Search Results (393)

Urban growth models often prioritize environmental and accessibility factors while underestimating behavioral and functional dynamics. This study develops a POI-enhanced Cellular Automata (CA) framework to simulate urban expansion by incorporating three semantic indicators derived from Point-of-Interest (POI) data—density (PD), diversity (PDI), and functional centrality (FC). Taking Yan’an, China, as a case, the model integrates these indicators with terrain and infrastructure variables via logistic regression to estimate land-use transition probabilities. To ensure robustness, spatial block cross-validation was adopted to reduce spatial autocorrelation bias. Results show that the POI-based model outperforms the baseline in both Kappa and Figure of Merit metrics. High-density and mixed-function POI zones correspond with compact infill growth, while high-centrality zones predict decentralized expansion beyond administrative cores. These findings highlight how functional semantics sharpen spatial prediction and uncover latent behavioral demand. Policy implications include using POI-informed maps for adaptive zoning, ecological buffer protection, and growth hotspot management. The study contributes a transferable workflow for embedding behavioral logic into spatial simulation. However, limitations remain: the model relies on static POI data, omits vertical (3D) development, and lacks direct comparison with alternative models like Random Forest or SVM. Future research could explore dynamic POI trajectories, integrate 3D building forms, or adopt agent-based modeling for richer institutional representation. Overall, the approach enhances both the accuracy and interpretability of urban growth modeling, providing a flexible tool for planning in functionally evolving and ecologically constrained cities. Full article

Reservoir architecture significantly influences fluid flow in ultra-low permeability reservoirs, yet this critical factor is frequently neglected in development strategies. This study investigates the Huang 57 block within the Jiyuan Oilfield of China’s Ordos Basin, where we conducted detailed analysis of well logging data, production history, and sedimentological characteristics. Our research established five diagnostic criteria for identifying architectural boundaries of subaqueous distributary channels, enabling classification of two fundamental architectural patterns—isolated and amalgamated—with four distinctive stacking styles. Analysis reveals that architectural heterogeneity exerts primary control over residual oil distribution, with concentrated accumulation occurring at poorly connected channel margins, interlayer barriers, and unswept zones. We verified these findings through horizontal well data and production performance analysis. The study presents a comprehensive framework for architectural characterization in low-permeability reservoirs and proposes specific development strategies, including strategic well conversion and optimized infill drilling, to enhance injection–production connectivity and improve recovery efficiency. These practical solutions offer valuable guidance for developing similar reservoirs worldwide. Full article

Offshore reservoirs in the high water-cut stage present significant development challenges, including declining production, complex remaining oil distribution, and the inadequacy of conventional evaluation methods to capture intricate flow dynamics. To overcome these limitations, this study introduces a novel approach based on flow diagnostics for performance evaluation and potential adjustment. The method integrates key metrics such as time-of-flight (TOF) and the dynamic Lorenz coefficient, supported by reservoir engineering principles and numerical simulation, to construct a multi-parameter evaluation system. This system, which also incorporates injection–production communication volume and inter-well fluid allocation factors, precisely quantifies and visualizes waterflood displacement processes and sweep efficiency. Applied to the QHD32 oilfield, this framework was used to establish specific thresholds for operational adjustments. These include criteria for infill drilling (waterflooded ratio < 45%, remaining oil thickness > 6 m, TOF > 200 days), conformance control (TOF < 50 days, dynamic Lorenz coefficient > 0.5), and artificial lift optimization (remaining oil thickness ratio > 2/3, TOF > 200 days). Field validation confirmed the efficacy of this approach: an additional cumulative oil production of 165,600 m³ was achieved from infill drilling in the C29 well group, while displacement adjustments in the B03 well group increased oil production by 2.2–3.8 tons/day, demonstrating a significant enhancement in waterflooding performance. This research provides a theoretical foundation and a technical pathway for the refined development of offshore heavy oil reservoirs at the ultra-high water-cut stage, offering a robust framework for the sustainable management of analogous reservoirs worldwide. Full article

Additive manufacturing has promising potential for the development of 3D-printed protective structures such as stab-resistant body armor. However, no research to date has examined the impact of 3D printing parameters on the protective performance of such 3D-printed structures manufactured using fused filament fabrication technology. This study, therefore, investigates the effects of five key printing parameters: layer thickness, print speed, print temperature, infill density (Id), and layer width, on the mechanical and protective performance of 3D-printed polycarbonate (PC) armor. A Taguchi L₂₇ matrix was employed to systematically analyze these parameters, with toughness, stab penetration depth, and armor panel weight as the primary responses. ANOVA results, along with the Taguchi approach, demonstrated that Id was the most influential factor across all print parameters. This is because a higher Id led to denser structures, reduced voids and porosities, and enhanced energy absorption, significantly increasing toughness while reducing penetration depth. Morphological analysis supported the statistical findings regarding the role of Id on the performance of such structures. With optimized printing parameters, no penetration to the armor panels was recorded, outperforming the UK body armor standard of a maximum permitted knife penetration depth of 8 mm. Moreover, an artificial neural network (ANN) utilizing the 5-14-12-3 topology was created to predict the toughness, stab penetration depth, and armor panel weight of 3D-printed armors. The ANN model demonstrated better prediction performance for stab penetration depth compared to the Taguchi method, confirming the successful application of such an approach. These findings provide a critical foundation for the development of high-performance 3D-printed protective structures. Full article

This study predicts sedimentary architectures and facies distribution within the Pliocene prograding prism of the Roussillon Basin (Gulf of Lion, France), developed along an onshore–offshore continuum. Boreholes and outcrops provide facies-scale observations onshore, while seismic data capture basin-scale structures offshore. Forward seismic modeling bridges spatial and scale gaps between these datasets, yielding characteristic synthetic seismic signatures for the sedimentary facies associations observed onshore, used as analogs for offshore deposits. These signatures are then identified in offshore seismic data, allowing seismic profiles to be populated with sedimentary facies without a well tie. Predicted offshore architectures are consistent with shoreline trajectories and facies successions observed onshore. The Roussillon prism records passive margin reconstruction in the Mediterranean Basin following the Messinian Salinity Crisis, through the following three successive depositional profiles marking the onset of infilling: (1) Gilbert deltas, (2) wave- and storm-reworked fan deltas, and (3) a wave-dominated delta. Offshore, transitions in clinoform type modify sedimentary architectures, influenced by inherited Messinian paleotopography. This autogenic control generates spatial variability in accommodation, driving changes in depositional style. Overall, this multi-scale and integrative approach provides a robust framework for predicting offshore sedimentary architectures and can be applied to other deltaic settings with limited land–sea data continuity. Full article

The change in impervious surface area (ISA) is an important factor reflecting urban expansion. This study used the global ISA dataset to analyze the spatiotemporal changes in ISA from 2001 to 2020 worldwide, explored the hotspots and patterns of ISA expansion, and analyzed the natural and socio-economic factors affecting ISA changes at three different levels, namely the continent, country, and city levels, by using the RF-SHAP method. The results are as follows: (1) The ISA has grown by 0.94 million km². (2) ISA in regions such as Asia and Africa has expanded faster than the global average. Developed countries had lower expansion rates. The hotspots of the ISA change rate were relatively concentrated in eastern Asia. Hotspot areas were mainly distributed in Asia and eastern South America in the early stage of the study period and appeared in eastern Europe in the later stage. (3) Edge expansion is the main pattern. Upper-middle-income countries have the largest area of ISA expansion, followed by high-income countries. Cities in developed countries have more infilling expansion; cities in developing countries have more edge expansion. (4) At the continent and country level, social factors, especially GDP, have the greatest impact on ISA change. At the city level, natural factors play a more influential role. Full article

Some communities in Valle del Cauca department (Colombia) live in houses made of bahareque walls. It is important to study the seismic performance of these structures as they are in an earthquake-prone region. This study develops a finite element modeling strategy to assess the cyclic behavior of bahareque walls in Colombia. Two types of walls are analyzed, including wood and guadua for the bare frame. The Puck failure criterion is used. The model is calibrated from results of pseudo-static tests on three walls without infill and two with infill. Results show that the model correctly predicts the first load cycles, but it presents convergence difficulties for higher cycles. It is necessary to further simulate some phenomena, such as the separation of nails in the joints. Full article

Open Ground-Storey (OGS) buildings, widely adopted for functional openness, are highly vulnerable to seismic collapse due to stiffness irregularity at the ground storey (GS). The magnification factor (MF), defined as the amplification applied to GS column design forces, acts as a practical strengthening measure to enhance GS stiffness and thereby mitigate the soft storey failure mechanism. While earlier studies recommended fixed MF values, their lack of adaptability often left stiffness deficiencies unresolved. This study develops a rational framework to quantify and predict the required MF for OGS columns, enabling safe yet functionally efficient design. A comprehensive set of three-dimensional reinforced concrete OGS models was analyzed under seismic loads, covering variations in plan geometry, ground-to-upper-storey height ratio (Hr), and GS infill percentage. Iterative stiffness-based evaluations established the MF demand needed to overcome stiffness deficiencies. To streamline prediction, advanced machine learning (ML) models were applied. Among these, black-box models achieved high predictive accuracy, but Symbolic Regression (SR) offered an interpretable closed-form equation that balances accuracy with transparency, making it suitable for design practice. A sensitivity analysis confirmed the Hr as the most influential parameter, with additional contributions from other variables. Validation on additional OGS configurations confirmed the reliability of the SR model, while seismic response comparisons showed that Modified OGS (MOGS) frames with the proposed MF achieved improved stiffness, reduced lateral displacements, uniform drift distribution, and shorter fundamental periods. The study highlights the novelty of integrating interpretable ML into structural design, providing a codifiable and practical tool for resilient OGS construction. Full article

The deep shale gas reservoirs of the southern Sichuan Basin exhibit high temperatures, high pressure, large stress differentials, and complex natural fracture systems. Since 2019, hydraulic fracturing technology in this region has evolved through four stages: exploratory fracturing, intensive limited-volume fracturing, tight spacing with controlled fluid and proppants, and balanced fracturing that combines long-section temporary plugging with short-section intensive cutting. Despite these advances, production remains suboptimal due to inefficient reserve utilization, a lack of quantitative methods for residual gas evaluation, and unclear identification of the remaining reserves. To address these challenges, we developed an integrated workflow combining dynamic production analysis, geomechanical modeling, and numerical simulation to evaluate representative fracturing techniques. Fracture propagation in the well group was modeled in the in-house hydraulic fracture simulator, ZFRAC, to assess fracture geometry, while production history and geological data were used to build calibrated reservoir simulation models. This enabled quantitative assessment of effective fracture parameters, reserve utilization, and residual gas distribution. The results show significant intra-stage heterogeneity driven by stress interference, effective fracture half-lengths of 60–105 m, and a cut-off ratio (proportion of effective fracture half-length to wetted fracture half-length) of 60–93%. Reserve utilization peaked at 60% for intensive limited-volume fracturing, while the efficacy of long-section temporary plugging was limited. These findings offer critical insights for optimizing infill strategies and enhancing sustainable shale gas development in southern Sichuan. Full article

Urban agglomerations underpin regional economic growth and sustainability transitions, yet the spatial heterogeneity and drivers of land use intensity (LUI) remain insufficiently resolved in inland settings. This study develops a high-resolution framework—combining a 1 km hexagonal grid with XGBoost-SHAP—to (i) map subsystem-specific LUI evolution, (ii) identify dominant drivers and nonlinear thresholds, and (iii) inform differentiated, sustainable land governance in the Guanzhong Plain Urban Agglomeration (GPUA) over 2000–2020. Composite LUI indices were constructed for human settlement (HS), cropland (CS), and forest (FS) subsystems; eleven natural, socioeconomic, urban–rural, and locational variables served as candidate drivers. The results show marked redistributions across subsystems. In HS, the share of low-intensity cells declined (86.54% to 83.18%) as that of medium- (12.10% to 14.26%) and high-intensity ones (1.22% to 2.56%) increased, forming a continuous high-intensity corridor between Xi’an and Xianyang by 2020. CS shifted toward medium-intensity (32.53% to 50.57%) with the contraction of high-intensity cells (26.62% to 14.53%), evidencing strong dynamism (55.1% net intensification; 38.5% net decline). FS transitioned to low-intensity dominance by 2020 (59.12%), with stability and delayed growth concentrated in conserved mountainous zones. Urban–rural gradients were distinct: HS rose by >20% (relative to 2000) in cores but remained low and stable in rural areas (mean < 0.20); CS peaked and stayed stable at fringes (mean ≈ 0.60); FS shifted from an inverse gradient (2000–2010) to core-area recovery by 2020. Explainable machine learning revealed inverted U-shaped relationships for HS (per capita GDP) and CS (population density) and a unimodal peak for FS with respect to distance to urban centers; model performance was strong (HS R² up to 0.82) with robust validation. Policy recommendations are subsystem-specific: enforce growth boundaries and prioritize infill/polycentric networks (HS); pair farmland redlines with precision agriculture (CS); and maintain ecological redlines with differentiated conservation and afforestation (FS). The framework offers transferable, data-driven evidence for calibrating thresholds and sequencing interventions to reconcile land use intensification with ecological integrity in rapidly urbanizing contexts. Full article

Gulf cities have embarked on ambitious public transport infrastructure initiatives in recent decades to foster more livable and sustainable cities. This investigation explores the interpretations and implementation of Transit-Oriented Development (TOD) principles in two prototypical urban districts: Doha’s West Bay, Qatar, and Riyadh’s King Abdullah Financial District (KAFD), Saudi Arabia. By following a comparative case study approach, the study explores how retrofitted (West Bay) and purpose-built (KAFD) TOD configurations fare regarding land use mix, density, connectivity, transit access, and environmental responsiveness. The comparative methodology was selected to specifically capture the spatial, climatic, and socio-economic complexities of TOD implementation in hyper-arid urban environments. Based on qualitative evidence from stakeholder interviews, spatial assessments, and geospatial indicators—such as metro access buffers, building shape compactness, and TOD proximity classification—the investigation reflects both common challenges and localized adaptations in hot-desert Urbanism. It emerges that, while benefiting from integrated planning and multimodal connectivity, KAFD’s pedestrian realm is delimited by climatic constraints and inactive active transport networks. West Bay, on the other hand, features fragmented public spaces and low TOD cohesion because of automotive planning heritages. However, it holds potential for retrofit through infill development and tactical Urbanism. The results provide transferable insights that can inform TOD strategies in other Gulf and international contexts facing similar sustainability and mobility challenges. By finalizing strategic recommendations for urban livability improvement through context-adaptive TOD approaches in Gulf cities, the study contributes to the wider discussion of sustainable Urbanism in rapidly changing environments and supplies a reproducible assessment frame for future TOD planning. This study contributes new knowledge by advancing a context-adaptive TOD framework tailored to the unique conditions of hyper-arid Gulf cities. Full article

The traditional construction industry significantly contributes to global resource consumption and climate change. Conventional methods limit the development of complex and multifunctional architectural forms. In contrast, 3D concrete printing (3DCP), an additive manufacturing technique, enables the creation of intricate building envelopes that integrate architectural and energy-efficient functions. Bioinspired design, recognized for its sustainability, has gained traction in this context. This study investigates the thermal and energy performance of various bioinspired and regular 3DCP infill patterns compared to conventional concrete building envelopes in tropical climates. A three-stage methodology was employed. First, bioinspired patterns were identified and evaluated through a literature review. Next, prototype models were developed using Rhino and simulated in ANSYS to assess thermal performance. Finally, energy performance was analyzed using Ladybug and Honeybee tools. The results revealed that honeycomb, spiral, spiderweb, and weaving patterns achieved 35–40% higher thermal and energy efficiency than solid concrete, and about 10% more than the 3DCP sawtooth pattern. The findings highlight the potential of bioinspired spiral infill patterns to enhance the sustainability of 3DCP building envelopes. This opens new avenues for integrating biomimicry into 3DCP construction as a tool for performance optimization and environmental impact reduction. Full article

In the pursuit of low-impact and renewable construction materials, various by-products from agriculture, forestry, and the wood processing industry are being explored as potential bio-based infill materials for wall assemblies. This study presents an experimental assessment of the fire performance of timber wall systems composed of block units filled with different lignocellulosic materials, subjected to radiative heat exposure. These assemblies are representative of external walls in contemporary timber-framed buildings. Two configurations were examined: one with sawdust infill and the other with wood pellet infill. Both samples were exposed to radiant heat from the interior side for 60 min, simulating conditions of a fully developed compartment fire. The applied heat flux was 20 kW·m⁻², delivered by a calibrated radiant panel. The results indicate that even minor design variations—particularly the choice of infill material—can significantly influence the thermal response, degradation kinetics of wood-based components, and the overall fire resistance of the wall assembly. The sawdust-filled system exhibited superior performance, achieving an estimated fire resistance rating of 60 min (60 REI). It showed reduced internal thermal degradation compared to the pellet-filled variant, which experienced greater charring depth due to internal voids between pellets, although it maintained structural integrity. Full article

Lightweight PLA (LW-PLA) filaments enable material-saving designs in fused filament fabrication (FFF), yet optimizing their mechanical performance remains challenging due to temperature-sensitive foaming behavior. This study aims to enhance the structural strength and material efficiency of LW-PLA parts using a multi-objective statistical approach. Four key process parameters—infill density (Id), material flow rate (Mf), wall line count (Wlc), and infill pattern (Ip)—were systematically varied using a Taguchi L₁₆ orthogonal array. Tensile strength (Ts), flexural strength (Fs), and material consumption (Mc) were selected as the critical response metrics. Grey Relational Analysis (GRA) was used to aggregate these responses into a single performance index, and ANOVA determined each factor’s contribution. The optimal combination of 60% infill density, 70% material flow, 4 wall lines, and line infill pattern yielded a 9.02% improvement in the overall performance index compared to the baseline, with corresponding Ts and Fs values of 13.58 MPa and 20.51 MPa. Mf and Wlc were the most influential parameters on mechanical behavior, while Id mainly affected Mc. These findings confirm that integrating Taguchi and GRA enables effective parameter tuning for LW-PLA, balancing strength and efficiency. This work contributes to the development of lightweight, high-performance parts suitable for functional applications such as UAVs and prototyping. Full article

With industrial transformation and the rise in the 15 min community life circle, optimizing walkability and preserving industrial heritage are key to revitalizing former industrial areas. This study, focusing on Shijingshan District in Beijing, proposes a walkability evaluation framework integrating multi-source big data and street-level perception. Using Points of Interest (POI) classification, which refers to the categorization of key urban amenities, pedestrian network modeling, and street view image data, a Walkability Friendliness Index is developed across four dimensions: accessibility, convenience, diversity, and safety. POI data provide insights into the spatial distribution of essential services, while pedestrian network data, derived from OpenStreetMap, model the walkable road network. Street view image data, processed through semantic segmentation, are used to assess the quality and safety of pedestrian pathways. Results indicate that core communities exhibit higher Walkability Friendliness Index scores due to better connectivity and land use diversity, while older and newly developed areas face challenges such as street discontinuity and service gaps. Accordingly, targeted optimization strategies are proposed: enhancing accessibility by repairing fragmented alleys and improving network connectivity; promoting functional diversity through infill commercial and service facilities; upgrading lighting, greenery, and barrier-free infrastructure to ensure safety; and delineating priority zones and balanced enhancement zones for differentiated improvement. This study presents a replicable technical framework encompassing data acquisition, model evaluation, and strategy development for enhancing walkability, providing valuable insights for the revitalization of industrial districts worldwide. Future research will incorporate virtual reality and subjective user feedback to further enhance the adaptability of the model to dynamic spatiotemporal changes. Full article