Hasil untuk "River, lake, and water-supply engineering (General)"

Ioannis Diamantis

Atmospheric Rivers (ARs) are filamentary moisture pathways responsible for a large fraction of extreme precipitation and often occur as interacting filament bundles within the same synoptic regime. Existing diagnostics typically analyze ARs in isolation, despite the frequent coexistence and interaction of multiple filaments. We introduce a topological framework for AR analysis based on framed braids and framed braidoids, which encodes both the geometric interaction of AR centroids and the internal evolution of moisture transport. In this approach, AR filaments are represented as strands whose time-ordered crossings form braid words, while moisture-based framing captures internal intensification or weakening along each filament. Applying this framework to reanalysis-derived Atmospheric River track data, we construct braid and framed braid representations over sliding time windows and analyze a strongly interacting multi-filament AR episode in the North Pacific. The results show that braid-based indicators capture structural reorganizations and moisture intensification episodes that are not apparent from centroid geometry or IVT magnitude alone, offering a complementary structural perspective on atmospheric moisture transport.

Junjie Shi, Weisong Sun, Zhenpeng Chen et al.

The rapid development of large language models is transforming software development. Beyond serving as code auto-completion tools in integrated development environments, large language models increasingly function as foundation models within coding agents in vibe-coding scenarios. In such settings, prompts play a central role in agent-based intelligent software development, as they not only guide the behavior of large language models but also serve as carriers of user requirements. Under the dominant conversational paradigm, prompts are typically divided into system prompts and user prompts. System prompts provide high-level instructions to steer model behavior and establish conversational context, while user prompts represent inputs and requirements provided by human users. Despite their importance, designing effective prompts remains challenging, as it requires expertise in both prompt engineering and software engineering, particularly requirements engineering. To reduce the burden of manual prompt construction, numerous automated prompt engineering methods have been proposed. However, most existing approaches neglect the methodological principles of requirements engineering, limiting their ability to generate artifacts that conform to formal requirement specifications in realistic software development scenarios. To address this gap, we propose REprompt, a multi-agent prompt optimization framework guided by requirements engineering. Experiment results demonstrate that REprompt effectively optimizes both system and user prompts by grounding prompt generation in requirements engineering principles.

SHI Rongqing, HUANG Lingmei, LI Jia et al.

To identify flood-prone areas in the Daqing River Basin and classify flood risk levels, the Spearman's rank correlation coefficient and the random forest method were employed to analyze the correlation and importance between flood loss rates and influencing factors. Based on the most significant indicator, a flood loss rate function was constructed, incorporating four key factors: precipitation, flood control and disaster mitigation capacity, socio-economic development, and natural resources. By using this function, flood loss under five shared socioeconomic pathways (SSPs) from 2030 to 2050 was estimated. The results indicate that the flood loss rate across provinces and cities is generally positively correlated with precipitation factors but negatively correlated with flood control and disaster mitigation capacity, socio-economic development, and natural resources. The multiple regression function effectively captures the variation pattern of flood loss rates, with a coefficient of determination (<italic>R</italic>²) ≥ 0.89 and a root mean square error (RMSE) ≤ 0.047 3. Under the rainfall scenarios of 1996 and 2012, future economic flood losses are projected to increase significantly by 392%~452% at maximum, while the number of affected people is expected to decrease, with a minimum reduction of 22%~35%.

T. Moustapha Mai, C. Azzaro-Pantel, M. Chin Choi et al.

This study investigates the potential of hydrogen as a sustainable energy carrier for mobility applications in island territories, which are traditionally dependent on fossil fuel imports. Green hydrogen is identified as a key component of the energy transition. A Mixed Integer Linear Programming (MILP) model with a multi-period, multi-objective framework is used to optimize the hydrogen supply chain based on system costs, greenhouse gas (GHG) emissions, and a risk index. The model incorporates critical island-specific factors such as water resource availability, renewable energy sources, tourism flow, and geographic constraints. A multi-criteria decision making tool based on a modified version of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) aids the identification of optimal solutions. Results suggest a decentralized Hydrogen Supply Chains (HSC) structure with minimized transport. The levelized cost of hydrogen (LCOH) is estimated at 6.54 ___/kg, and GHG emissions range from 1.32 to 1.75 kgCO 2 e/kg H 2. This study highlights the impact of tourism on energy demand and the crucial role of water resources, offering a novel approach to optimizing island-specific HSC.

Michael Scheutzow, Michael Grinfeld

We consider the deterministic and stochastic versions of a first order non-autonomous differential equation which allows us to discuss the persistence of rivers ("fleuves") under noise.

Hasan Rezaei, Mohamad Motamedi Rad

Introduction Increasing the efficiency of water consumption and water management is necessary to meet the water needs of agricultural plants which need to consider the variables affecting water consumption, including water needs and the amount of evaporation and transpiration. In this regard, evaporation and transpiration are important indicators in the process of plant growth and their amount is considered equal to the water requirement of the plant. On the other hand, climate change can affect water demand by changing the expected patterns for the average weather condition in a long term in a specific region or for the entire global climate. In the present study, the phenological stages of seedless barberry tree were determined based on field observations at Ghaen synoptic meteorological station. The seedless barberry tree is one of the commercial cultivars in Iran. In this research, the effect of climate change on the water requirement of barberry cultivation has been evaluated based on RCP scenarios in the near and far future. Materials and Methods In the field part, in order to identify the occurrence time of the phenology stages and temperature thresholds, a series of visits and daily and weekly notes were made in the field in the growing season of the barberry tree. For this purpose, a private and fertile commercial orchard with suitable cultivated area of ​​seedless barberry trees was selected. The studied garden group with three hectares of cultivated area in Qain city was identified as one of the most fertile gardens in the region. This private garden is located in Qain city, at the position of 33 degrees and 43 minutes of north latitude and 59 degrees and 10 minutes of east longitude and a height of 1432 meters above sea level. In this study, the phenology stages of seedless barberry tree as one of the commercial cultivars of Iran were determined. The BBCH coding system was used to record the phenology stages (Enriquez‐Hidalgo et al., 2020). This scale has a 100-part table with codes from 0 to 99 and is designed for different phases (Feldmann and Rutikanga, 2021). It was used in the synoptic meteorological station of Qain city during one year from the beginning of germination to the end of the dormant period. In fact, the codes of the phenology stages were observed and recorded in the field.After determining the phenological stages of barren barberry trees, the water requirement of the selected tree species has been calculated. In the next step, to determine the water requirement, the reference evaporation and transpiration rate must be multiplied by the plant coefficient. For this purpose, the available data including hours of sunshine, average temperature during the growing season, average rainfall, minimum temperature, maximum temperature, evaporation, and transpiration obtained from the National Meteorological Organization for 18 valid meteorological stations from 1987 to 2017 on hourly and daily time scales were used to predict the climatic condition. Toward this, the climatic condition of the near future (2059-2030) and the far future (2089-2060) has been predicted considering pessimistic (RCP8.5), and optimistic (RCP4.5) scenarios. Results and Discussion The results showed that barberry needs six phenological stages to complete the growth period from early April to late November. Also, the amount of water requirement for barberry treesin the base period (1987-2017) on a daily basis in the eastern region under study is more than in the west and northwest of the region. The water requirement in the northwest and west parts is more than in the east of the region under study, which is the reason for the increase in the length of the barberry phenology stage in the region has been mentioned. The results of climate change analysis showed that the daily water requirement of barberry (2030-2059) based on the RCP8.5 model during the growing season varies between 4.5-5.8 mm per day and the total water requirement is 990-1260 mm. According to the RCP4.5 model, the daily water requirement of barberry varies between 5.6-5.8 mm per day and the total water requirement is 1290-990 mm. The daily water requirement of barberry according to the RCP4.5 model (2060-2089) varies between 4-5 mm per day and the total water requirement is 960-1150 mm. Also, the daily water requirement of barberry according to the RCP8.5 model varied between 4.5-8.2 mm per day. The total water requirement of the barberry tree is 950-1300 mm. ConclusionThe present study was conducted with the aim of measuring the phenology stages of the seedless barberry tree and the water requirement of the barberry tree according to the conditions of climate change in the areas prone to its cultivation in Iran. The results showed that the barberry tree needs six phenology stages to complete its growth cycle. The growth period according to climatic conditions and topography lasts from early April to late November. The results of estimating the water requirement in the base period showed that the cities of Kerman, Yazd, Qain, Birjand, Zahedan and Torbat Heydarieh need the most water during the growth stage (1330-1240 mm per day) and the lowest water requirement of the barberry tree in the north It is in the west and west of the country, but in the future, the amount of water needed by the barberry tree in the northwest and west is more than the center and east of the study area, which is the reason for the earlier completion of the phenology stages in the center and east of the country, for this reason, these areas are among the unsuitable areas. It is considered cultivation. Since the annual rainfall changes from year to year; Therefore, the irrigation project cannot be planned only based on one year's information, so long-term records are needed to calculate the effective rainfall based on the probability of occurrence. Cultivation of barberry is very desirable in terms of irrigation for dry and semi-arid areas where farmers are facing water shortage. Considering that water is the main and essential requirement of any product; Therefore, it is essential to estimate the water requirement of each plant.

Tao Chen, Miqing Li

Configurable software systems can be tuned for better performance. Leveraging on some Pareto optimizers, recent work has shifted from tuning for a single, time-related performance objective to two intrinsically different objectives that assess distinct performance aspects of the system, each with varying aspirations. Before we design better optimizers, a crucial engineering decision to make therein is how to handle the performance requirements with clear aspirations in the tuning process. For this, the community takes two alternative optimization models: either quantifying and incorporating the aspirations into the search objectives that guide the tuning, or not considering the aspirations during the search but purely using them in the later decision-making process only. However, despite being a crucial decision that determines how an optimizer can be designed and tailored, there is a rather limited understanding of which optimization model should be chosen under what particular circumstance, and why. In this paper, we seek to close this gap. Firstly, we do that through a review of over 426 papers in the literature and 14 real-world requirements datasets. Drawing on these, we then conduct a comprehensive empirical study that covers 15 combinations of the state-of-the-art performance requirement patterns, four types of aspiration space, three Pareto optimizers, and eight real-world systems/environments, leading to 1,296 cases of investigation. We found that (1) the realism of aspirations is the key factor that determines whether they should be used to guide the tuning; (2) the given patterns and the position of the realistic aspirations in the objective landscape are less important for the choice, but they do matter to the extents of improvement; (3) the available tuning budget can also influence the choice for unrealistic aspirations but it is insignificant under realistic ones.

FANG Mingyi, SHI Haoran, HAILAI Yibo et al.

In view of the frequent tropical storm surge in Nandu River Estuary in recent years,the increasing population in Haikou City each year,severe pollution emissions,and increasing upstream water use year by year,this paper studies the pollutant distribution in Nandu River Estuary under the storm surge and reduction of upstream water inflow on the basis of the hydrodynamic-water quality model.In addition,the changes of pollutants under different environments are analyzed.The results demonstrate that pollutants are mainly distributed on the left bank of the river and are mainly in striped shape due to the topography of the river.When the upstream flow is reduced by 20%,the effect of the tidal current is more significant,and pollutants are greatly affected by convection;the pollution zone becomes narrower,and the diffusion distance is the farthest.When the downstream tidal level is raised by 0.4 m,the interaction between the upstream inflow and tidal current is obvious;the flow rate decreases,and the pollutant retention is serious.In this case,pollutants mainly diffuse to the upstream by diffusion.Therefore,the upstream water resources should be effectively regulated and used,and the water surrounding the sewage outlet should be monitored with more efforts to provide a reference for the water environment management of the estuary section of Haikou City in the future.

Han Zhang, Jungang Luo, Jingyan Wu et al.

Flash floods show strong regional differentiation in spatial–temporal distribution and driving forces, thereby hindering their effective prevention and control. This study analyzed the spatiotemporal characteristics of flash floods in Shaanxi Province, China, differentiated among the northern Shaanxi (NS), Guanzhong (GZ), and southern Shaanxi (SS) regions based on the Mann–Kendall, Theil–Sen Median, and standard deviation ellipse methods. The main factors driving disasters and their interactions in each region were then identified within the three categories of precipitation factor (PPF), surface environment factor, and human activity factor (HAF) based on a geographical detector. Finally, the differences in flash flood characteristics among the NS, GZ, and SS regions were analyzed. The results showed that flash floods in Shaanxi Province are greatly affected by the PPF and the HAF, although the spatial–temporal characteristics and disaster-causing factors were significantly different in each region. The regions were ranked according to the number and growth trends of flash floods as follows: SS > GZ > NS. Furthermore, flash floods were affected by multiple factors, with the interaction between factors acting as a driving force of flash floods. The results of this study can provide a reference for the management of flash floods under regional differentiation. HIGHLIGHTS Taking Shaanxi Province as a typical region of regional differentiation, the temporal and spatial characteristics of flash floods are evaluated.; The main disaster-causing factors and their interaction of flash floods in each region are discussed.; Results are helpful to put forward the flash flood prevention and control measures according to local conditions in the same administrative region and reduce the potential risks.;

Tommaso Tedeschi, Diego Ciangottini, Marco Baioletti et al.

The continuous growth of data production in almost all scientific areas raises new problems in data access and management, especially in a scenario where the end-users, as well as the resources that they can access, are worldwide distributed. This work is focused on the data caching management in a Data Lake infrastructure in the context of the High Energy Physics field. We are proposing an autonomous method, based on Reinforcement Learning techniques, to improve the user experience and to contain the maintenance costs of the infrastructure.

LI Dongqin, HUANG Ya, YI Ling et al.

Based on the daily data of precipitation and runoff over the Longtan reservoir from 1960 to 2015,this paper selects four weight assignment methods to calculate the feature vector of flood season stages based on Fisher optimal dissection method,and analyzes the number of optimal flood season stages of the reservoir.The results show that:When ten days are used as the unit of flood season staging,the weight coefficients have little influence on the result of flood season staging.The flood season staging results of the Longtan reservoir based on the Fisher optimal dissection method can better reflect the characteristics of rainstorms and flood in the flood season of the basin,and the optimal number of flood season stages is five.According to the optimal staging results,the flood season in the Longtan reservoir is divided into pre-flood transition period (April 1~April 30),pre-flood period (May 1~May 20),main flood period (May 21~July 20),post-flood period (July 21~September 10) and post-flood transition period (September 11~October 31).

Sabah Al-Fedaghi, Mahdi Modhaffar

Models are fundamentally crucial to many scientific fields, including software engineering, systems engineering, enterprise modeling, and business modeling. This paper focuses on diagrammatic conceptual modeling, as opposed to mathematical or computational models, wherein a conceptual model is a translation of reality processes into an abstract mechanism that has similar structure and parallel events of the external processes. Although various modeling approaches exist, including UML (Unified Modeling Language) in software engineering and its dialect, SysML (System Modeling Language), in systems engineering, several difficulties arise in such models, including the problem of model multiplicity that is related to the lack an integrated view of structure and behavior. This paper generalizes conceptual modeling to be applied in organizations at large. According to authorities, the so-called organization theory portrays organizations as machine-like systems. As a machine, an organization coordinates its parts to transform inputs into outputs. Therefore, we synthesize the notion of an organization as a machine and apply a new modeling methodology called thinging machine (TM) to real engineering operations. The results show the viability of the TM methodology serving as a foundation for high-level modelling of systems.

Armin Moin

This doctoral dissertation proposes a novel approach to enhance the development of smart services for the Internet of Things (IoT) and smart Cyber-Physical Systems (CPS). The proposed approach offers abstraction and automation to the software engineering processes, as well as the Data Analytics (DA) and Machine Learning (ML) practices. This is realized in an integrated and seamless manner. We implement and validate the proposed approach by extending an open source modeling tool, called ThingML. ThingML is a domain-specific language and modeling tool with code generation for the IoT/CPS domain. Neither ThingML nor any other IoT/CPS modeling tool supports DA/ML at the modeling level. Therefore, as the primary contribution of the doctoral dissertation, we add the necessary syntax and semantics concerning DA/ML methods and techniques to the modeling language of ThingML. Moreover, we support the APIs of several ML libraries and frameworks for the automated generation of the source code of the target software in Python and Java. Our approach enables platform-independent, as well as platform-specific models. Further, we assist in carrying out semiautomated DA/ML tasks by offering Automated ML (AutoML), in the background (in expert mode), and through model-checking constraints and hints at design-time. Finally, we consider three use case scenarios from the domains of network security, smart energy systems and energy exchange markets.

Konstantina Dritsa, Thodoris Sotiropoulos, Haris Skarpetis et al.

How different are search engines? The search engine wars are a favorite topic of on-line analysts, as two of the biggest companies in the world, Google and Microsoft, battle for prevalence of the web search space. Differences in search engine popularity can be explained by their effectiveness or other factors, such as familiarity with the most popular first engine, peer imitation, or force of habit. In this work we present a thorough analysis of the affinity of the two major search engines, Google and Bing, along with DuckDuckGo, which goes to great lengths to emphasize its privacy-friendly credentials. To do so, we collected search results using a comprehensive set of 300 unique queries for two time periods in 2016 and 2019, and developed a new similarity metric that leverages both the content and the ranking of search responses. We evaluated the characteristics of the metric against other metrics and approaches that have been proposed in the literature, and used it to (1) investigate the similarities of search engine results, (2) the evolution of their affinity over time, (3) what aspects of the results influence similarity, and (4) how the metric differs over different kinds of search services. We found that Google stands apart, but Bing and DuckDuckGo are largely indistinguishable from each other.

Christie L. Alappat, Johannes Hofmann, Georg Hager et al.

Hardware platforms in high performance computing are constantly getting more complex to handle even when considering multicore CPUs alone. Numerous features and configuration options in the hardware and the software environment that are relevant for performance are not even known to most application users or developers. Microbenchmarks, i.e., simple codes that fathom a particular aspect of the hardware, can help to shed light on such issues, but only if they are well understood and if the results can be reconciled with known facts or performance models. The insight gained from microbenchmarks may then be applied to real applications for performance analysis or optimization. In this paper we investigate two modern Intel x86 server CPU architectures in depth: Broadwell EP and Cascade Lake SP. We highlight relevant hardware configuration settings that can have a decisive impact on code performance and show how to properly measure on-chip and off-chip data transfer bandwidths. The new victim L3 cache of Cascade Lake and its advanced replacement policy receive due attention. Finally we use DGEMM, sparse matrix-vector multiplication, and the HPCG benchmark to make a connection to relevant application scenarios.

Nicolas Anquetil, Anne Etien, Mahugnon H. Houekpetodji et al.

Advanced reverse engineering tools are required to cope with the complexity of software systems and the specific requirements of numerous different tasks (re-architecturing, migration, evolution). Consequently, reverse engineering tools should adapt to a wide range of situations. Yet, because they require a large infrastructure investment, being able to reuse these tools is key. Moose is a reverse engineering environment answering these requirements. While Moose started as a research project 20 years ago, it is also used in industrial projects, exposing itself to all these difficulties. In this paper we present ModMoose, the new version of Moose. ModMoose revolves around a new meta-model, modular and extensible; a new toolset of generic tools (query module, visualization engine, ...); and an open architecture supporting the synchronization and interaction of tools per task. With ModMoose, tool developers can develop specific meta-models by reusing existing elementary concepts, and dedicated reverse engineering tools that can interact with the existing ones.

PILAR CAROLINA VILLAR, RICARDO HIRATA

O artigo 45 da Lei 11.445/2007 trouxe um requisito externo aos previstos na legislação de águas para a outorga de poços, pois proibe a existência de soluções alternativas de abastecimento em áreas dotadas de rede pública de água. Com base nesse conflito, o objetivo do trabalho é avaliar como os tribunais interpretam a compatibilidade do artigo 45 com a presença de poços em áreas dotadas ou não de rede pública. A metodologia consistiu na análise da jurisprudência dos Tribunais de Justiça Estaduais e do Superior Tribunal de Justiça. A interpretação dos Tribunais foi no sentido de proibir os poços quando há rede de água. Se inexistente, os poços sem outorga podem ser regularizados, contudo há divergência nas condições em que isso seria feito, algumas decisões mantêm a lacração até a regularização, outras permitem o funcionamento do poço durante esse processo. A obrigatoriedade da conexão das instalações hidráulicas prediais na rede pública tem justificativas. Porém não se pode ignorar o papel das soluções alternativas na melhora da resiliência do sistema de abastecimento público, o qual apresenta graves deficiências. Há que se fomentar um debate de como conduzir um modelo de coexistência da rede pública e das soluções alternativas que estimule um uso mais eficiente, uma melhora na estrutura da rede e o fim da clandestinidade dos poços que se beneficiam de um recurso público e não dão qualquer contrapartida socioambiental, seja porque não podem se regularizar ou porque não querem.

Arka Daw, R. Quinn Thomas, Cayelan C. Carey et al.

To simultaneously address the rising need of expressing uncertainties in deep learning models along with producing model outputs which are consistent with the known scientific knowledge, we propose a novel physics-guided architecture (PGA) of neural networks in the context of lake temperature modeling where the physical constraints are hard coded in the neural network architecture. This allows us to integrate such models with state of the art uncertainty estimation approaches such as Monte Carlo (MC) Dropout without sacrificing the physical consistency of our results. We demonstrate the effectiveness of our approach in ensuring better generalizability as well as physical consistency in MC estimates over data collected from Lake Mendota in Wisconsin and Falling Creek Reservoir in Virginia, even with limited training data. We further show that our MC estimates correctly match the distribution of ground-truth observations, thus making the PGA paradigm amenable to physically grounded uncertainty quantification.

Ignacio J. General

MaxCal is a variational principle that can be used to infer distributions of paths in the phase space of dynamical systems. It has been successfully applied to different areas of classical physics, in particular statistical mechanics in and out of equilibrium. In this work, guided by the analogy of the formalism of MaxCal with that of the path integral formulation of quantum mechanics, we explore the extension of its applications to the realm of quantum physics, and show how the Lagrangians of both relativistic and non-relativistic quantum fields can be built from MaxCal, with a suitable set of constraints. Related, the details of the constraints allow us to find a new interpretation of the concept of inertia.

Aqdas Malik, Aditya Johri, Rajat Handa et al.

Each year, significant investment of time and resources is made to improve diversity within engineering across a range of federal and state agencies, private/not-for-profit organizations, and foundations. In spite of decades of investments, efforts have not yielded desired returns - participation by minorities continues to lag at a time when STEM workforce requirements are increasing. In recent years a new stream of data has emerged - online social networks, including Twitter, Facebook, and Instagram - that act as a key sensor of social behavior and attitudes of the public. Almost 87% of the American population now participates in some form of social media activity. Consequently, social networking sites have become powerful indicators of social action and social media data has shown significant promise for studying many issues including public health communication, political campaign, humanitarian crisis, and, activism. We argue that social media data can likewise be leveraged to better understand and improve engineering diversity. As a case study to illustrate the viability of the approach, we present findings from a campaign, #ILookLikeAnEngineer (using Twitter data - 19,354 original tweets and 29,529 retweets), aimed at increasing gender diversity in the engineering workplace. The campaign provided a continuous momentum to the overall effort to increase diversity and novel ways of connecting with relevant audience. Our analysis demonstrates that diversity initiatives related to STEM attract voices from various entities including individuals, large corporations, media outlets, and community interest groups.