Hasil untuk "Hydraulic engineering"

B. Lecampion, A. Bunger, Xi Zhang

Development of numerical methods for hydraulic fracture simulation has accelerated in the past two decades. Recent advances in hydraulic fracture modeling and simulation are driven by increased industry and research activity in oil and gas, a drive toward consideration of more complex behaviors associated with layered and naturally-fractured rock formations, and a deepening understanding of the underlying mathematical model and its intrinsic challenges. Here we review the basic approaches being employed. Some of these comprise enhancements of classical methods, while others are imported from other fields of mechanics but are completely new in their application to hydraulic fracturing. After a description of the intrinsic challenges associated with the mechanics of fluid-driven fractures, we discuss both continuum and meso-scales numerical methods as well as engineering models which typically make use of additional assumptions to reduce computational cost. We pay particular attention to the verification and validation of numerical models, which is increasingly enabled by an ever-expanding library of laboratory experiments and analytical solutions for simple geometries in a number of different propagation regimes. A number of challenges remain and are amplified with a drive toward fully-coupled, three-dimensional hydraulic fracture modeling that accounts for host-rock heterogeneity. In the context of such a drive to complex models, we argue that the importance of best-practice development that includes careful verification and validation is vital to ensure progress is constrained by the appropriate underlying physics and mathematics with a constant attention to identifying conditions under which simpler models suffice for the intended modeling purposes.

Peixin Gao, Tao Yu, Yuanlin Zhang et al.

Abstract Vibrations in aircraft hydraulic pipeline system, due to multi-source excitation of high fluid pressure fluctuation and serious vibration environment of airframe, can cause the pipeline system vibration failures through overload in engineering field. Controlling the vibrations in hydraulic pipeline is a challenging work to ensure the flight safety of aircraft. The common vibration control technologies have been demonstrated to be effective in typical structures such as aerospace structures, shipbuilding structures, marine offshore structures, motor structures, etc. However, there are few research literatures on vibration control strategies of aircraft hydraulic pipeline. Combining with the development trend of aircraft hydraulic pipeline system and the requirement of vibration control technologies, this paper provides a detailed review on the current vibration control technologies in hydraulic pipeline system. A review of the general approaches following the passive and active control technologies are presented, which are including optimal layout technique of pipeline and clamps, constrained layer damping technique, vibration absorber technique, hydraulic hose technique, optimal pump structure technique, and active vibration control technique of pipeline system. Finally, some suggestions for the application of vibration control technologies in engineering field are given.

Shengnan Tang, Yong Zhu, Shouqi Yuan

Hydraulic axial piston pump is broadly-used in aerospace, ocean engineering and construction machinery since it is the vital component of fluid power systems. In the light of the undiscoverability of its fault and the potential serious losses, it is valuable and challenging to complete the fault identification of a hydraulic pump accurately and effectively. Owing to the limitations of shallow machine learning methods in the intelligent fault diagnosis, more attention has been paid to deep learning methods. Hyperparameter plays an important role in a deep learning model. Although some manual tuning methods may represent good results in some cases, it is hard to reproduce due to the differences of datasets and other factors. Hence, Bayesian optimization (BO) algorithm is adopted to automatically select the hyperparameters. Firstly, the time-frequency images of vibration signals by continuous wavelet transform are taken as input data. Secondly, by setting some hyperparameters, a preliminary convolutional neural network (CNN) model is established. Thirdly, by identifying the range of each hyperparameter, BO based on Gaussian process is employed to construct an adaptive CNN model named CNN-BO. The performance of CNN-BO is verified by comparing with traditional LeNet 5 and improved LeNet 5 with manual optimization. The results indicate that CNN-BO can accomplish the intelligent fault diagnosis of a hydraulic pump accurately.

Daniel Rodriguez-Cardenas, Xiaochang Li, Marcos Macedo et al.

Large language models for code are advancing fast, yet our ability to evaluate them lags behind. Current benchmarks focus on narrow tasks and single metrics, which hide critical gaps in robustness, interpretability, fairness, efficiency, and real-world usability. They also suffer from inconsistent data engineering practices, limited software engineering context, and widespread contamination issues. To understand these problems and chart a path forward, we combined an in-depth survey of existing benchmarks with insights gathered from a dedicated community workshop. We identified three core barriers to reliable evaluation: the absence of software-engineering-rich datasets, overreliance on ML-centric metrics, and the lack of standardized, reproducible data pipelines. Building on these findings, we introduce BEHELM, a holistic benchmarking infrastructure that unifies software-scenario specification with multi-metric evaluation. BEHELM provides a structured way to assess models across tasks, languages, input and output granularities, and key quality dimensions. Our goal is to reduce the overhead currently required to construct benchmarks while enabling a fair, realistic, and future-proof assessment of LLMs in software engineering.

Paloma Guenes, Rafael Tomaz, Maria Teresa Baldassarre et al.

The Impostor Phenomenon (IP) impacts a significant portion of the Software Engineering workforce, yet it is often viewed primarily through an internal individual lens. In this position paper, we propose framing the prevalence of IP as a form of Human Debt and discuss the relation with the ICSE2026 Pre Survey on the Future of Software Engineering results. Similar to technical debt, which arises when short-term goals are prioritized over long-term structural integrity, Human Debt accumulates due to gaps in psychological safety and inclusive support within socio-technical ecosystems. We observe that this debt is not distributed equally, it weighs heavier on underrepresented engineers and researchers, who face compounded challenges within traditional hierarchical structures and academic environments. We propose cultural refactoring, transparency and active maintenance through allyship, suggesting that leaders and institutions must address the environmental factors that exacerbate these feelings, ensuring a sustainable ecosystem for all professionals.

Emma Asbridge, Claire Krause, Richard Lucas et al.

Tropical cyclones can significantly impact mangrove forests, with some recovering rapidly, whilst others may change permanently. Inconsistent approaches to quantifying these impacts limit the capacity to identify patterns of damage and recovery across landscapes and cyclone categories. Understanding these patterns is critical as the changing frequency and intensity of cyclones and compounding effects of climate change, particularly sea-level rise, threaten mangroves and their ecosystem services. Improvements in Earth observation data, particularly satellite-based sensors and datacube environments, have enhanced capacity to classify time-series data and advanced landscape monitoring. Using the Landsat archive within Digital Earth Australia to monitor annual changes in canopy cover and extent, this study aims to quantify and classify immediate and long-term impacts of category 3–5 cyclones for mangroves in Australia. Closed canopy mangrove forests experienced the greatest immediate impact (loss of canopy cover). Most immediate impacts were minor, implying limited immediate mortality. Impacts varied spatially, reflecting proximity to exposed coastlines, cyclone track and forest structure (height, density, condition and species). Recovery was evident across all cyclones, although some areas exhibited permanent damage. Understanding the impacts and characteristics of vulnerable and resilient forests is crucial for managers tasked with protecting mangroves and their services as the climate changes.

María Victoria Mitre Núñez, Luis Roberto Alfaro De Arcia, Denisse Morales De León

Conocer el estado de los cuerpos de agua, tanto superficiales como subterráneos, es fundamental para la gestión adecuada de las cuencas prioritarias del país, como la del río Guararé, en Panamá. El objetivo de este proyecto fue establecer la relación entre las porquerizas, los puntos de contaminación y su posible impacto en la calidad del agua. Para ello, se realizaron muestreos en puntos específicos de la cuenca y se utilizaron herramientas de Sistemas de Información Geográfica (SIG). La investigación buscó identificar fuentes de contaminación y comprender cómo afectan al ecosistema acuático de la región. Se llevaron a cabo dos campañas de muestreo, con análisis de calidad de agua realizados en sitio y en laboratorio. Estos estudios permitieron obtener datos sobre los parámetros críticos de calidad hídrica. Posteriormente, se elaboraron mapas de contaminación con el objetivo de identificar y visualizar sitios críticos y potencialmente críticos en la subcuenca. Los resultados muestran que, aunque existe cierta correlación entre la densidad de porquerizas y algunos parámetros de calidad de agua muestreados, la contaminación hídrica parece estar más asociada a la concentración poblacional y otras actividades humanas. Estos hallazgos sirven de base para establecer estrategias de intervención, promover la gestión integrada del recurso hídrico en la región y reducir los impactos negativos sobre los cuerpos de agua.

Dong Li, Min Zhao, Hailong Zhang et al.

The inland water portion of the carbon cycle is an essential component of the global carbon cycle and is a promising direction to seek missing carbon sinks. Inland waters fix inorganic carbon to form autochthonous organic carbon (Auto-OC) and accept laterally transferred terrestrial OC. Calculating the carbon sink flux of inland water requires a quantitative estimation of the proportion of the aforementioned processes. In the current study, n-alkanes are used as biomarkers and the dual carbon isotope method (Bayesian mixing model) is applied to estimate the proportions of Auto-OC in the sediment of a simulation site comprising five shallow submerged macrophyte-dominated subsystems. The study results showed that a high proportion of Auto-OC was present in all sediment, regardless of the season or subsystem. However, the proportions were higher in the warm-humid season than in the cold-dry season. Results from a correlation analysis showed that temperature-controlled seasonal variations in the photosynthetic strength of aquatic organisms are the most likely cause of this difference. The average deposition rates of total organic carbon and Auto-OC were high (66.7 and 58.2 g C/m2/yr, respectively). Throughout the year, the weighted average percentage of Auto-OC ranged from 76% to 90%, with a mean value of 86% in the five aquatic subsystems. Establishing and maintaining submerged macrophyte-dominated systems have a potential of decreasing carbon dioxide (CO2) evasion and sequestrating more carbon (C) in headwaters. Working for clear submerged macrophyte-dominated lakes is beneficial for increasing carbon sinks.

Marvin Wyrich, Lloyd Montgomery

A well-rounded software engineer is often defined by technical prowess and the ability to deliver on complex projects. However, the narrative around the ideal Software Engineering (SE) candidate is evolving, suggesting that there is more to the story. This article explores the non-technical aspects emphasized in SE job postings, revealing the sociotechnical and organizational expectations of employers. Our Thematic Analysis of 100 job postings shows that employers seek candidates who align with their sense of purpose, fit within company culture, pursue personal and career growth, and excel in interpersonal interactions. This study contributes to ongoing discussions in the SE community about the evolving role and workplace context of software engineers beyond technical skills. By highlighting these expectations, we provide relevant insights for researchers, educators, practitioners, and recruiters. Additionally, our analysis offers a valuable snapshot of SE job postings in 2023, providing a scientific record of prevailing trends and expectations.

Timo Kehrer, Robert Haines, Guido Juckeland et al.

Anecdotal evidence suggests that Research Software Engineers (RSEs) and Software Engineering Researchers (SERs) often use different terminologies for similar concepts, creating communication challenges. To better understand these divergences, we have started investigating how SE fundamentals from the SER community are interpreted within the RSE community, identifying aligned concepts, knowledge gaps, and areas for potential adaptation. Our preliminary findings reveal opportunities for mutual learning and collaboration, and our systematic methodology for terminology mapping provides a foundation for a crowd-sourced extension and validation in the future.

Laisheng Huang, Bo Li, Bo Wang et al.

As a commonly used and effective technology for increasing the permeability of coal–rock reservoirs, hydraulic fracturing has been widely used in engineering sites to realize the efficient exploitation and utilization of gas resources in coal–rock reservoirs. The core of hydraulic fracturing is the initiation, propagation, and path of hydraulic cracks. In this paper, the combination of true triaxial physical test and numerical simulation is used to study the influence of coal bedding characteristics on the crack propagation of hydraulic fracturing and to discuss the important role of bedding in hydraulic crack formation. Results show that the control effect of the coal bedding dip angle on the hydraulic crack propagation under the same stress conditions is stronger than that of the maximum principal stress, and the control effect of the bedding on the crack propagation is weaker under the bedding dip angles of 0° and 90°. Reasonable fracturing fluid displacement setting is conducive to the formation of complex hydraulic fracture network structure, small displacement is conducive to the opening of primary natural fractures, and large displacement is conducive to hydraulic cracks that pass through the structural surface and the coal–rock interface. Global and local methods of finite element mesh embedding zero-thickness cohesion element and a pore-pressure node merging method to simulate fracturing are established using Python language and ABAQUS numerical analysis platform, respectively. The numerical simulation results suggest that the main fractures are formed along the principal stress direction, and the secondary branch fractures are formed along the bedding direction under the condition wherein the coal bedding dip angle is 30°. Under the conditions of different stress fields and fracturing fluid discharges, the controlling effect of bedding on hydraulic fracture is closely related to the fracturing parameters. 1. A cohesive element method is proposed to simulate the seam network of coal and rock mass. 2. The cohesive element hydraulic fracturing numerical model of bedding coal fracture network hydraulic fracturing is established. 3. The effect of bedding angle on crack growth under water pressure is studied by combining true triaxial test with numerical simulation.

Sanjeev Kumar Gupta, Vijay Kumar Dwivedi

Understanding the intricate dynamics of hydraulic jumps in sloped channels holds pivotal importance in various engineering applications. This research explores the intricate relationship between the size of the bed material and the basic properties of hydraulic jumps, providing insight into the relative jump length, height, and energy efficiency. The goal of the research is to get important knowledge that will be useful for optimizing hydraulic systems and enhancing their overall efficiency in diverse engineering domains. This study used an open-channel flow arrangement with four-bed slopes (0° to 6°) and three irregularity heights (10 to 30 mm). During the investigation, the Froude number differed from 2.30 to 8.85 and the Reynolds number differed from 5450 to 25500. A novel instinctive technique was used to create correlations for different hydraulic jump characteristics in roughen-bed inclined channels. The study examines the combined effects of roughness and slope of the bed, and it was discovered that the relative jump height and efficiency of hydraulic jump increase by 19.37% and 8.44% respectively while the relative jump length decreases by 23.05% with an increase in bed slope from 0° to 6°. The relative jump height and efficiency of the hydraulic jump increase by 14.20% and 21.06% respectively while the relative jump length decreases by 29.09% with a rise in bed roughness from 0 to 30 mm.

Yong Zhu, Hongsheng Su, Shengnan Tang et al.

Since the hydraulic axial piston pump is the engine that drives hydraulic transmission systems, it is widely utilized in aerospace, marine equipment, civil engineering, and mechanical engineering. Operating safely and dependably is crucial, and failure poses a major risk. Hydraulic axial piston pump malfunctions are characterized by internal concealment, challenging self-adaptive feature extraction, and blatant timing of fault signals. By completely integrating the time-frequency feature conversion capability of synchrosqueezing wavelet transform (SWT), the feature extraction capability of VGG11, as well as the feature memory capability of the long short-term memory (LSTM) model, a novel intelligent fault identification method is proposed in this paper. First, the status data are transformed into two dimensions in terms of time and frequency by using SWT. Second, the depth features of the time–frequency map are obtained and dimensionality reduction is carried out by using the deep feature mining capability of VGG11. Third, LSTM is added to provide the damage identification model for long-term memory capabilities. The Softmax layer is utilized for the intelligent evaluation of various damage patterns and health state. The proposed method is utilized to identify and diagnose five typical states, including normal state, swash plate wear, sliding slipper wear, loose slipper, and center spring failure, based on the externally observed vibration signals of a hydraulic axial piston pump. The results indicate that the average test accuracy for five typical state signals reaches 99.43%, the standard deviation is 0.0011, and the average test duration is 2.675 s. The integrated model exhibits improved all-around performance when compared to LSTM, LeNet-5, AlexNet, VGG11, and other typical models. The proposed method is validated to be efficient and accurate for the intelligent identification of common defects of hydraulic axial piston pumps.

Johan Cederbladh, Antonio Cicchetti

In this paper we discuss the growing need for system behaviour to be validated and verified (V&V'ed) early in model-based systems engineering. Several aspects push companies towards integration of techniques, methods, and processes that promote specific and general V&V activities earlier to support more effective decision-making. As a result, there are incentives to introduce new technologies to remain competitive with the recently drastic changes in system complexity and heterogeneity. Performing V&V early on in development is a means of reducing risk for later error detection while moving key activities earlier in a process. We present a summary of the literature on early V&V and position existing challenges regarding potential solutions and future investigations. In particular, we reason that the software engineering community can act as a source for inspiration as many emerging technologies in the software domain are showing promise in the wider systems domain, and there already exist well formed methods for early V&V of software behaviour in the software modelling community. We conclude the paper with a road-map for future research and development for both researchers and practitioners to further develop the concepts discussed in the paper.

Oleksandr Kosenkov, Michael Unterkalmsteiner, Jannik Fischbach et al.

Context: Regulatory acts are a challenging source when eliciting, interpreting, and analyzing requirements. Requirements engineers often need to involve legal experts who, however, may often not be available. This raises the need for approaches to regulatory Requirements Engineering (RE) covering and integrating both legal and engineering perspectives. Problem: Regulatory RE approaches need to capture and reflect both the elementary concepts and relationships from a legal perspective and their seamless transition to concepts used to specify software requirements. No existing approach considers explicating and managing legal domain knowledge and engineering-legal coordination. Method: We conducted focus group sessions with legal researchers to identify the core challenges to establishing a regulatory RE approach. Based on our findings, we developed a candidate solution and conducted a first conceptual validation to assess its feasibility. Results: We introduce the first version of our Artifact Model for Regulatory Requirements Engineering (AM4RRE) and its conceptual foundation. It provides a blueprint for applying legal (modelling) concepts and well-established RE concepts. Our initial results suggest that artifact-centric RE can be applied to managing legal domain knowledge and engineering-legal coordination. Conclusions: The focus groups that served as a basis for building our model and the results from the expert validation both strengthen our confidence that we already provide a valuable basis for systematically integrating legal concepts into RE. This overcomes contemporary challenges to regulatory RE and serves as a basis for exposure to critical discussions in the community before continuing with the development of tool-supported extensions and large-scale empirical evaluations in practice.

Kai Wang, Guodong Zhang, Yanhai Wang et al.

Hydraulic fracturing and permeability enhancement are effective methods to improve low-permeability coal seams. However, few studies focused on methods to increase permeability, and there are no suitable prediction methods for engineering applications. In this work, PFC2D software was used to simulate coal seam hydraulic fracturing. The results were used in a coupled mathematical model of the interaction between coal seam deformation and gas flow. The results show that the displacement and velocity of particles increase in the direction of minimum principal stress, and the cracks propagate in the direction of maximum principal stress. The gas pressure drop rate and permeability increase rate of the fracture model are higher than that of the non-fracture model. Both parameters decrease rapidly with an increase in the drainage time and approach 0. The longer the hydraulic fracturing time, the more complex the fracture network is, and the faster the gas pressure drops. However, the impact of fracturing on the gas drainage effect declines over time. As the fracturing time increases, the difference between the horizontal and vertical permeability increases. However, this difference decreases as the gas drainage time increases. The higher the initial void pressure, the faster the gas pressure drops, and the greater the permeability increase is. However, the influence of the initial void pressure on the permeability declines over time. The research results provide guidance for predicting the anti-reflection effect of hydraulic fracturing in underground coal mines.

M. Stosiak, M. Karpenko, A. Deptuła et al.

This paper identifies mechanical vibrations occurring in the operating environment of hydraulic systems used in marine engineering. Particular attention was paid to the influence of periodic vibrations on changes in the amplitude-frequency spectrum in a marine hydraulic system. For the case of analysing the effect of vibration on changes in the pressure pulsation spectrum with a proportional directional valve, a modified mathematical model was used. Experimental results were presented and compared with the results obtained from the mathematical model. A way of limiting the transmission of vibrations to the directional control valve body was proposed.

Kyle A. Lethander, Clark N. Taylor

To understand the error sources present in inertial sensors, both the white (time-invariant) and correlated noise sources must be properly characterized. To understand both sources, the standard approach (IEEE standards 647-2006, 952-2020) is to compute the Allan variance of the noise and then use human-based interpretation of linear trends to estimate the separate noise sources present in a sensor. Recent work has sought to overcome the graphical nature and visual-inspection basis of this approach leading to more accurate noise estimates. However, when using noise characterization in a filter, it is important that the noise estimates be not only accurate but also conservative, i.e., that the estimated noise parameters overbound truth. In this paper, we propose a novel method for automatically estimating conservative noise parameters using the Allan variance. Results of using this method to characterize a low-cost MEMS IMU (Analog Devices ADIS16470) are presented, demonstrating the efficacy of the proposed approach.

Bishal Lakha, Kalyan Bhetwal, Nasir U. Eisty

Context: On top of the inherent challenges startup software companies face applying proper software engineering practices, the non-deterministic nature of machine learning techniques makes it even more difficult for machine learning (ML) startups. Objective: Therefore, the objective of our study is to understand the whole picture of software engineering practices followed by ML startups and identify additional needs. Method: To achieve our goal, we conducted a systematic literature review study on 37 papers published in the last 21 years. We selected papers on both general software startups and ML startups. We collected data to understand software engineering (SE) practices in five phases of the software development life-cycle: requirement engineering, design, development, quality assurance, and deployment. Results: We find some interesting differences in software engineering practices in ML startups and general software startups. The data management and model learning phases are the most prominent among them. Conclusion: While ML startups face many similar challenges to general software startups, the additional difficulties of using stochastic ML models require different strategies in using software engineering practices to produce high-quality products.

Kelechi G. Kalu, Taylor R. Schorlemmer, Sophie Chen et al.

The primary theory of software engineering is that an organization's Policies and Processes influence the quality of its Products. We call this the PPP Theory. Although empirical software engineering research has grown common, it is unclear whether researchers are trying to evaluate the PPP Theory. To assess this, we analyzed half (33) of the empirical works published over the last two years in three prominent software engineering conferences. In this sample, 70% focus on policies/processes or products, not both. Only 33% provided measurements relating policy/process and products. We make four recommendations: (1) Use PPP Theory in study design; (2) Study feedback relationships; (3) Diversify the studied feedforward relationships; and (4) Disentangle policy and process. Let us remember that research results are in the context of, and with respect to, the relationship between software products, processes, and policies.