Search Results (23)

To address grid variability caused by renewable energy integration and to maintain grid reliability and resilience, hydropower must quickly adjust its power generation over short time periods. This changing energy generation landscape requires advance technology integration and adaptive parameter optimization for hydropower systems via digital twin effort. However, this is difficult owing to the lack of characterization and modeling for the nonlinear nature of hydroturbines. To solve this issue, this paper first formulates a six-coefficient Kaplan hydroturbine model and then proposes a parametric optimization tuning framework based on the Nelder–Mead algorithm for adaptive dynamic learning of the six-coefficients so as to build models that describe the turbine. To assess the performance of the proposed optimal parametric tuning technique, operational data from a real-world Kaplan hydroturbine unit are collected and used to model the relationship between the gate opening and the generated power production. The findings show that the proposed technique can effectively and adaptively learn the unknown dynamics of the Kaplan hydroturbine while optimally tune the unknown coefficients to match the generated power output from the real hydroturbine unit with an inaccuracy of less than 5%. The method can be used to provides optimal tuning of parameters critical for controller design, operational optimization and daily maintenance for hydroturbines in general. Full article

Generative AI (Gen-AI) revolutionizes design by leveraging machine learning to generate innovative solutions. It analyzes data to identify patterns, creates tailored designs, enhances creativity, and allows designers to explore complex possibilities for diverse industries. This study uses a Gen-AI design generation process to develop an urban landscape fumigation service robot. This study proposes a machine-learned multimodal and feedback-based variational autoencoder (MMF-VAE) model that incorporates a readily available spraying robot dataset and includes design considerations from various research efforts to ensure real-time deployability. The objective is to demonstrate the effectiveness of data-driven and feedback-based approaches in generating design specifications for a fumigation robot with the targeted requirements of autonomous navigation, precision spraying, and an extended runtime. The design generation process comprises three stages: (1) parameter fixation, emphasizing functionality-based and aesthetic-based specifications; (2) design specification generation using the proposed MMF-VAE model with and without a spraying robot dataset; and (3) robot development based on the generated specifications. A comparative analysis evaluated the impact of the dataset-driven design generation. The design generated with the dataset proved more feasible and optimized for real-world deployment with the integration of multimodal inputs and iterative feedback refinement. A real-time prototype was then constructed using the model’s parametric constraints and tested in actual fumigation scenarios to validate operational viability. This study highlights the transformative potential of Gen-AI in robotic design workflows. Full article

Sliding mode control (SMC) has been widely used to control linear and nonlinear dynamics systems because of its robustness against parametric uncertainties and matched disturbances. Although SMC design has traditionally addressed process model-based approaches, the rapid advancements in instrumentation and control systems driven by Industry 4.0, coupled with the increased complexity of the controlled processes, have led to the growing acceptance of controllers based on data-driven techniques. This review article aims to explore the landscape of SMC, focusing specifically on data-driven techniques through a comprehensive systematic literature review that includes a bibliometric analysis of relevant documents and a cumulative production model to estimate the deceleration point of the scientific production of this topic. The most used SMC schemes and their integration with data-driven techniques and intelligent algorithms, including identifying the leading applications, are presented. Full article

Today, suburban areas are home to an ever-increasing majority of the global population. Models indicate that the next generation of US metropolitan growth will rapidly continue outside of urban cores, where car-based development patterns have served as the dominant paradigm for more than a century. With the emergence of autonomous mobility technologies and services, the suburbs of the future offer key opportunities to tackle pressing environmental challenges, such as significant GHG emissions from private vehicle trips, underutilized and fragmented landscape spaces, and a high proportion of impervious surfaces. To leverage this opportunity, our research team employed a novel scenario-based parametric modeling framework to generate and optimize suburban land use patterns and block configurations that leverage autonomous mobility to optimize environmental performance and accessibility metrics. The framework performed through our project, NOGAS (Next Optimized Generation of Autonomous Suburbs), consists of five key parametric modules and a heuristic design process covering various planning and design decision-making stages including scenario generation, analysis, optimization, and visualization. It is the first of its kind tailored for suburban settings with emerging mobility systems, which, more importantly, prioritizes landscape performance and accessibility over the traditional automobile-centric approach in suburban development. One of the most significant findings from this research is that substantial enhancements to a neighborhood’s environmental performance and overall accessibility can be achieved by modifying existing suburban land use patterns and individual block configurations, without the necessity of increasing density. The results of the framework further suggest that a strategic atomized land use scheme, combined with an innovative clustered block typology, is favored for the anticipated widespread adoption of autonomous mobility systems and improved environmental performance. The innovative methods and findings introduced in this research illuminate an alternative approach to sustainable suburban development, offering valuable insights for city planners and developers to shape future suburban master plans, zoning regulations, and design guidelines. Full article

The escalation of the urban population and energy demands has exacerbated the carbon emission intensity at the operational stage of urban old communities. The spatial elements of the built environments comprising building groups, roads and landscape, and the spatial morphology of these elements, are endowed not only with human activities but also impact local microclimates and overall carbon emissions. Nonetheless, little attention has been paid to the correlation mechanism between the spatial morphology of the urban built environments and carbon emissions. In this paper, the aim is to combine carbon emissions simulation and statistical analysis to find the correlation between the spatial morphological indices and carbon emissions and to bridge the gaps. Thus, guided by the principles of urban energy modeling, this research adopts a parametric process of “information model construction–carbon emission simulation–statistical analysis”. First, taking 60 typical samples of an old community in Jinan, China, as objects, morphological indices such as density, texture and layout are analyzed through regression analysis to highlight their impacts on carbon emissions. Then, a carbon emission prediction model based on spatial morphological indices is established and verified. The results show that the floor area ratio (FAR), building coverage ratio (BCR), enclosure degree (ED), shape factor (SF) and average road aspect ratio (AS) have significant impacts on carbon emissions during the operational stage. Among these indices, the FAR and the ED are identified as the pivotal influencers. The findings confirm the important role of spatial morphological design of old communities in cold regions in improving urban carbon reduction potential, and they provide theoretical underpinnings and empirical data as references for urban morphology design formulated within the context of low-carbon objectives. Full article

A prevalent engineering task in practice is calculating the annual balance of sediments on some watercourses. This is particularly challenging when assessing the backfilling of river reservoirs that have a multifunctional purpose. Trakošćan Lake was built in the period from 1850 to 1862 as a pond and landscape addition to the park and Trakošćan castle. After 60 years, the lake was drained in 2022, and the work began on sediment excavation to improve the lake’s ecological condition due to about 200,000 cubic meters of deposited silt in the lake. In this research, the annual sediment production is calculated for the long-term period 1961–2020, based on empirical parametric methods (Fleming, Brunne). The results are compared with results from previous projects and recent sediment deposit investigations. Since there are no changes in LC/LU on this natural catchment, the decreasing trends in long-term sediment transport were compared with meteorological values, daily rainfall, and snow days. It is concluded that the intensity characteristics of the rainfall should be investigated more in detail and could provide much more tangible information regarding climate change impacts. Some targets for future monitoring design and research techniques are set. Full article

With the extensive application of data analysis in various parts of the landscape design process, Building Information Modeling (BIM), City Information Modeling (CIM), and Landscape Information Modeling (LIM) all aim to achieve key data sharing and collaboration in the whole cycle and promote the development of smart cities. Landscape element indicators are complex, diverse, and difficult to quantify, which is one of the reasons for the slow development of LIM. However, with the development requirements of LIM, quantifying landscape elements and transforming landscapes into digital landscape information has become a hot spot in the landscape design industry. Landscape parametric design aims to transform the design elements into quantifiable parameters, obtain the design scheme by changing the value of the parameters, and form the design results based on digital information. It is one of the foundations of LIM. Based on the Rhino + Grasshopper (R+G) platform, this study takes Shuixizhuang Park as an example and establishes the parametric design approach for the park entrance. The approach involves several steps: (1) Confirming the boundary and key points of the park to prepare the basic data for parametric design. (2) Utilizing the Physarealm Algorithm Method (PAM) to simulate crowd paths, the Site Slope Algorithm Model (SSAM) to analyze terrain slope, the Road Intersection Algorithm Model (RIAM) to determine the scope of the park entrance area based on the national and local design codes, and the Crowd Density Algorithm Model (CDAM) and Crowd Convenience Algorithm Model (CCAM) to analyze the density and convenience of the crowd to preliminarily confirm the park entrance. (3) Meeting the basic requirements of the crowd and vehicle gathering and spread by using the Square Area Review Algorithm Model (SARAM) and Parking Lot Review Algorithm Model (PLRAM) to recheck the site area of the park entrance square and park lot to optimize the park entrance. This approach constructs several site analysis models based on the R+G platform and introduces PAM to analyze crowd activity paths, proposing a landscape parametric design method that integrates crowd activity and landscape design requirements. Compared with the classical design, the landscape parametric design derived from the comprehensive data analysis reduces human interference, is more scientific and practical, and better meets the requirements of people entering the park. The approach also provides ideas for other landscape parametric site selections. By adjusting the values of element parameters, the approach can also be applied to the site selection and design of other landscapes. Full article

Parametric design, with its unique scientific and logical nature, is gradually applied in the field of landscape design. Therefore, the GIS (geographic information systems) technology of parametric software was applied to the optimization of traditional landscape architecture, and its practical application quality was discussed. The actual analysis results showed that the evaluation result of parametric design had the highest score of 7.71 in behavioral perception. The overall score was 7.28, showing a high scientific nature. In the evaluation of landscape environmental benefits, after the optimization of landscape greening by parametric design, the air cleanliness and living comfort were generally improved, compared with those before optimization, and the highest values were 11.97 ± 6.01 and 5.86 ± 2.11 respectively. In the evaluation of the economic benefits of gardens, the economic income of gardens in the past 8 years generally increased, reaching the highest of 3.5795 billion yuan, with a growth rate of 78.92%. At the same time, the return on investment reached 26.17%, far exceeding the expected 20%. Among the social benefits, the weight of increasing employment opportunities was the largest at 0.36. In summary, parameterized optimization of traditional landscape design can effectively improve its social, environmental, and economic benefits and has good practical value. Full article

This paper takes the garden road system as the research object and proposes a method of generating paths for classical gardens based on parametric design. Firstly, by studying the distribution characteristics of roads, the data on the curvature, angle, and view area of roads were collected. Secondly, the obtained data were transferred to the parameterized platform, and a method of intelligent generation was used for calculation. Finally, the road system was optimized by the genetic algorithm for better application in modern landscape design. According to the current situation, the road system plan generated by the algorithm inherits the characteristics of classical garden roads. This method can be applied to the courtyard, the community park, the urban park, and other objects. This research not only identifies the characteristics of landscape cultural heritage, but also produces an innovative, intelligent design tool. It provides new methods for the parameterized inheritance and application of traditional landscape heritage. Full article

Noise is the number two environmental health risk in Europe. With the majority of the world’s inhabitants residing in ever-growing cities, urban noise impacts an increasing number of people. Urban airports significantly contribute to urban noise, and their spatial effects far exceed their boundaries. While indoor acoustic mitigation in architecture is growingly addressed using parametric tools, there is limited research on mitigating noise with digital means through landscape and urban design. Moreover, there is a lack of methods for ameliorating urban noise through ground-forming. To address this, this paper contributes a novel method for integrating acoustic analysis in parametric landscape-forming. The method includes collecting on-line and on-site noise data, developing alternative landscape formations for mitigating noise, and evaluating design alternatives within a single digital design environment. This method was applied using research by design and examined on a case-study site adjacent to the Munich Airport. Three landform landscape designs for a park are developed, and their acoustic performance is compared. The results indicate the possibility of integrating acoustic considerations in landscape architecture, and the method provides a step-by-step guide for doing so. This capacity also promotes the long-term goal of increasing the environmental performance of urban grounds. Full article

Although geodesign techniques have been studied and developed worldwide, there is still a lack of in-depth application of geodesign workflows for redesigning urban river wetlands with characteristics of ecologically engineered landscaping (EEL). The study mainly aims at putting forward a proper approach in the methodological foundation for EEL practices in river wetlands. A typical EEL-oriented project of river restoration in Hangzhou, China, was conducted in this study. Based on in-situ geodata and tools within QGIS, individual geological factors analysis, with the hierarchical analysis method (AHP) and ecological vulnerability evaluation (EVE), was conducted by experts’ voting and the weighted linear combination (WLC) method. Analysis of hydrological-related factors proceeded. This GIS-based analysis with expert knowledge provided comprehensive redesign solutions for the redesign project, i.e., restoration of the riverbed, spatial restoration in the horizontal and vertical dimensions, and integration with the multifunctional design. Detailed three-dimensional models for design practices were developed to present redesigned topology and space accordingly. Terrain, inundation, and visibility analysis proceeded with parametric mapping programs within Grasshopper to check the feasibility. The adapted geodesign-based workflow in the study also applies to the site analysis, sustainable assessment and landscape planning for urban wetlands EEL projects. Full article

Stabilizing farm revenues is a goal of agricultural policies around the world, especially in vulnerable regions with limited access to crop insurance. One potential pathway to revenue stability follows the agricultural “insurance hypothesis”, which holds that crop diversification has stabilizing effects on productivity that mitigate risks from environmental stressors and market shocks, thereby producing a form of natural insurance against crop loss. While substantial support for the hypothesis exists, most studies testing the hypothesis have occurred at the farm or landscape levels and have controlled for a limited range of socioeconomic and environmental factors. This study tests the insurance hypothesis by examining the effects of crop species production diversity on revenue stability in low-income regions of southern Mexico. Here, rural farms experience chronic vulnerability to climatic shocks and market forces. Using parametric and non-parametric approaches, three groups of models are used to examine the effects of socio-environmental factors and farm structural and functional characteristics on the crop diversity-revenue stability relationship. Additionally factored in the relationship are the effects of cropping portfolios: statistical groupings of different crop species (n = 304) that characterize distinct farming areas (1340 municipalities). Findings support the insurance hypothesis and underscore the importance of crop diversification in the region. However, findings also show that irrigation plays an even stronger role than crop diversification in stabilizing farm revenues. Furthermore, some crop portfolios negatively impact revenue stability, including some portfolios with high crop diversity. In sum, a better understanding of farm contexts—contributing factors and cropping portfolios—is key to designing policies that help stabilize farm revenues through crop diversification. Full article

This manuscript focuses on the need for tailoring flood assessment products to decision making within the humanitarian sector. Decision-makers often struggle to extract all of the information contained in scientific products, either because they come from different fields of expertise or because they have different needs that are not captured in the results or the processing of the data. Here we define the key elements of a flood assessment product designed for the humanitarian sector. From a remote sensing perspective, in order to assess flooding, the measurement sampling properties, i.e., spatial resolution and temporal repeat, are key. We have therefore implemented a methodology through the processing and interpretation of the measurements from the Cyclone Global Navigation Satellite System (CYGNSS) mission. CYGNSS measurements are usually parametrized in various possible observables. Those observables are then linked to the surface characteristics, such as, in this case, the presence of inundation in the CYGNSS footprint. Our methodology includes the variability of the pixels in landscapes with infrastructure, rivers, agricultural fields, rural areas, and other elements characteristic of the agricultural-urban interface. We provide an original methodology that uses CYGNSS mission bistatic radar measurements and an artificial intelligence classification algorithm based on statistical properties of the land pixels through a k-means clustering strategy to detect and monitor flooding events, as well as to characterize the land surface prior to and post flooding events. The novel methodology to derive a flooding product is then evaluated towards the needs of the humanitarian sector by a cognizant link (a translator) between technologists or scientists and decision-makers. The inclusion of humanitarian needs into product development following the advice of a cognizant link is novel to the applications developed employing GNSS bistatic radar data. Full article

The traditional teaching model of landscape architecture education is teacher-centered classroom lectures, which cannot effectively satisfy students’ curiosity and stimulate their creative thinking and computational thinking skills, resulting in students’ low willingness to learn, inattentiveness, and lack of participation in discussions and interactions. This study attempts to combine the BOPPPS teaching structure and Design-Based Learning model to innovate the teaching design, construct the knowledge chain of landscape architecture design modeling and inspire the logic of thinking, with visual programming language, virtual reality parametric modeling and 3D printing hands-on activities while integrating sustainable development goals and related thematic issues to develop practical skills and problem-solving abilities. Through collecting students’ learning performance, examining the quality and effectiveness of teaching and learning, reflecting on the revised teaching content and methods and establishing a practical teaching plan for sustainable landscape architecture education. The results of the study show that the combination of innovative teaching and learning models with SDG-related thematic issues and collaborative group discussions with teaching activities helps to enhance students’ learning effectiveness and bring the learning performances of different learners closer together. In addition, the analysis of learning satisfaction shows that it enhances students’ interest and motivation in learning. Full article

The paper used technical parameters to investigate optimized solutions to protect the ecological environment and improve the microclimate adaptability among the traditional villages in Beijing. Shuiyu Village was used as a case study to analyze the coupling relationship between landscape patterns and the microclimate of traditional villages, with a focus on the ecological relationship between residents and the microclimate. This study also developed a climate index system, which includes computer numerical simulation and microclimate comprehensive analysis methods. The distinct types of landscape patterns were studied using the system. In addition, this paper studied the adaptive design mechanism in-depth, the form parameters of comfort evaluation controllability, and map expression technology of morphological parameters. The findings of this study include the optimized value of the environment based on landscape pattern and the map through the Rhino modeling platform. An interactive platform was developed, and a parametric-assisted optimization design process for traditional villages in the northern part of China was proposed. Moreover, this study concluded optimized strategies and technical guidelines for future planning of the rural areas in northern China with a goal to protect traditional villages and transform them into smart villages with microclimate adaptability. Full article