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

Kingsley Safo, Norbert Onen Rubangakene, Hussien Noby et al.

The steel industry produces many byproducts, requiring extensive land for storage and causing significant environmental contamination. Industrial effluents discharged into water bodies negatively impact both aquatic ecosystems and human health. To solve this problem, this study synthesized a composite of titanium dioxide (TiO2) and steel slag nanocomposites (SSNC) at a 1:2 mass ratio to create a robust photocatalyst for the treatment of synthetic wastewater. The efficacy of this catalyst in degrading various dye pollutants, including methylene blue (MB), was tested under simulated solar light conditions. Comprehensive analyses were conducted to assess the physical and chemical characteristics, crystalline structure, energy gap, and point of zero charge of the composite. The TiO2-SSNC composite catalyst exhibited excellent stability, with a point of zero charge at 8.342 and an energy gap of 2.4 eV. The degradation process conformed to pseudo-first-order kinetics. Optimization of operational parameters was achieved through the response surface methodology. Reusability tests demonstrated that the TiO2-SSNC composite catalyst effectively degraded up to 93.41% of MB in the suspended mode and 92.03% in the coated mode after five cycles. Additionally, the degradation efficiencies for various dyes were significant, highlighting the potential of the composite for broad applications in industrial wastewater treatment. This study also explored the degradation mechanisms and identified byproducts, establishing a pathway for contaminant breakdown. The cost-benefit analysis revealed a total cost of 0.842 8 USD per cubic meter for each treatment activity, indicating low operational and production costs. These findings underscore the promise of the TiO2-SSNC composite as a cost-effective and efficient alternative for wastewater purification.

Bianca Trinkenreich, Fabio Calefato, Geir Hanssen et al.

The adoption of Large Language Models (LLMs) is not only transforming software engineering (SE) practice but is also poised to fundamentally disrupt how research is conducted in the field. While perspectives on this transformation range from viewing LLMs as mere productivity tools to considering them revolutionary forces, we argue that the SE research community must proactively engage with and shape the integration of LLMs into research practices, emphasizing human agency in this transformation. As LLMs rapidly become integral to SE research - both as tools that support investigations and as subjects of study - a human-centric perspective is essential. Ensuring human oversight and interpretability is necessary for upholding scientific rigor, fostering ethical responsibility, and driving advancements in the field. Drawing from discussions at the 2nd Copenhagen Symposium on Human-Centered AI in SE, this position paper employs McLuhan's Tetrad of Media Laws to analyze the impact of LLMs on SE research. Through this theoretical lens, we examine how LLMs enhance research capabilities through accelerated ideation and automated processes, make some traditional research practices obsolete, retrieve valuable aspects of historical research approaches, and risk reversal effects when taken to extremes. Our analysis reveals opportunities for innovation and potential pitfalls that require careful consideration. We conclude with a call to action for the SE research community to proactively harness the benefits of LLMs while developing frameworks and guidelines to mitigate their risks, to ensure continued rigor and impact of research in an AI-augmented future.

Morgan M. Fong, Hilary Egan, Marc Day et al.

Background: Harnessing advanced computing for scientific discovery and technological innovation demands scientists and engineers well-versed in both domain science and computational science and engineering (CSE). However, few universities provide access to both integrated domain science/CSE cross-training and Top-500 High-Performance Computing (HPC) facilities. National laboratories offer internship opportunities capable of developing these skills. Purpose: This student presents an evaluation of federally-funded postgraduate internship outcomes at a national laboratory. This study seeks to answer three questions: 1) What computational skills, research skills, and professional skills do students improve through internships at the selected national laboratory. 2) Do students gain knowledge in domain science topics through their internships. 3) Do students' career interests change after these internships? Design/Method: We developed a survey and collected responses from past participants of five federally-funded internship programs and compare participant ratings of their prior experience to their internship experience. Findings: Our results indicate that participants improve CSE skills and domain science knowledge, and are more interested in working at national labs. Participants go on to degree programs and positions in relevant domain science topics after their internships. Conclusions: We show that national laboratory internships are an opportunity for students to build CSE skills that may not be available at all institutions. We also show a growth in domain science skills during their internships through direct exposure to research topics. The survey instrument and approach used may be adapted to other studies to measure the impact of postgraduate internships in multiple disciplines and internship settings.

Yihao Hu, Jin Wang, Sajjadur Rahman

Data discovery from data lakes is an essential application in modern data science. While many previous studies focused on improving the efficiency and effectiveness of data discovery, little attention has been paid to the usability of such applications. In particular, exploring data discovery results can be cumbersome due to the cognitive load involved in understanding raw tabular results and identifying insights to draw conclusions. To address this challenge, we introduce a new problem -- visualization recommendation for data discovery over data lakes -- which aims at automatically identifying visualizations that highlight relevant or desired trends in the results returned by data discovery engines. We propose LakeVisage, an end-to-end framework as the first solution to this problem. Given a data lake, a data discovery engine, and a user-specified query table, LakeVisage intelligently explores the space of visualizations and recommends the most useful and ``interesting'' visualization plans. To this end, we developed (i) approaches to smartly construct the candidate visualization plans from the results of the data discovery engine and (ii) effective pruning strategies to filter out less interesting plans so as to accelerate the visual analysis. Experimental results on real data lakes show that our proposed techniques can lead to an order of magnitude speedup in visualization recommendation. We also conduct a comprehensive user study to demonstrate that LakeVisage offers convenience to users in real data analysis applications by enabling them seamlessly get started with the tasks and performing explorations flexibly.

YIN Ming, CHEN Xing, XIONG Kun

Deformation control, seismic safety, and durability present significant challenges for 250 m ultra-high concrete face rockfill dams (CFRD) in cold and seismically active regions. These challenges necessitate an elevated standard for waterstop design. Using the 233.5 m high Yulongkashi CFRD as a case study, this paper quantitatively proposes a joint deformation control standard based on the results of 3D static and dynamic finite element analysis, in conjunction with relevant engineering experiences. In addition, a tailored waterstop size design is carried out for different joints. Considering the unique characteristics of the project and dam deformation, factors such as varying stress distribution across the dam face, the impact of freezing in fluctuating water levels, prevention of extrusion failure, and interplate constraints are taken into account. Measures such as multi-channel redundant design, polyurea coating for covering plates, incorporation of seaming materials in vertical joints, and localized reinforcement of compressive joints are employed in the customized design of waterstops for perimeter joints, vertical joints, horizontal joints of the wave wall, and settlement joints. These findings serve as valuable references for similar projects.

Javanshir AziziMobaser, Erfan Faraji Amogein

IntroductionIrrigation planning is one of the management strategies, which is based on determining the exact water requirement. The lysimetric method is the most accurate method of determining the water requirement of the plant, but due to the high cost and the need for high technical knowledge, it cannot be used anywhere. The basis for determining the water requirement in the Ardabil Plain is the use of NETWAT software output information, which is known as the National Water Document of Iran. This software calculates the water requirement using the Penman-Monteith FAO model. The output of this software due to the need to update climate information, not introducing the exact range of plains, ignoring sub-climates in some plains and catchments (including Ardabil Plain), and not considering some important crops in the plain (lack of potato water requirement in Ardabil Plain) and the creation of new databases in recent years, should be reconsidered. Material and MethodsThis study in Ardabil Plain and water requirement of the dominant crop pattern including wheat, barley, potato, alfalfa, and bean crops was calculated by the Penman-Monteith method and CROPWAT software. To calculate the net irrigation requirement, first, the evapotranspiration potential of the plain was obtained using climatic information from three stations Ardabil, Abi Biglou, and Namin. Then, the effective rainfall of the plain was extracted by the information from Ardabil, Abybeigloo, Namin, Koozeh Topraghi, Gilande, and Samian rain gauge stations. Required information on plain soil was prepared using 22 points in the plain. In the last step of the information preparation phase, the characteristics of the cropping pattern plants were defined using field measurements, local experiments, and FAO publication No. 56. The cropping pattern (91.4% of the cultivated area of Ardabil Plain) included wheat, barley, potatoes, alfalfa, and beans, which according to the five-year statistics ending in 2021, the cultivated area of these crops was 18,300 (32.6%), 10300 (19.4%), 15700 (28%), 5200 (9.2%) and 1200 (2.2%) hectares. After preparing the case information, the water requirement was calculated for each of the wheat, barley, potato, alfalfa and bean products in each of the soil sampling points in 10-day periods during the growing season. Based on the point information obtained, a zoning map of net irrigation needs in the Ardabil Plain was prepared. Results and DiscussionBased on the obtained point information, a zoning map of net irrigation needs in the Ardabil Plain was prepared. The results showed that the zoning of the net need for irrigation divides the Ardabil Plain into three separate parts in this regard. The northern part and the southern part are divided into high consumption, the eastern and southeastern parts are low consumption, and the western part and parts of the center are divided into medium consumption. In addition, according to the zoning results, the average, minimum, and maximum net irrigation needs of the crops were calculated. For the wheat crop, the average, minimum, and maximum net irrigation requirements were 164, 314, and 259 mm, respectively. For the barley crop, the average, minimum, and maximum net irrigation requirements were 110, 255, and 205 mm, respectively. For the potato crop, the average, minimum, and maximum net irrigation requirements were calculated as 325, 613, and 484 mm, respectively. In addition, for alfalfa and bean crops, the mean, minimum, and maximum net irrigation requirements were estimated at 425, 872, and 670 mm and 337, 637, and 497 mm, respectively. ConclusionThe results showed that if the average of the whole plain is used for wheat, barley, potato, alfalfa, and bean crops, instead of point or regional information, about 18, 20, 21, 23, and 22% deficit irrigation, respectively, and in Low consumption sector accounts for about 58, 86, 49, 58, and 48% of excess irrigation. Also, the results showed that using the output numbers of NETWAT software will cause wrong water management in Ardabil Plain. Therefore, using the results of the National Water Document (NETWAT) will lead to incorrect water management due to the problems mentioned. That is if the results of the national document are used as the basis for determining the water requirement in the Ardabil Plain, compared to the minimum and maximum numbers obtained from this research, about 32 and 38 MCM will occur in the exceeding irrigated and deficit irrigated plains, respectively (without considering the impact potato crop due to not calculating its water requirement in the national water document for Ardabil Plain). Considering climate change and also the development of different databases, it is suggested to use up-to-date information for water requirement calculations. Also, considering that the Ardabil Plain is divided into three separate parts in terms of the net need for irrigation, therefore it is recommended that instead of using one number as the consumption in the whole plain, from point or regional information obtained from this research for wheat, barley, Use potatoes, alfalfa and beans.

Lei Zhang, Andriy Miranskyy

A flaky test yields inconsistent results upon repetition, posing a significant challenge to software developers. An extensive study of their presence and characteristics has been done in classical computer software but not quantum computer software. In this paper, we outline challenges and potential solutions for the automated detection of flaky tests in bug reports of quantum software. We aim to raise awareness of flakiness in quantum software and encourage the software engineering community to work collaboratively to solve this emerging challenge.

Dmitry Zaborov

High energy neutrino astronomy has seen significant progress in the past few years. This includes the detection of neutrino flux from the Galactic plane, as well as strong evidence for neutrino emission from the active galaxy NGC 1068, both reported by IceCube. New results start coming from the two km$^3$-scale neutrino telescopes under construction in the Northern hemisphere: KM3NeT in the Mediterranean Sea and Baikal-GVD in Lake Baikal. After briefly reviewing the status of the field, we present the current status of the Baikal-GVD neutrino telescope and its recent results, including observations of atmospheric and astrophysical neutrinos.

Lyle Regenwetter, Cyril Picard, Amin Heyrani Nobari et al.

The field of engineering is shaped by the tools and methods used to solve problems. Optimization is one such class of powerful, robust, and effective engineering tools proven over decades of use. Within just a few years, generative artificial intelligence (GenAI) has risen as another promising tool for general-purpose problem-solving. While optimization shines at precisely identifying highly-optimal solutions, GenAI excels at inferring problem requirements, bridging solution domains, handling mixed data modalities, and rapidly generating copious numbers of solutions. These differing attributes also make the two frameworks complementary. Hybrid `generative optimization' algorithms have gained traction across a few engineering applications and now comprise an emerging paradigm for engineering problem-solving. We expect significant developments in the near future around generative optimization, leading to changes in how engineers solve problems using computational tools. We offer our perspective on existing methods, areas of promise, and key research questions.

Rajesh Sigdel, Gregory Carlton, Bivek Gautam

Abstract Despite the fact that it is one of the most sacred and holy rivers in the world, the Ganges River is paradoxically among the most polluted. Over the past decade, researchers have described various mechanisms and actions for improving the pollution problem within the Ganges watershed. The aim of this policy‐centric systematic review is to summarize these recommendations to make them more accessible for concerned citizen groups and planners while also critically appraising their findings. Using the Reporting standards for Systematic Evidence Syntheses (ROSES) framework, our findings indicate that there are a wide range of potential solutions for mitigating pollution in the river system that originate from 37 peer‐reviewed sources that encompass field studies, modeling analyses, and review articles. While we find that there are many actionable and thought‐provoking recommendations for improving water quality and pollution mitigation given by authors studying the Ganges, there are also areas for improvement. Notably, there is a heavy focus on state‐centric planning in the basin with only a few examples of policies that have been tailored toward encouraging community‐based solutions. This lack of community‐based planning may relate to the fact that there is also a missing social dimension to policy recommendations in the Ganges watershed, where most of the articles that we reviewed were published in natural science journals and were not interdisciplinary in nature. Better reporting standards for recommendations arising from reviews and a greater focus on the interrelations between different components of the Ganges system may also yield novel and more trustworthy policy findings for practitioners.

YANG Yugui, XUAN Xiaoming, LIU Guozhen et al.

Affected by the construction of a series of projects,the semi-enclosed harbor often appears the phenomenon of weakening hydrodynamic force and worsening water exchange.In order to study the impact of project construction on the hydrodynamic environment of semi-closed harbors,a typical semi-enclosed port,namely Xiangzhou Fishing Port,in the Pearl River Estuary was taken as an example,and the impact of detailed control planning of the surrounding areas on flood discharge,tidal influx,and water exchange in Xiangzhou Fishing Port was studied.The results show that after the implementation of the planning scheme,the water level of the water area near the planning area and the upstream entrance gate,as well as the tidal volume of the tidal channel on the west side of Lingdingyang change slightly,but the tidal volume in the area of Xiangzhou Port decreases by about 1%.The hydrodynamic force is further weakened,and the semi-exchange cycle of the water body increases by about 3.2%.In particular,the water exchange capacity in the northwest corner of the port area is relatively poor,which is unfavorable to the water environment for a long time,and it is necessary to take hydrodynamic enhancement measures.The research results can provide a reference for hydrodynamic improvement in the water area of Xiangzhou Port.

Ertugrul Basar

Noise: an enemy to be dealt with and a major factor limiting communication system performance. However, what if there is gold in that garbage? In conventional engineering, our focus is primarily on eliminating, suppressing, combating, or even ignoring noise and its detrimental impacts. Conversely, could we exploit it similarly to biology, which utilizes noise-alike carrier signals to convey information? In this context, the utilization of noise, or noise-alike signals in general, has been put forward as a means to realize unconditionally secure communication systems in the future. In this tutorial article, we begin by tracing the origins of thermal noise-based communication and highlighting one of its significant applications for ensuring unconditionally secure networks: the Kirchhoff-law-Johnson-noise (KLJN) secure key exchange scheme. We then delve into the inherent challenges tied to secure communication and discuss the imperative need for physics-based key distribution schemes in pursuit of unconditional security. Concurrently, we provide a concise overview of quantum key distribution (QKD) schemes and draw comparisons with their KLJN-based counterparts. Finally, extending beyond wired communication loops, we explore the transmission of noise signals over-the-air and evaluate their potential for stealth and secure wireless communication systems.

Daniel Badawi, Eduardo Gildin

Physics-Informed machine learning models have recently emerged with some interesting and unique features that can be applied to reservoir engineering. In particular, physics-informed neural networks (PINN) leverage the fact that neural networks are a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process, and can be described by partial differential equations. The transient diffusivity equation is a fundamental equation in reservoir engineering and the general solution to this equation forms the basis for Pressure Transient Analysis (PTA). The diffusivity equation is derived by combining three physical principles, the continuity equation, Darcy's equation, and the equation of state for a slightly compressible liquid. Obtaining general solutions to this equation is imperative to understand flow regimes in porous media. Analytical solutions of the transient diffusivity equation are usually hard to obtain due to the stiff nature of the equation caused by the steep gradients of the pressure near the well. In this work we apply physics-informed neural networks to the one and two dimensional diffusivity equation and demonstrate that decomposing the space domain into very few subdomains can overcome the stiffness problem of the equation. Additionally, we demonstrate that the inverse capabilities of PINNs can estimate missing physics such as permeability and distance from sealing boundary similar to buildup tests without shutting in the well.

Manuel Parra-Royón, Jesús Sánchez-Castañeda, Julián Garrido et al.

The Square Kilometre Array (SKA) infrastructure will consist of two radio telescopes that will be the most sensitive telescopes on Earth. The SKA community will have to process and manage near exascale data, which will be a technical challenge for the coming years. In this respect, the SKA Global Network of Regional Centres plays a key role in data distribution and management. The SRCNet will provide distributed computing and data storage capacity, as well as other important services for the network. Within the SRCNet, several teams have been set up for the research, design and development of 5 prototypes. One of these prototypes is related to data management and distribution, where a data lake has been deployed using Rucio. In this paper we focus on the tasks performed by several of the teams to deploy new storage endpoints within the SKAO data lake. In particular, we will describe the steps and deployment instructions for the services required to provide the Rucio data lake with a new Rucio Storage Element based on StoRM and WebDAV within the Spanish SRC prototype.

YIN Sheng, LIU Bolong, SUN Desen

Qiang Wu, Hui Yu

Identification of critical source areas (CSAs) is pivotal for the management of nonpoint source (NPS) pollution of watersheds. Most studies focus on source (S) factors and ignore the driving (D) factors of such pollution. The Soil and Water Assessment Tool (SWAT) model and the export coefficient method (ECM) were incorporated to quantify the S factors of ammonia nitrogen (NH4-N) and total phosphorus (TP) as NPS pollution. Specifically, S factors coupled with D factors, including precipitation, slope, soil and land use, were regarded as multi-factors. Moreover, the analytical hierarchy process (AHP) method was adopted to determine the respective weights of multi-factors after overlaying the factor maps to identify the CSAs. These CSAs accounted for 23.86% of the total area, and generated 54.94% of NH4-N and 42.59% of the TP loads. In contrast with single and multi-factors, we found that using multi-factors having differing weights was more accurate for identifying CSAs. Our study results indicate this approach is reasonable for CSAs' identification in watersheds, and it can provide insights into different pollution sources and migration, thus providing a sounder basis for future decision-making. HIGHLIGHTS SWAT-ECM was incorporated to quantify nutrient loads in the watershed.; Both source and driving factors were used to identify CSAs.; AHP method can calculate the weight of different factors.; Considering multi-factors can improve the accuracy of CSAs identification.;

Alexander Felfernig, Stefan Reiterer, Martin Stettinger et al.

The knowledge engineering bottleneck is still a major challenge in configurator projects. In this paper we show how recommender systems can support knowledge base development and maintenance processes. We discuss a couple of scenarios for the application of recommender systems in knowledge engineering and report the results of empirical studies which show the importance of user-centered configuration knowledge organization.

Yan Zhao, Imen Megdiche, Franck Ravat

Data Lake (DL) is a Big Data analysis solution which ingests raw data in their native format and allows users to process these data upon usage. Data ingestion is not a simple copy and paste of data, it is a complicated and important phase to ensure that ingested data are findable, accessible, interoperable and reusable at all times. Our solution is threefold. Firstly, we propose a metadata model that includes information about external data sources, data ingestion processes, ingested data, dataset veracity and dataset security. Secondly, we present the algorithms that ensure the ingestion phase (data storage and metadata instanciation). Thirdly, we introduce a developed metadata management system whereby users can easily consult different elements stored in DL.

Ogryzek Marek P., Rząsa Krzysztof, Ciski Mateusz

Rural development policy of Agricultural Property Stock (APS) of the State Treasury in Poland is run by the National Support Centre for Agriculture (until 31.08.2017 Agricultural Property Agency). In the article, on the example of the Braniewo municipality, the size and spatial distribution of land transferred from the Agricultural Property Stock (APS) of the State Treasury to the municipality was analysed. One of the most important goals associated with this was activities related to social aspects, often part of the revitalization and renewal of the rural areas. After Poland's accession to the European Union, it was possible to obtain subsidies that allowed the rural population to apply for financing projects, such as: road construction, creating school playgrounds or socio-cultural facilities. Authors also analysed examples of good practices in this area in the municipality of Braniewo, as a recommendation for other municipalities. Attempts have also been made to indicate the role of the National Support Centre for Agriculture in the transformation of the Polish countryside, with particular emphasis on the areas of former State Agricultural Farms.