Hasil untuk "Hydraulic engineering"

P. Nielsen

N. Chien, Zhaohui Wan

J. Davidovits

D. Corenblit, E. Tabacchi, J. Steiger et al.

Lei Wang, Minmin Jin, Yonghua Wu et al.

Abstract Low heat Portland (LHP) cement has been widely used in hydraulic projects in China, while the relatively low early strength limits its further application in engineering. In this study, the effect of silica fume (SF) content, varying between 0 and 12%, by mass of binder, on hydration heat, hydration products and pore structure of LHP cement-based materials were investigated by isothermal calorimetry, thermal analysis, and mercury intrusion porosimetry (MIP), respectively. Besides, the mechanical strength, shrinkage behavior and fractal characteristics of SF modified LHP cement-based materials were studied and compared with those of ordinary Portland cement (OPC)-based ones. The results indicate that the addition of SF effectively accelerates the hydration of LHP cement and obviously consumes the Ca(OH)2 in LHP cement paste. In addition, concrete based on LHP cement with 8 wt% SF exhibits excellent performance such as high early strength, low hydration heat and low shrinkage. It is also found that the pore structure of SF-modified LHP cement concrete becomes finer and more complex as the SF dosage increases, resulting in higher fractal dimension (Ds) values. Moreover, there exists a linear relationship between Ds and shrinkage of concrete, thus Ds may serve as a new parameter to evaluate the shrinkage behavior of concrete.

Ju Wang, Liang Chen, R. Su et al.

Abstract With the rapid development of nuclear power in China, the disposal of high-level radioactive waste (HLW) has become an important issue for nuclear safety and environmental protection. Deep geological disposal is internationally accepted as a feasible and safe way to dispose of HLW, and underground research laboratories (URLs) play an important and multi-faceted role in the development of HLW repositories. This paper introduces the overall planning and the latest progress for China's URL. On the basis of the proposed strategy to build an area-specific URL in combination with a comprehensive evaluation of the site selection results obtained during the last 33 years, the Xinchang site in the Beishan area, located in Gansu Province of northwestern China, has been selected as the final site for China's first URL built in granite. In the process of characterizing the Xinchang URL site, a series of investigations, including borehole drilling, geological mapping, geophysical surveying, hydraulic testing and in situ stress measurements, has been conducted. The investigation results indicate that the geological, hydrogeological, engineering geological and geochemical conditions of the Xinchang site are very suitable for URL construction. Meanwhile, to validate and develop construction technologies for the Beishan URL, the Beishan exploration tunnel (BET), which is a 50-m-deep facility in the Jiujing sub-area, has been constructed and several in situ tests, such as drill-and-blast tests, characterization of the excavation damaged zone (EDZ), and long-term deformation monitoring of surrounding rocks, have been performed in the BET. The methodologies and technologies established in the BET will serve for URL construction. According to the achievements of the characterization of the URL site, a preliminary design of the URL with a maximum depth of 560 m is proposed and necessary in situ tests in the URL are planned.

K. Yuen

Zheng Wang, Tongge Cui, Bangbiao Wu et al.

The integration of face mask fibers (FMF) into cement materials has been proposed as a method to enhance material properties while mitigating pollution. Despite the validation of such advantages through extensive studies, the effects of mask fibers on the dynamic properties of the composite remain to be comprehensively investigated. This study examined dynamic tensile properties of cement mortar incorporating FMF at various volume percentages (0 %, 0.1 %, 0.2 %, 0.3 % and 0.5 %). X-ray Computed Tomography (CT) was utilized to assess specimen integrity. A split Hopkinson pressure bar (SHPB) system was employed to conduct dynamic Brazilian splitting tests, and quasi-static BD test was conducted for comparation. High-speed camera and digital image correlation (DIC) technology was used to analyse the specimen fracture during loading. Subsequently, both macro and micro-observations were made on the fragmented specimens. The results demonstrate that the inclusion of face mask generally reduces voids and microcracks within mortars, leading to material quality improvement for 8.6∼21.0 % characterized by CT value. As compared with the plain mortar, both the static and dynamic tensile strengths increase across all FMF mixtures, with the enhancement correlating with the material quality. The fracture energy density of the mortars showed significant improvement at higher loading rates (0.25–0.45 J/cm2 at 250 GPa/s), exhibiting pronounced rate sensitivity due to mask inclusion. The crushing pattern of the specimen also changes and shows certain microscopic characteristics. Based on these tensile properties, the optimum content of FMF is 0.3 %. These findings enhance the subsequent understanding of the effects of mask incorporation and provide a basis for determining the potential applications of such composite materials.

Neha Pandey, Chandrakant Thakur, Nayna Agarwal et al.

Electrochemical reactors play a vital role in scaling up wastewater treatment processes, with efficiency influenced by electrode material, reactor geometry, flow dynamics, power supply, and operational mode. This study investigated the continuous electrocoagulation treatment of paper mill wastewater using a reactor equipped with four aluminum electrodes. The effects of flow rate (0.1–0.6 L/min) and retention time on pollutant removal efficiency were examined. Effluent was continuously fed into the reactor via a peristaltic pump, ensuring controlled inflow and uniform distribution for optimal treatment conditions. Experimental results demonstrated that 80% removal of total dissolved solids, total organic carbon, chemical oxygen demand, and color was achieved under optimal conditions: a pH value of 5.0, a conductivity of 7.59 mS/cm, an electrode gap of 1.38 cm, a current density of 10.72 mA/cm2, a retention time of 120 min, and a flow rate of 0.1 L/min. The sludge generated during treatment was characterized using scanning electron microscopy, energy dispersive X-ray spectroscopy, X-ray diffraction, and Fourier transform infrared spectroscopy to assess its composition and potential for reuse or safe disposal. Additionally, the pollutant removal mechanism using aluminum electrodes was elucidated. This study provides a novel contribution by exploring a continuous-flow electrocoagulation system for pulp and paper mill wastewater treatment, an area with limited prior research, and by integrating detailed sludge characterization to evaluate treatment performance and resource recovery potential. These results underscore the effectiveness of continuous electrocoagulation for treating paper mill effluents, advancing sustainable wastewater management practices.

Jing Zhang, Pei Li, Junfeng Wan et al.

Proper management of nitrogen-containing pig manure is crucial to realize its benefits of supporting plants-grow as fertilizer while minimizing its impact on the environment and climate change. Dry collection, rinsing and water submerging are manure cleaning techniques adopted in different types of pig farms and in different regions. As the first step of manure management, manure cleaning technique affects manure generation and nitrogen flow in the subsequent treatment and utilization processes. This short communication is to discuss different manure cleaning techniques and their impacts on nitrogen flow through pig manure management processes. Reducing nitrogen losses should focus on solid manure treatment such as composting when manure is dry collected. More diversified pathways of nitrogen losses are possible when manure is cleaned using water submerging technique. It is thus needed to develop proper and specific nitrogen management strategies and technologies, taking into account the manure cleaning technique adopted in pig farms.

Xinpeng Liu, Xuemei Zhang, Yongli Zhong et al.

We present a two-scale physics-informed neural network (TSPINN) algorithm to address structural parameter inversion problems involving small parameters. The algorithm’s core mechanism directly embeds small parameters into the neural network architecture. By constructing a two-scale neural network architecture, this approach enables the simultaneous analysis of structural dynamic responses and local parameter perturbation effects, which effectively addresses challenges posed by high-frequency oscillations and parameter sensitivity. Numerical experiments demonstrate that TSPINNs significantly improve prediction accuracy and convergence speed compared to conventional physics-informed neural networks (PINNs) and maintain robustness in high-stiffness scenarios. The T-shaped tower shaking table test results confirm that the model’s identification errors for stiffness reduction coefficients and mass parameters remain below 10% under lower noisy conditions, demonstrating high precision and strong generalization capability for multi-damage scenarios and random load excitations.

Shalini Chakraborty, Sebastian Baltes

The IT industry provides supportive pathways such as returnship programs, coding boot camps, and buddy systems for women re-entering their job after a career break. Academia, however, offers limited opportunities to motivate women to return. We propose a diverse multicultural research project investigating the challenges faced by women with software engineering (SE) backgrounds re-entering academia or related research roles after a career break. Career disruptions due to pregnancy, immigration status, or lack of flexible work options can significantly impact women's career progress, creating barriers for returning as lecturers, professors, or senior researchers. Although many companies promote gender diversity policies, such measures are less prominent and often under-recognized within academic institutions. Our goal is to explore the specific challenges women encounter when re-entering academic roles compared to industry roles; to understand the institutional perspective, including a comparative analysis of existing policies and opportunities in different countries for women to return to the field; and finally, to provide recommendations that support transparent hiring practices. The research project will be carried out in multiple universities and in multiple countries to capture the diverse challenges and policies that vary by location.

Mia Mohammad Imran, Tarannum Shaila Zaman

Large Language Models (LLMs) are increasingly used in empirical software engineering (ESE) to automate or assist annotation tasks such as labeling commits, issues, and qualitative artifacts. Yet the reliability and reproducibility of such annotations remain underexplored. Existing studies often lack standardized measures for reliability, calibration, and drift, and frequently omit essential configuration details. We argue that LLM-based annotation should be treated as a measurement process rather than a purely automated activity. In this position paper, we outline the \textbf{Operationalization for LLM-based Annotation Framework (OLAF)}, a conceptual framework that organizes key constructs: \textit{reliability, calibration, drift, consensus, aggregation}, and \textit{transparency}. The paper aims to motivate methodological discussion and future empirical work toward more transparent and reproducible LLM-based annotation in software engineering research.

Yuliang Wang, Dezhong Kong, Guiyi Wu et al.

D. Valero, S. Felder, M. Kramer et al.

ABSTRACT High Froude-number open-channel flows can entrain significant volumes of air, a phenomenon that occurs continuously in spillways, in free-falling jets and in hydraulic jumps, or as localized events, notably at the toe of hydraulic jumps or in plunging jets. Within these flows, turbulence generates millions of bubbles and droplets as well as highly distorted wavy air–water interfaces. This phenomenon is crucial from a design perspective, as it influences the behaviour of high-velocity flows, potentially impairing the safety of dam operations. This review examines recent scientific and engineering progress, highlighting foundational studies and emerging developments. Notable advances have been achieved in the past decades through improved sampling of flows and the development of physics-based models. Current challenges are also identified for instrumentation, numerical modelling and (up)scaling that hinder the formulation of fundamental theories, which are instrumental for improving predictive models, able to offer robust support for the design of large hydraulic structures at prototype scale.

Claudio Di Sipio, Riccardo Rubei, Juri Di Rocco et al.

Software engineering (SE) activities have been revolutionized by the advent of pre-trained models (PTMs), defined as large machine learning (ML) models that can be fine-tuned to perform specific SE tasks. However, users with limited expertise may need help to select the appropriate model for their current task. To tackle the issue, the Hugging Face (HF) platform simplifies the use of PTMs by collecting, storing, and curating several models. Nevertheless, the platform currently lacks a comprehensive categorization of PTMs designed specifically for SE, i.e., the existing tags are more suited to generic ML categories. This paper introduces an approach to address this gap by enabling the automatic classification of PTMs for SE tasks. First, we utilize a public dump of HF to extract PTMs information, including model documentation and associated tags. Then, we employ a semi-automated method to identify SE tasks and their corresponding PTMs from existing literature. The approach involves creating an initial mapping between HF tags and specific SE tasks, using a similarity-based strategy to identify PTMs with relevant tags. The evaluation shows that model cards are informative enough to classify PTMs considering the pipeline tag. Moreover, we provide a mapping between SE tasks and stored PTMs by relying on model names.

Salma M. Elsherif, Mohamad H. Kazma, Ahmad F. Taha

The operation of water distribution networks simply aims at efficiently delivering consumers adequate water while maintaining safe water quality (WQ). However, this process entails a multi-scale interplay between hydraulic and WQ dynamics evolving spatio-temporally within such a complex infrastructure network. While prior research has addressed the hydraulic optimization problem and WQ regulation as decoupled or coupled, they often overlook control-theoretic guided solutions. This paper takes a novel approach by investigating the coupling between hydraulic and WQ dynamics from a control networks perspective. We propose a quality-aware control framework that embeds WQ controllability metrics into the network-level pump scheduling problem, acknowledging the direct influence of system hydraulics on WQ controller behavior. We examine the trade-offs between pump control energy cost and WQ performance across various network sizes and scenarios. Our results showcase how network topology, hydraulic constraints, and WQ metrics jointly impact optimal pump schedules and, accordingly, the achievable level of WQ regulation, offering insights into designing efficient control strategies for water infrastructure networks governed by interdependent dynamics.

Johannes Schleiss, Aditya Johri

In this practice paper, we propose a framework for integrating AI into disciplinary engineering courses and curricula. The use of AI within engineering is an emerging but growing area and the knowledge, skills, and abilities (KSAs) associated with it are novel and dynamic. This makes it challenging for faculty who are looking to incorporate AI within their courses to create a mental map of how to tackle this challenge. In this paper, we advance a role-based conception of competencies to assist disciplinary faculty with identifying and implementing AI competencies within engineering curricula. We draw on prior work related to AI literacy and competencies and on emerging research on the use of AI in engineering. To illustrate the use of the framework, we provide two exemplary cases. We discuss the challenges in implementing the framework and emphasize the need for an embedded approach where AI concerns are integrated across multiple courses throughout the degree program, especially for teaching responsible and ethical AI development and use.

Mesfin Reta Aredo, Tarun Kumar Lohani, Abdella Kemal Mohammed

AbstractGroundwater is the primary source of water supply in Ethiopia. The study area was challenged due to increasing water demand, uneven water resource distribution, and noticeable changes in groundwater levels. The study focused on the examining of existing abstraction and future water demand scenarios on groundwater balance in the Weyib watershed using the WetSpass-M and MODFLOW-2005 models. The input datasets, such as aquifer properties, observed groundwater heads, hydrogeology, groundwater recharge, the Digital Elevation Model (DEM), and hydrological data were used. Datasets were prepared to better represent subsurface hydrology and its future demand effects evaluated using calibrated steady-state numerical groundwater modeling. The WetSpass-M and MODFLOW-2005 models depicted good performances during the simulations of groundwater recharge and groundwater budget under existing abstractions and estimated demand scenarios, respectively. The mean annual groundwater recharge estimated was 177.66 mm/year. The existing groundwater abstraction was 34,686.39, estimated short-term and long-term water demand scenarios were 72,113.61 and 93,795.57 m3/day, respectively. The upstream area has the highest groundwater head and recharge, while decreasing as it approaches the Weyib watershed outlet. During the outflow groundwater budget, the groundwater abstractions increased as expenses of river leakage and head dept. bounds increased. Moreover, the increasing groundwater withdrawal would reduce groundwater heads, and the estimated future water demand scenarios would substantially impact the groundwater budget, which would also have an impact on the watershed hydrology and ecosystem.

Dayana K. Melo da Silva

As the city of São Paulo grew and developed during the latter part of the 19th century and in the course of the 20th, its approximately 300 rivers were gradually built over, causing them to fade from use and public awareness. Various collectives and social initiatives are now engaged in the rediscovery of these watercourses. Using participant observation and document analysis, we investigated their activities and the impact of information and communication technologies (ICTs) on the process. Our research showed that, in addition to producing, distributing, storing and retrieving information in the digital environment, collectives and social initiatives also play a role in the creation and development of tools and platforms that reveal São Paulo’s hydrographic network. We conclude that ICTs allow these activist groups to provide São Paulo’s citizens with concrete tools for noticing channelised and buried rivers and streams. We also observe that hybridisation of the physical and digitalinformational territories suggests a new way of seeing and occupying the city.