Hasil untuk "Hydraulic engineering"

Alfonso Arrieta-Pastrana, Edwin A. Martínez-Padilla, Modesto Pérez-Sánchez et al.

Currently, hydrodynamic models for bay and estuarine systems involve many parameters that require proper calibration to design coastal structures effectively. However, in coastal regions with limited data availability, the implementation of such models becomes challenging. This research introduces a simplified hydrodynamic methodology designed to analyse the impact of hydraulic control structures in shallow waters. This approach offers a computationally efficient alternative that allows engineers to rapidly evaluate the impact of horizontal and vertical constrictions in shallow waters experiencing wave propagation. A practical application is demonstrated in a one-dimensional channel with a length of 200,000 m and an average depth of 5 m. The only parameter required for calibration in the proposed methodology is bed friction. The three analysed scenarios—longitudinal constriction, plan-view constriction, and the influence of bed friction—demonstrate the model’s sensitivity to these variations, highlighting its reliability as a decision-making tool for coastal engineering projects. Moreover, the comparison of the proposed hydrodynamic simulation methodology at the stabilised tidal inlet structure in Cartagena de Indias, Colombia, demonstrated its ability to reproduce observed water levels accurately, reinforcing its reliability and potential for broader application.

LI Meng-yu, LÜ Chao-fan, LU Jin-you, LUAN Hua-long, ZHU Yong-hui, ZHU Jia-xi, GE Jian-zhong, Makiko Iguchi

[Objective] Freak wave is a marine disaster characterized by extremely large wave height, strong nonlinearity, and high destructiveness. The results of wave superposition method for simulating freak waves are influenced by multiple parameters, and the sensitivity and interaction mechanisms of these factors require systematic investigation. [Methods] Based on a self-developed viscous-flow numerical wave tank, we conducted a numerical simulation on the generation of freak waves and their influencing factors. First, the reliability of the numerical model was verified against physical experimental data. Subsequently, the harmonic separation method was employed to examine the influence of wave group nonlinearity on wave surface deformation, focusing characteristics, and frequency spectrum structure. Through numerical experiments, the effects of key parameters—including spectral type, number of constituent waves, spectral bandwidth, spectral peak frequency, and water depth—were investigated. [Results] 1) During the generation of a freak wave, wave-wave nonlinear interactions caused energy to transfer from the primary frequency to both high and low frequencies, resulting in significant spectral broadening. Low-frequency free pseudo-harmonics propagated faster, leading to an actual wave height slightly larger than the theoretical value. High-frequency bound harmonics formed a tail wave, which had a minor influence on the shape of the main peak. 2) The spectral type significantly influenced the wave profile characteristics: the JONSWAP and P-M spectra, with concentrated energy, tended to generate freak waves with steep crests. The CWA spectrum produced gentle wave profiles; the CWS spectrum yielded the smallest focused amplitude. 3) The number of constituent waves affected the focusing recurrence period. An insufficient number could generate secondary focused waves. It was recommended to use 29 constituent waves to balance computational accuracy and efficiency. 4) Under finite water depth conditions, the focused amplitude reached its maximum when the spectral bandwidth was 0.7 Hz, indicating that the amplitude was co-modulated by the spectral bandwidth, water depth, and spectral peak frequency. 5) An increase in the spectral peak frequency enhanced nonlinearity, resulting in wave profile steepening. However, an excessively high frequency led to wave breaking, thereby reducing the amplitude. 6) Water depth influenced the wave profile by altering the dispersion characteristics. A greater water depth resulted in faster wave speed and a higher amplitude, whereas an excessively small water depth readily induced wave breaking. [Conclusion] The main innovations of this research include: establishing a high-precision viscous-flow numerical model capable of accurately simulating the evolution of nonlinear waves including breaking effects; employing the harmonic separation method to reveal the influence mechanism of wave group nonlinearity on wave surface structure and energy distribution; and clarifying the coupling effects of various factors under finite water depth conditions through multi-parameter sensitivity experiments. The findings of this study deepen the understanding of freak wave generation mechanisms, provide an important theoretical basis and parameter selection guidance for laboratory simulation of freak waves.

FU Jian-jun, LI Yun-qi, YUAN Li, CHEN Peng, GONG Rou-yan

[Objective] To address the mismatch between traditional rainfall analysis methods (April to October) for hilly irrigation areas in south China and actual intra-seasonal water demand during rice growth stages (late rice from July to October), this study focuses on intra-seasonal rainfall during the rice growth stages, integrating GIS technology to investigate the water supply reliability of the Maweizao irrigation area. [Methods] Using daily meteorological data from 1989 to 2019 in the irrigation area, the intra-seasonal rainfall frequency analysis method was employed to identify typical representative years and characteristic values for normal years (P=50%), moderately dry years (P=75%), and dry years (P=90%). The FAO Penman-Monteith method and water balance method were then used to calculate the crop water requirements and net irrigation water requirements for rice. [Results]The results showed that: (1) In dry years, the intra-seasonal rainfall during the late rice growth stages (160 mm) accounted for only 21.2% of the total rainfall from April to October (755 mm). Moreover, a mismatch was observed between the rainfall peak (August) and the critical water demand period (booting to heading stage, September). This led to 14% higher net field irrigation water requirements (560 mm) calculated by intra-seasonal rainfall frequency analysis compared to traditional methods, accurately reflecting the typical contradiction in hilly irrigation areas where there was “no rain during water demand periods but excessive rain during non-demand periods.” (2) GIS-based spatial simulations revealed a distinct bimodal structure in the irrigation area during dry years. Croplands near the main water source (Maweizao Reservoir) benefited from sufficient storage capacity (27.02 million m3) and a canal system integrity rate above 85%, achieving a water supply reliability rate greater than 80%, thus forming a high-yield and stable-production core zone. Areas dependent on small reservoirs for water regulation and storage, where storage capacity utilization declined to 60% due to sedimentation, had a water supply reliability rate of 60%-80%. Limited by scattered ponds (406 ponds), insufficient catchment areas (<5 km2 per pond), and damaged main and lateral canals (integrity rate <40%), the overall reliability rates dropped below 40%, posing a high risk of yield reduction. (3) For every 10% increase in water supply reliability rate, late rice yield increased by 35-50 kg per mu(1mu≈666.67 m2), showing a significant positive linear correlation (R2=0.89). When the reliability rate exceeded 80%, soil water content remained stable at 18%-24% (optimal range for rice growth), resulting in yields of 400-500 kg per mu.When the reliability rate fell below 40%, soil water content dropped sharply below 10%, leading to plant wilting or even total crop failure (yield <200 kg per mu). Within the 60%-80% range of reliability rate, each 1 m3 irrigation water increase produced an extra 1.2-1.5 kg of rice, indicating optimal resource use efficiency. [Conclusion] By focusing on intra-seasonal rainfall during rice growth stages, this study reveals the underlying mechanism of irrigation water supply-demand imbalance in hilly irrigation areas and proposes the following three practical strategies. Over 70% irrigation water should be allocated during the booting to heading stages (September) based on crop water requirements, with priority given to areas maintaining water supply reliability rates above 60%. For areas with water supply reliability rates below 40%, the “pond desilting + intelligent water control” project should be implemented to increase small water source utilization rate from 45% to 75%, while restoring main and lateral canals to achieve an integrity rate above 60%. By focusing on intra-seasonal rainfall during rice growth stages, this study provides a scientific basis for precise irrigation management and confirmation of agricultural water use rights in hilly irrigation areas, holding important practical significance for optimizing water resource allocation and enhancing grain production capacity.

Fahim Hafiz, Md Jahidul Hoq Emon, Md Abid Hossain et al.

This paper proposes a novel curriculum for the microprocessors and microcontrollers laboratory course. The proposed curriculum blends structured laboratory experiments with an open-ended project phase, addressing complex engineering problems and activities. Microprocessors and microcontrollers are ubiquitous in modern technology, driving applications across diverse fields. To prepare future engineers for Industry 4.0, effective educational approaches are crucial. The proposed lab enables students to perform hands-on experiments using advanced microprocessors and microcontrollers while leveraging their acquired knowledge by working in teams to tackle self-defined complex engineering problems that utilize these devices and sensors, often used in the industry. Furthermore, this curriculum fosters multidisciplinary learning and equips students with problem-solving skills that can be applied in real-world scenarios. With recent technological advancements, traditional microprocessors and microcontrollers curricula often fail to capture the complexity of real-world applications. This curriculum addresses this critical gap by incorporating insights from experts in both industry and academia. It trains students with the necessary skills and knowledge to thrive in this rapidly evolving technological landscape, preparing them for success upon graduation. The curriculum integrates project-based learning, where students define complex engineering problems for themselves. This approach actively engages students, fostering a deeper understanding and enhancing their learning capabilities. Statistical analysis shows that the proposed curriculum significantly improves student learning outcomes, particularly in their ability to formulate and solve complex engineering problems, as well as engage in complex engineering activities.

Bertrand Meyer

Software engineering concepts and processes are worthy of formal study; and yet we seldom formalize them. This "research ideas" article explores what a theory of software engineering could and should look like. Software engineering research has developed formal techniques of specification and verification as an application of mathematics to specify and verify systems addressing needs of various application domains. These domains usually do not include the domain of software engineering itself. It is, however, a rich domain with many processes and properties that cry for formalization and potential verification. This article outlines the structure of a possible theory of software engineering in the form of an object-oriented model, isolating abstractions corresponding to fundamental software concepts of project, milestone, code module, test and other staples of our field, and their mutual relationships. While the presentation is only a sketch of the full theory, it provides a set of guidelines for how a comprehensive and practical Theory of Software Engineering should (through an open-source community effort) be developed.

Xiaowen Tao, Yinuo Wang, Jinzhao Zhou

End-to-end reinforcement learning (RL) for motion control trains policies directly from sensor inputs to motor commands, enabling unified controllers for different robots and tasks. However, most existing methods are either blind (proprioception-only) or rely on fusion backbones with unfavorable compute-memory trade-offs. Recurrent controllers struggle with long-horizon credit assignment, and Transformer-based fusion incurs quadratic cost in token length, limiting temporal and spatial context. We present a vision-driven cross-modal RL framework built on SSD-Mamba2, a selective state-space backbone that applies state-space duality (SSD) to enable both recurrent and convolutional scanning with hardware-aware streaming and near-linear scaling. Proprioceptive states and exteroceptive observations (e.g., depth tokens) are encoded into compact tokens and fused by stacked SSD-Mamba2 layers. The selective state-space updates retain long-range dependencies with markedly lower latency and memory use than quadratic self-attention, enabling longer look-ahead, higher token resolution, and stable training under limited compute. Policies are trained end-to-end under curricula that randomize terrain and appearance and progressively increase scene complexity. A compact, state-centric reward balances task progress, energy efficiency, and safety. Across diverse motion-control scenarios, our approach consistently surpasses strong state-of-the-art baselines in return, safety (collisions and falls), and sample efficiency, while converging faster at the same compute budget. These results suggest that SSD-Mamba2 provides a practical fusion backbone for resource-constrained robotic and autonomous systems in engineering informatics applications.

Alexandros Gazis, Ioannis Papadongonas, Athanasios Andriopoulos et al.

This article provides a comprehensive overview of sensors commonly used in low-cost, low-power systems, focusing on key concepts such as Internet of Things (IoT), Big Data, and smart sensor technologies. It outlines the evolving roles of sensors, emphasizing their characteristics, technological advancements, and the transition toward "smart sensors" with integrated processing capabilities. The article also explores the growing importance of mini-computing devices in educational environments. These devices provide cost-effective and energy-efficient solutions for system monitoring, prototype validation, and real-world application development. By interfacing with wireless sensor networks and IoT systems, mini-computers enable students and researchers to design, test, and deploy sensor-based systems with minimal resource requirements. Furthermore, this article examines the most widely used sensors, detailing their properties and modes of operation to help readers understand how sensor systems function. The aim of this study is to provide an overview of the most suitable sensors for various applications by explaining their uses and operations in simple terms. This clarity will assist researchers in selecting the appropriate sensors for educational and research purposes or understanding why specific sensors were chosen, along with their capabilities and possible limitations. Ultimately, this research seeks to equip future engineers with the knowledge and tools needed to integrate cutting-edge sensor networks, IoT, and Big Data technologies into scalable, real-world solutions.

Jianjun Zhao

Quantum computing has demonstrated the potential to solve computationally intensive problems more efficiently than classical methods. Many software engineering tasks, such as test case selection, static analysis, code clone detection, and defect prediction, involve complex optimization, search, or classification, making them candidates for quantum enhancement. In this paper, we introduce Quantum-Based Software Engineering (QBSE) as a new research direction for applying quantum computing to classical software engineering problems. We outline its scope, clarify its distinction from quantum software engineering (QSE), and identify key problem types that may benefit from quantum optimization, search, and learning techniques. We also summarize existing research efforts that remain fragmented. Finally, we outline a preliminary research agenda that may help guide the future development of QBSE, providing a structured and meaningful direction within software engineering.

Hengjie Luan, Mingkang Liu, Qinglin Shan et al.

Natural fractures and cavities are the primary spaces for oil and gas accumulation in fracture-cavity carbonate reservoirs. Establishing the connection between these spaces and the wellbore through hydraulic fracturing treatment is important for oil and gas extraction from such reservoirs. Due to the discontinuity and heterogeneity of the existing natural fracture-cavity system, anticipating the viability of hydraulic fracturing treatment is troublesome. A new method to simulate the hydraulic fracturing propagation in fracture-cavity reservoirs is proposed based on the continuous damage theory. The method considers the random spatial distribution of fractures and cavities and can simulate the arbitrary expansion of hydraulic fractures in the three-dimensional direction. Based on this method, the influence of different geological and engineering factors on the propagation patterns of hydraulic fractures in the fracture-cavity reservoirs is investigated. It is found that the increase of reservoir burial depth significantly limits the propagation ranges of hydraulic fractures. The propagation modes of hydraulic fractures encountering natural fractures change with increasing burial depth, undergoing a transition from “penetrate and deflect” to ”defect” and then to ”penetrate”. The reduction of horizontal stress difference increases the complexity of hydraulic fractures, but it is not conducive for hydraulic fractures to connect more natural fractures and cavities. The increase in fracturing pump rate is significantly beneficial for hydraulic fractures to connect more natural fractures and cavities. The viscosity of fracturing fluid has a significant impact on the morphology of hydraulic fracture propagation, which undergoes a transition from simple to complex, and then to simple with the change of the fracturing fluid viscosity from low to high. either too high or too low viscosity of the fracturing fluid is not conducive to the connection of more natural fractures and cavities by hydraulic fractures. The obtained conclusions can provide a reference for the design of hydraulic fracturing treatment for fracture-cavity carbonate reservoirs.

علیرضا زارعی قورخودی, علی شاهنظری

هدف از این مطالعه اثرات تشکیل بازارهای آب بر ارتقای بهره‌وری آب در حوضه آبریز تجن می‌باشد. در این پژوهش از یک سیستم مدل‌سازی، مدل برنامه‌ریزی ریاضی و تابع هدف حداکثرسازی سود در محیط زبان برنامه‌نویسی متلب استفاده شد. پس از شبیه‌سازی تشکیل بازار آب، تأثیر آن بر شاخص‌های بهره‌وری فیزیکی و اقتصادی آب در دو گروه شامل مزارع بدون محدودیت آب (گروه A) و مزارع با محدودیت آب (گروه B) موردارزیابی قرار گرفت. براساس نتایج، تشکیل بازار آب منجر به افزایش 13 درصد سود در گروه (A) و 30 درصد سود در گروه (B) می‌شود. با توجه به نتایج، تشکیل بازار آب میزان مصرف آب در مزارع نماینده (A) و (B) را به‌ترتیب کاهش و افزایش می‌دهد. نتایج ارزیابی شاخص‌های بهره‌وری آب حاکی از آن است که در گروه (A) در دسترس‌بودن آب و در نتیجه افزایش سطح زیر کشت و در گروه (B) جبران کمبود آب و افزایش سطح زیر کشت منجر به افزایش بهره‌وری فیزیکی شده است. در مزارع گروه (A) فروش آب و در مزارع گروه (B) تخصیص آب به محصولات با ارزش اقتصادی بالاتر افزایش بهره‌وری اقتصادی آب را در پی داشته است. به‌طورکلی، می‌توان بیان نمود که تشکیل بازار آب موجب افزایش بهره‌وری می‎گردد، اما تنهایی منجر به‌دستدست‌یابی به کشاورزی پایدار و کاهش مصرف آب در سطح حوضه آبریز نمی‌شود. بنابراین اجرای سیاست‌های دیگر نظیر کنترل برداشت از منابع آب سطحی و زیرزمینی، تحویل حجمی آب براساس الگوی کشت بهینه و تخصیص آب به محصولات با ارزش اقتصادی بالاتر همراه با رویکرد بازار آب می‌تواند علاوه‌ بر کاهش مصرف آب، بهره‌وری آب را نیز ارتقا دهد.

Nelly Bencomo, Jordi Cabot, Marsha Chechik et al.

Modern software-based systems operate under rapidly changing conditions and face ever-increasing uncertainty. In response, systems are increasingly adaptive and reliant on artificial-intelligence methods. In addition to the ubiquity of software with respect to users and application areas (e.g., transportation, smart grids, medicine, etc.), these high-impact software systems necessarily draw from many disciplines for foundational principles, domain expertise, and workflows. Recent progress with lowering the barrier to entry for coding has led to a broader community of developers, who are not necessarily software engineers. As such, the field of software engineering needs to adapt accordingly and offer new methods to systematically develop high-quality software systems by a broad range of experts and non-experts. This paper looks at these new challenges and proposes to address them through the lens of Abstraction. Abstraction is already used across many disciplines involved in software development -- from the time-honored classical deductive reasoning and formal modeling to the inductive reasoning employed by modern data science. The software engineering of the future requires Abstraction Engineering -- a systematic approach to abstraction across the inductive and deductive spaces. We discuss the foundations of Abstraction Engineering, identify key challenges, highlight the research questions that help address these challenges, and create a roadmap for future research.

Xianlei Fu, Maozhi Wu, Sasthikapreeya Ponnarasu et al.

This research introduces a hybrid deep learning approach to perform real-time forecasting of passenger traffic flow for the metro railway system (MRS). By integrating long short-term memory (LSTM) and the graph convolutional network (GCN), a hybrid deep learning neural network named the graph convolutional memory network (GCMN) was constructed and trained for accurate real-time prediction of passenger traffic flow for the MRS. Data collected of the traffic flow in Delhi’s metro rail network system in the period from October 2012 to May 2017 were utilized to demonstrate the effectiveness of the developed model. The results indicate that (1) the developed method provides accurate predictions of the traffic flow with an average coefficient of determination (R²) of 0.920, RMSE of 368.364, and MAE of 549.527, and (2) the GCMN model outperforms state-of-the-art methods, including LSTM and the light gradient boosting machine (LightGBM). This study contributes to the state of practice in proposing a novel framework that provides reliable estimations of passenger traffic flow. The developed model can also be used as a benchmark for planning and upgrading works of the MRS by metro owners and architects.

Michael Dorner, Maximilian Capraro, Oliver Treidler et al.

The engineering of complex software systems is often the result of a highly collaborative effort. However, collaboration within a multinational enterprise has an overlooked legal implication when developers collaborate across national borders: It is taxable. In this article, we discuss the unsolved problem of taxing collaborative software engineering across borders. We (1) introduce the reader to the basic principle of international taxation, (2) identify three main challenges for taxing collaborative software engineering making it a software engineering problem, and (3) estimate the industrial significance of cross-border collaboration in modern software engineering by measuring cross-border code reviews at a multinational software company.

ZHANG Xiaoju, REN Dawei

For highly built-up urban areas,further improving the waterlogging prevention and control standards and refining the waterlogging prevention and control system with a limited land use space are problems demanding prompt investigation.Taking Shenzhen's improvement strategies for waterlogging prevention and control standards as an example,this paper analyzed the main points and applicability of several measures,including source optimization,vertical adjustment,improvement of pipe network standards,multi-aspect drainage system,diversified detention measures,and joint control of flood and waterlogging.By investigating representative basins,this paper also built a Mike Flood model to evaluate the effects of different waterlogging prevention and control schemes.The results show that an 85% reduction of waterlogging risk areas can be achieved by comprehensively applying the waterlogging prevention and control measures according to local conditions under a once-in-a-hundred-year rainstorm,indicating the efficacy of those measures.The results provide a reference for cities to develop improvement strategies for waterlogging prevention and control standards under similar conditions.

Zohreh Masoumi

Abstract In urban areas, flood susceptibility assessment is of special importance because of the high settlement population, properties, and infrastructures. Geospatial information science (GIS) provides a tool for investigating flood susceptibility based on several aspects including economic damages and critical infrastructures in cities. This study aims to provide a tool based on GIS analyses to support decision‐makers in identifying flood hazards in urban areas, in which previous flood data, flood causative factors, and urban infrastructure data are not adequately available. To assess flood susceptibility in the study area, the related spatial high‐resolution data were produced. Then, flood zones were estimated for different recurrence intervals using meteorological data. Finally, susceptibility was assessed in urban areas for different urban infrastructures using GIS modeling. The model was designed based on the assumption that any critical urban infrastructure, such as power towers, was affected by flood zones and, in addition to flooding, could cause hazards by itself. Moreover, five scenarios were defined to calculate susceptibility when in the problematic locations of the floodway. DoAsb Floodway was chosen as a case study located in Zanjan city, northwest of Iran. The results indicated the high‐susceptible areas around the floodway. Moreover, the flood susceptibility level for each urban infrastructure in the study area was calculated and classified into five classes from low susceptible to very high susceptible. Also, the results of the five scenarios showed if some parts of the floodway had problems, the susceptibility rate would be high. The generated flood susceptibility maps of this model can be used to plan suitable programs in order to avoid flood damage and ensure public safety.

LIU Yitao, WANG Jianda, SU Zhenguo, LI Shaogang, MO Yunlong, BI Huijie

Aiming at the problem that the small coal pillar roadway is affected by the lateral hanging roof of adjacent goaf in the mining process of kilometer gas mine, taking the small coal pillar roadway of 1208 working face in a mine as the research background. On the basis of engineering practice, this paper introduces the construction technology and method of double end plugging hydraulic fracturing technology in detail, and analyzes the engineering construction effect. The research results show that the double end plugging hydraulic fracturing technology can avoid the existence of fractures and achieve effective pressure maintenance, which is a better method for lateral hanging roof lag; based on borehole peeping, stress monitoring and analysis of mine pressure law, the cracks of surrounding rock are obviously developed after roof cutting, and the front overhanging roof affected by mining has been broken, which shows that the borehole stress meter data is significantly decreased, and the pressure at the lower part of the working face is significantly weakened under the influence of secondary mining, achieving a good effect.

Schouten Thijs, van Rhee Cees, Keetels Geert

In dredging applications, deep sea mining and land reclamation projects typically large amounts of sediments are transported through pipes in the form of hyper concentrated (40% sediment or more) sediment-water mixtures or slurries. In this paper it is investigated how well a generic Euler-Euler CFD-model is capable to model velocity, concentration profiles and the pressure gradient of sediment above deposition limit velocity in a pipeline. This Euler-Euler solver treats both phases as a continuum with its own momentum and continuity equations. The full kinetic theory for granular flows is accounted for (no algebraic form is used) and is combined with a buoyant k-ε turbulence model for the fluid phase. The influence of the mesh size has been checked and grid convergence is achieved. All numerical schemes used are of second-order accuracy in space. The pressure gradient was calibrated by adjusting the specularity coefficient in one calibration case and kept constant afterwards. Simulations were carried out in a wide range of slurry flow parameters, in situ volume concentration (9–42%), pipe diameter (0.05–0.90 m), particle diameter (90–440 μm) and flow velocity of (3–7 m/s). The model shows satisfactory agreement to experimental data from existing literature.

Changqing Wang, Zhoutian Fu, Lan Yang

Silicon photonics has been studied as an integratable optical platform where numerous applicable devices and systems are created based on modern physics and state-of-the-art nanotechnologies. The implementation of quantum mechanics has been the driving force of the most intriguing design of photonic structures, since the optical systems are found of great capability and potential in realizing the analogues of quantum concepts and phenomena. Non-Hermitian physics, which breaks the conventional scope of quantum mechanics based on Hermitian Hamiltonian, has been widely explored in the platform of silicon photonics, with promising design of optical refractive index, modal coupling and gain-loss distribution. As we will discuss in this chapter, the unconventional properties of exceptional points and parity-time symmetry realized in silicon photonics have created new opportunities for ultrasensitive sensors, laser engineering, control of light propagation, topological mode conversion, etc. The marriage between the quantum non-Hermiticity and classical silicon platforms not only spurs numerous studies on the fundamental physics, but also enriches the potential functionalities of the integrated photonic systems.

Célio Fernandes, Salah Faroughi, Ricardo Ribeiro et al.

Accurately resolving the coupled momentum transfer between the liquid and solid phases of complex fluids is a fundamental problem in multiphase transport processes, such as hydraulic fracture operations. Specifically we need to characterize the dependence of the normalized average fluid-particle force $\langle F \rangle$ on the volume fraction of the dispersed solid phase and on the rheology of the complex fluid matrix. Here we use direct numerical simulations (DNS) to study the creeping flow ($Re\ll 1$) of viscoelastic fluids through static random arrays of monodisperse spherical particles using a finite volume Navier-Stokes/Cauchy momentum solver. The numerical study consists of $N=150$ different systems, in which the normalized average fluid-particle force $\langle F \rangle$ is obtained as a function of the volume fraction $φ$ $(0 < φ\leq 0.2)$ of the dispersed solid phase and the Weissenberg number $Wi$ $(0 \leq Wi \leq 4)$. From these predictions a closure law $\langle F \rangle(Wi,φ)$ for the drag force is derived for the quasi-linear Oldroyd-B viscoelastic fluid model which is, on average, within $5.7\%$ of the DNS results. Additionally, a flow solver able to couple Eulerian and Lagrangian phases is developed, which incorporates the viscoelastic nature of the continuum phase and the closed-form drag law. Two case studies were simulated using this solver, in order to assess the accuracy and robustness of the newly-developed approach for handling particle-laden viscoelastic flow configurations with $O(10^5-10^6)$ rigid spheres that are representative of hydraulic fracture operations.

Arnaud Mazier, Alexandre Bilger, Antonio E. Forte et al.

In this paper, we develop a framework for solving inverse deformation problems using the FEniCS Project finite element software. We validate our approach with experimental imaging data acquired from a soft silicone beam under gravity. In contrast with inverse iterative algorithms that require multiple solutions of a standard elasticity problem, the proposed method can compute the undeformed configuration by solving only one modified elasticity problem. This modified problem has a complexity comparable to the standard one. The framework is implemented within an open-source pipeline enabling the direct and inverse deformation simulation directly from imaging data. We use the high-level Unified Form Language (UFL) of the FEniCS Project to express the finite element model in variational form and to automatically derive the consistent Jacobian. Consequently, the design of the pipeline is flexible: for example, it allows the modification of the constitutive models by changing a single line of code. We include a complete working example showing the inverse deformation of a beam deformed by gravity as supplementary material.