Flooding Method Research Articles

Effect of Nano-ZnO on Growth and Yield of Summer Maize under Drip Irrigation in Laterite Soil

A field experiment was conducted at Agricultural Farm, Palli Siksha Bhavana, Visva-Bharati, West Bengal, India during summer season (February–June), 2022 and 2023, respectively to investigate the effects of drip irrigation and nano zinc oxide biofortification on maize. In the main plot, four drip irrigations scheduling treatments viz., once-in-2 days, once-in-3 days, once-in-4 days and Irrigation by surface flooding method were accommodated. The sub-plot treatments consisted of five methods of zinc applications viz., control, soil application of ZnSO4 at 20 kg ha-1, foliar application of ZnO NP at 40 ppm, seed priming of ZnO NP (NP:Nano Particles) at 40 ppm, and seed coating of ZnO NP at 40 ppm. Growth parameter like plant height and number of leaves were highest with application water through drip irrigation once-in-3 days and seed coating of ZnO NP at 40 ppm at 30 DAS for both the years but at 90 DAS, drip irrigation once-in-2 days and seed coating of ZnO NP recorded highest growth parameters. Aerial dry matter accumulation in unit area recorded maximum in drip irrigation once-in-3 days and seed coating of ZnO NP at 40 ppm at 30 DAS but at 90 DAS drip irrigation once-in-2 days and seed coating of ZnO NP recorded highest. Cob girth, number of grains cob-1, seed index, grain yield and biological yield was observed highest with drip irrigation once-in-2 days and seed coating of ZnO NP in zinc treatment for both the years.

Is the rate of extremely climate-intensifying rainfall for Bangkok severely propagating into flooding?

ABSTRACT The present paper assesses whether the extremely climate-intensifying rate (i.e., 14%/°C) for maximum rainfall in Bangkok is severely propagating into flooding. The impact evaluation involves the development of a flooding assessment method for a drainage system (DS) representative of the capital and the application of the developed procedure to assess the interested effect of the DS on its flooding. Considering the DS of Thammasat University (DS-TU) as the typical DS for the city, the popular storm water management model (SWMM) is then used for developing the dynamic simulation method against the most critical flooding condition of the DS-TU. Applying this SWMM for impact assessment of the intense rainfall rate has indicated that the rising temperature in excess of 2 °C would cause the gradient to severely propagate into the flooding because of the rapid increase in its associated peak, volume and duration properties. The propagated flooding has been shown to be further escalated, as a result of the clogging in the DS-TU. The clogging height that exceeded the 30% threshold of the full openings would intensify the volume and duration properties increasingly.

Surface topography and corrosion resistance of AISI 630 stainless steel after finish turning under different cooling methods

AISI 630 stainless steel (SS) is widely used for medical devices. This paper describes the effects of dry, flood and minimum quantity lubrication (MQL) machining conditions on the surface topography and corrosion resistance (CR) of AISI 630 SS after finish turning. Small areas of valleys and large areas of peaks were observed on the surfaces with minimum surface roughness (SRmin) after dry machining at the feed rate (f) of 0.1 mm/rev and at the f = 0.14 mm/rev using the MQL method. Only small areas of peaks were observed after flood machining at the f = 0.1 mm/rev. Regardless of cooling methods, regularly distributed deep valleys and high peaks were observed on the surfaces with maximum surface roughness (SRmax) machined at the f = 0.35 mm/rev. Surfaces of the samples with SRmin and SRmax under flood machining and with SRmax under MQL machining had high oxygen content in the range of ∼ (20−30) %wt. during 7–72 days of the sample storage in SBF. Such an oxygen content is observed on the machined surfaces for which maximum peak height Sp parameters were in the range of ∼ (10–16) μm and maximum valley height Sv – ∼ (8–10) μm. Compared to SRmin, high ion diffusion was observed on surfaces with SRmax. This means that surfaces with regular deep valleys and high peaks provide high ion mobility between them. In addition, compared to dry and MQL machining, higher resistivity was obtained for the samples under flood machining. Depending on the industrial application requirements, the passivity and CR of AISI 630 SS can be modulated by selecting machining conditions and surface topography. It has been established that in order to achieve favorable CR of the AISI 630 SS surface after finish turning, the flood method is recommended.

SURFACTANT–POLYMER FLOODING: GEOCHEMICAL MONITORING OF THE PROPERTIES OF FORMATION FLUIDS AT THE IMPACT AREA

Chemical flooding methods improve oil extraction after standard waterflooding processes. Chemical EOR methods modify different properties of fluids and/or rock to mobilize the remaining oil. It is expected that the residual oil will be different in properties than conventional. A new technology is presented to study a surfactant–polymer flooding, based on a periodic sampling and measuring properties of oil and water during 15 months. The study area is a terrigenous reservoir with 3 chemical injection wells and 16 production wells. High-precision mass spectrometry methods were carried out on each sample, which made it possible to evaluate the effectiveness of ongoing work on chemical flooding. At each sampling date, 2D reservoir model was built to track these changes in the study area. It is shown that the composition of the water has changed - highly permeable channels were closed and formation waters were involved in the production. The properties of oil have also changed - depending on the site of impact, there are areas with more degraded oil in production after the injection of chemicals. Geochemical monitoring shows the redistribution of filtration flow directions in the reservoir volume.

Experimental investigation of nanofluid lubrication on surface roughness under MQL aluminum alloy 6061-T6 series in drilling

PurposeThis study aims to investigate the impact of varying the number of minimum quantity lubrication (MQL) nozzles, wind pressure, spindle speed and type of lubrication on surface roughness, fatigue life and tool wear in the drilling of aluminum alloy 6061-T6.Design/methodology/approachThe effect of using different lubricants such as palm oil, graphene/water nanofluid and SiO2/water in the MQL method was compared with flood and dry methods. The lubricant flow and feed rate were kept constant throughout the drilling, while the number of nozzles, wind pressure and spindle speed varied. After preparing the parts, surface roughness, fatigue life and tool wear were measured, and the results were analyzed by ANOVA.FindingsThe results showed that using MQL with four nozzles and graphene/water nanofluid reduced surface roughness by 60%, followed by SiO2 nanofluid at 56%, and then by palm oil at 50%. Increasing the spindle speed in MQL mode with four nozzles using graphene nanofluid decreased surface roughness by 52% and improved fatigue life by 34% compared to the dry mode. SEM results showed that tool wear and deformation rates significantly decreased. Increasing the number of nozzles caused the fluid particles to penetrate the cutting area, resulting in improved tool cooling with lubrication in all directions.Originality/valueNumerous attempts have been made worldwide to eliminate industrial lubricants due to environmental pollution. In this research, using nanofluid with wind pressure in MQL reduces environmental impacts and production costs while improving the quality of the final workpiece more than flood and dry methods.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-01-2024-0021/

Forecasting the efficiency of waterflooding, thermal and chemical enhanced oil recovery methods in Bobrikovian reservoirs

The development of reserves contained viscous and highly viscous oil poses one of the major challenges in modern reservoir engineering. The poor performance of conventional waterflooding prompts the application of enhanced oil recovery (EOR) methods, of which thermal and chemical EOR are considered the most efficient. Reservoir simulation is a powerful tool for evaluating EOR performance. Serial runs of a history-matched model of a Bobrikovian reservoir are used to evaluate the incremental oil production due to each EOR technique and formulate the efficiency limits of the process performance criteria. In contrast to previous studies that evaluated EOR applications using reservoir simulation modeling, an entirely new quality model is derived through automatic history matching performed by solving an inverse problem. Another novel feature is the automated selection of the optimum field development scenario given a user-defined objective function. Evaluating the performance of hot water injection in a Bobrikovian reservoir suggests that this technology yields positive effects when the injected water temperature ranges from 50 °C to 90 °C. The surfactant–polymer flooding method is also investigated. The largest incremental oil production with a constant surfactant concentration of 0.5% is observed for a polyacrylamide concentration of 0.25%, which can be attributed to a water cut reduction due to plugging the well-drained and flushed reservoir zones. The greatest incremental oil production is achieved when injecting 1.5% surfactant and 0.25% polyacrylamide. The highest efficiency per ton of injected chemicals is obtained when injecting 0.5% polyacrylamide and 0.10% surfactant. Keywords: High-viscosity oil; EOR; thermal methods; surfactant-polymer flooding; reservoir simulation; history matching; injection simulation scenario.

Water Management and Hydrological Characteristics of Paddy-Rice Fields under Alternate Wetting and Drying Irrigation Practice as Climate Smart Practice: A Review

Paddy-rice cultivation using the traditional continuous flooding method requires much water, up to 2500 L, to produce 1 kg of rice. Decreasing water availability is being exacerbated by climate dynamics, i.e., droughts and rainfall variability negatively affecting food security in developing regions, particularly Africa. Alternate wetting and drying (AWD) practice is a climate-smart water management strategy that, together with puddling (a critical field preparation process), significantly affects soil hydrological and physicochemical regimes, such as soil water dynamics and oxidation states in paddy fields. However, there are limited reviews on the effects and interaction of the AWD duration on hydrological conditions in the paddy-rice rhizosphere continuum under AWD practice at different rice growth stages. Our review synthesizes key scientific literature to examine water management and hydrological properties of paddy soils under AWD practice with climate change and sheds light on why farmers are skeptical in adopting the practice. To develop this paper, we reviewed scientific information from published journal articles, reliable reports, and our knowledge on paddy-rice cultivation and water management with climate change in Asia and Sub-Saharan Africa. Several studies confirm that AWD practice increases water–rice–crop productivity, yields, and reduces methane emissions. Limitations and challenges of AWD irrigation, including changes in soil structure that influence irrigation water application, variations in hydraulic conductivity caused by the duration and frequency of irrigation cycles, and frequent manual water level (WL) monitoring, are discussed. Opportunities to improve the integration of AWD strategies within government policies, irrigation schemes, and farmer acceptance due to skepticism, limited knowledge, and fear of unreliable water hindering adoption are highlighted. Future research suggestions include the following: (i) long-term measurement of water stress indices using infrared thermometers; (ii) seasonal suitability mapping using NDVI, GIS, and remote sensing; and (iii) application of smart sensors based on the Internet of Things (IoT) to address AWD challenges for precision water management in paddy fields with climate change.

Suitability of Sprinkler and Drip Irrigation in Transplanted and Direct Seeded Rice (Oryza sativa L.) in Haryana, India

On-farm trials on rice crop were conducted at farmer field over a span of three years (2018, 2019 and 2020) to assess the effectiveness of micro-irrigation methods (specifically drip and sprinkler irrigation) on water usage and crop yield in rice cultivation. The aim was to compare these methods with the conventional surface irrigation (flooding) method both in transplanted (manually or mechanically) and direct seeded rice so as to determine the feasibility of micro-irrigation in rice to tackle the problem of groundwater depletion in Haryana. In transplanted rice (TPR), grain yield obtained with drip and sprinkler irrigation was statistically similar to that obtained with conventional method. But the yield of direct seeded rice (DSR) increased significantly (15.1- 21.1% increase) when it was irrigated by drip or sprinkler methods than by conventional method. The yield of DSR was significantly lower than that of TPR when it was irrigated by conventional surface flooding method but the DSR yielded at par with TPR when irrigated by drip or sprinkler method. The grain yield of the crop obtained with drip and sprinkler irrigation was at par, irrespective of the crop establishment techniques. Over the conventional irrigation, the drip and sprinkler irrigation saved 54.4-57.2% and 47.4-49.0% of irrigation water, respectively in TPR whereas the saving of irrigation water over the conventional method in DSR was 52.5-53.9% and 38.3-39.3%, respectively. Irrespective of establishment techniques, the highest water use efficiency was achieved with drip irrigation (6.73-9.46 kg/ha/mm), followed by sprinkler irrigation (5.66-7.85 kg/ha/mm) whereas it was the lowest with the conventional irrigation (3.28-3.55 kg/ha/mm). It is evident from the findings that it is feasible to adopt sprinkler irrigation in rice (both in TPR and DSR) as it saved substantial quantity of irrigation water without any penalty in yield and net profit in TPR and even increased the yield and net profit in DSR over the conventional irrigation method. Therefore, sprinkler irrigation can be an effective strategy to manage the depletion of groundwater in Haryana. On the other hand, the drip irrigation, despite saving more water and being comparable to the sprinkler irrigation in respect of its effect on yield, may not be economically viable due to its higher initial cost.

Submergence Stress Reduces the Ability of Rice to Regulate Recovery after Disaster

Flood submergence has devastating effects on agricultural production in China, with rice being particularly vulnerable to its impacts. Previous studies on rice submergence stress have primarily focused on immediate yield reduction and short-term growth. In this study, a submergence stress experiment was carried out by using the method of potted rice flooding. The growth recovery characteristics of rice under different submergence stress were analyzed through the continuous observation of rice growth after the disaster. The results showed that submergence stress had a persistent effect on rice growth, which persisted until the recovery period after the disaster. The recovery ability of rice plants decreased with the aggravation of stress, leading to increased damage to the plant. The average yield decreased by 17.07% and 15.56% due to submergence stress during the jointing and booting stage, respectively. The current study pointed out that the growth traits of and, furthermore, the mechanism of physiological changes in rice during the recovery period need to be explored in order to understand the effects of flooding stress on rice.

A Comparative Analysis of Flooding Methods on Random and Real Network Topologies

The Internet of Things (IoT) is revolutionizing industries by connecting everyday objects, known as smart devices, via the Internet. These devices, embedded with sensors and communication technologies, gather and share data. For the guaranteed gathering of information, the devices share global knowledge with each other, by using dissemination mechanisms in order to broadcast information. This study evaluates four flooding methods for broadcasting information across network nodes, namely: (i) blind flooding; (ii) probabilistic flooding; (iii) m-probabilistic flooding; and (iv) scoped probabilistic flooding, the latter to be introduced here. The evaluation considers random networks that are based on the Burr Type XII distribution and seven real networks. The evaluated flooding methods are studied on three different metrics: (i) coverage achieved; (ii) number of messages exchanged; and (iii) a metric that is based on binomial approximation. The latter is introduced to provide deeper insights into the particulars of the under-evaluation flooding methods. The results show that, under certain conditions, m-probabilistic flooding outperforms probabilistic flooding in terms of coverage, while requiring significantly fewer messages. Additionally, the study revealed that the scoped probabilistic flooding achieves coverage comparable to that of the probabilistic flooding while reducing the number of exchanged messages.

Research on nowcasting prediction technology for flooding scenarios based on data-driven and real-time monitoring.

With the impact of global climate change and the urbanization process, the risk of urban flooding has increased rapidly, especially in developing countries. Real-time monitoring and prediction of flooding extent and drainage system are the foundation of effective urban flood emergency management. Therefore, this paper presents a rapid nowcasting prediction method of urban flooding based on data-driven and real-time monitoring. The proposed method firstly adopts a small number of monitoring points to deduce the urban global real-time water level based on a machine learning algorithm. Then, a data-driven method is developed to achieve dynamic urban flooding nowcasting prediction with real-time monitoring data and high-accuracy precipitation prediction. The results show that the average MAE and RMSE of the urban flooding and conduit system in the deduction method for water level are 0.101 and 0.144, 0.124 and 0.162, respectively, while the flooding depth deduction is more stable compared to the conduit system by probabilistic statistical analysis. Moreover, the urban flooding nowcasting method can accurately predict the flooding depth, and the R2 are as high as 0.973 and 0.962 of testing. The urban flooding nowcasting prediction method provides technical support for emergency flood risk management.

A review of scale inhibitor methods during modified smart water injection

AbstractEnhancing oil recovery (EOR) through water flooding methods, including smart water injection, low salinity water injection, polymer injection, and surfactant injection has become a pivotal strategy for enhancing productivity. Despite their promising outcomes, these methods often encounter challenges such as scaling formation and deposition, impacting reservoir permeability and production rates. A comprehensive understanding of scaling formation is crucial for effective implementation of these methods. This article explores various scaling types prevalent in the field, examining key parameters (temperature, pressure, and pH) that influence scaling formation. Additionally, it presents a diverse range of inhibitors employing both chemical and mechanical methods to mitigate and prevent scaling, thus safeguarding reservoir performance. The efficiency of inhibitors is scrutinized concerning chemical composition and performance maintenance under different temperature and pressure conditions. This study serves as a valuable resource for researchers, engineers, and industry experts involved in the oil industry and reservoir management. By elucidating scaling mechanisms, delineating consequences, and offering extensive solutions, it enhances comprehension and provides a foundation for improving oil recovery strategies. The findings of this study contribute to a better understanding of scaling mechanisms, providing insights that can be applied to optimize oil recovery processes, mitigate reservoir challenges, and improve overall reservoir management strategies.

Development of Membrane Permeability Coefficient by Means of Novel Molecular Dynamics Methods

The membrane permeability, and its evaluation, is crucial factor in the process of uptake of compounds from outside to inside the cell and in the inhibition of the activity of disease-causing target proteins. Although molecular dynamics (MD) simulations have been shown to be able to reproduce the conformational changes of compounds occurring during membrane permeation, it is still challenging to extract the membrane permeability at an affordable computational workload solely by conventional MD. Indeed, the time scale accessible by MD is far below the one characterizing the actual permeation process. Phenomena occurring in living organisms escaping the reach of standard MD are generally referred to as biological rare events, and the membrane permeation process is one of them. To overcome this time-scale problem, several enhanced sampling methods have been proposed over the years to improve conformational sampling. In this review, a hybrid sampling method that combines the parallel cascade selection MD (PaCS-MD) and the outlier flooding method (OFLOOD), introduced and developed by our group, is proposed as a tool to study the membrane permeation from structural sampling (rare-event sampling). The obtained trajectories are used to estimate the free energy profiles for the membrane permeation and to compute the membrane permeation coefficients. Moreover, we present an example of application of the free energy reaction network method as a versatile way for incorporating explicitly into reaction coordinates the degrees of freedom related to internal motion.

An Overview of Oil Recovery Techniques: From Primary to Enhanced Oil Recovery Methods

As we all know, numerous methods have been invented for better managing of the reservoirs to recover the trapped oil from them as much as possible. These techniques included primary techniques that were implemented primarily at the beginning of this industry. As these techniques were not effective enough, secondary techniques, like; water flooding and gas injection methods were created and the amount of recovered oil were increased, as well. On the contrary, the demand for more oil was raised up and it was felt that much more effective techniques are necessary. It resulted to creation of Enhanced Oil Recovery Techniques and these techniques are included; thermal methods (steam injection, steam assisted gravity drainage and in-situ combustion), Chemical methods (alkali flooding, surfactant flooding, polymer flooding, foam flooding, and combination of alkali-surfactant-polymer flooding), and microbial EOR. The most promising technique is microbial EOR because of being cost-effective and ecofriendly. GEMEOR (Genetically Engineered MEOR) and EEOR (Enzyme Enhanced Oil Recovery) are two new trends of MEOR that own potential hopes in petroleum industry.

Spatiotemporal assessment of urban flooding hazard using social media: A case study of Zhengzhou ‘7·20’

Urban flooding is occurring more frequently and with more serious consequences. The importance of flood disaster management has been highlighted. Social media has become an important source of flood disaster information in flood hazard assessment, however, it suffers from a lack of geolocation information and many qualitative descriptions. To improve the application of social media in flood hazard assessment, this study proposed a flooding hazard assessment method. Machine learning (ML)-based named entity recognition (NER) technique was used to identify the location and time of inundation in tweets, which can complement and correct the spatiotemporal properties of tweets. The textual description of waterlogging level in social media was quantified by lexicon-based NER technique. Taking a heavy rainfall event that occurred in Zhengzhou in July 2021 as an example, the results show that social media-based flood hazard maps are effective in identifying waterlogging. This study provides a feasible way to obtain near real-time hazard information from social media to help rapid hazard response.

Study on time-varying characteristics and flow behavior of microencapsulated polymer

Due to the challenges posed by high injection pressure and significant viscosity shear loss, conventional polymer flooding methods are unable to effectively meet the urgent demand for enhanced oil recovery in medium- and low-permeability reservoirs. Microencapsulated polymer flooding is a promising solution to address the aforementioned challenges due to its advantages of easy wellbore injection, shear resistance, and delayed thickening. However, there is a lack of research on the release behavior and time-dependent characteristics of microencapsulated polymer and its impact on flow behavior in reservoirs. To address this gap, we conducted a series of experiments, including thermal stability tests, microfluidic chip experiments, and micro-scale oil displacement experiments, to reveal the time-varying behavior generated by the triggered release of microencapsulated polymers. The results showed that microencapsulated polymer can be fully triggered after 8 days of aging at 85 °C, with a viscosity exceeding the initial viscosity by more than 25 times. The release mechanism of the polymer aligned with the Ritger-Peppas model, transitioning from super Case-II transport to anomalous transport, and finally to Fickian diffusion with increasing temperature. During the triggering process, the presence of particles stabilized shear and improved oil displacement, particularly in small pore throats. Higher triggering degrees of the solution resulted in greater flow resistance within the microchannel, effectively suppressing fluid fingering. The oil displacement effectiveness of fully triggered microencapsulated polymer was comparable to that of conventional polymers. This study provides insights into the flow behavior of microencapsulated polymer at a microscopic level, offering valuable references for its application in the field.

Root Cause Identification of Industrial Alarm Floods Using Word Embedding and Few-Shot Learning

Alarm systems are commonly deployed in modern industrial facilities to monitor process operations. However, due to the presence of nuisance alarms and alarm floods, their efficiencies are much degraded. Especially, alarm floods are among the most difficult issues in industrial alarm management and recognised as the main causes of many industrial accidents. To address alarm floods, this paper proposes a Root Cause Identification method (RCI) for industrial alarm floods based on word embedding and few-shot learning. The contributions are threefold: 1) A textual encoding method based on word embedding is proposed to convert alarm messages into numerical word vectors that can be used in the modeling of RCI; 2) an alarm priority based adaptive weighting strategy is designed to make the RCI more sensitive to alarms of higher priorities and appearing earlier; 3) a few-shot learning method based on the long short-term memory is adapted to identify root causes of alarm floods based on limited instances of labeled data. The effectiveness and superiority of the proposed method are demonstrated by a case study based on data from the Vinyl Acetate Monomer (VAM) public model.

Chemical strategies for enhancing CO2-Hydrocarbon miscibility

Carbon dioxide (CO2) flooding holds immense potential for enhancing hydrocarbon recovery and facilitating geological carbon storage. Among CO2 flooding methods, miscible flooding demonstrates significantly higher production compared to immiscible flooding. However, in certain reservoirs, the high miscibility pressure presents a challenge for achieving miscibility under reservoir pressure conditions. Nonionic surfactants offer a solution by reducing the miscibility pressure in hydrocarbon-CO2 systems. In this study, eight nonionic surfactants were assessed, and two of the most effective surfactants were selected. These surfactants were combined to create a novel nonionic surfactant system aimed at lowering the miscibility pressure. The minimum miscibility pressure (MMP) of the hydrocarbon-CO2 system was measured using a slim-tube experiment, and a comparative analysis was conducted between the vanishing interfacial tension method (VIT) and the slim-tube method. Furthermore, the microscopic mechanism by which surfactants reduce the miscibility pressure was studied and analyzed. The findings indicate that the compound nonionic surfactant SF, with a total concentration of 1.0 wt% and a SMF to Span20 ratio of 1:1, reduces the miscibility pressure by 18.30%. The slim-tube data were processed to obtain a narrower range for MMP using criteria such as the crude oil recovery factor (ORF) and the break-over pressure (BOP). The maximum error between MMP measured by the VIT method and the slim-tube experiment is 5.86%, demonstrating the high accuracy of the VIT method in this study. The surfactant effectively reduces the miscibility pressure by decreasing the interfacial tension (IFT) between oil and gas, enhancing the CO2 extraction efficiency on intermediate hydrocarbons within the crude oil, and improving the solubility of CO2 in the crude oil. The findings of this study hold significant guidance for future investigations on the miscibility in the processes of geological CO2 utilization and storage.

Terrafloc Polymer Application to Increase Oil Recovery: Study Literature

To determine the performance of terrafloc polymer, we must first know the characteristics of the polymer because all of these will affect the increase in oil recovery. Many factors affect the performance of the polymer. Here, using a micromodel to see the movement of oil in 2D, the sweep efficiency of the polymer injection can be seen clearly. The micromodel flooding method was carried out in a series of studies, starting with micromodel preparation, followed by waterflooding and polymer injection at a certain injection flow rate. The data was then analyzed using digital image analysis (DIA) to determine how much oil recovery increased after the injection of terrafloc polymer.

Systematic review of flood resilience assessment approaches and methods in urban environments

Systematic review of flood resilience assessment approaches and methods in urban environments