Stream Patterns Research Articles

CFD investigation of flow forces on a safety valve

In this article, authors investigated a DN50/80 size safety valve with computer fluid dynamics (CFD) simulation to determine the lift forces and mass flows acting on the valve disc at 3.5 to 5.5 barg inlet pressures and to observe the evolution of turbulent streamlines in the outlet side of the valve, with static disc position. The simulation results were compared with measured data. Authors studied the inner flow field of the valve with fixed 5 mm disc elevation. Lift force acting the disc and overall stream pattern were investigated with the gas vale. To eliminate backflow, authors applied a virtual streamtube on the outlet nozzle with various lengths. Differences between data of the valve measured and simulated results were investigated besides changing the length (50, 150, 250, 350 and 400 mm) of the applied tube.

Experimental riparian forest gaps and increased sediment loads modify stream metabolic patterns and biofilm composition

AbstractForest management operations greatly influence stream habitats. Canopy clearing and subsequent canopy development during succession, site preparation, and ditching alter the light environment, and increase sediment inputs and nutrient exports from upland and riparian soils to streams. These physicochemical changes affect aquatic biofilms and metabolic rates, and in this study, we tested their individual and combined effects. We used 12 artificial streamside channels, together with a field survey of nine streams in and around clear‐cuts, to assess the effects of shading, substrate composition, and nutrient addition on biofilm biomass and composition, as well as metabolic rates. We found that biofilm biomass and gross primary production (GPP) were light limited in channels under 70% canopy shading. Nitrate additions at this shading level only marginally increased autotrophic biomass, while the rates of respiration increased 10‐fold when carbon was added. Open (unshaded) channels had three times higher rates of GPP compared with channels with 70% shading, and autotrophic biomass was twice as high, largely caused by the colonization of filamentous green algae. These changes to biofilm biomass, composition, and GPP were caused by differences in light alone, as temperature was not affected by the shading treatment. Notably, higher rates of GPP led to no positive effect on net ecosystem production. Further, fine‐grained substrates negatively affected GPP as compared with stone substrates in the experimental channels. In the surveyed streams, the negative effects of fine‐grained substrates exceeded the positive influence of light on biofilm biomass. Altogether, our results highlight the need for riparian management that protects headwaters from unwanted stressors by focusing on preventing sediment erosion and carbon transport in clear‐cuts, while providing variable shade conditions in second‐growth forests.

Increasing spruce budworm defoliation increases catchment discharge in conifer forests

Forest insect outbreaks cause significant reductions in the forest canopy through defoliation and tree mortality that modify the storage and flow of water, potentially altering catchment runoff and stream discharge patterns. Despite a growing understanding of the impacts of insect outbreaks on the hydrology of broadleaf forests, little is known about these impacts to catchment hydrology in northern conifer-dominated forests. We measured the effects of cumulative defoliation by spruce budworm (Choristoneura fumiferana) on stream discharge and runoff in 12 experimental catchments (6.33–9.85 km2) across the central Gaspé Peninsula in eastern Québec, Canada over a three-year period (2019–2021). Six catchments were aerially treated with BtK (Bacillus thuringiensis kurstaki) insecticide to suppress the outbreak and six catchments were left untreated, leading to a defoliation gradient across the study sites. Stage-discharge relationships were established between June and October from 2019 to 2021. Stream volumetric discharge (r = 0.71, p < 0.01, t(34) = 5.85), runoff (r = 0.55, p < 0.01, t(34) = 3.81) and runoff ratios (r = 0.67, p < 0.01, t(33) = 5.19) were all strongly positively correlated with cumulative defoliation intensity, likely by reducing available water storage in the catchment and therefore enhancing runoff generation. Seasonally, volumetric discharge, runoff, and runoff ratios were more strongly correlated with defoliation in the summer than autumn months, likely because available catchment storage was more limited following the freshet. Overall, we found that insect defoliation impacts forested catchment hydrology similar to other landscape disturbances, and such consequences should be considered in forest management and the control of forest insect outbreaks.

Plume dispersal of a hyper-eutrophic micro-estuary to the eastern mediterranean during base flow and flood events

Rivers are the primary source of dissolved and particulate materials entering the oceans. Recent studies conducted in Mediterranean streams showed a decrease in freshwater flow which indicates that this oligotrophic region, and probably other semi-arid oligotrophic regions, are likely to become more affected by small stream discharge and an increase in flood event intensity and frequency which indicates the increasing importance of studying flood conditions. However, little is known about the dispersal patterns of small streams and micro-estuaries and their influence on the coastal environment. We investigated the discharge from the Alexander Stream micro-estuary into the eastern Mediterranean as a case study for the fate of nutrients and pollutants discharged from micro-estuaries. Our objective is to characterize the Alexander Stream plume dispersal during base flow and flood events using salinity as a tracer for solute dispersal and by measuring the concentrations of suspended matter. The advection pattern during base flow was characterized by a current that clings to shore and mostly flows southward as a thin layer. This steady influx enriches the coastal water with high nutrient loads and carries pollutants toward Beit Yannai recreational beach, chronically exposing the shore and its users year-round. During floods, the plume disperses mostly northward along the coastline, and a considerable volume of suspended sediments settles near the estuary outfall, creating a hotspot of potentially contaminated sediment. At the peak discharge of the flood, the high concentrations of suspended sediments form hyperpycnal flows seaward near the seafloor and along the shelf. These results show the influence of small streams on the marine and coastal environments in semi-arid regions, which is predicted to expand to more temperate zones in the future.

BurstSketch: Finding Bursts in Data Streams

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Burst</i> is a common pattern in data streams which is characterized by a sudden increase in terms of arrival rate followed by a sudden decrease. Burst detection has attracted extensive attention from the research community. To detect bursts accurately in real time, we propose a novel sketch, namely BurstSketch, which consists of two stages. Stage 1 uses the technique Running Track to select potential burst items efficiently. Stage 2 monitors the potential burst items and captures the key features of burst pattern by a technique called Snapshotting. We further propose an optimization, namely Dynamic Buckets, which can improve the accuracy of BurstSketch. We provide theoretical error bounds for Stage 1, Stage 2 and the optimized version. Experimental results show that, compared with the strawman solution, Burstsketch achieves 2.00 to 11.63 times higher F1 score, and 1.56 times higher throughput. We also integrate BurstSketch into Apache Flink, and show that using BurstSketch can be faster than simply using the built-in APIs provided by Apache Flink.

The heat is on: Predicting urban stream temperature responses to summer storms

AbstractShort‐term increases in stream temperature in response to storm events have frequently been observed in urban areas, highlighting the need for improved understanding of the factors influencing urban stream temperature. Urban land cover complexity and infrastructure designed for rapid water routing to the sewer system create a direct link between storm events and water release processes, influencing urban stream temperature responses. This study aims to identify predictors of diverse stream temperature response patterns to summer storms. We analysed 403 storm events from six urban and semi‐urban catchments along the US East Coast using dynamic time warping to identify archetype patterns of stream temperature responses. We further disentangled observed stream temperature increase patterns to reveal the drivers associated with ‘heat pulses’, which are characterized by a rapid but high‐magnitude temperature increase followed by a sharp temperature drop at the start of the hydrograph increase. Our results show that stream temperature patterns were event‐specific and linked to pre‐event conditions and rainfall–runoff characteristics, with the shape of the hydrograph and rainfall–runoff response identified as the most important determinators of the observed temperature response patterns. Ponded surface waters and storm drains, as well as cooler water from the shallow subsurface, were identified as potential sources contributing to temperature patterns. These findings have important implications for understanding urban hydrology and the contributions of different source zones in urban catchments. Specifically, our results suggest that stream temperature may serve as a cost‐effective tracer providing information about urban water sources and pathways, thus aiding in the understanding of complex urban hydrology.

CEP-DTHP : A Complex Event Processing using the Dual-Tier Hybrid Paradigm Over the Stream Mining Process

CEP is a widely used technique for the reliability and recognition of arbitrarily complex patterns in enormous data streams with great performance in real time. Real-time detection of crucial events and rapid response to them are the key goals of sophisticated event processing. The performance of event processing systems can be improved by parallelizing CEP evaluation procedures. Utilizing CEP in parallel while deploying a multi-core or distributed environment is one of the most popular and widely recognized tackles to accomplish the goal. This paper demonstrates the ability to use an unusual parallelization strategy to effectively process complicated events over streams of data. This method depends on a dual-tier hybrid paradigm that combines several parallelism levels. Thread-level or task-level parallelism (TLP) and Data-level parallelism (DLP) were combined in this research. Many threads or instruction sequences from a comparable application can run concurrently under the TLP paradigm. In the DLP paradigm, instruc-tions from a single stream operate on several data streams at the same time. In our suggested model, there are four major stages: data mining, pre-processing, load shedding, and optimization. The first phase is online data mining, following which the data is materialized into a publicly available solution that combines a CEP engine with a library. Next, data pre-processing encompasses the efficient adaptation of the content or format of raw data from many, perhaps diverse sources. Finally, parallelization approaches have been created to reduce CEP processing time. By providing this two-type parallelism, our proposed solution combines the benefits of DLP and TLP while addressing their constraints. The JAVA tool will be used to assess the suggested technique. The performance of the suggested technique is compared to that of other current ways for determining the efficacy and efficiency of the proposed algorithm.

Learning Ship Activity Patterns in Maritime Data Streams: Enhancing CEP Rule Learning by Temporal and Spatial Relations and Domain-Specific Functions

Maritime surveillance systems are of particular importance for the smooth and safe operation of maritime traffic. Such systems must efficiently analyze the continuous stream of incoming ship movement data to provide an up-to-date picture of the situation at sea. Complex Event Processing (CEP) is a software technology dedicated to the analysis of data streams in real time and seems to be promising for maritime surveillance as well. CEP is based on rules that usually have to be formulated manually by domain experts. Recently, several approaches of learning CEP rules have been proposed. However, all these approaches are limited to standard CEP rule languages which are not well suited for describing maritime situations. In this paper, we extend Bat4CEP, an innovative bat-inspired approach to automatic CEP rule learning, to meet the specific needs of the maritime domain. In particular, we extend the rule language of Bat4CEP to include temporal-spatial operators and domain-specific functions. This extended rule language makes it possible to express complex maritime facts in a simple and understandable form. Furthermore, it is shown how the proposed rule language extensions can be integrated into the Bat4CEP learning approach. The effectiveness of the approach is demonstrated through extensive experiments with real maritime data streams.

Incremental Learning Based on Granular Ball Rough Sets for Classification in Dynamic Mixed-Type Decision System

Granular computing, a new paradigm for solving large-scale and complex problems, has made significant progresses in knowledge discovery. Granular ball computing (GBC) is a novel granular computing method, which can rapidly generate scalable and robust information granules, that is, granular balls. However, a comprehensive index for measuring the performance of a granular ball does not exist. Furthermore, GBC lacks a mechanism to deal with dynamic decision systems. Therefore, in this study, the quality index of a granular ball is first formulated. Next, with this index, a novel granular ball rough sets model (GBRS) based on GBC is proposed. GBRS is more conducive to learning knowledge from uncertain datasets and more suited to incremental learning than the latest granular ball neighborhood rough sets model based on GBC. Subsequently, an incremental mechanism is introduced into GBRS, and two incremental learning models are developed for objects increasing in stream patterns and batch patterns, respectively. In the incremental learning process, three patterns of granular balls, that is, update, fusion, and split, were well studied when a set of objects was added to the decision system. Finally, to verify the effectiveness and efficiency, we apply GBRS and these two incremental learning models into classification tasks. Compared with four current state-of-the-art classification methods based on granular computing and four classical classifiers in machine learning, the proposed classifiers in this paper achieve higher classification accuracy as well as better efficiency on benchmark datasets.

Mapping stream and floodplain geomorphometry with the Floodplain and Channel Evaluation Tool

AbstractBroad‐scale mapping of stream channel and floodplain geomorphic metrics is critical to improve the understanding of geomorphic change, biogeochemical processes, riverine habitat quality, and opportunities for management intervention. The Floodplain and Channel Evaluation Tool (FACET) was developed to provide an open‐source tool for automated processing of digital elevation models (DEMs) to generate regional‐scale estimates of bank height, channel width, floodplain width, and a suite of other fluvial geomorphic dimensions that can be summarized at the stream reach‐ or catchment‐scale. FACET was tested on 3‐m DEMs covering the Delaware River watershed and 85% of the Chesapeake Bay watershed in the United States (U.S.) and on 1‐m DEMs for a subset of the study area. Accuracy was assessed from data collected at 67 field sites in the study area. FACET successfully measured geomorphometry for over 270,000 stream reaches (88% of streams attempted) in the study area. Factors that reduced the ability of FACET to accurately estimate geomorphic metrics included errors in DEM hydro‐conditioning, gradually sloping banks, incised stream channels, and the use of fixed input parameters to define buffer lengths. Even with these limitations, FACET was able to map regional patterns in stream and floodplain geomorphometry providing a robust dataset that can enhance modeling and management efforts throughout the mid‐Atlantic region, U.S.

Morphometry of the cold-climate Bory Stobrawskie Dune Field (SW Poland): Evidence for multi-phase Lateglacial aeolian activity within the European Sand Belt

Abstract Aeolian dunes have been widely identified in the European Sand Belt, which was formed during the Pleniglacial and Late Glacial when cold and dry climatic conditions were favorable for intense Aeolian processes. In this study, we mapped and analyzed the fixed Bory Stobrawskie Dune Field (SW Poland) to determine factors that drive the evolution of dunes, expressed by the occurrence of different dune types and their spatial patterns. The study identified the longitudinal zonation within the dune field, as shown by the changeable proportion of specific dune types comparable to low-latitude dune fields. However, climatically controlled periodic and low sand supply combined with a changing vegetation cover caused the non-continuous and multi-phase evolution of the dune field. Additionally, we found that a dense pattern of streams has controlled the extent of the dune field. The trapping of sand by rivers led to a limitation of the dune field expansion; on the other hand, the supply of sand into rivers led to overloading of the fluvial system, affecting their transformation into braided rivers.

Candida auris Blood stream infection- a descriptive study from Qatar

BackgroundCandida auris is an emerging yeast pathogen that can cause invasive infections, particularly candidemia, in healthcare settings. Candida auris is characterized by resistance to multiple classes of antifungal drugs and high mortality.ObjectiveTo describe the risk factors, clinical characteristics, antifungal susceptibility pattern and outcomes of Candida auris blood stream infection.MethodsWe conducted a retrospective review of electronic medical records of C. auris fungemia cases in the facilities under Hamad Medical corporation, Qatar from 1/11/2018 to 31/7/2021. Demographic data, risk factors, antibiogram and 30-day outcome are described.ResultsWe identified 36 patients with C. auris fungemia. Most of the patients were in intensive care unit following severe COVID-19 pneumonia and had received steroids and broad-spectrum antibiotics. Most cases were central line related. Over 90% of isolates were non-susceptible to fluconazole, while amphotericin B resistance reached 85%. Factors associated with high mortality included initial SOFA score of 9 or above and absence of source control.ConclusionOur study reveals a concerning 41.6% mortality rate within 30 days of C. auris candidemia. Furthermore, the prevalence of amphotericin B resistance in Qatar exceeds what has been reported in the literature necessitating further exploration. Echinocandins retains nearly 100% susceptibility and should be prioritized as the treatment of choice. These findings emphasize the need for vigilant monitoring and appropriate management strategies to combat C. auris infections and improve patient outcomes.

Variations in the 30–60‐Day Intra‐Seasonal Variability of Spring Precipitation Over the Mid‐Low Reaches of the Yangtze River and the Possible Mechanism

AbstractThe precipitation intra‐seasonal variability (ISV) has an important influence on extreme precipitation events, profoundly influencing agricultural activities over the mid‐low reaches of the Yangtze River (MLRYR). Spectrum analysis reveals the existence of 30–60‐day ISV in the MLRYR spring precipitation. The mechanism analysis indicates that, on the intra‐seasonal time scale, the MLRYR precipitation ISV is primarily driven by a wave train over the Eurasian continent. The wave train, with an anomalous anticyclone (cyclone) over the East European Plain and an anomalous cyclone (anticyclone) over Central Asia, could cause more (less) precipitation over the MLRYR. On the inter‐annual and inter‐decadal time scales, the precipitation ISV intensity is influenced by a meridional dipole pattern of the westerly jet stream (WJS) over the Eurasian continent. The positive WJS pattern facilitates the barotropic instability generation and 30–60‐day ISV growth over the East European Plain. Therefore, the ISV intensity of the pronounced wave train is enhanced and further intensifies the MLRYR spring precipitation ISV. In contrast, the negative WJS pattern is unfavorable for regional barotropic instability generation, and therefore the spring precipitation ISV intensity over the MLRYR would be weak. Further analysis shows that the underlying snow cover and soil temperature anomalies could have a contribution to forming the WJS dipole pattern through changing the meridional temperature gradient. The results of this study could deepen our understanding of the spring precipitation ISV over the MLRYR and the mechanisms.

Using biological traits to assess diet selection: the case of the Pyrenean Desman.

Traditionally, researchers have assessed diet selection by comparing consumed versus available taxa. However, taxonomic assignment is probably irrelevant for predators, who likely base their selection on characteristics including prey size, habitat, or behavior. Here, we use an aquatic insectivore, the threatened Pyrenean Desman (Galemys pyrenaicus), as a model species to assess whether biological traits help unravel the criteria driving food and habitat preferences. We reanalyzed data from a previous taxonomy-based study of prey selection in two contrasting streams, one with excellent conservation status and the other affected by diversion for hydropower and forestry. Available and consumed prey were characterized according to nine biological traits, and diet selection was estimated by comparing availability-measured from Surber net samples, and consumption-analyzed by metabarcoding desman feces. Traits offered a biologically coherent image of diet and almost identical selection patterns in both streams, depicting a highly specialized rheophilic predator. Desmans positively selected prey with a preference for fast flow and boulder substrate, indicating their preferred riffle habitat. On the other hand, they positively selected prey with larger but not the largest potential size, living in the water column or the litter, and not inside sediments. They also chose agile prey, swimmers or prey attached to the substrate, prey with high body flexibility, and prey living exposed and clustered in groups. Overall, our results offer a picture of desman diet preference and point to biological traits as being better than taxonomic identity to describe the diet preference of consumers.

Numerical study on thermo-solutal combined convection in a lid-driven chamber with heat/cold sources on sidewalls

The intention of the present numerical investigation is to study the combined convection in dual diffusive mode with thermal and solutal transfer in a cavity covered by a lid. The vertical walls treated with five distinct heat and cold zones. The adiabatic condition is imposed on the horizontal walls in upper and lower part. The implementation of finite volume methodology is applied to solve the leading equalities. The graphs are interpreted after carrying out the computations for a variety of parameters. The impact on the heat situation and cold situation place a momentous role on the pattern of stream and the resultant thermal, mass transport in the chamber. The influence of the leading regulatory constraints such as the ratio of buoyancy, Richardson number are examined on the streamlines, thermal and solutal transfer rates for distinct positions of the thermal and mass source. The distinct position of heat and mass source impacts the structure of the flow and the solutal, thermal rates.

Study on Drainage Network Pattern and Morphometric Analysis by Using Hydrology Support Algorithm

Abstract The degree of accuracy in the extraction of the drainage network and morphometric analysis of the basin plays a vital role in assessing geomorphological characteristics and hydrological processes. The extraction of the exact flow network from SRTM-DEM quantifies the drainage network, and morphometric parameters, which is the main objective of this study. The Thamirabarani river basin in Tamil Nadu, India is taken as the study area. The stream order threshold algorithm is used for stream rasterization to get the pattern of the basin’s drainage network. The hydrology-based algorithm uses a different range of threshold values to determine the stream pattern, which is comparable to the stream vectors of the toposheet. The drainage network distribution with a threshold value of 10000 gives many minor streams which imply dissimilarities with the stream network of toposheet, whereas the threshold value of 20000 shows remarkable similarity to an existing river system. The model with threshold 20000 provides a Stranhler-based drainage network with a basin area of 5664.52 km2. The basin is the fifth-order stream network with many lower-order streams. The drainage pattern is resulted in dendritic and sub-dendritic. The morphometric parameters of the basin are evaluated with the help of an aspect, slope, and contour. The slope of the study area is flat in the east and steeper in the west, along the area of Western Ghats. A bifurcation ratio ranges from 1.05 to 2.42, indicating that the drainage network is not influenced by structural disturbances in that area. The comprehensive evaluation of flow patterns along with morphometric properties obtained from this study provides data support for estimation of the volume of water in the basin, reservoir operation, and construction of hydrological structures. Also, this result can be used to compute watershed attributes normally used in hydrologic and water resources studies. The hydrology-based algorithm can be employed in other river basins to extract drainage network patterns.

Electrodialysis membrane desalination for water and wastewater processing: irregular attack angles of membrane spacers.

Electrodialysis desalination is constructed with a number of anion exchange membranes (AEM), cation exchange membranes (CEM), anode, cathode, adjacent silicon gasket integrated membrane spacers, and inlet/outlet holes per cell. At the boundary among an ionic solution and an ion exchange membrane, concentration polarization develops. Spacers placed in between channel's walls function as stream baffles to increase turbulence, improve heat and mass transfer, diminish the laminar boundary layer, and lessen fouling problems. The current study offers a systematic review of membrane spacers, spacer-bulk attack angles, and irregular attack angles. Spacer-bulk attack angle is accountable for variations in the pattern and direction of stream which impact heat-mass transfer and concentration polarization. Irregular attack angles (e.g., 0°, 15°, 30°, 37°, 45°, 55°, 60°, 62°, 70°, 74°, 80°, 90°, 110°, 120°) in the present study were found to provide unique stream patterns due to the spacer's filaments being less or more transverse in respect to the primary solution direction, which may significantly alter heat transfer, mass transport, pressure drop, and overall flow dynamics. Spacer applies shear stress resulting by continuous stream tangent to the membrane exterior, which lessens polarization. In the end, 45° is concluded as the preferred attack angle that offers balanced rates of heat transfer, mass transport, and pressure drop throughout the feed channel while greatly lowering the rate of concentration polarization.

Environmental filtering, spatial processes and biotic interactions jointly shape different traits communities of stream macroinvertebrates

The metacommunity concept has been widely used to explain the biodiversity patterns at various scales. It considers the influences of both local (e.g., environmental filtering and biotic interactions) and regional processes (e.g., dispersal limitation) in shaping community structures. Compared to environmental filtering and spatial processes, the influence of biotic interactions on biodiversity patterns in streams has received limited attention. We investigated the relative importance of three ecological processes, namely environmental filtering (including local environmental and geo-climatic factors), spatial processes and biotic interactions (represented by interactions of macroinvertebrates and diatom), in shaping different traits of macroinvertebrate communities in subtropical streams, Eastern China. We applied variance partitioning to uncover the pure and shared effects of different ecological processes in explaining community variation. The results showed that environmental filtering, spatial processes, and biotic interactions jointly determined taxonomic and trait compositions of stream macroinvertebrates. Spatial processes showed a stronger influence in shaping stream macroinvertebrate communities than environmental filtering. The contribution of biotic interactions to explain variables was, albeit significant, rather small, which was likely a result of insufficient representation (by diatom traits) of trophic interactions associated with macroinvertebrates. Moreover, the impact of three ecological processes on macroinvertebrate communities depends on different traits, especially in terms of environmental filtering and spatial processes. For example, spatial processes and environmental filtering have the strongest effect on strong dispersal ability groups; spatial processes have a greater effect on scrapers than other functional feeding groups. Overall, our results showed that the integration of metacommunity theory and functional traits provides a valuable framework for understanding the drivers of community structuring in streams, which will facilitate the development of effective bioassessment and management strategies.

Dynamics pattern of a radioactive rGO-magnetite-water flowed by a vibrated Riga plate sensor with ramped temperature and concentration

In recent times, the dynamics study of an electrically weak performing fluid stream regulated by Riga sensors has become an emerging research topic for scientists. Riga sensors’ utility for improving the effectiveness of heat and mass transport rates in industrial and engineering systems is diverse. This motivates us to inspect the stream pattern and heat-mass transmission mechanism of an electrically low-performing hybrid nanofluid (rGO-magnetite-water) near a vertically straightened Riga plate sensor embedding with absorbing materials under the guidance of thermal and concentration buoyancy and magnetization. The taken flow is being modelled by incorporating pertinent physical influences, namely radiation heat emission, chemical reaction, and ramped temperature and concentration at the boundary wall. The flow is presented mathematically in terms of unsteady partial differential equations. The compact-form expressions for model entities are founded by opting for the Laplace transform methodology. The Riga plate’s shear stress, heat and mass transfer rates are tabulated and graphed. The physical behaviours of substantial flow entities against model factors are conversed and judged graphically. The vital findings of this study demonstrate a swelling in the velocity distribution with an enhancement in modified Hartmann number and diminishing with an enlargement in the width of electrodes. The temperature and concentration are higher for constant plate temperature (CPT) and lower for ramped plate temperature (RPT). It is also motivating to note down that hybrid nanofluid containing reduced graphene nanomaterials will transmit extra heat in the flow regime. The heat flow across the Riga sensor elevates against the higher radiation parameter’s value. These novel findings will be extremely applicable in steam generators, chemical reactors, hybrid Riga plate electromagnetic devices, and phase transitions during material processing.

Process-Oriented heterogeneous graph learning in GNN-Based ICS anomalous pattern recognition

Over the past few years, massive penetrations targeting an Industrial Control System (ICS) network intend to compromise its core industrial processes. So far, numerous advanced methods have been proposed to detect anomalous patterns in the numeric data streams with respect to the heterogeneous field devices involved in the industrial processes. These methods, despite reporting decent results, usually conduct system-wise detection instead of fine-grained anomalous pattern recognition at the device level. Furthermore, lacking explicit consideration of the exclusive process-related features with respect to each differentiated device, the fitness of their application in specified industrial processes is undermined. To tackle these issues, a GNN-based Attributed Heterogeneous Graph Analyzer (the AHGA) is designed to perform device-wise anomalous pattern detection via in-depth process-oriented associativity learning. The AHGA’s framework is constructed with four building blocks: a graph processor, a feature analyzer, a link inference decoder, and an anomaly detector. Its performance is assessed and compared against multiple link inference and anomaly detection baselines over 2 popular ICS datasets (SWaT and WADI). Comparative results demonstrate the AHGA’s reliability in capturing sophisticated process-oriented relations among heterogeneous devices as well as its effectiveness in boosting the performance of anomalous pattern recognition at device-level granularity.