Hasil untuk "River protective works. Regulation. Flood control"

Kaihua Guo, Mingfu Guan, Jie Yin

ABSTRACT Flash flooding is amongst the most severe natural hazards, causing widespread socioeconomic impacts across both wet regions and drylands. In ungauged mountainous basins, effective risk warning based on hydrodynamic modelling is challenging due to sparse hydrological observations and complex terrain. Rainfall forecasts can enable timely alerts despite the computational demands of modelling, but their inherent uncertainties further complicate predictions. This study explores the potential of a Flash Flood Risk Index (FFRI), which integrates hydrodynamic simulation outputs with socio‐economic exposure and vulnerability indicators, to provide actionable early risk signal under data‐scarce conditions. The 2022 Datong flash flood in China is used as a case study. Grid‐based hydrodynamic simulations were conducted across varying key parameters and rainfall scenarios to discuss model uncertainty. Model performance was evaluated using UAV‐derived inundation extents, achieving high F1 scores (0.88–0.90), indicating reliable reproduction of flood extents. Simulated water depths and river discharges, however, exhibited substantial discrepancies, particularly in downstream convergence zones, which highlights the critical influence of parameter and rainfall uncertainty on hydrodynamic outputs. The FFRI proposed in the study mitigated these uncertainties, consistently identifying high‐risk areas, especially at the administrative (village) scale across all scenarios. These findings demonstrate that, in data‐limited basins, integrating hydrodynamic modelling with socio‐economic indicators is a practical way to provide actionable risk signal, supporting early‐warning and emergency response where traditional calibration and detailed observations are unavailable.

Amir H. Azimi

A new semianalytical model for the prediction of local scour profiles downstream from typical grade-control structures is proposed on the basis of the variation in bed shear stress and the sediment bed curvature concept. The proposed method was applied to a continuous boundary between the flow and sediment regions to predict the scour profile downstream of submerged sharp-crested weirs. By applying the momentum equation, the nappe flow over the weir was modeled as an oblique point force on the bed surface boundary, and the eroded profile was represented by a system of differential equations. The scour length and sediment resistance strength are the two unknowns in the shear stress and sediment bed curvature (SSC) differential equations. A series of laboratory experiments were carried out under clear water conditions to evaluate the accuracy and performance of the proposed model. The scour profile was calculated via prediction equations that are based on the known maximum scour depth, dmax, which was proposed in this study and in the literature. The effects of the submergence ratio and flow intensity on the maximum scour depth and scour profile were investigated, and a model was developed to predict the equilibrium scour depth. The prediction error associated with equations based on the equilibrium scour depth, dmax, resulted in a significant error in scour length prediction. Furthermore, the deviation between the measured and predicted geometrical characteristics was also correlated with predictions of dmax and scour length, L, as functions of flow intensity and submergence.

Deng Majok Chol, Jim W. Hall, Kevin G. Wheeler et al.

ABSTRACT The Sudd wetland in South Sudan extends over 90,000 km2. Large‐scale flood events in recent years (2019–2022) are said to have led to the displacement of an estimated 1.8 million people in total. However, these estimates are approximate and to date there has not been a systematic analysis of population exposure to flooding in the Sudd region. This study seeks to address this gap by using global flood modeling, satellite observations of flood extent, and global gridded population datasets to analyze population exposure. Recognizing the inevitable limitations of these datasets, we intersect all the available global flood mapping and population datasets. The results indicate that 0.8–2.9 million people are currently exposed to the 100‐year return period flood extent, depending on the flood model and population dataset used. Aggregated results of the model agreement intercomparison indicate that all five global models agree on key flood‐prone areas within and around the Sudd, which is further corroborated with satellite flood observations. Intercomparison of the population density among the four georeferenced population products demonstrates that WorldPop and GHSL‐Pop population distributions better represent the patterns of the Sudd rural settlements that are typically in forms of clusters. The uncertainty in exposure estimates is attributable to variations in both flood outlines and geospatial population estimates. These findings provide hitherto unavailable insights into flood exposure in South Sudan, to inform flood management decisions and disaster reduction responses in the Sudd region. This study demonstrates the global significance of model intercomparison as best practice for any flood exposure analysis to underpin policy and decision‐making in Africa and other data‐scarce regions.

Nimra Yousaf, Avidesh Seenath, Linda Speight

ABSTRACT Flood risk communication is a core component of flood risk management, yet persistent challenges limit its effectiveness in supporting public understanding, preparedness and adaptive behaviour. Here, we examine flood risk maps as communication tools at the interface of scientific modelling, visual design, and human risk perception. Using a narrative and scoping approach, we synthesise conceptual, theoretical and empirical literature, with particular attention to risk perception theory, framing and map design. We show that flood risk maps often fail to communicate effectively due to poor readability, technical language, inconsistent colour conventions and cognitive biases that shape interpretation and response. Although probabilistic flood maps have been developed to better represent spatial variability and uncertainty in flood risk, they are frequently misunderstood without appropriate framing and contextual support. Our review highlights the critical role of framing choices, communication channels and trust in information sources in shaping how flood risk information is interpreted and acted upon. We further show that participatory mapping can enhance local relevance, understanding and trust by incorporating lived experience, but its application is constrained by issues of scalability, institutional capacity and potential bias. We, therefore, argue that flood risk maps are most effective when embedded within broader, multi‐channel communication strategies.

Junzheng Liu, Jinliang Zhang, Zhe Huang et al.

The prediction of the flow resistance (usually quantified as the hydraulic roughness) of a movable flatbed is a key issue affecting the calculation accuracy of flood levels in river training projects. Bedload motion on a movable flatbed causes additional energy loss and increases hydraulic roughness. Several theoretical and empirical predictors for characterizing this phenomenon have been proposed, but the accuracy and physical basis of these models should be improved. In this study, the total energy dissipation rate is separated into two components: the energy dissipation rate due to grain drag and the additional energy dissipation rate due to bedload motion. Following the energy dissipation rate balance equation, a new predictor was proposed for movable flatbed flows. The water temperature was empirically coupled with the fluid viscosity and its associated physical variables. A new empirical relation between two dimensionless flow‒sediment combination variables was established to demarcate the various bedform transitions induced by the water temperature. The new predictor was compared with other predictors, and the prediction results were compared to the measured data. The error metric showed that the new predictor provided the highest accuracy, with ∼88.5% of the 826 data points falling within the ±30% error band. The new predictor suggested that the additional drag is nonlinearly proportional to the grain drag, and the scale factor between these two parameters is related to five flow‒sediment variables. In addition, the ability of the new predictor to quantify water temperature effects was examined. The predicted resistance exhibited three change modes with increasing water temperature, and the results suitably agreed with the measurements. The effect of the water temperature on the resistance of a movable flatbed is jointly controlled by the suspension number and roughness Reynolds number. This study provides an effective predictor that can be used by decision makers for modeling the hydraulic roughness of a movable flatbed.

Arash Majidi, Seyed Abbas Hosseini

ABSTRACT Flood management in urban areas requires innovative and adaptive strategies to address the growing challenges posed by climate change, land use transformations, and socio‐economic developments. This study provides a comprehensive analysis of the complex interactions within an urban area using integrated modeling approaches, offering critical insights into potential future challenges. These approaches incorporate climate, land use, hydrological, hydraulic, and damage models, complemented by an adaptation pathways map and recommendations for the most effective strategies, conducted in a flood‐prone urban area. The analysis projects an increase by 2080 of 3.39°C in temperature, 46% in precipitation, and 29% in flood‐related damages. The study underscores the substantial impact of land use changes on flood damages, highlighting the need for integrating land use planning into flood mitigation strategies. A rigorous evaluation identified a combination of measures—including concrete dyke construction, dredging, afforestation, and forest conservation—as effective actions for mitigating flood risks in the region near the Caspian Sea. Forest conservation and afforestation reduce peak flood discharge by 12.2% and 23.1%, respectively, for a 100‐year return period. Economic evaluations were performed for all adaptation pathways to assess their feasibility and cost‐effectiveness. Using the Analytic Hierarchy Process (AHP), the study determined that the optimal strategy is the simultaneous implementation of concrete dyke construction, dredging, and forest conservation. Additionally, six adaptation pathways were defined through the Dynamic Adaptive Policy Pathways (DAPP) method to provide a structured roadmap for implementing and adjusting flood management measures over time. These pathways aim to reduce potential future flood damage to negligible levels. Overall, this research highlights the importance of adopting integrated and adaptive strategies to address the multi‐faceted challenges posed by environmental changes, ensuring effective flood management amidst growing deep uncertainties.

Lea Dasallas, Barry Evans, Dion Todd et al.

ABSTRACT The increasing frequency of urban flooding due to climate‐induced extreme rainfall highlights the critical need for adaptive emergency preparedness. Maintaining public access to essential services during such events is critical, yet flood risks to the transport network can compromise public safety and mobility. This study employed a combined depth‐velocity stability function to assess the risks posed to individuals navigating floodwaters and evaluates accessibility to key service points using basic risk‐avoidance criterion. Transport network analysis compares the no‐flood, depth‐only and depth‐velocity risk scenarios. Analysis indicates that risk assessments solely based on flood depth significantly underestimate localised risk in urban environments. At the flood peak, high‐risk areas for vehicles and pedestrians are underestimated by 18.2% and 83.3%, respectively, while these increase to 36.4% and 240.0% for medium‐risk areas. Applying depth‐velocity thresholds determined the obstructed roads and inaccessible zones. Risk‐adjusted alternative routes were generated considering the obstructions, providing viable paths for the public to use during the flood peak. The integrated approach, combining flood modelling, stability functions and network analysis offers a framework that can significantly contribute to the improvement of risk resilience and transport management for flood‐prone cities.

Xiaoteng Pang, Jianwei Liu, Haihua Jing et al.

ABSTRACT Reliable long‐term daily and extreme streamflow simulation, essential for watershed sustainable development, remains challenge in changing environments due to the complementary limitations inherent in conventional physical‐driven and data‐driven models. This study proposed a physics‐guided machine learning (ML) approach that coupled SWAT with interpretable ML to enhance streamflow simulation accuracy for both daily and extreme streamflow whilst maintaining physical interpretability. This study systematically compared SWAT and three SWAT‐ML models (SWAT‐DT, SWAT‐LSBoost, and SWAT‐RF) to modify systematic model residuals, incorporating Shapley additive explanations (SHAP) to quantify feature contributions to streamflow simulations, and apply it to the Taoer River Basin (TRB), China. Results demonstrated that coupled models achieved daily streamflow simulation with KGE values consistently above 0.94 and PBIAS values for extreme streamflow within 17%. In comparison with the standalone SWAT, the coupled framework further cut runtime from nearly 200 h to a few minutes. Additionally, multi‐model comparisons revealed the superior performance of SWAT‐LSBoost in streamflow simulations, with SHAP further highlighting the predominant role of watershed hydrological process in governing coupled model. Thus, this approach enhanced modeling precision while strengthening the reliability and transparency of outputs, offering a scientifically robust foundation for decision‐making in long‐term water resources planning and flood‐drought disaster mitigation strategies.

Mojtaba Mehraein, Vahid Reza Zendehnam, Seyed Hossein Mohajeri et al.

The scour hole caused by 3-dimensional wall jets (3DWJ) is a serious problem downstream of dams and power stations. The current study utilized a newly created hybrid machine learning (ML) model to predict the changes in the dimensions of the primary scour hole over time caused by a 3DWJ. To fill the gap in the available knowledge, different experiments were done using uniform and non-uniform sediment. ML models and the linear regression were used to derive the prediction models. The results of the current study showed that the ML models have better accuracy than the linear regression model. Among all the developed hybrid ML models, the accuracy of the hybridized Categorical Boosting (CatBoost) with Gray Wolf Optimization algorithm (GWO-CB) yielded superior predictions. Sensitivity analysis confirmed the densimetric Froude number and the scouring time were important predictors. The effects of the expansion ratio on maximum scour depth and ridge height were the less important. However, the expansion ratio effects were larger than the effects of the tailwater depth ratio and sediment size ratio in the development of the scour hole in the streamwise and spanwise directions. The accuracy of GWO-CB models was considerably higher than the models previously applied in the literature. The proposed methodology revealed a robust and reliable model for predicting the scour hole dimensions.

Severin Beger, Sandra Hirche

Robustly compensating network constraints such as delays and packet dropouts in networked control systems is crucial for remotely controlling dynamical systems. This work proposes a novel prediction consistent method to cope with delays and packet losses as encountered in UDP-type communication systems. The augmented control system preserves all properties of the original model predictive control method under the network constraints. Furthermore, we propose to use linear tube MPC with the novel method and show that the system converges robustly to the origin under mild conditions. We illustrate this with simulation examples of a cart pole and a continuous stirred tank reactor.

Michael Hertneck, David Meister, Frank Allgöwer

The defining characteristic of event-based control is that feedback loops are only closed when indicated by a triggering condition that takes recent information about the system into account. This stands in contrast to periodic control where the feedback loop is closed periodically. Benefits of event-based control arise when sampling comes at a cost, which occurs, e.g., for Networked Control Systems or in other setups with resource constraints. A rapidly growing number of publications deals with event-based control. Nevertheless, some fundamental questions about event-based control are still unsolved. In this article, we provide an overview of current research trends in event-based control. We focus on results that aim for a better understanding of effects that occur in feedback loops with event-based control. Based on this summary, we identify important open directions for future research.

Seungtaek Kim, Jonghyup Lee, Kyoungseok Han et al.

To address the computational challenges of Model Predictive Control (MPC), recent research has studied using imitation learning to approximate MPC with a computationally efficient Deep Neural Network (DNN). However, this introduces a common issue in learning-based control, the simulation-to-reality (sim-to-real) gap. Inspired by Robust Tube MPC, this study proposes a new control framework that addresses this issue from a control perspective. The framework ensures the DNN operates in the same environment as the source domain, addressing the sim-to-real gap with great data collection efficiency. Moreover, an input refinement governor is introduced to address the DNN's inability to adapt to variations in model parameters, enabling the system to satisfy MPC constraints more robustly under parameter-changing conditions. The proposed framework was validated through two case studies: cart-pole control and vehicle collision avoidance control, which analyzed the principles of the proposed framework in detail and demonstrated its application to a vehicle control case.

Lukas Schüepp, Giulia De Pasquale, Florian Dörfler et al.

There is an increasing need for effective control of systems with complex dynamics, particularly through data-driven approaches. System Level Synthesis (SLS) has emerged as a powerful framework that facilitates the control of large-scale systems while accounting for model uncertainties. SLS approaches are currently limited to linear systems and time-varying linear control policies, thus limiting the class of achievable control strategies. We introduce a novel closed-loop parameterization for time-varying affine control policies, extending the SLS framework to a broader class of systems and policies. We show that the closed-loop behavior under affine policies can be equivalently characterized using past system trajectories, enabling a fully data-driven formulation. This parameterization seamlessly integrates affine policies into optimal control problems, allowing for a closed-loop formulation of general Model Predictive Control (MPC) problems. To the best of our knowledge, this is the first work to extend SLS to affine policies in both model-based and data-driven settings, enabling an equivalent formulation of MPC problems using closed-loop maps. We validate our approach through numerical experiments, demonstrating that our model-based and data-driven affine SLS formulations achieve performance on par with traditional model-based MPC.

Yeji Kim, Jeil Oh, Matthew Bartos

: Surface water quality is a priority in central Texas. There are several different entities within central Texas who require that stormwater to be treated prior to being discharged into streams, rivers, and lakes. Looking into various regulations throughout the area as well as plans for the future, the desired treatment strategies have varying efficiencies and applications. This presentation will cover applications and projects throughout the region and how municipalities are protecting source waters that lead to our water supply.

Xiaojun Huang, Jia He, Qifei Zhang et al.

Weakening wetland ecosystem services (ES) significantly hinders the achievement of the Sustainable Development Goals (SDGs). It is essential to combine multiple methods for evaluating wetland ecosystem services value (ESV) and to clearly depict the spatial distribution of ESVs. Based on the local conditions of the Pearl River Delta (PRD), this study proposed a monetary evaluation system for wetland ESV, developed a method for spatially allocating individual ESVs, and identified the dominant wetland functions across different cities and types of wetlands. The results yielded the following findings: (1) The wetland ESV system effectively identifies differences in ESV across cities and wetland types. The PRD's ESV increased by 23.29% between 2000 and 2020. (2) The new spatial allocation method analyzed individual ESVs to provide spatial references for improving wetland ESV. Fishery products and flood control and water storage are the two largest wetland functions in the PRD. All ESVs increased except for temperature regulation and water purification. (3) The identification and classification of dominant wetland functions provide insights into site-specific management of urban wetlands informed by ESV. These results provide a reference for assessing wetland ESV in other delta regions facing high population density and wetland degradation pressures. Understanding the role of wetland ESs in supporting the SDGs and how they interconnect and contribute to their achievement will be a key future research topic.

Sirui Zhong, Shenglian Guo, Yanfeng He et al.

The regulation of upstream cascade reservoirs has significantly altered the downstream hydrologic regime and should be taken into account in design flood estimation. The current flood regional composition (FRC) methods do not consider the unfavorable situations for reservoir flood control operation. In this paper, a novel framework, the most unfavorable flood regional composition (MUFRC) method, was proposed based on flood risk analysis to estimate design flood in the cascade reservoir operation period. The cascade reservoirs in the Yalong River basin were selected as a case study. The results indicated that (1) the proposed MUFRC method would allocate more flood volume to the downstream uncontrolled sub-basin, and the precise definition of flood disaster loss could have a significant impact on the MUFRC method for the rational estimation of design flood. (2) The 1000-year design flood peak, and 3-day and 7-day flood volumes at the outlet section estimated by the MUFRC method are 15,400 m3/s, 3.91, and 8.42 billion m3, respectively, which are higher than the values estimated by other FRC methods. (3) The flood control water level in the downstream reservoir can be adjusted for the reduction in design floods in the operation period, which can additionally generate 460 million kW·h (+1.82%) of hydropower during the flood season. A comparison study and sensitivity analysis further proved that the MUFRC method can rationally allocate flood volume while balancing the flood risk and comprehensive utilization benefits, which is worth further study and practical application.

Xinyu Fu, Rob Bell, Juliana Reu Junqueira et al.

Abstract Flooding is one of the most frequent and costliest natural hazards around the world. Traditionally, flood risk management has relied on building protective structures such as levees and dams to protect assets based on historical data (e.g., 1% AEP flood), which encourages development on floodplains, provides a potentially false sense of security to communities, particularly in the context of climate change, and increases residual flood risk (the risk remaining after implementing risk reduction measures). This article aims to contribute to the management of residual risk by drawing on empirical findings from a survey carried out with flood risk practitioners from the public and private sector in Aotearoa New Zealand. Findings indicate fundamental concerns relating to how to best manage residual flood risk, despite its long profile and integration in current policy and practice. Other issues revolve around the use of outdated information to guide decisions and the lack of regulatory power to restrict developments in flood‐prone areas protected by hard defense structures. Identified barriers to improving current practice include the lack of national guidance and support, financial resources, public awareness, and some technical constraints such as uncertainties in flood modeling, staff expertise, and data availability.

Lucy Davis, Tatiana Larionova, Dhairya Patel et al.

Abstract Around 45% of natural hazards reported worldwide are related to floods, and current indications show that exposure to floods and inherent losses will keep escalating. Historic centres are particularly vulnerable in this context due to the structural and material characteristics of the buildings and because they embrace social and cultural values that must be safeguarded. This article aims to contribute to this research area by presenting and discussing the application of an index‐based methodology specifically tailored to assess flood risk in historic urban centres. The historic city centre of Tomar, Portugal, an area that encompasses over 500 buildings and has a rich history of floods, is used here as a case study. Vulnerability data resulting from the application of the vulnerability assessment approach are then combined with flood hazard—that is, water velocity and depth obtained from flood peaks estimated for 20‐ and 100‐year periods of return—and used to identify the buildings at risk. Finally, a set of depth‐damage curves is derived and used here to carry out a cost–benefit analysis for different flood adaptation measures.

مهدی وفاخواه, مصطفی ذبیحی سیلابی, صدیقه مدرسی طباطبایی et al.

مقدمه بررسی وضعیت اقلیمی در حوزه‌­های آبخیز، نقش تعیین‌کننده‌ای در برنامه‌ریزی‌های مدیریت منابع آب دارد. این در حالی است که تغییرات دما و بارش اثر زیادی بر روی دبی رودخانه­‌ها، فرسایش خاک، نوسان سطح سفره‌های آب زیرزمینی و وقوع سیلاب­‌ها به‌جا می­‌گذارند. انجام پژوهش‌­های مرتبط با تغییر اقلیم، به‌منظور آمادگی هرچه بیشتر برای مقابله با هزینه‌های خسارت‌بار ناشی از این تغییر بسیار ضروری است. بررسی مطالعات انجام گرفته در کشور نشان می‌دهد، مقیاس مطالعه در اکثر موارد در سطح محلی است و بررسی روند دبی متوسط سالانه و بزرگی آن به‌ویژه در سطح کشور مطالعه نشده است. بنابراین، پژوهش حاضر با هدف تعیین روند دبی متوسط سالانه و بزرگی آن در سطح کشور انجام شد.مواد و روش‌­هادر این پژوهش، روند دبی­ متوسط سالانه در سطح کشور با لحاظ اثر سدها، با استفاده از روش­ من‌کندال و شیب‌سن انجام شده است. ابتدا، آمار تمامی ایستگاه‌های هیدرومتری موجود در زیرحوضه‌های شش حوزه آبخیز بزرگ کشور از شرکت مدیریت منابع آب کشور دریافت شد. در نهایت، 139 ایستگاه هیدرومتری با طول دوره آماری 17 تا 65 سال انتخاب شد. آمار این ایستگاه‌ها با اطلاعات موجود در ایستگاه‌های مجاور مقایسه و مقادیر مشکوک نیز کنترل شد. همگن‌ بودن داده­‌ها نیز با استفاده از آزمون توالی و بازسازی سال‌های فاقد آمار با استفاده از رگرسیون خطی از طریق استفاده از ایستگاهی با بالاترین ضریب همبستگی برای هر ایستگاه با آمار ناقص، انجام شد. در گام بعدی، بررسی روند دبی متوسط سالانه و بزرگی آن از آزمون‌های غیر پارامتریک من‌کندال و تخمین‌گر شیب‌سن در محیط نرم‌افزار XLSTAT انجام شد. پس از تعیین روند ایستگاه‌های مطالعاتی، نقشه­ توزیعی روند دبی جریان در سطح کشور مشتمل بر شش حوزه آبخیز بزرگ کشور در محیط نرم‌افزار ArcGIS10.2 تهیه شد.نتایج و بحثنتایج این پژوهش نشان داد، 14 ایستگاه تحت تأثیر سد بوده‌اند که با ‌این‌ وجود، در ایستگاه‌های بدون دخالت سد، تعداد 84 ایستگاه دارای روند کاهشی (60 درصد)، شش ایستگاه روند افزایشی (پنج درصد) و 35 ایستگاه (25 درصد) دیگر نیز در سطح اطمینان 95 درصد فاقد روند بودند. بررسی روند سری زمانی میانگین دبی سالانه در هر یک از شش حوزه آبخیز بزرگ کشور نیز نشان داد، 80 درصد از ایستگاه‌­های مطالعاتی در حوزه آبخیز خلیج فارس و دریای عمان دارای روند کاهشی بوده است، در حالی‌که به‌ترتیب 20، 10 و نه درصد از کل ایستگاه‌های مطالعاتی حوز­ه­‌های آبخیز دریای خزر، فلات مرکزی و خلیج ‌فارس و دریای عمان و نیز تمام ایستگاه­‌های حوزه آبخیز مرزی شرق (هامون) فاقد روند بوده‌‌اند. در این ‌بین، کل ایستگاه‌­های مطالعاتی در حوزه آبخیز دریاچه ارومیه و سرخس و 68 درصد از ایستگاه‌­های مطالعاتی در حوزه آبخیز دریای خزر از روند کاهشی برخوردار بوده‌اند.نتیجه‌گیرینتایج به‌دست ‌آمده از این پژوهش، نشان‌دهنده وجود روند کاهشی و معنی­دار در غالب ایستگاه‌های مطالعاتی (84 ایستگاه) بود. از همین ‌رو، روند کاهشی ایستگاه‌های هیدرومتری در سطح کشور را می‌توان به کاهش بارش، افزایش دما و ظهور خشکسالی‌های طاقت‌فرسایی ناشی از تغییرات اقلیمی و همچنین دخالت‌های انسانی از جمله افزایش بی‌رویه احداث سدها و نیز تغییر کاربری غیراصولی ارتباط داد. با ‌این‌حال، یکی از محدودیت‌های پژوهش حاضر، عدم لحاظ تغییرات اقلیمی و تغییرات کاربری اراضی و تعیین سهم هرکدام از عوامل مذکور در روند کاهشی و افزایشی ایستگاه‌های مذکور است. نتایج پژوهش حاضر می‌تواند برای برنامه‌ریزان و سیاست‌مداران عرصه آب به جهت مدیریت منابع آب بسیار مفید و حائز اهمیت باشد.

Ayoub Raji, Nicola Musiu, Alessandro Toschi et al.

In this paper, we present a novel formulation to model the effects of a locked differential on the lateral dynamics of an autonomous open-wheel racecar. The model is used in a Model Predictive Controller in which we included a micro-steps discretization approach to accurately linearize the dynamics and produce a prediction suitable for real-time implementation. The stability analysis of the model is presented, as well as a brief description of the overall planning and control scheme which includes an offline trajectory generation pipeline, an online local speed profile planner, and a low-level longitudinal controller. An improvement of the lateral path tracking is demonstrated in preliminary experimental results that have been produced on a Dallara AV-21 during the first Indy Autonomous Challenge event on the Monza F1 racetrack. Final adjustments and tuning have been performed in a high-fidelity simulator demonstrating the effectiveness of the solution when performing close to the tire limits.