Flow Time Research Articles

Model Pemilihan Rute Antara Jalan Nasional dan Jalan Tol Surabaya (Bundaran Waru)-Jombang dengan Metode Pembebanan Bertahap

The interactions that occur between the City of Surabaya and the City of Jombang are not only influenced by economic factors, but are also influenced by social factors of life. Residents who are outside the Jombang City area will try to choose the fastest route from several routes that connect their home zone with Jombang City. This research was conducted based on factors that influence the process of choosing a travel route from Surabaya City to Jombang City using class I, class II and class III vehicles. The influencing factors are travel time and vehicle flow. The available route options are via national roads and toll roads. In this research, an analysis of route selection was carried out using the gradual loading method. The gradual loading method was chosen because it can determine the relationship between traffic flow and travel time, without depending on driver assumptions and road network characteristics. After carrying out the analysis using the gradual loading method, the wardrop balance value can then be calculated, the results of which can show that the conditions are balanced and the driver can determine which route to take. From the results of a simple linear regression analysis, a model of the flow - travel cost relationship on the Surabaya - Jombang National Road route was obtained with the equation form 55.63 + 0.031X, while on the Surabaya - Jombang Toll Road route the equation form was 32.044 + 0.024X. The wardrop balance value at a uniform fraction loading of 25% was found to be 0.18 and at a uniform fraction loading of 10% and a non-uniform fraction of 10%, 20%, 30%, 40% the value was 0.03. This value is relatively small and can be interpreted that the condition is close to wardrop equilibrium.

Effect of para-wood ash and calcium carbonate on the properties of eco-friendly self-compacting mortar reinforced with electronic waste fibers

This paper deals with reducing CO2 emissions from cement production and finding alternative uses for electronic waste (E-waste) fibers in some innovative applications in self-compacting mortar (SCM). In the present research, an attempt has been made to establish the optimum incorporation of E-waste fiber into SCM by varying the fiber content from 5 % to 25 %, combined with para-wood ash and calcium carbonate as supplementary cementitious materials. In this laboratory study, the mix design had a constant water-to-powder ratio of 0.35 and a cement content of 550 kg/m³. Additionally, 20 % of the cement volume was replaced by 10 % para-wood ash and 10 % calcium carbonate. The results indicated a continuous increase of the mini-slump values from 255 mm for the control mix to 270 mm for the mix with the highest fiber content. Mini V-funnel flow times increased from 3.63 to 8.83 s as the fiber content increased. Lower fiber contents of 5 % improved compressive strength because they had a reinforcing role in the matrix of SCM besides the microcrack-bridging role. Higher contents of 10–25 % decreased the strength due to the clustering of fibers and resulting voids. SEM analysis at 28 days showed increased voids with higher percentages of E-waste fibers and para-wood ash alone. The results underline that optimizing fiber content is critical in balancing workability and mechanical properties, and 5 % e-waste fiber content can be considered optimal for enhancing the performance of SCM. This work also creates part of sustainable construction practice with the green solution required to reduce CO2 emissions and work accumulation against E-waste.

Impact of preocular and ocular circulatory dynamics on the vascular density of retinal capillary plexuses and choriocapillaris.

To highlight the influence of preocular and ocular vascular circulatory dynamics on the vascular density (VD) of retinal capillary plexuses (RCPs) and choriocapillaris (CC) in patients with and without cardiovascular risk (CVR) factors. A retrospective observational study in patients with and without CVR factors (type 1 and 2 diabetes, arterial hypertension, and hypercholesterolemia). Fluorescein (FA) and indocyanine (ICGA) angiography circulatory times were arterial time (FAAT), start (FAstartLF) and end (FAendLF) of laminar flow, and arterial time (ICGAAT), respectively. OCT angiography VDs were superficial (VDSCP) and deep (VDDCP) RCPs and CC (VDCC) VDs. Correlation and regression analysis were performed after adjusting for confounding factors. 177 eyes of 177 patients (mean age: 65.2 ± 15.9years, n = 92 with and 85 without CVR) were included. VDSCP and VDDCP were significantly inversely correlated with FAAT, FAstartLF and FAendLF likewise VDCC with ICGAAT. Correlations were stronger in patients without CVR than with CVR. CVR, FAAT, FAstartLF and FAendLF were more strongly correlated with VDDCP than VDSCP. FAAT, FAstartLF and FAendLF significantly impacted VDSCP and VDDCP, likewise ICGAAT impacted VDDCP. VDDCP was most strongly impacted by FAAT and FAstartLF. Ocular and pre-ocular circulatory dynamics significantly impacted RCPs and CC VDs, especially deep RCP.

Recovering the activity parameters of an active fluid confined in a sphere.

The properties of an active fluid, for example, a bacterial bath or a collection of microtubules and molecular motors, can be accessed through the dynamics of passive particle probes. Here, in the perspective of analyzing experimental situations of confinement in droplets, we consider the kinematics of a negatively buoyant probe particle in an active fluid, both confined within a spherical domain. The active bath generates a fluctuating flow that pushes the particle with a velocity that is modeled as a colored stochastic noise, characterized by two parameters, the intensity and memory time of the active flow. When the particle departs a little from the bottom of the spherical domain, the configuration is well approximated by a particle in a two-dimensional harmonic trap subjected to the colored noise, in which case an analytical solution exists, which is the base for quantitative analysis. We numerically simulate the dynamics of the particle and use the planar, two-dimensional mean square displacement to recover the activity parameters of the bath. This approach yields satisfactory results as long as the particle remains relatively confined; that is, as long as the intensity of the colored noise remains low.

Identifying Urban functional regions: A multi-dimensional framework approach integrating metro smart card data and car-hailing data

Urban functions often diverge from initial planning due to changes driven by residents’ behaviors. Effective urban planning and renewal require accurately identifying urban functional regions based on residents’ behavior data (including activity and travel data). However, previous methods have primarily relied on either point of interest (POI) data or a single source of traffic data, and often ignore the combined influence of residents’ activities and travel behaviors. In this study, we introduce a novel framework that integrates multiple sources of traffic data (such as metro smart card data and car-hailing data) with POI data to identify urban functional regions. This approach is unique because it simultaneously considers two critical dimensions of residents’ behavior: travel and activity behaviors. By combining these dimensions, we extract a comprehensive set of characteristics, including travel time, travel flow, origin-destination patterns, activity types, and activity time, which are then aggregated at the regional level (i.e., traffic analysis zone). To process these characteristics, we use latent Dirichlet allocation (LDA) to extract high-level semantic features from each data type. Additionally, to handle the sparse data from metro smart cards, we employ a specialized clustering technique. The integration of diverse and complementary information from multiple data sources enables more accurate and nuanced identification of urban functional regions than single data source and k-means clustering algorithm, providing valuable insights for urban planners.

Spatio-Temporal Variability of Water Quality in the Middle Danube—The Influence of Air Temperature and Discharge

Large watercourses are characterised by significant spatial and temporal changes in water quality due to both natural and anthropogenic impacts. The paper analyses changes in the Danube’s spatial and seasonal water quality in its middle part at five monitoring stations for the period 2018–2022. Examined water quality parameters include oxygen saturation (Os), ammonium (N-NH4), pH, 5-day biochemical oxygen demand (BOD), nitrate nitrogen (N-NO3), orthophosphates (P-PO4), suspended solids (SS), electrical conductivity (EC), and water temperature (WT). Furthermore, the analysis took into account the influence of two additional factors: air temperature (AT) and discharge (D). Throughout the entire period under study, all parameters were characterised by low concentration values, which met the environmental objective of good ecological status. The use of multivariate statistical methods allowed for the identification of EC, N-NH4, WT, Os, SS, and N-NO3 as determining the greatest spatio-seasonal variability of water quality in a selected section of the Danube. Regression models determined WT, EC and nitrogen nitrate changes as depending on AT, flow, and exposure time. Knowing models not only gives a better understanding of the dynamics of changes in water quality in the stretch of the Danube under study but potentially allows the prediction of these parameters based on easily measurable environmental variables.

Influence of Manufactured Sand on Fresh Properties, Strength Properties and Morphological Characteristics of Self-Compacting Coconut Shell Concrete

This research examines the fresh properties, strength performance, and morphological analysis of self-compacting coconut shell concrete (SCCSC) blended with crushed coconut shell and manufactured sand (M-sand). Crushed coconut shell (CS) was used as a coarse aggregate (CA), and M-sand replaced river sand (R-sand) at 25%, 50%, 75%, and 100%. The study focused on the workability characteristics, mechanical behavior, and microstructural analysis of SCCSC. Experiments were performed on fresh and mechanical characteristics, including slump flow diameter, T500 slump flow time, L-Box blocking ratio, V-funnel and a wet sieving stability test. Mechanical characteristics include compressive, split tensile, flexural, impact resistance and bond strength. Utilizing M-sand develops the mechanical performance of SCCSC. The morphological characteristics, using scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), Fourier transform infrared (FTIR) and the X-ray diffraction (XRD) technique, were studied in this research work. The findings show that the addition of M-sand increases the concrete strength. The microstructural analysis demonstrates that adding different amounts of M-sand to SCCSC reduced the porosity and anhydrous cement percentage, although it increased calcium hydroxide and hydration products. The substitution of 100% M-sand at 28 days increased compressive strength by 3.79% relative to the reference SCCSC. Based on the findings, the mechanical strength of SCCSC containing M-sand significantly improved compared to the concrete with river sand.

Short-Term Traffic Flow Prediction Based on Wavelet Analysis and XGBoost

Traffic flow prediction is of great significance for urban planning and alleviating traffic congestion. Due to the randomness and high volatility of urban road network short-term traffic flow, it is difficult for a single model to accurately estimate traffic flow and travel time. In order to obtain more ideal prediction accuracy, a combined prediction model based on wavelet decomposition and reconstruction (WDR) and the extreme gradient boosting (XGBoost) model is developed in this paper. Firstly, the Mallat algorithm is applied to perform multi-scale wavelet decomposition on the average travel time series of the original traffic data, and single branch reconstruction is performed on the components at each scale. Secondly, XGBoost is used to predict each reconstructed single-branch sequence, so as to obtain multiple sub-models, and the Bayesian algorithm is used to optimize the hyperparameters of the sub-models. Finally, the algebraic sum of the predicted values of all sub-models is used to obtain the overall traffic prediction result. To test the performance of the proposed model, actual traffic flow data has been collected from a certain link of the Brooklyn area in New York, USA. The performance of proposed WDR-XGBoost model has been compared with other existing machine learning models, e.g., support vector regression model (SVR) and single XGBoost model. Experimental findings demonstrated that the proposed WDR-XGBoost model performs better on multiple evaluation indicators and has significantly outperformed the other models in terms of accuracy and stability.

Machine learning mapping of lattice correlated data

We discuss a machine learning (ML) regression model to reduce the computational cost of disconnected diagrams in lattice QCD calculations. This method creates a mapping between the results of fermionic loops computed at different quark masses and flow times. The ML mapping, trained with just a small fraction of the complete data set, makes use of translational invariance and provides consistent result with comparable uncertainties over the calculation done over the whole ensemble, resulting in a significant computational gain.

Potential Legacy of SWOT Mission for the Estimation of Flow–Duration Curves

Flow–duration curves (FDCs) provide a compact view of the historical variability of river flows, reflecting climate conditions and the main hydrologic features of river basins. The Surface Water and Ocean Topography (SWOT) satellite mission will enable the estimation of river flows globally, by sensing rivers wider than 100 m with a sampling recurrence from 3 to 21 days. This study investigated the lifetime mission potential for FDC estimation through the comparison between remotely-sensed and empirical FDCs. We employed the Global Runoff Data Center dataset and derived SWOT-like river flows by selecting gauging stations of rivers wider than 100 m with more than 10-year long daily river flow time series. Overall, 1200 gauged river cross-sections were examined. For each site, we created a set of 24 SWOT-simulated FDCs (i.e., based on different sampling recurrences, mean biases, and random errors) to be compared against their empirical counterparts through the Nash–Sutcliffe efficiency and the mean relative error. Our results show that climate and the sampling recurrence play a key role on the performance of SWOT-based FDCs. Tropical and temperate climates performed the best, whereas arid climates mostly revealed higher uncertainties, especially for high- and low-flows.

Multilayer Diamond‐Like Carbon Films on Monocrystalline Diamond

Multilayer films of diamond‐like carbon (DLC) on monocrystalline diamond substrates have been for the first time obtained by plasma‐chemical deposition. Their chemical composition and structural and morphological properties are studied. The DLC individual layers differ in their sp3 carbon content. The multilayer nature of the resulting coatings is confirmed by periodic density modulation on the small‐angle X‐ray reflectometry curve and modulations in the CsC8, CsC6, CsC4 lines on the crater depth profile of secondary ions of elements (secondary ion mass spectrometry). The dependence of the deposition rate of multilayer DLC films on diamond, their composition and properties on the argon additive to the reaction gas mixture, as well as on methane flow, pressure and growth time, are studied.

Flow control and imbibition dynamics studies in paper membranes using inert additives

Regulating fluid transport and efficiently controlling imbibition dynamics across the surface of paper assays may increase the detection sensitivity in medical diagnostic applications. The present paper deals with inert additives strategically implemented on various cellulose-based filter-paper membrane surfaces to control the flow dynamics. Studies have been carried out to investigate the effect of additive positioning, additive amount, and the cascading effect of the additive on time delay. Fluid-imbibed images have been processed via mean grayscale intensity variation to understand the saturation extent qualitatively. The tactical application of additives resulted in a flow time increment of up to 121.6 %. A flow time delay analysis was carried out to display the effect of the influencing parameters. Further, imbibition dynamics in the additive-laden paper membrane were captured using a modified Lucas-Washburn model. Finally, the extent of reusability of the paper membranes used was investigated using various drying procedures.

Mechanical performance of eco-friendly self-compacting concrete (SCC) mixtures and two-way slabs partially containing cement kiln dust as cement replacement and internally reinforced with waste plastic mesh

A large quantity of cement kiln dust (CKD) is produced annually during the production of Portland cement. The majority of the produced CKD remains unused except in specific cases related to soil stabilization projects. The current research investigates the production of self-compacting concrete (SCC) mixtures, in which CKD is used as a substitute for cement in different weight proportions, 3 %, 6 %, 9 %, 12 %, and 15 %. The hardened mechanical properties of SCC, such as compressive strength, splitting tensile strength, and flexural strength, as well as the fresh state characteristics (i.e., slump flow diameter, T500, V-funnel, and L-box tests), were recorded and compared with the control mixture which was entirely cast using cement. Results revealed that with an increase in the CKD content beyond 6 %, the slump flow diameter of SCC mixtures significantly decreased. Also, the increase ratios in the V-Funnel flow time for self-compacting concrete mixtures, when replacing cement with CKD ratios of 3 %, 6 %, 9 %, 12 %, and 15 %, were 13.3 %, 30 %, 46 %, 58 %, and 66.7 % respectively, compared with the reference mixture. Additionally, the impact behavior of two-way SCC slabs cast using CKD ratios ranging from 3 to 15 % and internally strengthened using various patterns of recycled plastic mesh was investigated. Strengthening the SCC slabs using two layers of recycled plastic grids proved to be effective in preventing the projectile from penetrating the whole thickness of the SCC slabs, regardless of the CKD content.

Comprehensive examination of regional railway passenger behavior and dwell time components: Insights from video-based observations in Victoria, Australia

In understudied regional railway operations, this study explores passenger boarding and alighting patterns and how station design impacts them, particularly dwell times. Despite extensive metropolitan and suburban train research, regional railways have been overlooked. This study investigates regional rail passenger flow and dwell time to bridge this gap. This article studies dwell times and passenger boarding and alighting at two regional stations in Victoria, Australia, using CCTV data. The objective is to identify insights that might improve regional railway services' efficiency and user experience and advocate for sector-specific solutions. Analysis indicates distinct station boarding and alighting features, highlighting the discovery of the ‘blinded phenomenon’ for train conductors particularly in the afternoon peak (PMP). The results of the study showed that PMP services, which prioritise alighting passengers, had higher dwell times than the morning peak (AMP) services, which emphasise boarding passengers. Obstructed views make it difficult for train conductors to monitor passenger alighting, prolonging dwell times. Better human resource strategies, artificial intelligence for crowd surveillance, and strategic CCTV system deployment to streamline operations and improve passenger experience on regional railways are proposed in the paper, laying the groundwork for future research and operational changes in this vital transportation sector.

A resource prediction method for air traffic cyber-physical-social system

Air traffic is exhibiting the characteristics of large flow, strong coupling, and high time variation. Therefore, the complex network of air traffic is more vulnerable to disturbances. When it is disturbed, the failure of some nodes spreads through dependency relationships in the network, resulting in cascade failure. In the event of a cascade failure, the network may quickly collapse until it is paralyzed, with widespread delays and flight cancellations. The current flow management and deployment methods still remain in the control-oriented stage, which is mainly completed by air traffic controls (ATCs), and lack of accurate flow adjustment and effective utilization of capacity. The whole air traffic system and its peripheral factors are intricate, so human and social factors must be integrated into the control and decision-making of the system. Considering engineering and social factors such as operation environment, social environment, personnel, rules, equipment, and information processing, we analyse the air traffic in a cyber-physical-social system (CPSS). To reflect the actual system behaviour rules, dynamic response, limit state, and so on, the corresponding computational experiment and comprehensive evaluation system are established. Based on neural networks and other technologies, a resource prediction scheme based on task demand is proposed for multi-dimensional resources such as airports, air routes, and ATC, to reduce the cost of system resource scheduling and improve resource utilization through resource prediction and adjustment. Finally, the accuracy of the proposed resource prediction algorithm is verified by theoretical analysis and simulation.

Pressurized liquid extraction followed by high-performance liquid chromatography for determination of beta-ecdysone extracted from Pfaffia glomerata (Spreng.) Pedersen

Pfaffia glomerata (Spreng.) Pedersen has among its main bioactive compounds saponins, with the phytoestroid β-ecdysone as its chemical marker. In this study, pressurized liquid extraction (PLE), a green extraction technique used to obtain bioactive compounds from plants, was employed to extract beta-ecdysone from P. glomerata leaves, stems, and roots. The 22 factorial design was used with the variables temperature (333 K and 353 K) and flow rate (1.5 and 2 mL min−1), pressure (300 Bar), time (60 min), and solvent [ethanol and distilled water (70:30 (v/v)] were kept constant for all parts of the plant. The results of experimental responses demonstrated that the factors temperature and flow rate significantly interfere with the yields of leaf (0.499%), root (0.65%) and stem (0.764%) extracts. The latter presented presents the highest yield compared to the other parts of the plant. HPLC results showed the presence of beta-ecdysone in all parts of the plant with concentrations of β-ecdysone 86.82, 76.53 and 195.86 mg L−1 to leaf, root and stem, respectively. FT Raman results exhibited typical peaks of beta-ecdysone, such as 3310 cm−1, 1654 cm−1, and 1073 cm−1 for all plant parts. Another interesting result was the presence of the peak at 1460 cm−1 in the PLE root extract can be associated with selenium. This foundational knowledge confirms that the PLE extraction process was efficient in obtaining the chemical marker of Pfaffia glomerata in all plant parts.

Effects of mixing water and environmental pH value on the properties of sulfoaluminate cement-based ultra-high water materials

In order to grasp the influence of the pH value of mixing water and environmental water on the properties of ultra-high water materials, this article separately carried out the influence of different pH values of mixing water on the properties of ultra-high water materials and the conservation of high-water materials in water environments with different pH values. Using test methods such as loss of flow time, compressive strength, Scanning Electron Microscope (SEM), X-Ray Diffraction (XRD), Thermogravimetric-Differential Thermal Analysis (TG–DTA), to conduct regular exploration and mechanism analysis. The study found that with the continuous increase of the pH value of the mixing water, the loss of flow time of the ultra-high water material gradually decreased, and the compressive strength of the samples at the same age continued to increase. A lower pH value will affect the compressive strength of the consolidated body of the ultra-high water material, but when the pH = 13 in the reaction solution, the compressive strength of the consolidated body will no longer increase and begin to produce a weakening effect. The pH of the construction water for ultra-high water materials is recommended to be 4–13. At the same time, it was found that under the conservation of an acidic environment, the consolidated body was severely eroded and the strength loss was large. The acid–base environment of the goaf suitable for filling with the ultra-high water material should be between pH = 7–10 to ensure that the filling body is not weakened by erosion.

Recycling and reuse of waste banded iron formation as fine aggregate in the production of lightweight foamed concrete: Fresh-state, mechanical, thermal, microstructure and durability properties assessment

This study investigates the possibility of using BIFs as sustainable fine aggregates to produce lightweight foam concrete (LWFC) by replacing sand with 5, 10, 15, 20, and 25 % banded iron formations (BIFs). The fresh concrete properties, such as slump flow, density, and setting time, as well as its mechanical properties, including compressive strength, splitting strength, and flexural strength, were investigated. The thermal conductivity, specific heat, porosity, gas permeability, pore distribution, and sorptivity were measured to determine durability and thermal performance. Microstructural analysis of the mixes was performed using SEM, energy-dispersive X-ray spectroscopy (EDX), and mapping. The results recommended a 10 % replacement ratio to achieve an increased compressive strength ratio of 55.88 % compared to the control mix at 7 days (d). The strength at later ages increased compared to that of the control mix by 33.9 %, 30 %, 42.48 %, and 42.4 % at 14, 28, 56, and 180 d, respectively. In addition, the flexure increased by 42.7 % at 7 d, 49.6 % at 14 d, and 45.6 % at 28 d compared to the control mix. In addition, the UPV also increased gradually from 2757 to 3699 km/s with increase in BIFs content. Furthermore, the porosity decreased at 7 d, 14 d, 28 d, and 90 d. Moreover, chloride penetration decreased by 2.5 %, where an improvement in thermal conductivity was achieved with BIFs to 0.342 W/mK compared to that of the control mix. In addition, a reduction in the specific heat of the material from 1042 J/kg K to 1007 J/kg K was observed. SEM showed a better arrangement of pores when BIFs were utilized compared with that of control mix without BIFs. In conclusion, the incorporation of waste BIFs as fine aggregates in lightweight foam concrete demonstrates a promising potential for enhancing the mechanical and thermal properties of construction materials, paving the way for durable building materials in the construction industry.

Tracking the porphyry-epithermal mineralization transition using U-Pb carbonate dating

Key metals important for the green energy transition concentrate during magmatic-hydrothermal processes. In porphyry deposits, epithermal mineralization can overprint earlier higher-temperature systems. It is not well understood whether mineralization occurs in a single evolving system or forms during pulsed, episodic overprinting events. The timing and duration of fluid flow therefore remain key data gaps in deposit models, but they are essential factors for understanding metal (re)mobilization and concentration processes. Carbonates are common gangue minerals that precipitate during fluid flow and can be dated using the U-Pb method, thereby directly dating hydrothermal processes. Here, 41 new U-Pb dates from a fault-controlled porphyry-epithermal system in Yukon, Canada, reveal a >50 m.y. record of carbonate precipitation between ca. 77 and 19 Ma. Results support a model of pulsed, episodic fluid flow, rather than a single evolving system, where epithermal carbonate precipitation at ca. 74−67 Ma was both coeval with and significantly postdated Cretaceous porphyry-related magmatism. Overprinting events at ca. 62−56 Ma, ca. 51−47 Ma, and younger than 40 Ma were not responsible for primary metal deposition but may have contributed to metal enrichment. Carbonate dates coincide with periods of brecciation and fault slip. Fault movement therefore enabled episodic overprinting by epithermal mineralization, mobilizing and (re)concentrating metals. This comprehensive reconstruction of a long-lived magmatic-hydrothermal system tracks the transition from porphyry to epithermal environments, demonstrating the power of carbonate U-Pb dating for critical minerals research.

Impact of climate change on water scarcity in Pakistan. Implications for water management and policy

ABSTRACT Water resources in Pakistan are under serious threat from climate change (CC), exacerbating water scarcity. The implications for water policy and management are far-reaching. Pakistan relies heavily on the Indus Basin Irrigation System (IBIS) for agricultural production and water supply, but the distribution and availability of water resources are threatened by changing climatic patterns, such as changing precipitation and melting glaciers. Water scarcity is heightened by faster glacial melt and erratic precipitation patterns, which affect the timing and quantity of water flow. Effective water management techniques, such as increased effectiveness, sustainable practices, and conservation measures, as well as robust infrastructure and governance are required to address these issues. Pakistan can benefit greatly from international cooperation and assistance to mitigate the impacts of CC and ensure water security for long-term development.