Computational Model Research Articles

Performance improvement of the H2 shaft furnace: A numerical study on hot-charge operation

This work proposes a retrofitted gas feed system for increasing thermal energy supply when the hydrogen-operated direct reduction shaft furnace adopts hot-charge operation. The potential of the new feed system is assessed further using a two-dimensional computational fluid dynamics model. The results show that the ascending gas is heated up quickly by the descending hot solid within a narrow uppermost zone when employing the conventional gas feed system, so the opportunities to obtain better furnace performance are limited since the thermal energy of the hot solid leaves the furnace in the form of high-temperature off-gas. Under a scenario adopting the hot-charge operation in conjunction with the new feed system, a high temperature favoring the endothermic reactions is maintained within almost the entire upper part of the furnace. Using an appropriate upper-row gas feed rate, the overall furnace performance can be substantially improved particularly with respect to final solid reduction degree.

Physics-constrained polynomial chaos expansion for scientific machine learning and uncertainty quantification

We present a novel physics-constrained polynomial chaos expansion as a surrogate modeling method capable of performing both scientific machine learning (SciML) and uncertainty quantification (UQ) tasks. The proposed method possesses a unique capability: it seamlessly integrates SciML into UQ and vice versa, which allows it to quantify the uncertainties in SciML tasks effectively and leverage SciML for improved uncertainty assessment during UQ-related tasks. The proposed surrogate model can effectively incorporate a variety of physical constraints, such as governing partial differential equations (PDEs) with associated initial and boundary conditions constraints, inequality-type constraints (e.g., monotonicity, convexity, non-negativity, among others), and additional a priori information in the training process to supplement limited data. This ensures physically realistic predictions and significantly reduces the need for expensive computational model evaluations to train the surrogate model. Furthermore, the proposed method has a built-in uncertainty quantification (UQ) feature to efficiently estimate output uncertainties. To demonstrate the effectiveness of the proposed method, we apply it to a diverse set of problems, including linear/non-linear PDEs with deterministic and stochastic parameters, data-driven surrogate modeling of a complex physical system, and UQ of a stochastic system with parameters modeled as random fields.

Enhancing sonothrombolysis outcomes with dual-frequency ultrasound: Insights from an in silico microbubble dynamics study

Sonothrombolysis is a technique that employs the ultrasound waves to break down the clot. Recent studies have demonstrated significant improvement in the treatment efficacy when combining two ultrasound waves of different frequencies. Nevertheless, the findings remain conflicted on the ideal frequency pairing that leads to an optimal treatment outcome. Existing experimental studies are constrained by the limited range of frequencies that can be investigated, while numerical studies are typically confined to spherical microbubble dynamics, thereby restricting the scope of the analysis. To overcome this, the present study investigated the microbubble dynamics caused by the different combinations of ultrasound frequencies. This was carried out using computational modelling as it enables the visualisation of the microbubble behaviour, which is difficult in experimental studies due to the opacity of blood. The results showed that the pairings of two ultrasound waves with low frequencies generally produced stronger cavitation and higher flow-induced shear stress on the clot surface. However, one should avoid the frequency pairings that are integer multipliers of each other, i.e., frequency ratio of 1/3, 1/2 and 2, as they led to resultant wave with low pressure amplitude that weakened the cavitation. At 0.5 + 0.85 MHz, the microbubble caused the highest shear stress of 60.5 kPa, due to its large translational distance towards the clot. Although the pressure threshold for inertial cavitation was reduced using dual-frequency ultrasound, the impact of the high-speed jet can only be realised when the microbubble travelled close to the clot. The results obtained from the present study provide groundwork for deeper understanding on the microbubble dynamics during dual-frequency sonothrombolysis, which is of paramount importance for its optimisations and the subsequent clinical translation.

Lower limb joint contact forces and ground reaction forces analysis based on Azure Kinect motion capture

Traditional gait analysis systems are typically complex to operate, lack portability, and involve high equipment costs. This study aims to establish a musculoskeletal dynamics calculation process driven by Azure Kinect. Building upon the full-body model of the Anybody musculoskeletal simulation software and incorporating a foot-ground contact model, the study utilized Azure Kinect-driven skeletal data from depth videos of 10 participants. The in-depth videos were prepossessed to extract keypoint of the participants, which were then adopted as inputs for the musculoskeletal model to compute lower limb joint angles, joint contact forces, and ground reaction forces. To validate the Azure Kinect computational model, the calculated results were compared with kinematic and kinetic data obtained using the traditional Vicon system. The forces in the lower limb joints and the ground reaction forces were normalized by dividing them by the body weight. The lower limb joint angle curves showed a strong correlation with Vicon results (mean ρ values: 0.78 ~ 0.92) but with root mean square errors as high as 5.66°. For lower limb joint force prediction, the model exhibited root mean square errors ranging from 0.44 to 0.68, while ground reaction force root mean square errors ranged from 0.01 to 0.09. The established musculoskeletal dynamics model based on Azure Kinect shows good prediction capabilities for lower limb joint forces and vertical ground reaction forces, but some errors remain in predicting lower limb joint angles.

Fuel transport mechanisms and power generation enhancement in air-breathing microfluidic fuel cells with discrete-hole anode

Current challenges in air-breathing microfluidic fuel cells (AMFCs) technology include insufficient fuel transfer and unsatisfactory power density. To address these issues, this study develops a three-dimensional computational model to optimize the performance of AMFC with a discrete-hole anode. This model reveals that the "petal-shaped" non-uniform fuel distribution is due to the shearing and dilution effects of the electrolyte. Additionally, discrete-hole structures such as size have a slight influence on fuel transport and current production, with performance deviations under 1.6%. Significant improvements are achieved by reducing the electrolyte flow rate and electrode length. Transitioning from a single cell with a long anode to a series/parallel stack of cells with short electrodes significantly boosts net power output and fuel utilization. Under optimal conditions, a maximum power density of 349.9 mW cm−3 and an output of 19.2 mW are obtained. This research provides valuable insights into fuel transport mechanisms and power enhancement strategies in the AMFCs, guiding the future design and optimization of microfluidic reactors for energy conversion.

Biofuel processing in a closed-loop geothermal system

Closed-loop geothermal systems (CLGS) provide a renewable heat source for district heating and electricity production. However, high capital costs can be a barrier to these applications. This study finds that the high pressures (>8MPa) and temperatures (>240°C) attained by working fluid inside the loop present additional opportunities: driving supercritical reactions that produce biodiesel from fatty acids. A new design for a subsurface geothermal reactor is proposed, enabling biofuel processing underground without the need for conventional processing equipment (pump, heater, reactors, and heat exchangers) or fossil fuel as energy source. To analyze the feasibility of this approach and its environmental and economic effects, a computational model that incorporates the simultaneous effects of flow dynamics, heat transfer, and reaction kinetics is developed. The application of CLGS is concluded to reduce the CO2 intensity of the resulting biodiesel by up to 33%. A geothermal-driven biofuel reactor could yield up to 95% fatty acid methyl esters. Additional sensible heat carried by the products can be redirected to electricity generation or district heating. The relevant requirements and optimal operating conditions for this approach to biofuel synthesis are identified. A technoeconomic analysis shows CLGS-based biofuel production cost can be comparable to natural gas-based production (∼840 $/ton). It also indicates return-on-investment after five years and highlights the most suitable locations that combine proximity to appropriate feedstocks and subsurface conditions. Integrated biodiesel production and energy extraction provides an alternative route to harnessing geothermal energy.

Conversion of images of 3D friction maps to study the coupling between coefficient of friction, velocity and contact temperature of the disc brake

The coefficient of friction during braking is not constant. Determining its variability requires measurements in real conditions. This paper presents a methodology of conversion of the measured time profiles of the sliding velocity Veq, contact temperature T, and coefficient of friction f, into analytical formulation of two variables z = f(x,y). This was executed in the following steps: 1) creating a three-column table Veq, T, f from experimental measurements; 2) interpolation using Kriging; 3) creating a contour map of the coefficient of friction dependent on the sliding velocity and temperature, 4) import of a grey scale image of the friction map into the finite element (FE) software, and 5) definition of a function z = f(x,y). The studies were carried out for five composite organic friction materials and cast-iron brake disc of a railway vehicle. The developed five friction maps for each friction pair were based the data from the full-scale bench tests during braking from the initial vehicle velocity of 80 kmh−1, 120 kmh−1, 140 kmh−1, 160 kmh−1, 200 kmh−1 to a stop. In the second part of the study the initial-value problem for the equation of motion combined with the heat conduction problem were formulated and solved numerically using special functionalities of the FE software, e.g. Deformed Geometry, Mathematics. Changes in the vehicle velocity and time profiles of the coefficient of friction were determined from the solution of the coupled thermal problem. The computational FE model was verified by comparing the measured and calculated changes in the vehicle velocity, coefficient of friction and evolutions of the brake disc temperature during single braking. The maximum calculated temperature 1 mm under the contact surface of the brake disc, during braking from initial vehicle velocity of 80 kmh−1, was obtained for the base friction material and was equal to T1,3,5Num.= 72 °C. The corresponding experimental value was T1-6Exp.= 66.1 °C. When braking from 140 kmh−1, for the same material it was T1,3,5Num.= 129.7 °C and T1-6Exp.= 130.7 °C. The obtained differences in braking times calculated and measured did not exceed 1.7 %. The corresponding temperature differences of the disc at the stopping time were lower than 5.5 %.

A model of the spatiotemporal distribution of ozone-squalene reaction and ozonolysis by-products from human body

Emissions of ozone and its by-products from ozonolysis on human surfaces lead to indoor air pollution. However, the spatiotemporal distribution of such emissions in indoor environments remains unclear, which may introduce bias when assessing human exposure to ozone and ozonolysis byproducts. This study developed a computational fluid dynamics model to describe the physical and chemical processes involved in the emission of ozone-dependent volatile organic compounds from the human body. The results showed that the reaction probability of ozone in the human body depends on the ozone concentration in the bulk air. For ozone concentrations ranging from 28 ppb to 200 ppb, the reaction probabilities ranged from 5.9 × 10−5 to 1.5 × 10−4. The concentrations of ozone and ozonolysis byproducts obtained from the experimental measurements were used for model validation. The ozonolysis by-products were found to be uniformly distributed in the chamber, whereas the ozone distribution showed less uniformity. The ozone concentration near the human surface was approximately 30 %∼50 % of that in the ambient air. Overall, a model was developed to understand the effect of ozone-surface interactions on indoor air quality. This model can be applied to analyze human exposure to ozone and ozonolysis byproducts and for health risk assessment in built environments.

Developmental patterns and computational mechanisms of school-aged children’s fairness-related decision making under social comparison

The developmental patterns and computational mechanisms underlying the impact of unfair offers and social comparisons on school-aged children’s fairness-related decision making remain unclear. To address this, we recruited 190 children aged 8 to 12 years (52.1% female) in a multi-responder ultimatum game. Results revealed an age-related decline in children’s tendency to reject unfair offers, partially mediated by emotions, alongside a slight increase in rejecting inferior social comparisons. Computational modeling identified two distinct motivations guiding children’s rejection behavior: inequity aversion and inferior social comparison avoidance. Furthermore, there was significant variability in responses to superior social comparisons, with some children displaying aversion and others seeking. Our refined model enhances the explanatory power of inequity aversion theory in complex multi-player social scenarios, validating and refining existing theories. In addition, the exploration of superior social comparison tendencies reveals individual heterogeneity, enriching our understanding of children’s social comparisons. These findings contribute to elucidating the developmental patterns and internal mechanisms of children’s socialization processes, offering implications for promoting their social adaptation and mental health.

Automatic lockbolt detection method for riveting quality evaluation based on specific geometric feature descriptors of 3D point cloud

Abstract Lockbolt is increasingly utilized in different fields due to its good performance in riveting and locking. However, the digital measurement and evaluation methods for the riveting quality of lockbolts still need to be explored. In this paper, we proposed a point cloud-based automatic lockbolt detecti on method, estimating the riveting quality via the protruding height of the lockbolt pin. The method involves three main stages: density computation for 3D point cloud, identification of real lockbolt regions, and segmentation for the top surface of the lockbolt. Firstly, a noise-weakened density computation model is proposed to suppress the density value of noise points. Secondly, the idea of PCA (principal component analysis) is adopted, and a set of SGFDs (specific geometric feature descriptors) is built to identify the real lockbolts from the candidate regions. Lockbolts can be robustly represented even if noise and missing in the point cloud. Thirdly, an efficient section-by-section segmenting algorithm is proposed to segment the top surface of the pin protrusion of the riveted lockbolt. Finally, the riveting quality of each lockbolt is evaluated based on the height from the top surface of the pin protrusion to the bottom plane of the lockbolt. Experiments on real data verified the accuracy, robustness, and efficiency of the proposed method.

Computational Modeling of Drug Response Identifies Mutant-Specific Constraints for Dosing panRAF and MEK Inhibitors in Melanoma.

This study explores the potential of pre-clinical in vitro cell line response data and computational modeling in identifying the optimal dosage requirements of pan-RAF (Belvarafenib) and MEK (Cobimetinib) inhibitors in melanoma treatment. Our research is motivated by the critical role of drug combinations in enhancing anti-cancer responses and the need to close the knowledge gap around selecting effective dosing strategies to maximize their potential. In a drug combination screen of 43 melanoma cell lines, we identified specific dosage landscapes of panRAF and MEK inhibitors for NRAS vs. BRAF mutant melanomas. Both experienced benefits, but with a notably more synergistic and narrow dosage range for NRAS mutant melanoma (mean Bliss score of 0.27 in NRAS vs. 0.1 in BRAF mutants). Computational modeling and follow-up molecular experiments attributed the difference to a mechanism of adaptive resistance by negative feedback. We validated the in vivo translatability of in vitro dose-response maps by predicting tumor growth in xenografts with high accuracy in capturing cytostatic and cytotoxic responses. We analyzed the pharmacokinetic and tumor growth data from Phase 1 clinical trials of Belvarafenib with Cobimetinib to show that the synergy requirement imposes stricter precision dose constraints in NRAS mutant melanoma patients. Leveraging pre-clinical data and computational modeling, our approach proposes dosage strategies that can optimize synergy in drug combinations, while also bringing forth the real-world challenges of staying within a precise dose range. Overall, this work presents a framework to aid dose selection in drug combinations.

Modeling smothering limit of smoldering combustion: Oxygen supply, fuel density, and moisture content

Smoldering, characterized as a slow, low-temperature, and flameless reaction process, represents one of the most persistent types of combustion phenomena. While oxygen supply is one of the governing mechanisms controlling smoldering, the specific oxygen threshold or smothering limit remains inadequately investigated. Herein, we built a physics-based 1-D computational model integrating heat-and-mass transfer and 5-step heterogeneous chemistry to investigate the oxygen threshold or smothering limit of smoldering propagation in porous pine needle beds subjected to forced internal oxidizer flow. Simulation results revealed that, the required oxidizer flow velocity or oxygen supply rate increased as the oxygen concentration decreased, and the predicted limiting oxygen concentration (LOC) was about 3 %, agreeing well with the experimental observations and theoretical analysis. Moreover, the required airflow velocity was predicted to increase as the fuel density and environmental temperature decreased, or the moisture content increased, and the predicted maximum moisture content capable of supporting smoldering was about 110 %. At the smothering limit, the modeled minimum smoldering temperature and propagation rate were around 300 °C and 0.5 cm/h. This work helps deepen our understanding of the limiting conditions of smoldering combustion, thus improving the mitigation strategy of smoldering fire and the efficiency of applied smoldering systems. Novelty and significance statementsOxygen supply is one of the key mechanisms governing the smoldering propagation. In the literature, scattered studies have examined the limiting oxygen concentration (LOC) of smoldering under different conditions, leading to disparate results even for the same fuels. In our previous work, for the first time, we developed a tubular smoldering reactor capable of precisely controlling the flow of oxidizer, and successfully quantified the exact oxygen supply limit of smoldering combustion. However, no computational model was established specifically for the oxygen threshold of smoldering with forced internal oxygen supply.The novelty of this research is the establishment of the first-ever computational model to investigate the oxygen threshold or smothering limit of smoldering propagation in porous pine needle beds subjected to forced internal oxidizer flow. It is significant because (1) it contributes to a fundamental understanding of smoldering combustion; (2) it investigates the role of fuel properties and environmental conditions in smoldering dynamics and the oxygen supply limits; (3) it assists in optimizing the applied smoldering systems and enriching prevention strategies for smoldering fires.

Excellent thermoelectric properties and significant anisotropy for filled-tetragonal NaZnAs caused by strong anharmonicity

We have theoretically investigated the transport properties of the filled-tetrahedral NaZnAs using first-principles calculations in combination with self-consistent phonon theory and the Boltzmann transport equation. The results show that the transport behavior of NaZnAs exhibits obvious anisotropy, and the influence of quartic anharmonicity on the lattice thermal conductivity cannot be neglected as shown by the thermal conductivity results obtained from different computational models. Both the increase in scattering rates(SRs) and the decrease in group velocity signify a strong anharmonicity. We further find that the special vibrational modes due to the weak bonding of Zn atoms are the main source of anharmonicity. We find that considering the bubble diagram for the phonon self-energy correction reduces the κL by up to 28.04% at 700 K, which favors the capture of large ZT values. In addition, The ZT value of NaZnAs can reach 3.07 at 700 K, which shows great potential for thermoelectric applications.

Exploring the electronic influence on coordination complexes formed from appended pyrrolidine azothioformamide ligands and copper(I) salts

Redox-active arylazothioformamide (ATF) ligands have seen attention through their unique coordination complexes formed with salts of late transition metals and their known ability to oxidatively dissolve zerovalent metals. When mixed with Cu(I) salts, ATF ligands form both 2:1 and 2:2 coordination complexes remaining neutral without undergoing any redox event. Herein, a series of para-substituted pyrrolidine-ATFs were synthesized, incorporating both electron-donating groups (i.e., -OMe and -Me) as well as electron-withdrawing groups (i.e., -CF3, and -CN). These ligands were then mixed with Cu(I) salts, including CuBr, CuI, and [(CH3CN)4Cu](BF4) to form coordination complexes. The resulting complexes underwent thorough characterization, with several producing X-ray quality crystals for detailed structural analysis. Both strong and weak intermolecular interactions were found through Hirshfeld surface analysis and the redox activity of the complexes was probed using cyclic voltammetry in the voltage range of -1.8 to 1.8 V. Through a UV–Vis titration study, the binding interactions between the ligand host and Cu(I) metal salt guest molecules were determined and ranged from 4,000 – 100,000 M-1. Computational modeling was employed to calculate the change in Gibbs free energy (ΔG) for the formation of the complexes, revealing the optimal orientations between the ligand and the metal. These studies have confirmed that para-substituted pyrrolidine-ATFs containing electron-donating groups exhibit a higher binding affinity towards Cu(I) metal salts compared to those with electron-withdrawing groups. With a thorough understanding of ATF-metal coordination, further ligand design can lead to exciting new catalysts and/or selective metal dissolution agents.

Investigations of the UVC 222 NM air cleaning system in an air-conditioned room

Far-Ultraviolet-C (far-UVC) 222 nm was introduced during the Covid-19 pandemic to disinfect the airborne pathogens, particularly SARS-CoV-2. Although far-UVC 222 nm has shown promising results in surface disinfection, its efficacy in air disinfection remains uncertain due to additional variables in air. This study investigated the efficacy of far-UVC 222 nm UVGI in air disinfection experimentally, using total plate count, and input the measured far-UVC intensity into the computational fluid dynamic model to predict infection risk using the Wells-Riley model. Experimental results indicated that after 1 h of far-UVC irradiation, an equivalent far-UVC dosage of 21.31 J/m2, airborne bacteria concentration was reduced by 44.4 %–74.1 %, while airborne fungal concentration showed a marginal reduction. In a recirculating air-conditioned room, a 20 W far-UVC fixture installation, referred to as Case 1, demonstrated the highest available dosage of 7.66 % difference compared to Case 2. The use of far-UVC in Case 1 can reduce the risk of infection for the influenza H1N1, SARS-CoV-2, and Mycobacterium tuberculosis by 54.48 %, 60.06 %, and 83.73 %, respectively. The study suggests installing far-UVC near the recirculating air-conditioner supply air jet and away from surrounding walls for optimum effectiveness. These results provide recommendations for alternatives to upper-room UVGI, offering a viable option for continuous room air and surface disinfection.

LPBF Processability of NiTiHf Alloys: Systematic Modeling and Single-Track Studies.

Research into the processability of NiTiHf high-temperature shape memory alloys (HTSMAs) via laser powder bed fusion (LPBF) is limited; nevertheless, these alloys show promise for applications in extreme environments. This study aims to address this limitation by investigating the printability of four NiTiHf alloys with varying Hf content (1, 2, 15, and 20 at. %) to assess their suitability for LPBF applications. Solidification cracking is one of the main limiting factors in LPBF processes, which occurs during the final stage of solidification. To investigate the effect of alloy composition on printability, this study focuses on this defect via a combination of computational modeling and experimental validation. To this end, solidification cracking susceptibility is calculated as Kou's index and Scheil-Gulliver model, implemented in Thermo-Calc/2022a software. An innovative powder-free experimental method through laser remelting was conducted on bare NiTiHf ingots to validate the parameter impacts of the LPBF process. The result is the processability window with no cracking likelihood under diverse LPBF conditions, including laser power and scan speed. This comprehensive investigation enhances our understanding of the processability challenges and opportunities for NiTiHf HTSMAs in advanced engineering applications.

Multiscale modeling shows how 2’-deoxy-ATP rescues ventricular function in heart failure

2'-deoxy-ATP (dATP) improves cardiac function by increasing the rate of crossbridge cycling and Ca[Formula: see text] transient decay. However, the mechanisms of these effects and how therapeutic responses to dATP are achieved when dATP is only a small fraction of the total ATP pool remain poorly understood. Here, we used a multiscale computational modeling approach to analyze the mechanisms by which dATP improves ventricular function. We integrated atomistic simulations of prepowerstroke myosin and actomyosin association, filament-scale Markov state modeling of sarcomere mechanics, cell-scale analysis of myocyte Ca[Formula: see text] dynamics and contraction, organ-scale modeling of biventricular mechanoenergetics, and systems level modeling of circulatory dynamics. Molecular and Brownian dynamics simulations showed that dATP increases the actomyosin association rate by 1.9 fold. Markov state models predicted that dATP increases the pool of myosin heads available for crossbridge cycling, increasing steady-state force development at low dATP fractions by 1.3 fold due to mechanosensing and nearest-neighbor cooperativity. This was found to be the dominant mechanism by which small amounts of dATP can improve contractile function at myofilament to organ scales. Together with faster myocyte Ca[Formula: see text] handling, this led to improved ventricular contractility, especially in a failing heart model in which dATP increased ejection fraction by 16% and the energy efficiency of cardiac contraction by 1%. This work represents a complete multiscale model analysis of a small molecule myosin modulator from single molecule to organ system biophysics and elucidates how the molecular mechanisms of dATP may improve cardiovascular function in heart failure with reduced ejection fraction.

Integrated hybrid membrane system for enhanced water treatment and desalination for environmental preservation

Technology advancements in desalination, water treatment, and energy efficiency are crucial to preserving our planet. It is critical to find solutions for the future that save natural resources and lessen environmental damage because the freshwater shortage is getting worse, and energy demand is increasing. They face various obstacles, even though their breakthroughs are extremely important. Lot of energy can be utilized for the traditional desalination techniques, as it negatively impacts the environment. Then, the process of the existing Water Treatment (WT) are expensive and ineffective. An Integrated Hybrid Membrane System for Enhanced WT (IHMS-EWT) is a unique technique for WT and desalination was suggested in this study. The integration of many membrane procedures like nanofiltration, reverse and forward osmosis, and membrane distillation, and these will helps in facilitating the best WT and desalination methods. Due to the incorporating Renewable Energy (RE), the IHMS-EWT also demonstrates the (SWMS) Sustainable Water Management System, as it enhances the EE and thereby reducing the environmental impact. The great potential in the wide range of applications was offered by the IHMS-EWT technique. Providing the decentralized WT solutions in the remote areas, this unique approach has the ability to reduce the fresh water scarcity in the coastal areas based on the demands of the municipal, industrial and agricultural demands. The environmental sustainability throughout the lenghthy operations was ensured by the support of IHMS-EWT. It also helps in providing resilience in the crisis situations. The cost-effective evaluations, operating parameter optimization, and performance prediction of the method was enabled by employing the computational modelling. Through simulatimg different contexts, the effective configurations and operational techniques are focussed on the study for enhancing the IHMS-EWT technology.The model shift in the SWM, the IHMS-EWT technique addresses the main problems and brings one step for more secure environment. Comparing to other existing methods, Improving the water purification by 98.2 %, 94.2 % efficiency rate, the EC prediction rate of 96.2 %, the cost-effectiveness rate by 82.4 % and the performance rate by 96.7 % by the suggested IHMS-EWT model and it was demonstrated by the outcomes of the experiment.

Application of surface geophysical investigations and pumping test data analysis for better characterization of aquifer hydraulic parameters, Upper Awash Sub-Basin, Central Ethiopia

Study regionUpper Awash River Sub-basin in central Ethiopia Study focusThe research aimed to estimate aquifer parameters and conduct resistivity modeling in the study area. Data were collected from 890 Schlumberger Vertical Electrical Soundings (VES) points strategically distributed across six selected zones. The VES data were analyzed using computer modeling and curve-matching techniques to interpret the resistivity responses of the geological formations. This analysis provided insights into the subsurface characteristics and identified potential aquifer zones. New insights for the regionThe interpreted curves from the VES data and Root Mean Square (RMS%) values ranging from 0.36 % to 1.67 %, indicating a good fit between observed and modeled data. Resistivity modeling and geoelectrical sections were produced along specific lines, visualizing subsurface structures and confirming the resistivity responses of the geological formations. To determine aquifer parameters, the Dar-Zarrouk parameters were calculated from the interpreted curves, yielding crucial information about hydraulic properties such as hydraulic conductivity (K) and transmissivity (T). Hydraulic conductivity values ranged from 1.1 m/day to 21.7 m/day, while transmissivity values ranged from 144.3 m²/day to 2763.3 m²/day. Validation against borehole pumping test data showed strong correlations: R² = 0.9873 for transmissivity and transverse resistance, and R² = 0.9352 for hydraulic conductivity and resistivity. These findings enhance the understanding of the complex volcanic aquifer characteristics in the Upper Awash River Sub-basin, aiding sustainable groundwater management and development in the area.

Experimentally Validated Potential Theory Approach for Investigation of the Flow Field Structure of an Open Pool of a Nuclear Reactor

Detailed information on the flow field structure is often important in numerous industrial applications. Although commercial computational fluid dynamics packages are often capable of providing the required data, they are costly and not universally available. This study was motivated by the operation of an open-pool nuclear research reactor where low radiation levels can be maintained by the installation of a stable purified hot water layer in the upper part of the pool. Maintaining a stable stratification requires a detailed description of the structure of the velocity field. Due to the inherent complications and restrictions of performing accurate measurements in a pool of a real-size operating reactor, either smaller-scale models or oversimplified fluid dynamics computational schemes are routinely used. These methods cannot be validated, and therefore do not necessarily capture the large-scale behavior correctly. We present an alternative approach to evaluate the velocity components in the pool that is based on the potential flow theory. The model results are validated by measurements using particle image velocimetry. The presented potential theory allows for the quick and easy assessment of the global properties of the fluid velocity distribution within the pool, and in particular, close to its surface. The suggested computational models are flexible and allow for easily varying the spatial dimensions of the flow field. The technique thus can be upscaled, and enables the validation of numerical computations in various fluid mechanical installations where the flow field cannot be resolved.