Flux Range Research Articles

Nonlinearity Measurement of Si Transferring Photodetector in the Low Radiation Flux Range

In order to establish a transferring chain from a photon flux of a single-photon source in quantum radiometry, the nonlinearity of the photodetector needs to be accurately measured. Using the flux superposition method, a nonlinearity measurement setup has been designed. The measurement setup consists of two tungsten halogen lamps, parent–child integrating spheres, an adjustable aperture, a diaphragm tube, and an optical filter. It has the advantage of low polarization error, low interference error, and low stray light effect. The Si photodiode to be measured is cooled to −40 °C to obtain a low noise level for low-flux radiation measurement. The nonlinearity of the Si photodetector is measured for photocurrent ranges from 10−12 A~10−6 A level, with a relative standard uncertainty from 0.0092~0.023%. The relative standard uncertainty of the nonlinearity correction factor ranged from 0.023~0.049%.

NIKA2 Cosmological Legacy Survey

Context. Finding and characterizing the heavily obscured galaxies with extreme star formation up to very high redshift is key for constraining the formation of the most massive galaxies in the early Universe. It has been shown that these obscured galaxies are major contributors to the accumulation of stellar mass to z ~ 4. At higher redshift, and despite recent progress, the contribution of dust-obscured galaxies remains poorly known. Aims. Deep surveys in the millimeter domain are necessary in order to probe the dust-obscured galaxies at high redshift. We conducted a large observing program at 1.2 and 2 mm with the NIKA2 camera installed on the IRAM 30m telescope. This NIKA2 Cosmological Legacy Survey (N2CLS) covers two emblematic fields: GOODS-N and COSMOS. We introduce the N2CLS survey and present new 1.2 and 2 mm number counts measurements based on the tiered N2CLS observations (from October 2017 to May 2021) covering 1169 arcmin2. Methods. After a careful data reduction and source extraction, we develop an end-to-end simulation that combines an input sky model with the instrument noise and data reduction pipeline artifacts. This simulation is used to compute the sample purity, flux boosting, pipeline transfer function, completeness, and effective area of the survey (taking into account the non-homogeneous sky coverage). For the input sky model, we used the 117 square degree SIDES simulations, which include galaxy clustering. Our formalism allows us to correct the source number counts to obtain galaxy number counts, the difference between the two being due to resolution effects caused by the blending of several galaxies inside the large beam of single-dish instruments. Results. The N2CLS-May2021 survey is already the deepest and largest ever made at 1.2 and 2 mm. It reaches an average 1σ- noise level of 0.17 and 0.048 mJy on GOODS-N over 159 arcmin2, and 0.46 and 0.14 mJy on COSMOS over 1010 arcmin2, at 1.2 and 2 mm, respectively. For a purity threshold of 80%, we detect 120 and 67 sources in GOODS-N and 195 and 76 sources in COSMOS at 1.2 and 2 mm, respectively. At 1.2 mm, the number counts measurement probes consistently 1.5 orders of magnitude in flux density, covering the full flux density range from previous single-dish surveys and going a factor of 2 deeper into the sub-mJy regime. Our measurement connects the bright single-dish to the deep interferometric number counts. At 2 mm, our measurement matches the depth of the deepest interferometric number counts and extends a factor of 2 above the brightest constraints. After correcting for resolution effects, our results reconcile the single-dish and interferometric number counts, which can be further accurately compared with model predictions. Conclusions. While the observation in GOODS-N have already reached the target depth, we expect the final N2CLS survey to be 1.5 times deeper for COSMOS. Thanks to its volume-complete flux selection, the final N2CLS sample will be an ideal reference for conducting a full characterization of dust-obscured galaxies at high redshift.

Superconducting quantum interference device readout circuit with tunable feedback polarity.

Feedback circuits, which act as functional units in superconducting quantum interference device (SQUID) readout circuits, such as positive feedback circuits for suppressing the preamplifier noise contribution or negative feedback circuits for increasing the linear flux range of SQUID, enable SQUIDs to achieve high performance in practical applications. Integrating feedback circuits with different functions into a single SQUID chip contributes to the construction of highly compact SQUID electronics. Here, we propose a SQUID readout circuit with tunable feedback polarity (TFP). The switching of the feedback polarity is easily realized by applying a control current to the superconducting switches integrated into the SQUID chip. The enhancement of the flux-to-voltage transfer coefficient or the linear flux range depends on the choice of feedback polarity. In addition, we introduce a two-stage scheme to address the degraded noise performance induced by negative feedback. This work attempts to develop a compact and versatile architecture of SQUID readout by using a set of compatible superconducting technologies.

Evaluation of Pressure, Surface Characteristics, and Fluid Properties Effect on Pool Boiling Heat Transfer Over Plain and External Micro-Finned Cylindrical Surfaces

Abstract Pool boiling is extensively used in high- and low-temperature heat exchangers as it results in a high heat transfer coefficient compared to natural and single-phase forced convection. Pool boiling experimental study conducted over a plain cylindrical surface (PS) and four external micro-finned cylindrical surfaces (MFCSs), with R123 and R141b at different pressures in the heat flux range 20–100 kW/m2, is presented in this paper. The objective of the present study is to explore the effect of pressure, surface characteristics, and fluid properties on pool boiling heat transfer over plain and micro-finned cylindrical surfaces. The boiling performance improved at a higher pressure, irrespective of the working fluid used for all the test surfaces. It was found that, with the rise in pressure, the boiling heat transfer coefficient (BHTC) for the MFCSs increases at a higher rate than the PS. In comparison with PS, the average rise in the BHTC with pressure, for the MFCS-1, MFCS-2, MFCS-3, and MFCS-4 with R123 were 69.3% to 84.3%, 3.3% to 9.9%, 16.9% to 22.4%, and 29.4% to 40.2%, respectively. The higher BHTC over micro-finned cylindrical surfaces results due to more nucleation site results from lower surface wettability and micro-finned geometry. It was observed that the pool boiling over the plain surface with R123 results in higher BHTC compared with R141b at all tested pressures, whereas the pool boiling characteristics over MFCSs varied based on the combined effect of micro-finned surface geometry, surface wettability, heat flux, pressure and fluid properties. The bubble departure diameters over all the surfaces were measured at 30 W, 60 W, and 90 W at different pressures, and a new model of bubble departure diameter was proposed based on dimensionless terms. The total mean absolute error (MAE) of the proposed bubble departure diameter model was about 6.79% for the whole range of data points.

Sediment accumulation rates and carbonate fluxes of deep-sea sediments in the southern Gulf of Mexico

Here we present the mass and carbonate annual fluxes, collected by two sediment traps at 1000 m depth, located on the western and southern deep-water region of the Gulf of Mexico (GM), and compare them with the total mass and carbonate accumulation rates (CAR) from 46 sediment cores retrieved from continental slopes and the abyssal plain of the southern Gulf of Mexico (sGM). CaCO3 fluxes in the sediment traps located close to 1000 m water depth, range between 15.1 and 22.4 g m−2 yr−1, these values fall on the high-end range of the mean fluxes reported for the global ocean (9–22 g m−2 yr−1). The carbonate fluxes from the water column are remarkably close to the CAR in the lower slope and abyssal sediments of the southern GM, implying that dissolution processes of biogenic carbonate in the sediments below 1000 m are negligible in the sGM. The spatial patterns of CARs in the sediments are mainly linked with surface productivity of calcareous organisms and export to depth over the continental slope and abyssal plain regions, with mean values of 15.7 ± 5.7 g m−2 yr−1 (0.15 ± 0.06 mol m−2 yr−1). However, there are some large areas over the abyssal plain to the north of the Campeche escarpment showing enhanced CAR values most likely as a result from two processes, lateral input from the Yucatan carbonate shelf region and massive collapse events originating at the Campeche escarpment and deposited to the north of the Yucatan Platform. These processes can account for an additional increase in carbonate mass accumulation by approximately 8 g m−2 yr−1 in this area, showing a decreasing gradient towards the N of the escarpment. Lateral transport by turbidity currents of carbonate platform sediments along submarine canyons and probably episodic gravity flows further aid to explain the localized higher carbonate mass accumulation (> 20 g m−2 yr−1) observed at the foot of the continental slopes to the west and south of the southern GM. We estimate total carbonate accumulation estimates for the entire Gulf of Mexico, from the upper slope to the abyssal plain (1000–3750 m), considering the northern deep-water region reported by Giering et al., 2018, of 0.09 to 0.12 Tmol/yr accounts for 0.8 to 1.8% of all carbonate sedimentation in the ocean below 1000 m. Taking into considerations its small areal extent of <0.3% of the global ocean the GM carbonate accumulation accounts for a factor of 3 to 6 its areal importance, implying that changes in the production and export of carbonate in the GM due to surface ocean warming and acidification processes in this inland sea will have a sensible effect in the global carbon cycle.

A transient mechanistic two-fluid model for Direct Contact Condensation

Intensified heat treatment, using Direct Contact Condensation (DCC), is applied in the production of dairy products to ensure a high level of food safety. The key challenge with DCC is the protein reactions and fouling that limit operational efficiency and sustainability. The use of validated, transient models to predict temperature, phase fraction and velocity gradients is essential and can improve the operation of DCC. Pilot plant scale experiments were performed for a wide range of steam mass fluxes, inlet water temperatures, water Reynolds number and channel pressures to validate a transient 1D two-fluid model. The model was tested against steady-state experimental data and showed good agreement. In addition the model was tested against transient data in which either the water flow rate was step wise decreased or the pressure was adjusted throughout the experiment. In general the model followed the experimental trend well provided that the flow inside the channel is homogeneous.

A mechanistic model for acoustically enhanced condensation heat transfer and pressure drop

Enhancing low-quality condensation where thermal resistance is the highest is critical for size reduction and efficiency improvements for many power generation, HVAC&R, and chemical processing applications. Recently, acoustic actuation has been shown to enhance low-quality condensation by ∼30% by introducing a sound wave that oscillates between the condenser headers and resonates within the tube, agitating the liquid-vapor interface and significantly altering the distribution of the liquid phase towards the end of condensation, thereby increasing the heat transfer rate. This paper presents a multiple flow-regime model to predict the pressure drop and heat transfer during acoustically actuated condensation based on hydrodynamic changes induced by forced oscillation. Experimental results for R134a flowing through a horizontal tube across the entire quality range for mass fluxes ranging from 120 to 235 kg m−2 s−1, actuation frequencies from 2 to 20 Hz, header volumes from 150 to 1000 mL, and wall-to-refrigerant temperature differences ranging from 6 to 12 K are used for the development of the models. Enhancement mechanisms are discussed and heat-and-momentum analogy-based correlations are developed to accurately predict actuated and unactuated condensation pressure drop and heat transfer data simultaneously within 23% and 7% on average, respectively.

Neutron imaging based vapor fraction measurements in an inductively heated boiling packed bed

During a loss of coolant accident, the formation of porous heat-generating debris bed causes concerns with the further progression of accident through inadequate removal of the decay heat. The sustainable heat removal or cooling of the porous debris bed using emergency coolant water poses limitations on the cooling mechanisms by imposing a maximum removable heat flux, also known as the dryout heat flux. Modeling debris bed cooling and the dryout heat flux requires the use of parameters that are non-linear functions of the vapor fraction in the two-phase flow. These models need high resolution vapor fraction data for validation, which is currently lacking in literature. This paper presents first of a kind high-resolution vapor fraction measurements in an inductively heated debris bed using a non-optical and non-intrusive neutron imaging technique. The neutron beam from TRIGA Mark II reactor at Kansas State University was used to image the packed bed test section and gather vapor fraction data. The vapor fraction measurements are presented for a range of heat fluxes up to the limiting dryout heat flux. Images showing the formation of a dryout zone for heat fluxes higher than the limiting dryout heat flux are also presented. The measured vapor fractions are compared with predictions from the classical 1D Lipinski model. The mean absolute deviation between the model predictions and the measured vapor fractions is found to be less than 10%, providing the first validation of the classical 1D Lipinski model.

Seasonal variability in water‒air CO2 exchanges and carbon origin in a subtropical estuary

The seasonal and interannual variabilities in the water‒air net carbon dioxide (CO2) flux were investigated in the lower zone of the Patos Lagoon Estuary (PLE), the largest choked lagoon worldwide. The studied region experienced periods of CO2 ingassing (outgassing) during ocean-dominated (riverine-dominated) conditions. During ocean-dominated conditions (summer/autumn), CO2 uptake was an average of −15 mmol m–2 d–1, whereas under riverine-dominated conditions (winter/spring), CO2 emissions prevailed, reaching an average of 22 mmol m–2 d–1. The magnitude of CO2 uptake in summer/autumn was comparable to the CO2 released to the atmosphere in winter/spring in the mesomixohaline zone. However, the CO2 uptake in summer/autumn was 4-fold higher than the CO2 released in winter/spring in the euhaline zone of the PLE. Unlike most estuarine systems, the PLE acted as a net CO2 sink, with a net CO2 uptake of −2 mmol m–2 d–1 during the period investigated (May 2017 to June 2021). The water‒air CO2 exchanges are modulated mainly by the balance between continental freshwater discharge and the inflow/outflow of seawater. However, the combined effect of wind speed, biological activity, and water residence time adds complexity to understanding the carbon exchanges in this region. The higher concentration of organic matter entails the highest estuarine CO2 concentration during autochthonous production, which indicates heterotrophy in estuarine waters. Part of this carbon produced in the estuary is likely exported to the coast, as suggested by the high CO2 concentration in the estuary mouth. The CO2 export from the PLE to the coastal zone appears to make the lagoon resilient to regional anthropogenic CO2 build-up. Owing to the water‒air net CO2 flux range associated with complex PLE biogeochemistry dynamics, further investigations as a long-term time-series program will improve knowledge of regional CO2 exchanges in the context of climate and elucidate the role of large estuaries and coastal bays in the global carbon budget.

Complete X-ray census of M dwarfs in the solar neighborhood

Context. X-ray emission is the most sensitive diagnostic of magnetic activity in M dwarfs and, hence, of the dynamo in low-mass stars. Moreover it is crucial for quantifying the influence of the stellar irradiation on the evolution of planet atmospheres. Aims. We have embarked in a systematic study of the X-ray emission in a volume-limited sample of M dwarf stars to explore the full range of activity levels present in their coronae. We look to obtain a better understanding of the conditions in their outer atmospheres and their possible impact on the circumstellar environment. Methods. Based on a recent catalog of Gaia objects within 10 pc from the Sun, we identified all its stars with spectral types between M0 and M4 and we carried out a systematic search for X-ray measurements of this sample. To this end, we used both archival data from ROSAT, XMM-Newton, and the ROentgen Survey with an Imaging Telescope Array (eROSITA) on board the Russian Spektrum-Roentgen-Gamma mission, as well as our own dedicated XMM-Newton observations. To make inferences on the properties of the M dwarf corona, we compared the range of their observed X-ray emission levels to the flux radiated by the Sun from different types of magnetic structures: coronal holes, background corona, active regions, and cores of active regions. In this work, we focus on the properties of stars with the faintest X-ray emission. Results. At the current state of our project, with more than 90% of the 10 pc M dwarf sample observed in the X-ray, there is only one star that has had no detections: GJ 745 A. With an upper limit luminosity of log Lx (erg s−1) &lt; 25.4 and an X-ray surface flux of log FX,SURF (erg cm−2 s−1) &lt; 3.6, GJ 745 A defines the lower boundary of the X-ray emission level for M dwarfs. Together with its proper motion companion (GJ 745 B), it is the only star in this volume-complete sample located in the range of X-ray surface flux that corresponds to the faintest solar coronal structures, namely: coronal holes. The fact that the ultra-low X-ray emission level of GJ 745 B (log Lx (erg s−1) = 25.6 and log FX,SURF (erg cm−2 s−1) = 3.8) is entirely attributed to flaring activity indicates that while its corona is dominated by “holes,” at least one magnetically active structure is present. This structure determines the total X-ray brightness and the coronal temperature of the star.

Experimental study on cooling heat transfer performance of supercritical CO2 in zigzag printed circuit heat exchanger

The zigzag printed circuit heat exchanger (PCHE) is promising as the precooler in the application of supercritical CO2 (S-CO2) Brayton cycle. In this study, the experimental investigation is conducted to explore the heat transfer performance of supercritical CO2 in the mini channels of zigzag PCHE. The experimental range of pressure, temperature and mass flux is 7.5–9.0MPa, 50–90°C and 300–600kg/(m2·s), respectively. The structural parameters of diameter, pitch, and bend angle are D=2.0mm, Lp = 7.24mm and θ = 40°, respectively. The effects of system pressure, inlet temperature, and mass flux on the heat transfer performance of supercritical CO2 are investigated by measuring multiple temperature points along the zigzag channel. The results show that the heat transfer coefficient exhibits a higher level near the pseudocritical region due to the dramatic thermophysical properties variation of supercritical CO2. Meanwhile, both the change of mass flux and pressure have a significant influence on the S-CO2 heat transfer coefficient, while the effect of inlet temperature is relatively small. Furthermore, the comparison is conducted between the existing heat transfer correlations and the experimental results. Four new cooling heat transfer correlations are proposed and compared by considering the effect of velocity change and cross-sectional thermophysical property variation on heat transfer performance. It is found that adding variates to the correlation can improve the prediction accuracy of the results while iterative calculation becomes more difficult. In order to improve the robustness and prediction accuracy, it is determined to choose the correlation without the density form, which predict 91.5% of the experimental data within ±25% error band.

Impacts of riverine pollution on greenhouse gas emissions: A comprehensive review

Many recent studies have revealed that polluted rivers are emerging as potent emitters of greenhouse gases (GHGs). However, the scientific understanding of GHG emissions is still limited. The present review aims to provide a systematic analysis of GHG emissions from polluted rivers in various eco-regions. The analysis highlighted that high nutrient loadings such as total nitrogen (TN), organic carbon (OC), total phosphorous (TP), and the anoxic condition of rivers are the major influencing factors for CO2, N2O, and CH4 emissions. Moreover, a strong positive correlation of trophic level index (TLI) with CH4 and CO2 fluxes was observed. The state-of-art suggested that based on land use and water quality, GHG fluxes from different rivers vary considerably. For instance, the reported N2O fluxes ranged between 0.007 and 3.721 mmol m-2d-1 for urban-impacted rivers and 0.009–0.049 mmol m-2d-1 for agricultural rivers. The CH4 fluxes ranged between 0.001 and 458 mmol m-2d-1, 0.05–1.02 mmol m-2d-1, and 1.40–14.30 mmol m-2d-1 for urban impacted, agricultural and natural rivers, respectively. Further reported CO2 fluxes range between 19.94 and 895 mmol m-2d-1 for urban-impacted rivers. Overall the in-depth analysis of the existing state of the art revealed that water pollution (i.e. eutrophication) enhances the GHG emissions from rivers; therefore, incorporating effective restoration measures can mitigate the intensity of GHG emissions from rivers and assist in achieving sustainable development goals (SDGs).

Soil concentrations and atmospheric emissions of biogenic hydrogen sulphide (H2S) in a Rhizophora mangrove forest

Mangrove forests are potentially large biogenic sources of atmospheric hydrogen sulphide (H2S), featuring among the carbon-richest ecosystems in the world associated with strong soil anoxia and large quantities of sulphates brought by tides. H2S is highly toxic and acts as a precursor for atmospheric sulphur compounds and sulphate aerosols, which contribute to acid deposition and have implications for global climate change. Therefore, understanding H2S emissions in mangroves holds great importance. Yet, its range of emissions remains uncertain. In this exploratory study, soil H2S concentrations were measured during tide stall at both high and low tide in a semi-arid mangrove, which has never been done before. Then, potential H2S fluxes to the atmosphere were estimated at low tide. Soil concentrations were greater at high tide than low tide, probably due to larger soil anoxia (average of −377 vs −179 mV), with average values of 1.40 ± 0.55 and 0.73 ± 0.32 mmol L−1, respectively. Temperature was a key factor controlling soil concentrations, with higher values in the warm season than in the cold season. Average H2S emissions ranged from 5.81 ± 2.58 to 28.74 ± 6.98 μg S m−2 h−1 with a mean value of 14.90 ± 7.90 μg S m−2 h−1. This study contributes to reducing the uncertainty in the variation range of H2S fluxes from mangroves, which may be significant for the global sulphur cycle.

Experimental study on convective heat transfer of S–CO2 under high heat flux

Since the S–CO2 power cycle is of great significance for energy development, in which the design of various vital components involves the heat transfer of S–CO2 at different temperatures and pressures, many researchers have conducted experimental research on the convective heat transfer characteristics of S–CO2. However, as the existing studies primarily focused on low heat flux conditions, there are some gaps in the high heat flux experimental data. In this study, by building an experimental facility, the heat transfer characteristics of S–CO2 in the range of heat flux from 500 kW/m2 to 1000 kW/m2 were studied, and the heat transfer correlation under high heat flux was fitted based on the experimental data. The results have revealed that the heat transfer of S–CO2 under high heat flux differs from that of low heat flux, and the existing empirical correlations have more significant errors under high heat flux. The newly proposed heat transfer correlation has the highest calculation accuracy, which calculates 94% of experimental data within ±30% error. It can meet the actual engineering needs.

Characterizing the flux effect on the irradiation embrittlement of reactor pressure vessel steels using machine learning

In-service exposure to high-energy neutrons embrittles reactor pressure vessel (RPV) steels. An increase in the yield stress (Δσy) results in a corresponding increase in the brittle to ductile transition temperature (ΔTc). Most existing models underpredict ΔTc at higher fluence following accelerated irradiations in test reactors. High fluence, up to 1020 n/cm2 in some cases, will be reached over extended RPV vessel operation of 80 years, or more, at low service flux. Embrittlement has been extensively studied in accelerated, higher flux test reaction irradiations. However, the use of test reactor data naturally raises the question of flux effects. This study used a machine learning approach trained on a set of hardening data, covering a wide range of flux, fluence, and steel compositions to determine the interactive effects of both irradiation and material variables on Δσy. The analysis included machine learning-based cross-plots of the variable dependence of Δσy for six core steels (i.e., CM6, LC, LD, LG, LH, and LI), with controlled differences in their Cu and Ni contents. A primary objective is to evaluate an effective to actual fluence (ɸte/ɸt) ratio, as a function of flux, fluence, and steel composition. This is information critical to properly use intermediate flux-high fluence data in calibrating a low flux-high fluence embrittlement model. The predicted ɸte/ɸt is reasonably consistent with estimates previously derived from a physics-based solute recombination trap model.

Towards a novel magnetic asphalt mixture containing ceramic ferrites for intelligently encoding road traffic sign information

With the development of smart road transport, the use of magnetic coding units (MCU) to store and transmit road traffic sign information is a novel technical solution that emerged in recent years for advancing the V2I communication. In this work, MCU was prepared by partly replacing the aggregates and mineral powder in the AC-13 asphalt mixture (AM) with ceramic ferrites (CF). It was found that the MCU was able to produce a stable and detectable magnetic field after magnetization, while its spatial distribution pattern is programmable. In order to provide technical guidance for MCU design, environmental impacts including erosion and thermal cycling on the magnetic performance of MCU were explored over in further. The following conclusions were obtained: (1) The experimental measurements show that CF has a remanence of more than 20 emu/g and a coercivity of more than 1 k Oe, and as a result, the addition of CF effectively improves the magnetic flux density and detectable range of MCU. (2) Satisfactory corrosion resistance of MUC is observed, which is mainly attributed to the stable hexagonal magnetoplumbite-type crystal structure and large binding energy of Fe3+ within the mixture. (3) Little irreversible flux density loss of the MCU is observed in a large number of thermal cycles in a range of 20–60 °C, which is attributed to the high curie temperature of the CF. Increasing the CF doping can enhance the Fe-O exchange interaction, thus reducing the reduction ratio of the MCU magnetic field at 60 ℃. (4) MCU material has typical viscoelastic response characteristics under mechanical loading, while its dynamic modulus is close to that of ordinary AC-13 AM. (5) The economic cost of using MCU to encode traffic sign information is merely 20.25% of that of conventional traffic signs, which supports further its application potential.

Optimization of divertor design for Pakistan spherical tokamak

Abstract Handling the power deposition, reducing erosion effects, and plasma configuration are the key factors in the design of a divertor. The design of Pakistan Spherical Tokamak (PST) is based on double-null divertor configuration with actively cooled graphite targets at outer/inner strike point and peak heat flux range capacity of 0.1–0.3 MW/m2. The configuration of PST divertor module is designed with mock-up (used flat type tiles on baffles and dome) and cassette (support PFC and cooling channels) technology. Helium-cooled stage and water-cooled stage are two options for divertor. Therefore, one part of this research is focused on water-cooling system for the divertor. This paper presents the divertor design for PST with cooling channel and material analysis of the divertor, which is carried out in three phases. In the first phase, the plasma edge temperature, density, particle velocity, input power, heat flux, and surface temperature are estimated. In second phase, physics and engineering design of divertor system has been performed. In the third phase, COMSOL simulation has been performed to analyses the material properties, surface temperature rise (∆T °C) at stable heat flux, and thermal hydraulic system for the divertor. It is found from the analysis that the specific heat flux of 0.3 MW/m2 up to 3 s is the safe zone limit. The R &amp; D work ratifies that manufacturing and installation processes are plausible for the proposed divertor design. This design is able to meet the requirement of PST. However, increasing time or specific heat flux beyond these limits would require redesigning of the cooling channel.

Retarded Interfacial Formation of Polyamine-Based Nanofiltration Membranes with Pyromellitic Acid: Separation, Acid Stability, and Antifouling Performance

Crosslinked and additive-added polyamide thin-film composite (TFC) nanofiltration (NF) membranes formed by the conventional interfacial polymerization (IP) process have shown good performances. However, studies on polyamine TFC NF membrane prepared via an adjusted IP process with low-cost acid ligands as an interfacial additive for improved liquid-based separation are still lagging. In this regard, a polyamine-based TFC NF membrane synthesized by retarding the interfacial polymerization (IP) process with pyromellitic acid (PMA) (a polycarboxylate acid ligand) is herein reported. The PMA-adjusted membrane displayed a superb range of pure water fluxes from 9.8 to 20.4 L m–2 h–1 bar–1, with the best-performed membrane achieving up to 95.1% for Na2SO4 rejection. Thus, the water permeability of the PMA-TFC membrane is ∼2.4 times as high as the control TFC membrane. The best-performed PMA-TFC membrane showed good hydrophilicity, pressure resistance, and long-term filtration stability. In addition, the membrane structural stability was maintained with ∼3.9% declination in salt rejection after 30 days of immersion in 0.1 M HNO3 solution. Also, an impressive fouling resistance was achieved after three-cycle of bovine serum albumin fouling tests. This work, therefore, offers a more feasible way of designing polyamine-based NF membranes with good prospects in water reuse and nitric acid-generating wastewater treatment application.

A new discrete model to better consider tracer distribution along boreholes during the Finite Volume Point Dilution Method

The Finite Volume Point Dilution Method (FVPDM) is a single-well tracer experiment which has been successfully used in many hydrogeological contexts to quantify groundwater fluxes. During continuous injection of tracer into a well, the tracer concentration evolution measured within the tested well directly depends on the groundwater flow crossing the well screens. Up to now, the FVPDM mathematical formulation used to simulate the tracer concentration evolution measured in the tested well assumed perfect homogenization of the tracer along the tested interval, which is a reasonable assumption in many cases. However, when FVPDM are performed in long-screened boreholes or in very permeable aquifer materials, the recirculation flow rate imposed to ensure mixing is suspected to be too low to perfectly homogenize the tracer. In order to assess the effect of non-perfect mixing on FVPDM results, we introduce here a new discrete model that explicitly considers the recirculation flow rate. The mathematical developments are validated using field measurements, and a sensitivity analysis is proposed to assess the effect of the mixing flow rate on tracer concentration homogenization within the well. Results confirm that, when the recirculation flow rate applied is not high enough compared to the groundwater flow rate, the tracer distribution is not uniform in the tested interval. In this case, the use of the classical analytical solution, commonly used to interpret the concentration evolution leads to highly overestimated groundwater fluxes. The discrete model introduced here can be used instead to properly estimate groundwater fluxes and assess the tracer distribution within the tested interval. The discrete model offers the possibility of interpreting field measurements conducted under non-perfect mixing conditions and increases the range of fluxes that can be investigated through FVPDM.

Experimental study on the correlation between bubble heat transfer coefficient and pressure oscillation frequency in the bubbling regime of steam jet

Direct contact condensation of steam–water is widely applied in the industrial and food fields. In this work, the bubble condensation pressure oscillation frequency and heat transfer coefficient in vertical upward and downward directions are studied. The steam mass flux range is 22.12–50.13 kg m−2 s−1, and the water subcooling degree is 20–40 K. The bubble heat transfer coefficient and the pressure oscillation frequency have a positive correlation in the two steam jet directions. The mechanism of the positive correlation is analyzed. An artificial neural network model is proposed to calculate the bubble heat transfer coefficient. The proposed model can accurately predict the bubble heat transfer coefficient with correlation coefficient R2 = 0.97, which provides a convenient path for obtaining the coefficient of heat transfer.