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19 pages, 3112 KiB  
Article
Study on the Distribution and Quantification Characteristics of Soil Nutrients in the Dryland Albic Soils of the Sanjiang Plain, China
by Jingyang Li, Huanhuan Li, Qiuju Wang, Yiang Wang, Xu Hong and Chunwei Zhou
Agronomy 2025, 15(8), 1857; https://doi.org/10.3390/agronomy15081857 - 31 Jul 2025
Viewed by 137
Abstract
The main soil type in the Sanjiang Plain of Northeast China, dryland albic soil is of great significance for studying nutrient distribution characteristics. This study focuses on 852 Farm in the typical dryland albic soil area of the Sanjiang Plain, using a combination [...] Read more.
The main soil type in the Sanjiang Plain of Northeast China, dryland albic soil is of great significance for studying nutrient distribution characteristics. This study focuses on 852 Farm in the typical dryland albic soil area of the Sanjiang Plain, using a combination of paired t-test, geostatistics, correlation analysis, and principal component analysis to systematically reveal the spatial differentiation of soil nutrients in the black soil layer and white clay layer of dryland albic soil, and to clarify the impact mechanism of plow layer nutrient characteristics on crop productivity. The results show that the nutrient content order in both the black and white clay layers is consistent: total potassium (TK) > organic matter (OM) > total nitrogen (TN) > total phosphorus (TP) > alkali-hydrolyzable nitrogen (HN) > available potassium (AK) > available phosphorus (AP). Both layers exhibit a spatial pattern of overall consistency and local differentiation, with spatial heterogeneity dominated by altitude gradients—nutrient content increases with decreasing altitude. Significant differences exist in nutrient content and distribution between the black and white clay layers, with the comprehensive fertility of the black layer being significantly higher than that of the white clay layer, particularly for TN, TP, TK, HN, and OM contents (effect size > 8). NDVI during the full maize growth period is significantly positively correlated with TP, TN, AK, AP, and HN, and the NDVI dynamics (first increasing. then decreasing) closely align with the peak periods of available nitrogen/phosphorus and crop growth cycles, indicating a strong coupling relationship between vegetation biomass accumulation and nutrient availability. These findings provide important references for guiding rational fertilization, agricultural production layout, and ecological environmental protection, contributing to the sustainable utilization of dryland albic soil resources and sustainable agricultural development. Full article
(This article belongs to the Section Soil and Plant Nutrition)
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18 pages, 4939 KiB  
Article
Decarbonizing Agricultural Buildings: A Life-Cycle Carbon Emissions Assessment of Dairy Barns
by Hui Liu, Zhen Wang, Xinyi Du, Fei Qi, Chaoyuan Wang and Zhengxiang Shi
Agriculture 2025, 15(15), 1645; https://doi.org/10.3390/agriculture15151645 - 30 Jul 2025
Viewed by 129
Abstract
The life-cycle carbon emissions (LCCE) assessment of dairy barns is crucial for identifying low-carbon transition pathways and promoting the sustainable development of the dairy industry. We applied a life cycle assessment approach integrated with building information modeling and EnergyPlus to establish a full [...] Read more.
The life-cycle carbon emissions (LCCE) assessment of dairy barns is crucial for identifying low-carbon transition pathways and promoting the sustainable development of the dairy industry. We applied a life cycle assessment approach integrated with building information modeling and EnergyPlus to establish a full life cycle inventory of the material quantities and energy consumption for dairy barns. The LCCE was quantified from the production to end-of-life stages using the carbon equivalent of dairy barns (CEDB) as the functional unit, expressed in kg CO2e head−1 year−1. A carbon emission assessment model was developed based on the “building–process–energy” framework. The LCCE of the open barn and the lower profile cross-ventilated (LPCV) barn were 152 kg CO2e head−1 year−1 and 229 kg CO2e head−1 year−1, respectively. Operational carbon emissions (OCE) accounted for the largest share of LCCE, contributing 57% and 74%, respectively. For embodied carbon emissions (ECE), the production of building materials dominated, representing 91% and 87% of the ECE, respectively. Regarding carbon mitigation strategies, the use of extruded polystyrene boards reduced carbon emissions by 45.67% compared with stone wool boards and by 36% compared with polyurethane boards. Employing a manure pit emptying system reduced carbon emissions by 76% and 74% compared to manure scraping systems. Additionally, the adoption of clean electricity resulted in a 33% reduction in OCE, leading to an overall LCCE reduction of 22% for the open barn and 26% for the LPCV barn. This study introduces the CEDB to evaluate low-carbon design strategies for dairy barns, integrating building layout, ventilation systems, and energy sources in a unified assessment approach, providing valuable insights for the low-carbon transition of agricultural buildings. Full article
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25 pages, 3785 KiB  
Article
Evolutionary Algorithms for the Optimal Design of Robotic Cells: A Dual Approximation for Space and Time
by Raúl-Alberto Sánchez-Sosa and Ernesto Chavero-Navarrete
Appl. Sci. 2025, 15(15), 8455; https://doi.org/10.3390/app15158455 - 30 Jul 2025
Viewed by 184
Abstract
The optimization of robotic cells is a key challenge in the manufacturing industry due to the need to maximize efficiency in limited spaces and minimize operation times. Traditional cell design methods often face challenges due to the high complexity and dynamic nature of [...] Read more.
The optimization of robotic cells is a key challenge in the manufacturing industry due to the need to maximize efficiency in limited spaces and minimize operation times. Traditional cell design methods often face challenges due to the high complexity and dynamic nature of real-world applications. In response, this study presents a dual approach to optimize both spatial design and traversal time in robotic cells, using bioinspired evolutionary algorithms. Initially, a genetic algorithm is employed to optimize the layout of the cell elements, reducing space usage and avoiding interferences between workstations. Subsequently, an ant colony optimization algorithm is used to optimize the robots’ trajectories, minimizing cycle time. Through simulations and a digital model of the cell, key metrics such as total space reduction, operational time improvement, and productivity increase are evaluated. The results demonstrate that the combination of both approaches achieves significant improvements, enabling an average reduction of 21.19% in the occupied area and up to 20.15% in operational cycle time, consistently outperforming traditional methods. This approach has the potential to be applied in various industrial configurations, representing a relevant contribution in the integration of artificial intelligence techniques for the enhancement of robotic systems. Full article
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23 pages, 7773 KiB  
Article
Strengthening-Effect Assessment of Smart CFRP-Reinforced Steel Beams Based on Optical Fiber Sensing Technology
by Bao-Rui Peng, Fu-Kang Shen, Zi-Yi Luo, Chao Zhang, Yung William Sasy Chan, Hua-Ping Wang and Ping Xiang
Photonics 2025, 12(7), 735; https://doi.org/10.3390/photonics12070735 - 18 Jul 2025
Viewed by 289
Abstract
Carbon fiber-reinforced polymer (CFRP) laminates have been widely coated on aged and damaged structures for recovering or enhancing their structural performance. The health conditions of the coated composite structures have been given high attention, as they are critically important for assessing operational safety [...] Read more.
Carbon fiber-reinforced polymer (CFRP) laminates have been widely coated on aged and damaged structures for recovering or enhancing their structural performance. The health conditions of the coated composite structures have been given high attention, as they are critically important for assessing operational safety and residual service life. However, the current problem is the lack of an efficient, long-term, and stable monitoring technique to characterize the structural behavior of coated composite structures in the whole life cycle. For this reason, bare and packaged fiber Bragg grating (FBG) sensors have been specially developed and designed in sensing networks to monitor the structural performance of CFRP-coated composite beams under different loads. Some optical fibers have also been inserted in the CFRP laminates to configure the smart CFRP component. Detailed data interpretation has been conducted to declare the strengthening process and effect. Finite element simulation and simplified theoretical analysis have been conducted to validate the experimental testing results and the deformation profiles of steel beams before and after the CFRP coating has been carefully checked. Results indicate that the proposed FBG sensors and sensing layout can accurately reflect the structural performance of the composite beam structure, and the CFRP coating can share partial loads, which finally leads to the downward shift in the centroidal axis, with a value of about 10 mm. The externally bonded sensors generally show good stability and high sensitivity to the applied load and temperature-induced inner stress variation. The study provides a straightforward instruction for the establishment of a structural health monitoring system for CFRP-coated composite structures in the whole life cycle. Full article
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31 pages, 5858 KiB  
Article
Research on Optimization of Indoor Layout of Homestay for Elderly Group Based on Gait Parameters and Spatial Risk Factors Under Background of Cultural and Tourism Integration
by Tianyi Yao, Bo Jiang, Lin Zhao, Wenli Chen, Yi Sang, Ziting Jia, Zilin Wang and Minghu Zhong
Buildings 2025, 15(14), 2498; https://doi.org/10.3390/buildings15142498 - 16 Jul 2025
Viewed by 174
Abstract
This study, in response to the optimization needs of fall risks for the elderly in the context of cultural and tourism integration in Hebei Province, China, established a quantitative correlation system between ten gait parameters and ten types of spatial risk factors. By [...] Read more.
This study, in response to the optimization needs of fall risks for the elderly in the context of cultural and tourism integration in Hebei Province, China, established a quantitative correlation system between ten gait parameters and ten types of spatial risk factors. By collecting gait data (Qualisys infrared motion capture system, sampling rate 200 Hz) and spatial parameters from 30 elderly subjects (with mild, moderate, and severe functional impairments), a multi-level regression model was established. This study revealed that step frequency, step width, and step length were nonlinearly associated with corridor length, door opening width, and step depth (R2 = 0.53–0.68). Step speed, ankle dorsiflexion, and foot pressure were key predictive factors (OR = 0.04–8.58, p < 0.001), driving the optimization of core spatial factors such as threshold height, handrail density, and friction coefficient. Step length, cycle, knee angle, and lumbar moment, respectively, affected bed height (45–60 cm), switch height (1.2–1.4 m), stair riser height (≤35 mm), and sink height adjustment range (0.7–0.9 m). The prediction accuracy of the ten optimized values reached 86.7% (95% CI: 82.1–90.3%), with Hosmer–Lemeshow goodness-of-fit x2 = 7.32 (p = 0.412) and ROC curve AUC = 0.912. Empirical evidence shows that the graded optimization scheme reduced the fall risk by 42–85%, and the estimated fall incidence rate decreased by 67% after the renovation. The study of the “abnormal gait—spatial threshold—graded optimization” quantitative residential layout optimization provides a systematic solution for the data-quantified model of elderly-friendly residential renovations. Full article
(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)
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26 pages, 9395 KiB  
Article
Study on Piping Layout Optimization for Chiller-Plant Rooms Using an Improved A* Algorithm and Building Information Modeling: A Case Study of a Shopping Mall in Qingdao
by Xiaoliang Ma, Hongshe Cui, Yan Zhang and Xinyao Wang
Buildings 2025, 15(13), 2275; https://doi.org/10.3390/buildings15132275 - 28 Jun 2025
Viewed by 255
Abstract
Heating, ventilation, and air-conditioning systems account for 40–60% of the energy consumed in commercial buildings, and much of this load originates from sub-optimal piping layouts in chiller-plant rooms. This study presents an automated routing framework that couples Building Information Modeling (BIM) with an [...] Read more.
Heating, ventilation, and air-conditioning systems account for 40–60% of the energy consumed in commercial buildings, and much of this load originates from sub-optimal piping layouts in chiller-plant rooms. This study presents an automated routing framework that couples Building Information Modeling (BIM) with an enhanced A* search to produce collision-free, low-resistance pipelines while simultaneously guiding component selection. The algorithm embeds protective buffer zones around equipment, reserves maintenance corridors through an attention-based cost term, and prioritizes 135° elbows to cut local losses. Generated paths are exported as Industry Foundation Classes (IFC) objects for validation in a BIM digital twin, where hydraulic feedback drives iterative reselection of high-efficiency devices—including magnetic-bearing chillers, cartridge filters and tilted-disc valves—until global pressure drop and life-cycle cost are minimized. In a full-scale shopping-mall retrofit, the method significantly reduces pipeline resistance and operating costs, confirming its effectiveness and replicability for sustainable chiller-plant design. Full article
(This article belongs to the Section Building Energy, Physics, Environment, and Systems)
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23 pages, 743 KiB  
Article
Process Concept of a Waste-Fired Zero-Emission Integrated Gasification Static Cycle Power Plant
by Augusto Montisci and Aiman Rashid
Sustainability 2025, 17(13), 5816; https://doi.org/10.3390/su17135816 - 24 Jun 2025
Viewed by 726
Abstract
The layout of an urban waste-fired zero-emission power plant is described in this paper. The principle layout, which is based on similar coal-fired plants retrieved from the literature, integrates gasification with a power-generation section and implements two parallel conversion processes: one relies on [...] Read more.
The layout of an urban waste-fired zero-emission power plant is described in this paper. The principle layout, which is based on similar coal-fired plants retrieved from the literature, integrates gasification with a power-generation section and implements two parallel conversion processes: one relies on the heat developed in the gasifier and consists of a thermoacoustic-magnetohydrodynamic (TA-MHD) generator; the other involves treating syngas to obtain almost pure hydrogen, which is then fed to fuel cells. The CO2 derived from the oxidation of Carbon is stocked in liquid form. The novelty of the proposed layout lies in the fact that the entire conversion is performed using static equipment. The resulting plant prevents the release of any type of emissions in the atmosphere and increases mechanical efficiency, compared to traditional plants—thanks to the absence of moving parts—resolving, nonetheless, the ever-increasing waste-related pollution issue. A case study of a Union of Municipalities in Southern Lebanon is considered. The ideal cycle handles 65 tons/day of urban waste and is capable of generating 7.71 MW of electric power, with a global efficiency of 52.39%. Full article
(This article belongs to the Section Environmental Sustainability and Applications)
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15 pages, 9452 KiB  
Article
Thermal Fatigue Behaviors of BGA Packages with an Optimized Solder Joint Layout
by Mohammed Abdel Razzaq, Michael Meilunas, Xian A. Cao, Jim Wilcox and Abdallah Ramini
Electronics 2025, 14(11), 2286; https://doi.org/10.3390/electronics14112286 - 4 Jun 2025
Viewed by 751
Abstract
Ball Grid Array (BGA) failures are often dominated by stress concentrations at the outer solder joints, particularly under thermomechanical loading. To mitigate this issue, this study investigates the mechanical and reliability implications of optimizing the BGA solder joint array by removing the outermost [...] Read more.
Ball Grid Array (BGA) failures are often dominated by stress concentrations at the outer solder joints, particularly under thermomechanical loading. To mitigate this issue, this study investigates the mechanical and reliability implications of optimizing the BGA solder joint array by removing the outermost rows and columns, positioning all connections directly beneath the silicon die. Two commonly used solder alloys—SAC305 and Sn37Pb—were selected to evaluate the effects of this optimized array design. A combined experimental and numerical approach was employed, including accelerated thermal cycling (–40 °C to 125 °C), in situ resistance monitoring, cross-sectional failure analysis, and finite element modeling (FEM) to assess fatigue behavior under the altered layout. The optimized array significantly improved performance for SAC305, yielding a 1.67× increase in mean cycles-to-failure and a 29% reduction in peak von Mises stress, with failure locations shifting from the corners to more evenly distributed areas beneath the die. Sn37Pb assemblies showed only a 1.01× improvement despite an 11% stress reduction, attributed to persistent shear-dominated failures at second-row joints. These results highlight the critical influence of joint array architecture and solder alloy selection on reliability, offering design-level guidance for applications prioritizing thermomechanical robustness with reduced I/O counts. Full article
(This article belongs to the Section Electronic Materials, Devices and Applications)
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22 pages, 5472 KiB  
Article
Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm
by Xiaoshi Zhuang, Honglue Wan, Dongran Song, Xinyu Fan, Yuchen Wang, Qian Huang and Jian Yang
Energies 2025, 18(11), 2846; https://doi.org/10.3390/en18112846 - 29 May 2025
Viewed by 395
Abstract
To address the high complexity layout optimization problem of an offshore wind and wave energy co-generation system, an improved seagull optimization algorithm-based method is proposed. Firstly, the levelized cost of electricity (LCOE) model, based on the whole-life-cycle cost, serves as the optimization objective. [...] Read more.
To address the high complexity layout optimization problem of an offshore wind and wave energy co-generation system, an improved seagull optimization algorithm-based method is proposed. Firstly, the levelized cost of electricity (LCOE) model, based on the whole-life-cycle cost, serves as the optimization objective. Therein, the synergistic effect between wind turbines and wave energy generators is taken into consideration to decouple the problem and establish a two-layer optimization framework. Secondly, the seagull optimization algorithm is enhanced by integrating three strategies: the nonlinear adjustment strategy for control factors, the Gaussian–Cauchy hybrid variational strategy, and the multiple swarm strategy, thereby improving the global search capability. Finally, a case study in the South China Sea validates the effectiveness of the model and algorithm. Using the improved algorithm, the optimal layout of the co-generation system and the optimal wind turbine parameters are obtained. The results indicate that the optimized system achieves a LCOE of 0.6561 CNY/kWh, which is 0.29% lower than that achieved by traditional algorithms. The proposed method provides a reliable technical solution for the economic optimization of the co-generation system. Full article
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15 pages, 32541 KiB  
Article
A High-Speed 8-Bit Single-Channel SAR ADC with Tailored Bit Intervals and Split Capacitors
by Xinyu Li, Ruida Wang, Liulu He and Kentaro Yoshioka
Electronics 2025, 14(10), 2032; https://doi.org/10.3390/electronics14102032 - 16 May 2025
Viewed by 706
Abstract
As wireless communication systems continue to demand higher data transmission rates, the need for analog-to-digital converters (ADCs) with a higher sampling rate becomes increasingly critical. However, traditional successive approximation register (SAR) ADCs operating at 1 bit/cycle often face speed limitations due to the [...] Read more.
As wireless communication systems continue to demand higher data transmission rates, the need for analog-to-digital converters (ADCs) with a higher sampling rate becomes increasingly critical. However, traditional successive approximation register (SAR) ADCs operating at 1 bit/cycle often face speed limitations due to the fixed bit intervals and comparator regeneration delays, which constrain their scalability in advanced technology nodes. To address these challenges, this paper presents a high-speed 8-bit single-channel SAR ADC featuring a novel delay generation circuit that enables tailored bit intervals (TBIs) to reduce conversion latency. A split capacitive digital-to-analog converter (CDAC) is employed to suppress input common-mode voltage shifts, while inverted dynamic latch pairs and early capacitor reset techniques are introduced to improve conversion speed. The proposed ADC is implemented in a 16 nm CMOS process, occupying only 0.0012 mm2. Post-layout simulations across extreme process and temperature corners validate the robustness of the design. The TBI-ADC achieves an effective number of bits (ENOB) of 7.20 bits at Typical–Typical (TT) 25 °C with a power consumption of 6.94 mW. Furthermore, it reaches a sampling rate of 1.6 GS/s at Fast–Fast (FF) −40 °C, representing a 33% improvement over the fastest previously reported single-channel, 1 bit/cycle, 8-bit SAR ADC. Full article
(This article belongs to the Special Issue Advanced High-Performance Analog Integrated Circuits)
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30 pages, 31813 KiB  
Article
Spatial and Temporal Variability of Near-Surface CO2 and Influencing Factors in Urban Communities
by Yueyue Wu, Yi Zheng, Jialei Liu, Qingxin Yang, Beixiang Shi, Chenghe Guan and Wanxin Deng
Land 2025, 14(4), 888; https://doi.org/10.3390/land14040888 - 17 Apr 2025
Viewed by 544
Abstract
CO2 is the primary contributor to global warming, and also the most significant anthropogenic emission gas in cities. This study investigates near-surface CO2 spatiotemporal variability patterns at the community scale to address the critical gap in urban CO2 high-resolution measurement [...] Read more.
CO2 is the primary contributor to global warming, and also the most significant anthropogenic emission gas in cities. This study investigates near-surface CO2 spatiotemporal variability patterns at the community scale to address the critical gap in urban CO2 high-resolution measurement and promote urban carbon neutrality. Combining fixed and mobile monitoring across five representative communities (1-km2 coverage) with two-hour temporal precision and 20 m spatial resolution, results revealed average CO2 concentrations of 440–480 ppm, exhibiting bimodal diurnal cycles and highlighting spatiotemporal divergent emission behaviors. Three communities peaked during 17:00–19:00 LT, while two peaked during 08:00–10:00 LT. Spatial correlation analysis identified two dominant patterns: road-adjacent “externally dominated” hotspots and “internally dominated” zones with elevated intra-community levels. Spearman correlation analysis, Random Forest, and Geographically and Temporally Weighted Regression models quantified spatial morphology and element contributions, demonstrating that building morphology exerted time-varying impacts across communities. Meanwhile, external traffic contributed 18–39% to concentration variability, while internal traffic and energy consumption drove localized peaks. The findings indicated that apart from the emission sources, the micro-scale urban spatial design elements also regulate the near-surface CO2 distribution. This high-resolution approach provides actionable insights for optimizing community layouts and infrastructure to mitigate localized emissions, advancing carbon neutrality targeted urban planning. Full article
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18 pages, 26619 KiB  
Article
A Framework for 3D Plant Simulation of Meal-Kit-Packaging Robot Automation System
by Tae Hyong Kim, Byoung Il Gu, Ki Hyun Kwon and Ah-Na Kim
Appl. Sci. 2025, 15(8), 4116; https://doi.org/10.3390/app15084116 - 9 Apr 2025
Viewed by 672
Abstract
A data-driven 3D simulation for the robotic automation of the most labor-intensive packaging process in meal kit production was developed using Tecnomatix plant simulation software. The workflow and environments of the existing manual process were analyzed. An existing production site was scanned using [...] Read more.
A data-driven 3D simulation for the robotic automation of the most labor-intensive packaging process in meal kit production was developed using Tecnomatix plant simulation software. The workflow and environments of the existing manual process were analyzed. An existing production site was scanned using a 3D Lidar scanner to create 3D models and design the initial assembly layout. Two types of 3D simulation models, implemented with a single or double delta robot, were designed to determine the optimal robot-automated packaging process. Key performance indicators for simulation models of a manual and two robot automation systems were analyzed. The throughputs of the manual, single delta robot and double delta robot models were 2112, 1510, and 2568 ea/h, respectively. The single robot system achieved only 68.3% of the throughput of the manual process, which is attributed to a cycle time of 2.36 s for picking and placing all components. On the other hand, the cycle time of the double robot system was 1.66 times faster, and the throughput was 1.7 times greater compared to the single robot system. The developed 3D simulation model for the meal kit packaging system demonstrates the potential of robotic automation in addressing the labor shortage issue as well as improving production efficiency. Full article
(This article belongs to the Special Issue Robotics and Intelligent Systems: Technologies and Applications)
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23 pages, 49147 KiB  
Article
The Applicability of Two Generative Adversarial Networks to Generative Plantscape Design: A Comparative Study
by Lu Feng, Yuting Sun, Chenwen Yu, Ran Chen and Jing Zhao
Land 2025, 14(4), 746; https://doi.org/10.3390/land14040746 - 31 Mar 2025
Viewed by 429
Abstract
Plantscape design combines both scientific and technical elements, with flower borders serving as a representative example. Generative Adversarial Networks (GANs), which can automatically generate images through training, offer new technological support for plantscape design, potentially enhancing the efficiency of designers. This study focuses [...] Read more.
Plantscape design combines both scientific and technical elements, with flower borders serving as a representative example. Generative Adversarial Networks (GANs), which can automatically generate images through training, offer new technological support for plantscape design, potentially enhancing the efficiency of designers. This study focuses on flower border plans as the research subject and creates a dataset of flower border designs. Subsequently, the research employed two algorithms, Pix2Pix and CycleGAN, for training and testing, enabling the automatic generation of flower border design images, with subsequent optimization of the results. The paper compares the generated results of both algorithms in terms of image quality and design patterns, providing both objective and subjective evaluations of CycleGAN, which performed better. Experimental results show that the algorithm can learn the latent patterns of flower border design to some extent and generate high-quality images with reasonable performance in terms of ornamental character and ecological character. Among the design types, bar-shaped layouts showed the best results. However, the algorithm still faces challenges in handling complex site processing, boundary clarity, and design innovation. Additionally, aspects such as vertical variation, texture harmony, low maintenance, and sustainability remain areas for future improvement. This study demonstrates the potential of GAN in small-scale plantscape design and offers innovative and feasible solutions for flower border design. Full article
(This article belongs to the Section Land Planning and Landscape Architecture)
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18 pages, 3728 KiB  
Article
Generative Adversarial Networks for Climate-Sensitive Urban Morphology: An Integration of Pix2Pix and the Cycle Generative Adversarial Network
by Mo Wang, Ziheng Xiong, Jiayu Zhao, Shiqi Zhou, Yuankai Wang, Rana Muhammad Adnan Ikram, Lie Wang and Soon Keat Tan
Land 2025, 14(3), 578; https://doi.org/10.3390/land14030578 - 10 Mar 2025
Cited by 2 | Viewed by 1019
Abstract
Urban heat island (UHI) effects pose significant challenges to sustainable urban development, necessitating innovative modeling techniques to optimize urban morphology for thermal resilience. This study integrates the Pix2Pix and CycleGAN architectures to generate high-fidelity urban morphology models aligned with local climate zones (LCZs), [...] Read more.
Urban heat island (UHI) effects pose significant challenges to sustainable urban development, necessitating innovative modeling techniques to optimize urban morphology for thermal resilience. This study integrates the Pix2Pix and CycleGAN architectures to generate high-fidelity urban morphology models aligned with local climate zones (LCZs), enhancing their applicability to urban climate studies. This research focuses on eight major Chinese coastal cities, leveraging a robust dataset of 4712 samples to train the generative models. Quantitative evaluations demonstrated that the integration of CycleGAN with Pix2Pix substantially improved structural fidelity and realism in urban morphology synthesis, achieving a peak Structural Similarity Index Measure (SSIM) of 0.918 and a coefficient of determination (R2) of 0.987. The total adversarial loss in Pix2Pix training stabilized at 0.19 after 811 iterations, ensuring high convergence in urban structure generation. Additionally, CycleGAN-enhanced outputs exhibited a 35% reduction in relative error compared to Pix2Pix-generated images, significantly improving edge preservation and urban feature accuracy. By incorporating LCZ data, the proposed framework successfully bridges urban morphology modeling with climate-responsive urban planning, enabling adaptive design strategies for mitigating UHI effects. This study integrates Pix2Pix and CycleGAN architectures to enhance the realism and structural fidelity of urban morphology generation, while incorporating the LCZ classification framework to produce urban forms that align with specific climatological conditions. Compared to the model trained by Pix2Pix coupled with LCZ alone, the approach offers urban planners a more precise tool for designing climate-responsive cities, optimizing urban layouts to mitigate heat island effects, improve energy efficiency, and enhance resilience. Full article
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25 pages, 9002 KiB  
Article
Pre-Assessment Research of Regional Spatial Planning from the Perspective of Spatial Evolution
by Guang Chen and Jian Gong
Land 2025, 14(3), 574; https://doi.org/10.3390/land14030574 - 9 Mar 2025
Viewed by 693
Abstract
As an important policy tool for guiding the development and protection of territorial space, the specific impact of spatial planning on the evolution of territorial space and the effects of its implementation have not yet been fully recognized. At the planning formulation stage, [...] Read more.
As an important policy tool for guiding the development and protection of territorial space, the specific impact of spatial planning on the evolution of territorial space and the effects of its implementation have not yet been fully recognized. At the planning formulation stage, the feedback cycle of the implementation effect of planning is too long, and the adjustment is too slow to take effect. This directly affects the effectiveness and relevance of planning implementation. In this study, we propose a framework for pre-assessment of regional spatial planning based on the evolution of territorial space. We construct an indicator system from four dimensions to pre-assess the effectiveness of territorial spatial planning. The results show that the land use change simulation model, based on historical data coupled with planning elements, achieves an accuracy of 0.8457, which can accurately reflect the impact of planning on the evolution of land space. The results of the evaluation show that: (1) Planning elements such as concentrated urban construction areas, schools, and other public service facilities are the main driving forces behind the future evolution of territorial space. (2) Regional spatial planning has a significant effect on adjusting the spatial layout and optimizing the spatial form, and it has a certain effect on restricting the total scale of the construction area, improving the efficiency of land use, and lowering carbon emissions. (3) Existing planning strategies are still too rigid, so further enhancement of “flexibility” and “blank space” in planning is necessary. Additionally, guidance for improving the efficiency of land development needs to be further strengthened. The main contribution of this study is to provide a reliable pre-evaluation framework for policymakers and scholars. This will help identify problems and shortcomings at the planning formulation stage, allowing them to be optimized and adjusted in a timely manner. Under the guidance of scientific and reasonable planning, it will further promote the green and high-quality development and protection of territorial space. Full article
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