Flow Map Research Articles

Geometric Approaches to Lagrangian Averaging

Lagrangian averaging theories, most notably the generalized Lagrangian mean (GLM) theory of Andrews and McIntyre, have been primarily developed in Euclidean space and Cartesian coordinates. We reinterpret these theories using a geometric, coordinate-free formulation. This gives central roles to the flow map, its decomposition into mean and perturbation maps, and the momentum 1-form dual to the velocity vector. In this interpretation, the Lagrangian mean of any tensorial quantity is obtained by averaging its pull-back to the mean configuration. Crucially, the mean velocity is not a Lagrangian mean in this sense. It can be defined in a variety of ways, leading to alternative Lagrangian mean formulations that include GLM and Soward and Roberts's volume-preserving version. These formulations share key features that the geometric approach uncovers. We derive governing equations both for the mean flow and for wave activities constraining the dynamics of the perturbations. The presentation focuses on the Boussinesq model for inviscid rotating stratified flows and reviews the necessary tools of differential geometry.

Study of oblique granular impingement flow through CFD-DEM simulations and energy consumption statistics

This paper investigates an experimental granular impingement flow system through simulations and energy consumption statistics. With the increase of solid concentration, flow patterns undergo cross flow (dense edge and dilute center), dispersed flow, and mixed-jet flow (dilute edge and dense center) in turn. The influence of gas phase on the flow pattern was investigated. According to the analysis of force and time-averaged velocity, it is revealed that gas-solid interaction will cause energy dissipation of granular flow, which cannot be ignored in specific cases. Then, a flow map is proposed according to both the Archimedes number and solid concentration. In addition, the flow pattern transition and local structure variations can be reflected by energy consumption statistics. Based on the simulations and methods developed in this work, it is promising to deepen the understanding and study of granular impingement flow from the viewpoints of energy consumption and new-type flow map.

Regularity with Respect to the Parameter of Lyapunov Exponents for Diffeomorphisms with Dominated Splitting

We consider families of diffeomorphisms with dominated splittings and preserving a Borel probability measure, and we study the regularity of the Lyapunov exponents associated to the invariant bundles with respect to the parameter. We obtain that the regularity is at least the sum of the regularities of the two invariant bundles (for regularities in [ 0 , 1 ] [0,1] ), and under suitable conditions we obtain formulas for the derivatives. Similar results are obtained for families of flows, and for the case when the invariant measure depends on the map. We also obtain several applications. Near the time one map of a geodesic flow of a surface of negative curvature the metric entropy of the volume is Lipschitz with respect to the parameter. At the time one map of a geodesic flow on a manifold of constant negative curvature the topological entropy is differentiable with respect to the parameter, and we give a formula for the derivative. Under some regularity conditions, the critical points of the Lyapunov exponent function are nonflat (the second derivative is nonzero for some families). Also, again under some regularity conditions, the criticality of the Lyapunov exponent function implies some rigidity of the map, in the sense that the volume decomposes as a product along the two complementary foliations. In particular for area preserving Anosov diffeomorphisms, the only critical points are the maps smoothly conjugated to the linear map, corresponding to the global extrema.

New centralities in medium-sized cities: analysis of the subcenters of the Tomba and Cidade Nova districts in Feira de Santana, Bahia

The objective of this article is to analyze the changes in urban centrality in Feira de Santana due to the consolidation of subcenters and to reflect on the alterations triggered by this process in its urban and economic dynamics, through the investigation of the Tomba and Cidade Nova districts. The methodology was based on bibliographic studies to provide a theoretical framework of the center, decentralization, and subcenters; fieldwork including the survey of tertiary establishments in the studied areas, data collection through interviews, and application of qualitative-quantitative questionnaires on the Google Forms platform, as well as the development of land use and occupancy maps and flow maps. The subcenters of Tomba and Cidade Nova can be considered the main expressions of centrality outside the central area of Feira de Santana, due to the diversity of tertiary activities that they offer and the decentralization experienced by the city. The emergence of new centralities affects the role of the Traditional Center, which was once considered the sole polarizing nucleus of the city and which now, due to changes in urban centrality, tends to relatively lose this role.

Dynamics and heat-transfer characteristics of the liquid film flow in upward- and vertical-facing spray cooling

In this study, an experimental investigation was conducted on the dynamics and heat-transfer characteristics of liquid film flow for upward- and vertical-facing spray cooling. The heat-transfer performances at different inlet pressures, nozzle-to-surface distances, and heat flux inputs between the two orientations were compared, and the morphologies, wetted areas, and velocities of the isolated liquid films were quantitatively captured. The morphologies of the HFE-7100 liquid films and their distributions on the vertical and upward surfaces exhibited no significant differences. In most cases, the heat-transfer performance of the upward surface was slightly better than that of the vertical surface. Gravity affected the velocity of the isolated liquid films on a smooth vertical surface, whereas its effect was significantly suppressed on an unpolished surface. The Bond number of the isolated liquid film flow on the upward surface was verified to be naturally smaller than that on the vertical surface. Dimensionless groups, including the Bo, We, and Re numbers of the liquid film flow in spray cooling, were obtained to further account for the effect of gravity. The reason why the dimensionless groups presented such small orders was explained. The data map of liquid film flow (dimensionless groups) during spray cooling was further enriched.

Cerebral perfusion metrics calculated directly from a hypoxia-induced step change in deoxyhemoglobin

Resting cerebral perfusion metrics can be calculated from the MRI ΔR2* signal during the first passage of an intravascular bolus of a Gadolinium-based contrast agent (GBCA), or more recently, a transient hypoxia-induced change in the concentration of deoxyhemoglobin ([dOHb]). Conventional analysis follows a proxy process that includes deconvolution of an arterial input function (AIF) in a tracer kinetic model. We hypothesized that the step reduction in magnetic susceptibility accompanying a step decrease in [dOHb] that occurs when a single breath of oxygen terminates a brief episode of lung hypoxia permits direct calculation of relative perfusion metrics. The time course of the ΔR2* signal response enables both the discrimination of blood arrival times and the time course of voxel filling. We calculated the perfusion metrics implied by this step signal change in seven healthy volunteers and compared them to those from conventional analyses of GBCA and dOHb using their AIF and indicator dilution theory. Voxel-wise maps of relative cerebral blood flow and relative cerebral blood volume had a high spatial and magnitude congruence for all three analyses (r > 0.9) and were similar in appearance to published maps. The mean (SD) transit times (s) in grey and white matter respectively for the step response (7.4 (1.1), 8.05 (1.71)) were greater than those for GBCA (2.6 (0.45), 3.54 (0.83)) attributable to the nature of their respective calculation models. In conclusion we believe these calculations of perfusion metrics derived directly from ΔR2* have superior merit to calculations via AIF by virtue of being calculated from a direct signal rather than through a proxy model which encompasses errors inherent in designating an AIF and performing deconvolution calculations.

The Relation between Flow Map Analysis and Residential Density Conditions in Sleman Regency, Special Region of Yogyakarta

The government of Sleman Regency has been seriously implementing the Smart Living concept under the Smart Regency idea. It is demonstrated by the achievements of the Transport Service Improvement Program in the form of developing type C terminal facilities, creating a transport licensing management information system, and data collection on public transport, types, number of modes, routes and route mapping. However, the affordability and availability of public transportation access in all government facilities (such as hospitals, schools and offices) as well as the integration of routes has not yet been fully realized. In order to support the identification of problems in the implementation of routes that should be integrated with residential areas, this research describe the relation between flow map analysis and residential density condition in Sleman Regency based on data respondent who has been living in Sleman Regency. The analysis was conducted by using quantitative method, especially using the ArcGIS as the analysis tool. Research data were collected through interviews, questionnaire distribution, observation which distribute all over the regency. The results showed that the current form of movement patterns originates from residential area that have high density (in terms of population), but not all of them are served by the existing transport public routes. The mapping results showed that although the majority of movement patterns are still operating in main service areas such as in the Yogyakarta Urban Area, however, there are still many areas that are not yet served, such as Kapanewon Moyudan, Minggir, Seyegan, Tempel, Turi, even Sleman as the administrative capital of Sleman Regency.

Eulerian-Lagrangian Fluid Simulation on Particle Flow Maps

We propose a novel Particle Flow Map (PFM) method to enable accurate long-range advection for incompressible fluid simulation. The foundation of our method is the observation that a particle trajectory generated in a forward simulation naturally embodies a perfect flow map. Centered on this concept, we have developed an Eulerian-Lagrangian framework comprising four essential components: Lagrangian particles for a natural and precise representation of bidirectional flow maps; a dual-scale map representation to accommodate the mapping of various flow quantities; a particle-to-grid interpolation scheme for accurate quantity transfer from particles to grid nodes; and a hybrid impulse-based solver to enforce incompressibility on the grid. The efficacy of PFM has been demonstrated through various simulation scenarios, highlighting the evolution of complex vortical structures and the details of turbulent flows. Notably, compared to NFM, PFM reduces computing time by up to 49 times and memory consumption by up to 41%, while enhancing vorticity preservation as evidenced in various tests like leapfrog, vortex tube, and turbulent flow.

Visual Mapping of Operating Theater Team Dynamics and Communication for Reflexive Feedback and Surgical Practice Optimization.

Effective operating theater (OT) communication and teamwork are essential to optimal surgical outcomes. We mapped the OT team dynamics and infection control practices using visual methods to guide reflexive feedback and optimize perioperative practices. Data were gathered from adult gastrointestinal surgical teams at a tertiary hospital in India using observations, sociograms (communication mapping tool), and focus group discussions (FGDs). Our methods aimed to map team communication, roles and responsibilities in infection-related practices, and door openings. Qualitative data were thematically analyzed. Quantitative data were analyzed using descriptive statistics. Data were gathered from 10 surgical procedures (over 51 hours) using 16 sociograms, 15 traffic flow maps, and 3 FGDs. Senior surgeons directly influence team hierarchies, dynamics, and communication. While the surgeons, anesthetic residents, and technicians lead most tasks during procedures, the scrub nurse acts as a mediator coordinating activity among role players across hierarchies. Failing to provide the scrub nurse with complete details of the planned surgery leads to multiple door openings to fetch equipment and disposables. Traffic flow observed in 15-minute intervals corresponds to a mean frequency of 56 door openings per hour (min: 16; max: 108), with implications for infection control. Implementing the World Health Organization surgical safety checklist was inconsistent across pathways and does not match reported compliance data. Human factors research is important in optimizing surgical teamwork. Using visual methods to provide feedback to perioperative teams on their communication patterns and behaviors, provided an opportunity for contextualized enhancement of infection prevention and control practices.

Active Wildland Fires in Central Chile and Local Winds (Puelche)

Central Chile (CC, latitudes 32–40°S) experienced very active fires in 2017 and 2023. These fires burned large areas and killed many people. These unprecedented fires for CC presented a need for more defined fire weather conditions on the synoptic scale. In this paper, fire weather conditions were analyzed using various satellite-derived fire data (hotspots, HSs), wind streamlines, distribution maps of wind flow and temperature, and various synoptic-scale weather maps. Results showed that local winds, known as Puelche, blew on the peak fire days (26 January 2017 and 3 February 2023). The number of HSs on these days was 2676 and 2746, respectively, about 90 times the average (30). The occurrence of Puelche winds was confirmed by streamlines from high-pressure systems offshore of Argentina to the study area in CC. The formation of strong winds and high-temperature areas associated with Puelche winds were identified on the Earth survey satellite maps. Strong winds of about 38 km h−1 and high temperatures above 32 °C with low relative humidity below 33% were actually observed at the weather station near the fire-prone areas. Lastly, some indications for Puelche winds outbreaks are summarized. This paper’s results will be used to prevent future active fire occurrences in the CC.

Motion-guided spatiotemporal multitask feature discrimination for self-supervised video representation learning

Powerful self-supervised representation models are able to step out of the traditional supervised paradigm and rely merely on unlabeled data to achieve a deep understanding of visual semantic features. However, previous approaches may suffer from background scene bias, making it difficult to perform a comprehensive exploration of video spatiotemporal structure. To address this challenge, this paper proposes a self-supervised video representation learning framework of motion-guided spatiotemporal multitask feature discrimination (MSMFD). The method mainly utilizes the consistency of motion cues between different views to guide the model for spatial and temporal feature similarity discrimination. Specifically, the model first selects video clips with large motion amplitudes based on the collected optical flow maps. Subsequently, the model introduces an instance discrimination task for overall spatiotemporal structure perception of the video, while a shuffled triplet and an augmented quadruple task are created to further enhance the exploration of intraframe sequence order and local spatial fine-grained. Furthermore, we propose joint motion alignment of spatial, temporal, and spatiotemporal dimensions under different views as a powerful compensation for acquiring motion features. Experimental results demonstrate that our self-supervised method is effective for learning video representations and achieves competitive performance in action recognition and video retrieval tasks compared to other state-of-the-art methods.

Analysis of Work Measurement Using a Stopwatch in a Motorcycle Workshop

In realizing competitiveness, a company/ business organization must have operational excellence. Operational excellence is obtained through the provision of facilities in the form of tools or work systems that enable workers to operate them more efficiently and effectively, where efficiency and effectiveness are two things that produce productivity. Apart from many influencing factors, such as worker experience and knowledge, CV. XYZ – a work organization engaged in the repair of two-wheeled motorized vehicles – is also trying to create an advantage that allows them to increase their productivity. This research is a quantitative descriptive study, which takes time data from the two jobs most routinely carried out by CV. XYZ, namely changing engine oil and gear oil. This research was carried out with the aim of finding out the standard time needed for workers to complete their work and making recommendations for possible improvements to be implemented by CV management. XYZ, namely recommendations for the layout of work facilities and also the sequence of work processes. The measurement results show that the standard time required to complete the job of changing engine oil and garden oil is 372.68 seconds and 417.99 seconds, respectively. Creating an operational flow map (current FPC) shows that the average distance that workers need to travel while working on engine oil and garden oil is 22 meters. The results of the FPC recommendation provided show that the distance has decreased to 16.5 meters or 5.5 meters shorter.

Motion-Aware Video Frame Interpolation

Video frame interpolation methodologies endeavor to create novel frames betwixt extant ones, with the intent of augmenting the video’s frame frequency. However, current methods are prone to image blurring and spurious artifacts in challenging scenarios involving occlusions and discontinuous motion. Moreover, they typically rely on optical flow estimation, which adds complexity to modeling and computational costs. To address these issues, we introduce a Motion-Aware Video Frame Interpolation (MA-VFI) network, which directly estimates intermediate optical flow from consecutive frames by introducing a novel hierarchical pyramid module. It not only extracts global semantic relationships and spatial details from input frames with different receptive fields, enabling the model to capture intricate motion patterns, but also effectively reduces the required computational cost and complexity. Subsequently, a cross-scale motion structure is presented to estimate and refine intermediate flow maps by the extracted features. This approach facilitates the interplay between input frame features and flow maps during the frame interpolation process and markedly heightens the precision of the intervening flow delineations. Finally, a discerningly fashioned loss centered around an intermediate flow is meticulously contrived, serving as a deft rudder to skillfully guide the prognostication of said intermediate flow, thereby substantially refining the precision of the intervening flow mappings. Experiments illustrate that MA-VFI surpasses several representative VFI methods across various datasets, and can enhance efficiency while maintaining commendable efficacy.

Value of Ultrasound Super-Resolution Imaging for the Assessment of Renal Microcirculation in Patients with Acute Kidney Injury: A Preliminary Study.

The present study aimed to explore the clinical applicability of ultrasound super-resolution imaging (US SRI) for assessing renal microcirculation in patients with acute kidney injury (AKI). A total of 62 patients with sepsis were enrolled in the present study-38 with AKI and 24 control patients-from whom renal ultrasounds and clinical data were obtained. SonoVue contrast (1.5 mL) was administered through the elbow vein and contrast-enhanced ultrasound (CEUS) images were obtained on a Mindray Resona A20 ultrasound unit for 2 min. The renal perfusion time-intensity curve (TIC) was analyzed and, after 15 min, additional images were obtained to create a microscopic blood flow map. Microvascular density (MVD) was calculated and its correlation with serum creatinine (Scr) levels was analyzed. There were significant differences in heart rate, Scr, blood urea nitrogen, urine volume at 24 h, and glomerular filtration rate between the two groups (p < 0.01), whereas other characteristics, such as renal morphology, did not differ significantly between the AKI group and control group (p > 0.05). The time to peak and mean transit times of the renal cortex in the AKI group were prolonged compared to those in the control group (p < 0.01), while the peak intensity and area under the TIC were lower than those in the control group (p < 0.05). The MVD of the renal cortex in the AKI group was lower than that in the control group (18.46 ± 5.90% vs. 44.93 ± 11.65%; p < 0.01) and the MVD in the AKI group showed a negative correlation with Scr (R = -0.84; p < 0.01). Based on the aforementioned results, US SRI can effectively assess renal microcirculation in patients with AKI and is a noninvasive technique for the diagnosis of AKI and quantitative evaluation of renal microcirculation.

Identifikasi Non-Added Value Activity Dalam Proses Pemeriksaan Substantif Permohonan Paten Menggunakan Value Stream Mapping

The process of substantive patent examination which is complicated and takes a long time is one of the reasons the inventor is "reluctant" to apply for a patent on his invention. This research was conducted using the Current State Value Stream Mapping (CSVSM) method, which began with the creation of a process flow map with the cycle time of each activity. It is known that most of the activities are value added activities. However, there is 1 activity that is required but not added value, namely the activity of verifying the technical field of application documents; and 1 non-value-added activity, namely initialing the Patent Granting letter. The number of waiting/delaying incidents is a waste in the process of substantive examination of patent applications caused by: (a) employees generally do double work; and (b) the absence of SOPs in each sub-process/sub-activity in the process of substantive examination of patent applications. Proposed improvements are submitted in the Future State Value Stream Mapping (FSVSM). As a result, lead-time can be reduced to 11 days, which was originally 26 days; and Process Cycle Efficiency which was originally 19.23% increased to 45.45%

A Systematic Review of Deep Learning for Intelligent Transportation Systems with Analysis and Perspectives

This study presents a systematic review of deep learning for intelligent transportation systems. Statistics are used to find the most cited articles, and the number of articles and quotes are used to find the most productive and influential authors, institutions, and countries or regions. Key topics and patterns of change are discovered using the authors’ keywords, and the most common issues and themes are revealed using flow maps and showing the corresponding trends. A co-occurrence keyword network is also developed to present the research landscape and hotspots in the field. The results explain how publications have changed over the past seven years. Researchers can use this study to have a deeper understanding of the current state and future trends in the role of deep learning in intelligent transportation systems.

Compressible fluids interacting with 3D visco-elastic bulk solids

We consider the physical setup of a three-dimensional fluid–structure interaction problem. A viscous compressible gas or liquid interacts with a nonlinear, visco-elastic, three-dimensional bulk solid. The latter is described by an evolution with inertia, a non-linear dissipation term and a term that relates to a non-convex elastic energy functional. The fluid is modelled by the compressible Navier–Stokes equations with a barotropic pressure law. Due to the motion of the solid, the fluid domain is time-changing. Our main result is the long-time existence of a weak solution to the coupled system until the time of a collision. The nonlinear coupling between the motions of the two different matters is established via the method of minimising movements. The motion of both the solid and the fluid is chosen via an incrimental minimization with respect to dissipative and static potentials. These variational choices together with a careful construction of an underlying flow map for our approximation then directly result in the pressure gradient and the material time derivatives.

Ultrasound vector mapping of common femoral artery blood flow in normal and early-stage stenosis

It is assumed that the wall shear stress (WSS), which determines the function of the endothelium, is constant along the arterial bed. The assessment of turbulence, blood flow velocity in the arterial system in healthy (13 patients) and in patients with the initial form of atherosclerosis in the femoral artery (42 patients) was discussed. The study quantified blood flow in the common femoral artery using V Flow with visualization of blood flow with a high frame rate. The results obtained in the femoral arteries were evaluated by the wall shear rate, velocity profile and oscillation index (OSI). It was shown that the average value of WSSmean in the femoral artery in healthy and in patients with stenosis &lt;30–35% is 0.9± 0.4 – 0.91±0.4 Pa and does not significantly differ. The wall thickness in the common femoral artery in patients with the initial form of atherosclerosis was 0.9–1.1 mm, and in healthy patients 0.8–0.9 mm. The correlation between the parameters was evaluated by nonparametric analysis of Kendall’s Taub. It was revealed that there is no correlation between WSSmean and blood flow velocity (Vs) in both healthy and patients with the initial form of atherosclerosis.

Strategies to Improve COVID-19 Vaccination in a Pregnant, Marginalized Population: Quality Improvement Project.

Objectives. To improve COVID-19 vaccination rates in pregnant and recently pregnant women from a baseline rate of 30.8% to 60% over 6 months in a marginalized population. Methods. This quality improvement (QI) project was conducted in a federally qualified health center in Western New York between November 2021 and April 2022, using a Lean Six Sigma method. The QI team created a fishbone diagram, process flow map, and driver diagram. Significant barriers were multiple preferred languages, limited health literacy, and a knowledge gap. Increased vaccination rates were the outcome measure. The process measures were attendance at educational events and increased knowledge in community health workers (CHWs) and doulas. Education for CHWs and patients, creating multilingual educational resources, and motivational interviewing sessions for CHWs and patients were the major interventions. We performed data analysis by using weekly run charts and a statistical process control chart. Results. We achieved a sustainable increase in the COVID-19 vaccination rates in women from 30.0% to 48% within 6 months. Conclusions. Patient education in their preferred languages and at health literacy levels and CHWs' engagement played a crucial role in achieving success. (Am J Public Health. 2024;114(S4):S322-S329. https://doi.org/10.2105/AJPH.2024.307665).

Artificial Neural Networks for Gas‐Liquid Flow Regime Classification in Small Channels

AbstractThe reliable design of multiphase micro‐structured apparatus requires a precise knowledge of the internal flow regime. Previous research indicated that classifiers based on artificial neural networks (ANN) are relatively simple to develop and provide a reasonable accuracy when trained with data for specific inlet designs. This paper introduces advanced ANN classifiers capable of predicting all relevant flow regimes regardless of the inlet design with a recall of 94 % and above for Taylor, churn, dispersed, rivulet, and parallel flows, between 89 % and 94 % for annular and bubbly flows, and 83 % for Taylor‐annular flow. These classifiers were trained and validated by using more than 13,000 experimental data points extracted from 97 flow maps.