data quality and by inconsistencies in LCZ to UCP translation. We conclude that advancing LCZ-based urban climate modeling will depend on improved LCZ products, standardized parameter libraries, and formalized cross-scale model couplings that allow existing tools to interoperate more reliably under growing urban-climate pressures. Full article

Macrocyclic drugs are promising for targeting undruggable proteins, including those in cancer. Our prior work identified BE-43547A₂ (BE) as a selective inhibitor of pancreatic cancer stem cells in PANC-1 cultures, but its high lipophilicity limits clinical application. To address this, we designed derivatives retaining BE’s backbone while modifying tail groups to improve its properties. A concise total synthesis enabled a versatile late-stage intermediate (compound 17), serving as a platform for efficient diversification of BE analogs via modular click chemistry. This approach introduced a central triazole ring connected by flexible alkyl spacers. Key properties, including lipophilicity, solubility, and Caco-2 permeability, were experimentally determined. These derivatives exhibited reduced lipophilicity and improved solubility but unexpectedly lost cellular activity. Direct target engagement studies using MicroScale Thermophoresis (MST) revealed compound-dependent deactivation mechanisms: certain derivatives retained binding to eEF1A1 with only modestly reduced affinity (e.g., compound 29), while others showed no detectable binding (e.g., compound 31). Microsecond-scale molecular dynamics simulations and free-energy calculations showed that, for derivatives retaining target affinity, tail modifications disrupted the delicate balance of drug–membrane and drug–solvent interactions, resulting in substantially higher transmembrane free-energy penalties (>5 kcal/mol) compared to active compounds (<2 kcal/mol). These insights emphasize the need to simultaneously preserve both target engagement and optimal permeability when modifying side chains in cell-permeable macrocyclic peptides, positioning compound 17 as a robust scaffold for future lead optimization. This work furnishes a blueprint for balancing drug-like properties with therapeutic potency in macrocyclic therapeutics. Full article