Water Buildup Research Articles

Estimating stream sediment loads to assess management options for a Southern Appalachian mountain lake

Enka Lake is a 25-ha reservoir in the Southern Appalachian mountains surrounded by the Biltmore Lake residential neighborhood. The aesthetic and recreational value of Enka Lake can be negatively affected by turbid water and sediment buildup, resulting from stormwater originating upstream in its 15.38 km2 watershed. In this study, we monitored streamflow and sediment loads for nearly 2 years to better understand sedimentation dynamics and evaluate management options. We collected nearly 500 water samples throughout the watershed, focusing on two tributaries that provide the majority of streamflow into Enka Lake. During baseflow conditions, those tributaries are very clear (turbidity ranging from 1 to 20 NTU), but sediment-laden stormflow (turbidity > 1000 NTU) from dirt roads, gravel driveways, and poorly vegetated yards is common and, during extreme storm events, causes lake discoloration. Discharge-sediment data pairs were used to construct sediment rating curves and estimate sediment fluxes through these tributaries. The predicted sediment fluxes were tested with high-frequency sampling during and after three storms in different seasons; predicted values underestimated the peak sediment fluxes (0–400%) but generally matched total measured sediment loads. Estimates of annual sediment load from the two tributaries (540–900 tonnes/year) suggest that a dredging effort commissioned by the neighborhood association in 2016 may have removed only about 1–3 years’ worth of sediment. Installing sediment forebays or other retention structures is likely the preferred sediment management strategy moving forward (over a regular dredging schedule) since they can be maintained more easily without affecting lake levels. Designing these retention structures will benefit from the estimates of stormflow and sediment fluxes, and the study design presented here—including the help of community-based volunteer samplers—provides a model that could be used at other sites in the Southern Appalachians and elsewhere.

تأثير طبوغرافية الأرض على تخطيط المدن بإستخدام تقنيات الاستشعار عن بعد ونظم المعلومات الجغرافية

This research aimed to show case how remote sensing technologies and geographic information systems can be utilized to identify issues arising from the Earths terrain. The study focused on the water accumulation during post rainfall, in the entrance of Tripoli specifically in the Tajoura (bivy) area. This water buildup often leads to traffic congestion resulting in road closures and rising water levels that sometimes reach building entrances. Such circumstances affect the planning of the area and its neighboring regions. Satellite images sourced from the US geological survey website were employed to analyze features of the study area and present them through digital maps illustrating surface topographical characteristics, like area shape, land slopes, water flow patterns, etc. Various analyses were conducted including assessments, hydrological studies, understanding structures and soil types within the study region with an objective to pinpoint core issues related to this phenomenon and explore potential solutions. Keywords: Remote sensing, geographic information systems, urban planning, topography, water buildup.

First experimental validation of silicon-based sensors for monitoring ultra-high dose rate electron beams

Monitoring Ultra-High Dose Rate (UHDR) beams is one of the multiple challenges posed by the emergent FLASH radiotherapy. Technologies (i.e., gas-filled ionization chambers) nowadays used in conventional radiotherapy are no longer effective when applied to UHDR regimes, due to the recombination effect they are affected by, and the time required to collect charges. Exploiting the expertise in the field of silicon sensors’ applications into clinics, the medical physics group of the University and INFN Torino is investigating thin silicon sensors as possible candidates for UHDR beam monitoring, exploiting their excellent spatial resolution and well-developed technology. Silicon sensors of 30 and 45 µm active thicknesses and 0.25, 1 and 2 mm2 active areas were tested at the SIT ElectronFlash machine (CPFR, Pisa) on 9 MeV electron beams, featuring a pulse duration of 4 µs, a frequency of 1 Hz, and a dose-per-pulse ranging from 1.62 to 10.22 Gy/pulse. The silicon sensors were positioned at the exit of the ElectronFlash applicator, after a solid water build-up slab, and were readout both with an oscilloscope and with a multi-channel front-end readout chip (TERA08). A response linearity extending beyond 10 Gy/pulse was demonstrated by comparison with a reference dosimeter (FlashDiamond), thus fulfilling the first requirement of a potential application in UHDR beam monitoring.

NUMERICAL INVESTIGATION OF LIQUID-CARRYING AXIAL AND SWIRL FLOW IN A BENT PIPE

Water condensation occurs in the sloping sections of natural gas pipelines due to fluctuations in temperature and pressure. This event has a major effect on the efficiency and security of gas transportation. In this numerical study, the flow of water via a swirling flow in a wavy pipeline is examined using computational fluid dynamics. A 1-inch pipe is used to simulate a low-lying area of the pipeline, which is normally where the condensate water would gather. The effect of swirl on the flow patterns in the U-shaped pipe with previously published experimental results is studied and validated. In order to comprehend the change of static and dynamic pressure, results are extended in the doubly undulated pipe (w-pipe). According to the innovative analysis in this study, higher swirl flow could empty the water build-up faster than swirl flow inlet velocities below 11.2 m/s in a given amount of time. When the effusion volume increases and the water-carrying capacity is enhanced, several flow regimes, including annular flow, plug flow, slug flow, stratified wave flow, and stratified flow, are observed along with an increase in air velocity.

Porous Electrode Optimization for PEMFCs Using 3D Printing Technology

Proton Exchange Membrane Fuel Cells (PEMFCs) represent a class of fuel cells that transform the chemical energy of fuels, ideally hydrogen and oxygen, into electrical power. Utilized in diverse applications, PEMFCs power vehicles and supply backup energy to buildings. The core of a PEMFC is the membrane electrode assembly (MEA), composed of a polymer electrolyte membrane, an anode, and a cathode. Oxygen, protons, and electrons merge at the cathode, forming water. One challenge PEMFCs face is water-induced cathode flooding at low temperatures, a consequence of the electrochemical reaction's water accumulation. This reduces the oxygen supply, potentially leading to decreased cell performance or even failure. This issue can have substantial undesired consequences, as PEMFCs depend on oxygen availability at the cathode to generate electricity.Gas Diffusion Layers (GDLs) serve as critical PEMFC components, providing porous structures that facilitate reactant access to the catalyst layer and enabling electron flow through the external circuit. GDLs also offer structural support and promote reactant distribution across the membrane surface. Water accumulation in the cathode may cause pore clogging within the GDL, restricting reactant flow, and reducing cell performance. Additionally, water build-up increases pressure drop across the GDL, hindering reactant access to the catalyst layer and diminishing fuel cell efficiency.Three-dimensional (3D) printing has emerged as a potential technique for fabricating GDLs in PEMFCs. 3D printing enables the creation of GDLs with ordered pore size structures, offering a more uniform surface than traditional GDLs with randomly oriented fibres. This uniformity enhances reactant distribution across the membrane surface and mitigates water accumulation risks. In addition, to prevent cathode flooding, 3D printed GDLs are immersed in PTFE solution to increase hydrophobicity.This talk delves into the creation and evaluation of 3D printed carbonized GDLs for PEMFC implementation. A desktop 3D printer constructed a polymer framework, which was subsequently carbonized in a high-temperature tube furnace. Isothermal thermogravimetric analysis (TGA) tests were performed to identify weight change across a temperature range of 30-900 °C under an N2 atmosphere, optimizing the carbonization step to reduce structural distortion and increase electrical conductivity.The 3D printed GDLs displayed pore size diameters spanning 80 to 120 μm and fibre radii of 20-30 μm. The 3D printing technique produced GDLs characterized by a consistent, planar structure without blocked pores that are normally caused by excess resin residue. Electrical conductivity assessments were conducted on the carbonized specimens, and tensile and compression tests measured their mechanical properties.GDLs possessing minimal pore sizes and thicknesses were integrated into membrane electrode assemblies (MEAs) and examined in low-temperature PEMFCs. Diverse spraying methodologies were investigated, involving either the catalyst being sprayed onto the 3D printed GDL or the membrane receiving a catalyst coating. Commercial MEAs, comprising Nafion membranes and platinum electrodes, acted as benchmarks for MEAs featuring 3D printed GDLs. Furthermore, the current challenges facing 3D printed GDLs, including material selection, production consistency, compatibility with other PEMFC components, costs, and scaling up are highlighted in the talk.These findings underscore the promise of 3D printed carbonized GDLs in boosting PEMFC performance, showing their potential as a cost-effective and proficient substitute for conventional carbon paper based GDLs. Figure 1

Assessment of glyphosate and its metabolites' residue concentrations in cultured African Catfish offered for sale in selected markets in Ibadan, Oyo State, Nigeria.

Introduction: Glyphosate is a non-targeted organophosphate insecticide whose solubility and mobility in hydrophilic solvents enable its rapid leaching into the soil and subsequent contamination of ground and surface water and possible build-up in the aquatic food chain. Based on the public health importance of glyphosate in fish through consumption, it is crucial to determine the current residue concentration in culture Clarias gariepinus species. The aim of the present study is to evaluate glyphosate's residue concentrations and its metabolites in cultured African Catfish offered for sale in selected markets in Ibadan. Methods: A total of twenty-five (25) adult Clarias gariepinus (300 ± 50g) were sourced from five (5) selected active fish markets (Ojoo, Iwo road, Eleyele, Challenge, and Apata) within the Ibadan metropolis. The collected fish tissue samples (liver, kidney, and spleen) were prepared for glyphosate residue concentration analysis using Liquid Chromatography (LC). Results: The results showed that glyphosate residues were recorded in all the seventy-five (75) fish tissue samples obtained from the selected fish markets in the Ibadan metropolis and all residue concentrations were above both the recommended Acceptable Daily Intake (ADI) of 1.0mg/kg (1 × 10-3mg/L) and Maximum Residue Limits (MRL) of 0.01mg/kg (1 × 10-5mg/L). Isopropylamine has the highest residue concentration followed by N-Phosphonomethyl and Aminomethylphosphonic Acid (AMPA), while N-Acetyl Glyphosate has the least residue concentration across the sampled markets. Discussion: The presence of residues of glyphosate and its metabolites in ready-to-eat fish calls for holistic, systematic, and effective risk management strategies towards monitoring pesticide/herbicide usage in aquaculture production and ensuring the provision of wholesome fish and fish products for the consumers.

On the low temperature limits for cryogenic etching: A quasi in situ XPS study

The cryogenic plasma etching of silicon for nano- and microelectromechanical devices is known to show an optimal operating temperature around –100 °C. The physicochemical mechanisms occurring beyond this limit, however, are not often discussed. Thus, to explore the adsorption of residual gases on the uppermost surface of a Si/SiO2 wafer at –100 ≤T≤ –147 °C, we performed a comprehensive, quasi in situ X-ray photoelectron spectroscopy (XPS) study. Precisely, the cooling down of the sample was performed in a typical plasma-etching reactor at a residual pressure of 10−4 Pa, being afterwards transferred to the XPS chamber at a constant temperature, under high vacuum. We report that water build-up on the surface becomes a major issue for T< –120 °C, as detected in the O 1 s spectra and modelled by QUASES-Generate. The thickness of the H2O layer increases exponentially as the surface temperature decreases, following an anti-Arrhenius behavior. At –147 °C, the overlayer thickness is estimated to ∼125 Å, thus, the silicon is barely probed by XPS. Adsorbed fluorine can also be detected at low temperatures, although less markedly. Finally, the effect of the temperature-dependent Fermi level change on the Si 2p peak binding energy is discussed.

Frequent pulse disturbances shape resistance and resilience in tropical marine microbial communities

The Johor Strait separates the island of Singapore from Peninsular Malaysia. A 1-kilometer causeway built in the early 1920s in the middle of the strait effectively blocks water flowing to/from either side, resulting in low water turnover rates and build-up of nutrients in the inner Strait. We have previously shown that short-term rather than seasonal environmental changes influence microbial community composition in the Johor Strait. Here, we present a temporally-intensive study that uncovers the factors keeping the microbial populations in check. We sampled the surface water at four sites in the inner Eastern Johor Strait every other day for two months, while measuring various water quality parameters, and analysed 16S amplicon sequences and flow-cytometric counts. We discovered that microbial community succession revolves around a common stable state resulting from frequent pulse disturbances. Among these, sporadic riverine freshwater input and regular tidal currents influence bottom-up controls including the availability of the limiting nutrient nitrogen and its biological release in readily available forms. From the top-down, marine viruses and predatory bacteria limit the proliferation of microbes in the water. Harmful algal blooms, which have been observed historically in these waters, may occur only when there are simultaneous gaps in the top-down and bottom-up controls. This study gains insight into complex interactions between multiple factors contributing to a low-resistance but high-resilience microbial community and speculate about rare events that could lead to the occurrence of an algal bloom.

Study of the Water Build-Up Effect Formation in Upcast Shafts

A theoretical study of the formation of water build-up, or water blanketing, and its influence on the ventilation of mine upcast shafts was carried out. Two scenarios for droplet moisture accumulation in the shaft were considered: condensation from saturated air rising up the shaft and groundwater inflows through the leaky shaft lining. Analytical dependencies of the pressure drop due to the influence of water build-up versus the outgoing air flow velocity and the height of the groundwater source were obtained, taking into account the fractional composition of the droplet moisture. Practical arrangements are proposed to reduce the influence of the effect of water build-up in upcast shafts in the case of groundwater inflows through the leaky shaft lining.

Modeling land use/cover change based on LCM model for a semi-arid area in the Latian Dam Watershed (Iran)

The monitoring and modeling of changes, based on a time-series LULC approach, is fundamental for planning and managing regional environments. The current study analyzed the LULC changes as well as estimated future scenarios for 2027 and 2037. To achieve accuracy in predicting LULC changes, the Land Change Modeler (LCM) was used for the Latian Dam Watershed, which is located approximately in the northeast of Tehran. The LULC time-series technique was specified utilizing four atmospherically endorsed surface reflectance Landsat images for the years t1 (1987), t2 (1998), t3 (2007), and t4 (2017) to authenticate the LULC predictions, so to obtain estimates for t5 (2027) and t6 (2037). The LULC classes identified in the watershed were water bodies, build-up areas, vegetated areas, and bare lands. The dynamic modeling of the LULC was based on a multi-layer perceptron (MLP), the neural network in LCM, which presented good results with an average accuracy rate equivalent to 84.89 percent. The results of the LULC change analysis showed an increase in the build-up area and a decrease in bare lands and vegetated areas within the duration of the study period. The results of this research could help in the formulation of public policies designed to conserve environmental resources in the Latian Dam Watershed and, consequently, minimize the risks of the fragmentation of orchards and vegetated areas. Also, careful regional planning ensuring the preservation of natural landscapes and open spaces is critical to creating a resilient regional environment and sustainable development.

Self-supervised and semi-supervised learning for road condition estimation from distributed road-side cameras

Monitoring road conditions, e.g., water build-up due to intense rainfall, plays a fundamental role in ensuring road safety while increasing resilience to the effects of climate change. Distributed cameras provide an easy and affordable alternative to instrumented weather stations, enabling diffused and capillary road monitoring. Here, we propose a deep learning-based solution to automatically detect wet road events in continuous video streams acquired by road-side surveillance cameras. Our contribution is two-fold: first, we employ a convolutional Long Short-Term Memory model (convLSTM) to detect subtle changes in the road appearance, introducing a novel temporally consistent data augmentation to increase robustness to outdoor illumination conditions. Second, we present a contrastive self-supervised framework that is uniquely tailored to surveillance camera networks. The proposed technique was validated on a large-scale dataset comprising roughly 2000 full day sequences (roughly 400K video frames, of which 300K unlabelled), acquired from several road-side cameras over a span of two years. Experimental results show the effectiveness of self-supervised and semi-supervised learning, increasing the frame classification performance (measured by the Area under the ROC curve) from 0.86 to 0.92. From the standpoint of event detection, we show that incorporating temporal features through a convLSTM model both improves the detection rate of wet road events (+ 10%) and reduces false positive alarms (- 45%). The proposed techniques could benefit also other tasks related to weather analysis from road-side and vehicle-mounted cameras.

The Effectiveness and Cost Optimization of Coagulant Aluminum Chlorohydrate (ACH), Aluminum Sulfate (AS), and Poly Aluminium Chloride (PAC) in Coagulation Process at The PT. Pupuk Sriwijaya (PT. Pusri) Utility Unit

PT. Pusri utilizes Musi River water as a source of process water. Colloidal particles suspended in Musi River water cancause blockage and build-up of scale on pipes and process equipment. Therefore, a good coagulation process is needed to reduce the content of colloidal solids suspended in water by using a coagulant. Coagulants that are often used for water treatment include ACH, AS, and PAC. The objectives of the study are to assess the Effectiveness and to optimize the usage of the coagulant ACH, AS, and PAC on decreasing the turbidity of Musi River water sample as a raw water in utility unit of PT. Pusri. The coagulation process was carried out by varying the concentration of each coagulant and adding 0.1 ppm of coagulant aid for all samples. Fast and slow stirring was carried out each at a speed of 150 rpm 30 rpm for 10 minutes. From the experiments conducted, it was found that the most efective coagulants to be used were ACH and PAC with the addition of a smaller coagulant dose of 12 ppm to achieve the standard water quality used at PT. Pusri. Meanwhile, the use of AS has higher eficiency when compared to ACH and PAC because it is more cost efective.

Pore Network Modeling to Study the Impacts of ‎Geometric Parameters on Water Transport inside Gas ‎Diffusion Layers

A pore network model (PNM) is proposed for the simulation of water transport inside the cathode side ‎gas diffusion layer (GDL) of polymer electrolyte fuel cells (PEFCs) during the transient start-up period as ‎well as the steady state. Numerous two-dimensional random networks representing GDL are generated ‎followed by statistical averaging of the results (Monte Carlo methods) to circumvent the uncertainties ‎imposed by random pore size distributions. The resulting liquid water saturation profiles within GDLs ‎exhibit concave patterns which is typically encountered in capillary fingering flow regimes in porous ‎media. The effect of GDL thickness and current collector rib width as two geometric parameters on water ‎transport dynamics are separately investigated. It turns out that thin and thick GDLs compared to the base ‎case can have contradicting outcomes on the account of total water saturation in the network. On the ‎other hand, wide current collector ribs give rise to liquid water saturation and build-up within GDL which ‎can lead to flooding. At the end, three-dimensional networks are generated demonstrating higher pore ‎connectivity which results in higher percolation times and different invasion patterns.‎

A Sustainable Slit Jet FTIR Spectrometer for Hydrate Complexes and Beyond

Fourier transform infrared (FTIR) absorption spectroscopy of cold molecules and clusters in supersonic slit jet expansions complements and extends more sensitive action spectroscopy techniques and provides important reference data for the latter. We describe how its major drawback, large substance and carrier gas consumption, can be alleviated by one to two orders of magnitude via direct and continuous recycling of the gas mixture. This is achieved by a combination of dry rotary lobe and screw pump compression. The signal-to-noise ratio is boosted by the established buffered giant gas pulse technique with full interferogram synchronization. The buildup of water impurities typically limits the recycling gain, but is turned into a feature for the study of hydrate complexes of volatile molecules. Continuous operation with a single gas filling over several days becomes practical and useful. Decadic absorbances in the low ppm range are detectable and the mid infrared range can be recorded simultaneously with the near infrared. The less straightforward hydration number assignment of spectral features in direct absorption spectroscopy is supported by a gradual water buildup at a rate of less than 0.5 mg/h. A recent reassignment proposal for the water dimer OH stretching spectrum is refuted and vibrational spectra of vacuum-isolated 18O-water clusters are presented for the first time. Methanol docking on asymmetric ketones is used to illustrate the advantages and limitations of the recycling concept. Previous assignments of the hydrate complex of 1-phenylethanol are confirmed. Additional features of the setup await testing and refinement, but the recycling technique already substantially widens the applicability of direct absorption spectroscopy of neutral molecular clusters. It may be attractive for other high-throughput jet spectrometers.

Land-use changes and ecosystem services under different scenarios in Nansi Lake Basin, China.

Ecosystem services (ESs) have been affected drastically by rapid urban sprawl and significant land-use changes (LUC) in Nansi Lake Basin (NLB) in China. Based on land-use data with a 30-m resolution from 1990 to 2015, we analyzed the process of LUC by atlas analysis and explored the impacts of LUC on ecological service value (ESV) under urban sprawl. The results showed that water area and buildup land increased significantly from 1990 to 2015. The area of cultivated land, forests, grassland, and unutilized land decreased. Land transfer mainly occurred between cultivated land, water area, and grassland. The total amount of land transfer was 4830.64 km2, and the average transfer rate is 185.79 km2/year in 26 years. The most obvious transfer occurred in period IV. The increased buildup land was mainly transferred from cultivated land. The total urban sprawl in the NLB was 1623.37 km2 in the past 26 years, with an average expansion rate of 62.44 km2/year, with the fastest sprawl in period IV. Tengzhou city was the most prominent area of expansion. Its ESV increased by 5.73 × 107 US$ with an increased rate of 2.21 × 106 US$/year. The annual total value of regulating and supporting services in the first-level ESs in the NLB accounted for 54.8 and 25.2% of the total ESV in all years, which were the primary types of ESs. Water area, forests, and cultivated land were the principal contributors to ESV changes. In conclusion, urban sprawl had a significant negative effect on ESV changes. Urban sprawl, water area, forests, and cultivated land were all sensitive factors for ESV changes.

Coupled pore network model for the cathode gas diffusion layer in PEM fuel cells

A pore network model (PNM) is developed for gas diffusion layer (GDL) in the cathode side of polymer electrolyte membrane fuel cells (PEMFCs). The model is coupled to network models of reactant oxygen and electron transport inside GDL and also to simple models of catalyst layer and membrane. The coupled model captures the simultaneous effect of reactant and charge access to reaction sites and the resulting water generation, allowing it a transient nature up to reaching the steady state, which is a notable modification to the available PNMs which assume uniform invasion of liquid water from catalyst layer. The results show strongly non-uniform water saturation distributions inside GDL with maxima under the current collector ribs. As an extra feature, the model can predict time evolution of oxygen concentration and water generation rate at catalyst layer as a result of liquid water build-up in GDL. Also included is a dry case coupled model in order to be compared with the main model. The local water blockages in GDL inflict an average of 38.8% loss on the produced limiting current of the fuel cell. Finally, the coupling allows prediction of concentration overvoltages which emerges to be most pronounced in the under-rib region.

On a possible mechanism for the water build-up formation in mine ventilation shafts

A one-dimensional mathematical model of water droplet accumulation in ventilation shafts is proposed. Model parameters are determined using the results of a ventilation survey of deep hard rock mines of Norilsk Nickel Company. The formation of drip water in the shaft is simulated not only due to excess moisture condensation, but also due to groundwater inflows through fissures in the shaft lining. A formula is obtained for calculating the pressure drop due to the water build-up. The pressure drop analysis showed that the water build-up has a significant impact on the fan operation only if there are additional groundwater inflows.

Two-phase flow characterization in PEM fuel cells using machine learning

This work presents a novel application of machine learning to identify the two-phase flow pressure drop in a flow channel of a proton exchange membrane (PEM) fuel cell. Liquid water management and flow-field design remain critical areas of research for many technologies including PEM fuel cells which are focused on in this work. Liquid water buildup in reactant flow channels can lead to parasitic pressure drop and performance degradation. To correlate liquid water distribution with a two-phase flow pressure drop, this work trains various machine learning models using images of water slugs in a flow channel to predict the pressure drop range. An ex-situ experimental setup was designed consisting of a single transparent PEM fuel cell channel with gas flow supplied by compressed air and liquid water production simulated using a digital injector feeding the gas diffusion layer side. A CCD camera monitored the liquid distribution from above while liquid–gas two-phase flow pressure drop was measured across the channel. Images were post-processed and used as input data to three machine learning models: Logistic Regression, Support Vector Machine and Artificial Neural Networks (ANN) to classify the images into three pressure classes: (i) pressure drop less than 15 Pa, (ii) pressure drop between 15 and 30 Pa, and (iii) pressure drop greater than 30 Pa. The performance comparison of machine learning models is reported using the confusion matrices and classification accuracy. ANN performed best for this application and resulted in 95% accuracy on both train and test datasets. This approach can be utilized to predict the pressure drop values in the flow channels of PEM fuel cells based on liquid water content distribution along the channel.

Thermal neutron radiography of a passive proton exchange membrane fuel cell for portable hydrogen energy systems

A proton exchange membrane fuel cell (PEMFC) for portable applications is studied with thermal neutron radiography. The PEMFC operates under passive conditions, with air-breathing cathode and dead-end anode supplied with static ambient air and dry hydrogen, respectively. A columnar cathodic plate favors the mobility of water drops over the cathode surface and their elimination. Thermal neutron images show liquid water build-up during operation of the cell in vertical and horizontal position, i.e. aligned parallel and perpendicular to the gravity field, respectively. Polarization curves and impedance spectroscopy show orientation dependent cell response that can be related with the water profiles. In vertical position, the elimination of drops sliding over the cathode surface as well as natural convection favor lower water contents in the cathode and improve oxygen transport. The vertical cell can be operated for hours in ambient conditions, providing steady power densities above 100 mW cm−2. In horizontal position, natural forces are less effective for water removal leading to 17% decrease in peak power density. The horizontal position is especially adverse if the upper electrode is the cathode, because anode flooding causes cell failure after production of a small amount of water (5 mg cm−2).

A detailed investigation of gamma-ray energy absorption and dose buildup factor for soft tissue and tissue equivalents using Monte Carlo simulation

In the present work, the gamma-ray energy absorption buildup factor for water and dose buildup factor for soft tissue (ICRU 4-component), A-150 tissue-equivalent plastic (A150TEP), and tissue equivalent-gas, methane-based (TEGMB) were studied for 356, 662, 1173, and 1332 keV gamma-ray energy up to depths of 10 mean free path (mfp) extensively using Monte Carlo simulation. The aim in this paper is to investigate the gamma buildup factor for soft-tissue equivalent materials and more specifically to study the relative difference between them at practical gamma energies through the Monte Carlo simulation method. The simulations have been performed by MCNPX code, which could be very useful for calculation of shielding estimates. The results revealed that by using the MCNPX code one can easily calculate the energy absorption and dose buildup factors for different materials and also different energies. The simulation results for water were verified by comparing data with those of experimental works wherever possible. In addition, the simulation results for soft tissue were verified by the G-P fitting method, as well. Moreover, the simulation results of the total mass attenuation coefficients of water, A150TEP, soft tissue, and TEGMB were compared with standard database of NIST-XCOM and a good agreement has been obtained. The materials selected have been studied for the first time in this work with respect to the gamma buildup factors at specific energies mentioned above by the Monte Carlo simulation method.