Hasil untuk "Hydraulic engineering"

Yu Chen, Haitao Wang, Jian Zheng et al.

Under drip irrigation conditions, the transport pattern of soil water in the root zone directly affects the water use efficiency of crops. The type of soil matrix, initial moisture content, and irrigation water quality jointly determine the hydrodynamic process of water infiltration. However, as a special type of irrigation water, the water movement mechanism of biogas slurry under drip irrigation in soilless cultivation substrates still lacks systematic investigation. In this study, transparent soil column infiltration experiments were conducted using two types of cultivation substrates—organic (coconut coir) and inorganic (desert sand)—under controlled facility conditions. Three initial moisture contents (10%, 15%, and 20%) and two irrigation water qualities (tap water and diluted biogas slurry) were combined to form twelve treatment groups. Soil moisture sensors and visualization techniques were employed to quantitatively analyze the wetting front morphology, vertical and horizontal infiltration rates, wetting ratio, and soil moisture profile distribution under different treatments. The results showed that the initial moisture content significantly influenced the advancement pattern of the wetting front. Higher initial moisture levels promoted the transformation of the wetting front shape from a “semi-pear” form to a “hemispherical” one and reduced the rate of infiltration decline. The coconut coir substrate exhibited stronger vertical infiltration capacity and a central water aggregation characteristic, whereas the desert sand demonstrated a wider horizontal expansion range. Under low and moderate initial moisture conditions, the application of biogas slurry enhanced horizontal water diffusion and improved the uniformity of the wetted zone, with the wetting ratio increasing by more than 6% compared with high moisture conditions. In addition, the power function model provided an excellent fit for the cumulative infiltration process across all treatments (R² > 0.96), indicating its suitability for describing the water transport process in facility cultivation substrates. This study provides theoretical support for precise water and fertilizer management and the efficient utilization of biogas slurry in soilless cultivation systems.

Nidhal Selmi, Jean-michel Bruel, Sébastien Mosser et al.

Decision-making is a core engineering design activity that conveys the engineer's knowledge and translates it into courses of action. Capturing this form of knowledge can reap potential benefits for the engineering teams and enhance development efficiency. Despite its clear value, traditional decision capture often requires a significant amount of effort and still falls short of capturing the necessary context for reuse. Model-based systems engineering (MBSE) can be a promising solution to address these challenges by embedding decisions directly within system models, which can reduce the capture workload while maintaining explicit links to requirements, behaviors, and architectural elements. This article discusses a lightweight framework for integrating decision capture into MBSE workflows by representing decision alternatives as system model slices. Using a simplified industry example from aircraft architecture, we discuss the main challenges associated with decision capture and propose preliminary solutions to address these challenges.

Jay Lee, Hanqi Su, Dai-Yan Ji et al.

Over the past ten years, the application of artificial intelligence (AI) and machine learning (ML) in engineering domains has gained significant popularity, showcasing their potential in data-driven contexts. However, the complexity and diversity of engineering problems often require the development of domain-specific AI approaches, which are frequently hindered by a lack of systematic methodologies, scalability, and robustness during the development process. To address this gap, this paper introduces the "ABCDE" as the key elements of Engineering AI and proposes a unified, systematic engineering AI ecosystem framework, including eight essential layers, along with attributes, goals, and applications, to guide the development and deployment of AI solutions for specific engineering needs. Additionally, key challenges are examined, and eight future research directions are highlighted. By providing a comprehensive perspective, this paper aims to advance the strategic implementation of AI, fostering the development of next-generation engineering AI solutions.

Marina Potapova, Daiana Markarian, Abigail King et al.

Microscopic eukaryotes are important components of coastal wetland ecosystems. The goal of this study was to investigate the diversity of microeukaryotes in the tidal pools of a New Jersey salt marsh and to compare the assemblages of natural and artificial pools excavated for controlling mosquito populations. We evaluated microeukaryotic assemblages using the amplicon sequencing of 18S and <i>rbc</i>L DNA markers and the microscopic identification of diatoms in water and sediment samples. 18S unique amplicon sequence variants (ASV) representing ciliates, dinoflagellates, diatoms, and cercozoans were the most diverse, while the reads of dinoflagellates, diatoms, ciliates, and nematodes were the most abundant. The dominant ASVs were attributed to organisms that are characteristic of coastal plankton and sediments or those known for their resistance to salinity, desiccation, hypoxia, and UV stress. The sediment assemblages were more diverse compared to those from the water column and contained a larger portion of ASVs that were not assigned to any low-rank taxa, reflecting the current gaps in understanding the diversity of microeukaryotes. Most taxonomic groups were significantly different in their abundance and composition between natural and artificial pools. Dinoflagellates, haptophytes, chrysophytes, pelagophytes, and raphidophytes—the groups that include a large proportion of mixotrophic taxa and species known for forming harmful algal blooms—were more abundant in the artificial than in the natural pools. Fungi, labyrinthulomycetes, and peronosporomycetes were also more abundant in artificial pools, which may be related to organic matter enrichment. Diatoms and foraminifera showed an opposite trend of higher abundance in natural pools.

HAN Guang

As a set of automated process has not yet been formed for constructing reservoir capacity curves using remote sensing technology, it is proposed to determine the optimal threshold with the inflection point method of the cumulative frequency curve based on the water body index method. The edge of the water body is optimized by the regional seed growth algorithm, so as to construct a complete set of automated process to quickly construct the reservoir capacity curves. With Sentinel-2 remote sensing images as the data source and Chegu Reservoir in Wuan City, Handan City, Hebei Province as the research object, this paper uses five land and water image metrics, namely, NDWI, MNDWI, RWI, MBWI, and AWEInsh to extract the area of the water body, construct the reservoir capacity curve, and compare it with the results of the measurements in 2017. The results are as follows. The extraction accuracy of NDWI and RWI water body index is high. The average error of Chegu water body area extraction is 2.5%. The relative error is -7.3%–5.8% and -6.2%–4.7%, and the <italic>R</italic>² is 0.993 36 and 0.990 49, respectively. The range of the relative error of the reservoir capacity is -9.4% to -1.8% and -9.3% to -1.7%, respectively. The study shows that the cumulative frequency curve inflection point method is highly applicable and stable in determining the optimal threshold of water body index, with a simple and feasible principle. The regional seed growth algorithm can effectively eliminate the discontinuity at the edge of the water body, reduce systematic error, and further improve the accuracy. The cumulative frequency curve inflection point method provides a new idea for remote sensing water body extraction, serving as a reference for the batch construction of national small and medium-sized reservoir capacity curve extraction.

Tao Wang, Jinchun Song

The electro-hydraulic servo system has advantages such as high pressure, large flow, and high power, etc., which can also realize stepless regulation, so it is widely used in many engineering machineries. A linear model is sometimes only a simple approximation of an idealized model, but in an actual system, there may be nonlinear and transient variation characteristics in the systems. Coupling is reflected in the fact that the components or functional structures implemented by each system used for the design of hydraulic systems are not completely or independently related to each other, but affect each other. The nonlinear clearance between the actuator and the load reduces the control accuracy of the system and increases the impact, thus losing stable working conditions. In the paper, based on the nonlinear clearance problem of the electro-hydraulic servo system, a mathematical transfer model with clearance is established, and on this basis, a clearance compensation method based on the Hopfield neural network is proposed. In this way, clearance compensation can be realized by adjusting the parameters of neural network nodes, through simple and convenient operation. Finally, by setting different clearance values, the results of the step response and sine response curve before and after clearance compensation of the hydraulic system are compared, and the effectiveness of Hopfield neural network compensation clearance control is verified based on the comparison simulation results.

Marvin Wyrich, Marvin Muñoz Barón, Justus Bogner

Software engineering (SE) is full of abstract concepts that are crucial for both researchers and practitioners, such as programming experience, team productivity, code comprehension, and system security. Secondary studies aimed at summarizing research on the influences and consequences of such concepts would therefore be of great value. However, the inability to measure abstract concepts directly poses a challenge for secondary studies: primary studies in SE can operationalize such concepts in many ways. Standardized measurement instruments are rarely available, and even if they are, many researchers do not use them or do not even provide a definition for the studied concept. SE researchers conducting secondary studies therefore have to decide a) which primary studies intended to measure the same construct, and b) how to compare and aggregate vastly different measurements for the same construct. In this experience report, we discuss the challenge of study selection in SE secondary research on latent variables. We report on two instances where we found it particularly challenging to decide which primary studies should be included for comparison and synthesis, so as not to end up comparing apples with oranges. Our report aims to spark a conversation about developing strategies to address this issue systematically and pave the way for more efficient and rigorous secondary studies in software engineering.

Aline de Campos, Jorge Melegati, Nicolas Nascimento et al.

Generative Artificial Intelligence (GenAI) has become an emerging technology with the availability of several tools that could impact Software Engineering (SE) activities. As any other disruptive technology, GenAI led to the speculation that its full potential can deeply change SE. However, an overfocus on improving activities for which GenAI is more suitable could negligent other relevant areas of the process. In this paper, we aim to explore which SE activities are not expected to be profoundly changed by GenAI. To achieve this goal, we performed a survey with SE practitioners to identify their expectations regarding GenAI in SE, including impacts, challenges, ethical issues, and aspects they do not expect to change. We compared our results with previous roadmaps proposed in SE literature. Our results show that although practitioners expect an increase in productivity, coding, and process quality, they envision that some aspects will not change, such as the need for human expertise, creativity, and project management. Our results point to SE areas for which GenAI is probably not so useful, and future research could tackle them to improve SE practice.

Binnur Görer, Fatma Başak Aydemir

Elicitation interviews are the most common requirements elicitation technique, and proficiency in conducting these interviews is crucial for requirements elicitation. Traditional training methods, typically limited to textbook learning, may not sufficiently address the practical complexities of interviewing techniques. Practical training with various interview scenarios is important for understanding how to apply theoretical knowledge in real-world contexts. However, there is a shortage of educational interview material, as creating interview scripts requires both technical expertise and creativity. To address this issue, we develop a specialized GPT agent for auto-generating interview scripts. The GPT agent is equipped with a dedicated knowledge base tailored to the guidelines and best practices of requirements elicitation interview procedures. We employ a prompt chaining approach to mitigate the output length constraint of GPT to be able to generate thorough and detailed interview scripts. This involves dividing the interview into sections and crafting distinct prompts for each, allowing for the generation of complete content for each section. The generated scripts are assessed through standard natural language generation evaluation metrics and an expert judgment study, confirming their applicability in requirements engineering training.

T. Yuan, X. Wang, K. Qu et al.

Driven by strong winds, huge ocean waves can cause devastating destruction to coastal regions during harsh weather events. There is growing evidence showing that extreme waves can occur in both shallow and deep waters. To protect the coast against the destructive power of huge waves, coastal protection facilities, such as seawalls, are often built along the coast. The integrity and stability of these coastal protection facilities are essential to the safety of coastal regions. Since huge waves are often accompanied by strong winds in real ocean environments, to fill the knowledge gap left by previous relevant studies, this study numerically investigates the hydrodynamic loads and overtopping of a coastal seawall model on a sloped beach under the coupled impact of an extreme wave group and wind. The influences of several main factors are considered, such as water depth, wind speed, and significant wave height. The research results reveal that strong wind can greatly increase the average overtopping rate and enhance the hydrodynamic loads exerted by the extreme wave group on the seawall.

WANG Bin, QIAO Shuaishuai, LIU Jifa

To comprehensively understand the impact of climate change on reference crop evapotranspiration (ET₀) in Inner Mongolia,the daily ET₀ of 50 meteorological stations in Inner Mongolia in the past 60 years was calculated using the FAO Penman-Monteith formula,and further investigated spatiotemporal characteristics,interdecadal and cyclical changes of ET₀ in Inner Mongolia.The results showed that the distribution trend of ET₀ gradually decreased from west to east in Inner Mongolia,the multi-year average was 1 018 mm,while the climate tilt rate was 4.2 mm/10a,showing a significant upward trend.The sum of ET₀ in spring,summer and autumn,the growing periods of crops,accounted for about 95% of the total annual value,while the spatial distribution was similar to the annual value.The annual average ET₀ in various climate zones followed a descending order:ultra-arid climate zone,arid climate zone,semi-arid climate zone,dry and semi-humid climate zone,humid and semi-humid climate zone.The variation coefficients of the climate zones were low,showing weak variability,and abrupt changes occurred in different climate zones at the end of the 1990s.The ET₀ change cycles were mainly 59a,14a and 24a.

YE Bangping, DING Yuhong, LIU Jinbao et al.

Taking a small watershed in the Pengzhou mountainous area of Sichuan as the research object,this paper employs historical precipitation data,watershed zoning data,DEM,and other data to calibrate the model parameters on a watershed runoff confluence model based on Navier-Stokes equation (N-S equation) with stable flow fields.The conclusions are as follows:① After model parameter calibration,the diffusion coefficient is 0.12,with an acceleration coefficient of 0.12 and a maximum water velocity of 3;② The analysis of confluence characteristics under different precipitation scenarios shows that with the increasing rainfall,the maximum water depth rises,and the time for maximum increase in water depth and the time for the maximum water depth decrease.The watersheds with the maximum time for a water depth of less than 200 min are mainly the upper watersheds,while those with the maximum time for a water depth of more than 200 min are mainly the main watersheds;③ The assessment reveals that there are no watersheds with high risk levels of mountain floods in the small watershed of Pengzhou mountainous area,17 watersheds with high levels,19 watersheds with relatively high levels,and only one watershed with low levels.

Kai Wang, Hongwei Fang, Guojian He et al.

Introduction: Damming significantly modifies the function of natural river networks and influences sediment dynamics with a reservoir’s operation. The dissolved organic matter (DOM) in reservoir sediments severely affects carbon flow from land to sea. However, the properties of DOM (e.g., quantity and quality) in reservoir sediments and their relationship with carbon cycling remain unclear as complex reservoir construction interrupts the environmental processes.Methods: This study characterizes the optical and molecular properties of sediment water-extractable organic matter (WEOM) in the Daning and Shennong tributaries of the world’s largest reservoir—the Three Gorges Reservoir (TGR)—by applying optical techniques and ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS).Results and Discussion: We first assessed the link between light-absorbing components and the individual molecules in WEOM, which were significantly different than DOM in water and indicated that there might be an intrinsic variation between DOM in sediment and in water. Then, with the unique optical–molecular property linkage assessed, multiple sources (autochthonous and terrestrial) were identified, and a declining trend of terrestrial and recalcitrant WEOM was revealed from the tributaries upstream to downstream. Finally, through covariance analysis of the properties between WEOM and sediment particles, we demonstrated that the WEOM dynamic was most likely regulated by hydrologic sorting-induced particle size and mineral composition variations of sediment. Moreover, assessment between lability and WEOM molecular properties suggested that the WEOM dynamic likely contributes to carbon burial in the reservoir. This study emphasizes the influence of dam construction on organic matter accumulation and riverine carbon cycling.

Xinlong Li, Junli Tan, Hong Li et al.

Sensitivity analysis, calibration, and verification of crop model parameters improve crop model efficiency and accuracy, facilitating its application. This study selected five sites within the Ningxia Yellow River Irrigation Area. Using meteorological data, soil data, and field management information, the EFAST (Extended Fourier Amplitude Sensitivity Test) method was used to conduct first-order and global sensitivity analyses of spring wheat parameters in the WOFOST (World Food Studies Simulation) Model. A Structural Equation Model (SEM) analyzed the contribution of crop parameters to different simulation indices, with parameter sensitivity rankings being discussed under varying water supply and climate conditions. Finally, the adapted WOFOST model was employed to assess its applicability in the Ningxia Yellow River Irrigation Area. TMNFTB3.0 (correction factor of total assimilation rate at 3 °C), SPAN (life span of leaves growing at 35 °C), SLATB0 (specific leaf area in the initial period), and CFET (correction factor transpiration rate) showed higher sensitivity index for most simulation indices. Under the same meteorological conditions, different water supply conditions have a limited impact on crop parameter sensitivity, mainly affecting leaf senescence, leaf area, and assimilate conversion to storage organs. The corrected crop parameters significantly enhanced the wheat yield simulation accuracy by the WOFOST model (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>M</mi><mi>E</mi></msub></mrow></semantics></math></inline-formula> = 0.9964; <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>R</mi><mrow><mi>M</mi><mi>S</mi><mi>E</mi></mrow></msub></mrow></semantics></math></inline-formula> = 0.2516; <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mi>M</mi><mrow><mi>B</mi><mi>E</mi></mrow></msub></mrow></semantics></math></inline-formula> = 0.1392; <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mi>R</mi><mn>2</mn></msup></mrow></semantics></math></inline-formula> = 0.0331). The localized WOFOST model can predict regional crop yield, with this study providing a theoretical foundation for its regional application, adjustment, and optimization.

Xiaofeng Wang, Henry Edison, Dron Khanna et al.

[Context] Systematic Literature Review (SLR) has been a major type of study published in Software Engineering (SE) venues for about two decades. However, there is a lack of understanding of whether an SLR is really needed in comparison to a more conventional literature review. Very often, SE researchers embark on an SLR with such doubts. We aspire to provide more understanding of when an SLR in SE should be conducted. [Objective] The first step of our investigation was focused on the dataset, i.e., the reviewed papers, in an SLR, which indicates the development of a research topic or area. The objective of this step is to provide a better understanding of the characteristics of the datasets of SLRs in SE. [Method] A research synthesis was conducted on a sample of 170 SLRs published in top-tier SE journals. We extracted and analysed the quantitative attributes of the datasets of these SLRs. [Results] The findings show that the median size of the datasets in our sample is 57 reviewed papers, and the median review period covered is 14 years. The number of reviewed papers and review period have a very weak and non-significant positive correlation. [Conclusions] The results of our study can be used by SE researchers as an indicator or benchmark to understand whether an SLR is conducted at a good time.

Srijoni Majumdar, Soumen Paul, Debjyoti Paul et al.

The Information Retrieval in Software Engineering (IRSE) track aims to develop solutions for automated evaluation of code comments in a machine learning framework based on human and large language model generated labels. In this track, there is a binary classification task to classify comments as useful and not useful. The dataset consists of 9048 code comments and surrounding code snippet pairs extracted from open source github C based projects and an additional dataset generated individually by teams using large language models. Overall 56 experiments have been submitted by 17 teams from various universities and software companies. The submissions have been evaluated quantitatively using the F1-Score and qualitatively based on the type of features developed, the supervised learning model used and their corresponding hyper-parameters. The labels generated from large language models increase the bias in the prediction model but lead to less over-fitted results.

Wouter Groeneveld, Laurens Luyten, Joost Vennekens et al.

Creativity is a critical skill that professional software engineers leverage to tackle difficult problems. In higher education, multiple efforts have been made to spark creative skills of engineering students. However, creativity is a vague concept that is open to interpretation. Furthermore, studies have shown that there is a gap in perception and implementation of creativity between industry and academia. To better understand the role of creativity in software engineering (SE), we interviewed 33 professionals via four focus groups and 10 SE students. Our results reveal 45 underlying topics related to creativity. When comparing the perception of students versus professionals, we discovered fundamental differences, grouped into five themes: the creative environment, application of techniques, creative collaboration, nature vs nurture, and the perceived value of creativity. As our aim is to use these findings to install and further encourage creative problem solving in higher education, we have included a list of implications for educational practice.

Ning Zhou, Lawrence Lau, Ruibin Bai et al.

Ultrawideband (UWB) technology has received considerable attention in indoor positioning because of its high ranging accuracy. However, UWB range measurements can be contaminated by the delayed signals resulting from obstruction and reflection in difficult indoor environments. These signals introduce delays to range measurements and degrade positioning accuracy if they are not resolved properly. In order to mitigate the effects of delayed range measurements on positioning and achieve a high-accuracy position estimation, this paper proposes a robust particle-filter-based indoor positioning algorithm. In the proposed algorithm, an outlier detection method is proposed for delayed measurement identification, and a constrained particle sampling method is proposed to optimize the distribution of the predicted particles. The proposed algorithm is assessed rigorously through testing. The test results show that the proposed algorithm can effectively identify delayed range measurements, mitigate their effects on position estimation, and improve positioning accuracy.

P. Rao, P. Rao, Y. Wang et al.

<p>Land surface soil moisture (SM) plays a critical role in hydrological processes and terrestrial ecosystems in desertification areas. Passive microwave remote-sensing products such as the Soil Moisture Active Passive (SMAP) satellite have been shown to monitor surface soil water well. However, the coarse spatial resolution and lack of full coverage of these products greatly limit their application in areas undergoing desertification. In order to overcome these limitations, a combination of multiple machine learning methods, including multiple linear regression (MLR), support vector regression (SVR), artificial neural networks (ANNs), random forest (RF) and extreme gradient boosting (XGB), have been applied to downscale the 36 km SMAP SM products and produce higher-spatial-resolution SM data based on related surface variables, such as vegetation index and surface temperature. Desertification areas in northern China, which are sensitive to SM, were selected as the study area, and the downscaled SM with a resolution of 1 km on a daily scale from 2015 to 2020 was produced. The results showed a good performance compared with in situ observed SM data, with an average unbiased root mean square error value of 0.057 m<span class="inline-formula">³</span> m<span class="inline-formula">⁻³</span>. In addition, their time series were consistent with precipitation and performed better than common gridded SM products. The data can be used to assess soil drought and provide a reference for reversing desertification in the study area. This dataset is freely available at <a href="https://doi.org/10.6084/m9.figshare.16430478.v6">https://doi.org/10.6084/m9.figshare.16430478.v6</a> (Rao et al., 2022).</p>

Xiaowen Zhang, Fangping Tang, Yueting Chen et al.

A bidirectional axial flow pump can realize bidirectional pumping, which has a wide application prospect in coastal low-head pumping stations and water jet propulsion systems. In this paper, a typical bidirectional axial flow pump is taken as the research object, and the hydraulic model of the bidirectional axial flow pump is manufactured. The hydrodynamic characteristics of the bidirectional axial flow pump are tested on the high-precision hydraulic mechanical test bench, including the positive and negative directions. In the experiment, multiple pressure pulsation monitoring points were arranged in the impeller chamber, and the pressure fluctuations in the pump under a total of 42 flow conditions were measured by a micro pressure pulsation sensor, involving 21 working conditions of forward operation and 21 working conditions of reverse operation. According to the experimental results, the hydrodynamic characteristics, especially the pressure pulsation characteristics in the pump, of the two-way axial flow pump under positive and negative operation are comprehensively compared and analyzed, and the energy characteristics and the propagation law of pressure pulsation of the two-way axial flow pump under positive and negative operation are revealed. The research results provide an important reference for the safe and stable operation of coastal bidirectional axial flow pump stations.