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Arsenic contamination in aqueous media is a serious environmental problem, especially in developing countries. In this research, the Box-Behnken response surface methodology was used to optimize the most relevant variables affecting arsenic adsorption on the ZnO-halloysite surface, including temperature, adsorbent dosage, pH, contact time, and As (III) initial concentration. The regression analysis indicated that the experimental data were appropriately fitted to a quadratic model with the adjusted R-squared value (R2) of 0.982 for As(III) adsorption capacity and a linear model with R2 of 0.931 for As(III) removal. The p-values for both adsorption capacity and removal efficiency were below 0.05, with F-values of 116.91 and 115.58, respectively, supporting the model's validity. The optimum conditions for maximum removal of As(III) were determined through numerical and graphical optimization using the desirability function. It was found that the optimum conditions for adsorption were pH = 7.99, contact time of 3.99 h, As(III) initial concentration of 49.96 mg/L, and adsorbent dosage of 0.135 g/40 ml. The accuracy of the optimization procedure was confirmed by a confirmatory experiment, which showed a maximum arsenic removal of 91.31% and an adsorption capacity of 12.63 mg/g under optimized conditions. Moreover, XPS analysis was performed at different pH levels to investigate the As (III) adsorption mechanism. The results demonstrated that As(III) adsorption occurs at acidic and neutral pH levels. On the other hand, when pH is increased to 8, As (III) oxidizes to As (V), and then adsorption occurs.

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A three-dimensional (3D) numerical model was developed to explore the intricate aerodynamic mechanisms associated with aerosol jet printing (AJP). The proposed approach integrates computational fluid dynamics and discrete phase modeling, offering a comprehensive understanding of the deposition mechanisms of the AJP process. Initially, numerical solutions of the governing equations were obtained under the assumptions of compressible and laminar flows, facilitating an analysis of certain key flow variables, in this case, the sheath gas flow rate and carrier gas flow rate across the fluid domain. Subsequently, incorporating a Lagrangian discrete phase model allowed a detailed examination of the droplet behavior after nozzle ejection, considering the influence of the Saffman lift force. Finally, experiments were performed to elucidate the influence of key flow variables on the printed width. Generally, the measured printed line morphology and corresponding line electrical performance exhibited close conformity with the numerical model, demonstrating that the proposed numerical model is important for making well-informed decisions during process optimization.

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Thanks to the distinctive morphology of graphite particles in its microstructure, compacted graphite iron (CGI) exhibits excellent thermal conductivity together with high strength and durability. CGI is extensively used in many applications, e.g., engine cylinder heads and brakes. The structural integrity of such metal-matrix materials is controlled by the generation and growth of microcracks. Although the effects of the volume fraction and morphology of graphite inclusions on the tensile response of CGI were investigated in recent years, their influence on crack initiation is still unknown. Experimental studies of crack initiation require a considerable amount of time and resources due to the highly complicated geometries of graphite inclusions scattered throughout the metallic matrix. Therefore, developing a 2D computational framework for CGI with a random microstructure capable of predicting the crack initiation and path is desirable. In this work, an integrated numerical model is developed for the analysis of the effects of volume fraction and nodularity on the mechanical properties of CGI as well as its damage and failure behaviours. Finite-element models of random microstructure are generated using an in-house Python script. The determination of spacings between a graphite inclusion and its four adjacent particles is performed with a plugin, written in Java and implemented in ImageJ. To analyse the orientation effect of inclusions, a statistical analysis is implemented for representative elements in this research. Further, Johnson-Cook damage criteria are used to predict crack initiation in the developed models. The numerical simulations are validated with conventional tensile-test data. The created models can support the understanding of the fracture behaviour of CGI under mechanical load, and the proposed approach can be utilised to design metal-matrix composites with optimised mechanical properties and performance.

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Among the many benefits of implementing numerical analysis on real objects, economic and environmental considerations are likely the most important ones. Nonetheless, it is also crucial to constrain the duration and space necessary for conducting experimental investigations. Although these benefits are clear, the applicability of such models must be appropriately verified. This research subjected validation of numerical models depicting the behavior of unstrengthened and strengthened laminated veneer lumber (LVL) beams. As a reinforcement, a carbon fiber reinforced polymer (CFRP) sheet and laminates were used. Experiments were conducted on full-scale members within the framework of the so-called four-point bending testing method. Numerical simulations were performed using the Abaqus software. Two types of material models were examined for laminated veneer lumber: linearly elastic and linearly elastic-perfectly plastic with Hill's yield criterion. A distinction was made in the material properties of carbon composites based on their location on the height of the cross-section. The outlined numerical models accurately depict the behavior of real structural elements. The precision of predicting load-bearing capacity amounts to a few percent for strengthened beams and a maximum of eleven percent for unstrengthened beams. The relative deviation between numerical and experimental values of bending stiffness was at a maximum of seven percent. Applying the elastic-plastic model enables accurate representation of the load versus deflection relation and the distribution of stress and deformation of strengthened beams. Based on the findings, directives were provided for further optimization of the positioning of composite reinforcement along the span of the beam. Reinforcement design of existing laminated veneer lumber members can be made using presented methodology.

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Currently available numerical models that describe the fecal contamination of aquatic environments using Escherichia coli as an indicator bacterium did not consider its survival in sediments. We conducted a series of comparative experiments to reveal the independent and interactive effects of sediment factors, including temperature, pH, water-extractable total dissolved solids (TDSs), coexisting microbes, and sampling sites, in lake environments on E. coli survival. In experiments, E. coli survival was observed by controlling any two factors at a time. Consequently, the decrease in pH and presence of coexisting microbes enhanced E. coli die-off, whereas the addition of water-extractable TDSs promoted its growth. To select factors to be considered for modelling E. coli survival in sediments, the independent effects of each factor and the interaction effect of the two factors were statistically compared based on their effect sizes (η2). As a result, pH (η2 = 59.5-89.0%) affected E. coli survival most significantly, followed by coexisting microbes (1.7-48.4%). Among the interactions affecting E. coli survival, including pH or coexisting microbes-which had larger independent effects-relatively larger statistically significant interactions were observed between pH and coexisting microbes (31.1%), coexisting microbes and water-extractable TDSs (85.4%), and coexisting microbes and temperature (26.4%).

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Tails play essential roles in functions related to locomotor stability and maneuverability among terrestrial and arboreal animals. In kangaroo rats, bipedal hopping rodents, tails are used as effective inertial appendages for stability in hopping, but also facilitate stability and maneuverability during predator escape leaps. The complexity of tail functionality shows great potential for bio-inspiration and robotic device design, as maneuvering is accomplished by a long and light-weight inertial appendage. To (i) further understand the mechanics of how kangaroo rats use their tails during aerial maneuvers, and to (ii) explore if we can achieve this behavior with a simplified tail-like appendage (i.e., template), we combined quantified animal observations, computational simulations, and experiments with a two degrees of freedom (2-DoF) tailed robot. We used video data from free-ranging kangaroo rats escaping from a simulated predator and analyzed body and tail motion for the airborne phase. To explain tail contributions to body orientation (i.e., spatial reorientation), we built a mid-air kangaroo rat computational model and demonstrate that three-dimensional body orientation of the model can be controlled by a simplified 2-DoF tail with a nonlinear control strategy. Resulting simulated trajectories show movement patterns similar to those observed in kangaroo rats. Our robot experiments show that a lightweight tail can generate a large yaw displacement and stabilize pitch and roll angles to zero, simultaneously. Our work contributes to better understanding of the form-function relationship of the kangaroo rat tail and lays out an important foundation for bio-inspiration in robotic devices that have lightweight tail-like appendages for mid-air maneuvering.

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Underground coal storage bunkers serve as crucial infrastructural components in the coal mining industry, providing secure and accessible locations for the storage of mined coal. The interaction between stored coal and underground water in coal storage bunkers indeed poses significant challenges due to the unpredictable nature of the resulting coal-water mixture. This phenomenon is particularly prevalent in coal mines operating under water hazards, where groundwater infiltration into storage areas can lead to the formation of coal-water mixtures, altering the physical properties of the stored coal. The interaction between coal and water can result in the formation of coal-water mixtures (hydromixture), which exhibit complex rheological properties. These mixtures may vary in viscosity, density, and particle size distribution, making their behavior difficult to predict. Underground water may exert hydrostatic pressure on the stored coal, influencing its mechanical behavior and compaction properties. Changes in pressure can result in coal compaction or expansion, affecting bunker stability and the integrity of surrounding rock strata. The main goal of the paper was to determine the values of pressure field variations exerted by the flowing hydromixture within underground coal storage bunkers. This objective reflects a critical aspect of understanding the dynamic behavior of coal-water mixtures (hydromixture) under varying conditions, particularly in environments where water hazards pose significant challenges to storage and operational stability. The paper utilized computational fluid dynamics (CFD) methods to examine the changes in pressure within underground coal storage bunkers induced by the flow of coal-water mixtures. The examination of damage to an underground coal storage bunker due to stress distribution was conducted using the finite element method (FEM). This computational technique is widely utilized in engineering and structural analysis to model complex systems and predict the behavior of materials under various loading conditions The results of the CFD numerical simulation were compared with the mathematical models.

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The aim of the current study was to understand the importance of the joint alignment following triple arthrodesis by analysing the contact characteristics in a normal and arthritic ankle joint using a patient-specific numerical model developed using open source software. The alignment of the hindfoot with respect to tibia is calculated from CT scans and the ankle joint model was numerically analysed for neutral, valgus and varus positions in both normal and arthritic conditions. The contact area, the magnitude and distribution of the contact pressure on the articular surface of the talar dome was evaluated using a cell-centred Finite Volume Method implemented in open-source software OpenFOAM. It was found that all positions of the hindfoot predict higher lateral pressures during heel strike. The varus position predicts the maximum increase in lateral pressures. Comparing the valgus and neutral positions, although the neutral position predicts 9.1 % higher increase in lateral pressures during heel strike than valgus, it predicts 33.6 % decrease in pressures during heel-rise and the distribution is more medial during toe-off. In the case of arthritic ankle, it could be observed that the neutral and varus hindfoot fusion positions result in a concentrated increase of lateral pressures in heel strike and flat-foot. In the case of toe-off, the neutral alignment results in an increase of 62.3 % in the contact pressures compared to the arthritic pressure of the unfused foot and is 20.8 % higher than the valgus alignment. The study helps to conclude that the fusion is more beneficial at the neutral position of the hindfoot for the patient specific ankle. However, the 5° valgus position of hindfoot alignment could be more beneficial in the arthritic ankle. Patient-specific approach to the placement of the hindfoot with the help of numerical analysis could help address the issue of ankle degradation following arthrodesis.

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The organic pollutants disposed at the Sardas landfill in Sabiñánigo (Huesca, northeastern Spain) by the INQUINOSA lindane factory have reached the Gállego alluvial aquifer and could affect the Sabiñánigo reservoir. The daily oscillations of the reservoir water level produce a tidal effect on the piezometric heads of the aquifer. These oscillations are transmitted in a damped way with a time lag, thus attesting that the silting sediments of the reservoir and the natural silts of the Gállego alluvial are interposed between the reservoir water and the layer of sands and gravels. A 2D finite element groundwater flow and total dissolved hexachlorocyclohexane (HCH) transport model through the Gállego alluvial aquifer is presented here. The flow model was constructed to: (1) Quantify the tidal effect, produced by the daily fluctuations of the reservoir water level on the aquifer; (2) Estimate the hydrodynamic parameters of the layer of sands and gravels; and 3) Estimate the vertical hydraulic conductivity of the silting sediments and silts; and (4) Quantify aquifer/reservoir interactions. The flow model reproduces the dynamics of the tidal effect and attests that groundwater velocity and flow direction changes daily in response to the oscillations of the reservoir level. Model results reproduce the measured well hydrographs and the Darcy velocity derived from tracer tests and confirm the validity of the conceptual model. The transport model of total dissolved HCH simulates the time evolution of the contaminant plume. The computed concentrations of total dissolved HCH and the contaminant mass outflux are very sensitive to changes in the source terms and the distribution coefficient, Kd of HCH. The best fit to the measured HCH plumes in September 2010 and December 2020 is obtained with a Kd ranging from 1 to 3 L/kg. The computed flux of dissolved HCH leaving the Sardas site in 2020 towards the Sabiñánigo reservoir ranges from 0.6 kg/year for Kd = 3 L/kg to 3.1 kg/year for Kd = 1 L/kg. The findings of this study will be most useful for planning and designing remedial and containment actions at the Sardas site and other similar lindane-affected sites.

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Numerical health risk assessment models have been developed to describe faecal contamination of water using Escherichia coli as an indicator bacterium. Although many previously established numerical models for E. coli in aquatic environments have only considered the effects of one or two water quality parameters such as temperature and sunlight, it is difficult to simulate E. coli survival with only one or two parameters because the aquatic environment is a complex system. This study conducted a series of comparative experiments to select water quality parameters that should be preferentially considered in a numerical model for E. coli survival in lakes. The parameters considered were temperature, pH, dissolved oxygen (DO), total dissolved solids (TDS), suspended solids (SS), coexisting microbes, and light intensity. In the laboratory experiments, the survival of E. coli was observed by controlling two of these seven parameters, and the effects of these parameters on the rate of E. coli population change were statistically compared. Consequently, light intensity affected the survival of E. coli most significantly, followed by the presence of coexisting microbes, temperature, pH, and TDS. However, DO and SS had smaller effects on survival than other parameters. High-impact interactions on E. coli survival were observed between temperature and TDS and temperature and coexisting microbes. These results suggest that existing numerical models for simulating E. coli survival in lakes should be modified to consider the independent and interactive effects of multiple parameters such as sunlight, coexisting microbes, temperature, pH, and TDS.

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Cancer invasion and migration play a pivotal role in tumor malignancy, which is a major cause of most cancer deaths. Rotating magnetic field (RMF), one of the typical dynamic magnetic fields, can exert substantial mechanical influence on cells. However, studying the effects of RMF on cell is challenging due to its complex parameters, such as variation of magnetic field intensity and direction. Here, we developed a systematic simulation method to explore the influence of RMF on tumor invasion and migration, including a finite element method (FEM) model and a cell-based hybrid numerical model. Coupling with the data of magnetic field from FEM, the cell-based hybrid numerical model was established to simulate the tumor cell invasion and migration. This model employed partial differential equations (PDEs) and finite difference method to depict cellular activities and solve these equations in a discrete system. PDEs were used to depict cell activities, and finite difference method was used to solve the equations in discrete system. As a result, this study provides valuable insights into the potential applications of RMF in tumor treatment, and a series of in vitro experiments were performed to verify the simulation results, demonstrating the model's reliability and its capacity to predict experimental outcomes and identify pertinent factors. Furthermore, these findings shed new light on the mechanical and chemical interplay between cells and the ECM, offering new insights and providing a novel foundation for both experimental and theoretical advancements in tumor treatment by using RMF.

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The membrane interface probe (MIP) is an efficient and economical in-situ tool for chlorinated hydrocarbon (CH) contaminated site investigation. Given that the interpretation of MIP test is currently limited to a qualitative level, a theoretical model considering multiphase flow and multifield coupling is firstly proposed to simulate MIP test process. This model can consider phase change, membrane effect, adsorption and dissolution of the CH liquid, gas diffusion, and evaporation. Then, the model is used to study the changes in soil temperature and soil CH concentration during MIP test, as well as the influences of soil CH concentration and soil properties (initial water saturation, soil intrinsic permeability, and thermal properties) on MIP response. Finally, a simplified MIP interpretation model is developed based on parametric analysis results and verified against field and laboratory test data. It is found that the soil CH concentration, rather than soil properties, dominates the MIP response. The simplified interpretation model can deliver practical prediction of the CH concentration through the detected results by MIP, which may improve the applicability of MIP.

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A new variant of the inherent strain (IS) method is proposed to predict component distortion in powder bed fusion additive manufacturing (AM) that addresses some of the shortcomings of the previous work by accounting for both the compressive plastic strain formed adjacent to the melt pool and the thermal strain associated with the changing macroscale thermal field in the component during fabrication. A 3D thermomechanical finite element (FE) model using the new approach is presented and applied to predict the distortion of a component fabricated in an electron beam powder bed fusion (EB-PBF) machine. To improve computational efficiency, each computational layer is comprised of six powder layers. A time-averaged volumetric heat input based on beam voltage and current data obtained from the EB-PBF system was calculated and applied to each computational layer, consistent with the process timing. The inherent strains were applied per computational layer as an initial anisotropic contribution to the thermal strain at the time of activation of each computational layer, resulting in the sequential establishment of static equilibrium during component fabrication, which accounts for the variation in the local macroscale thermal field. The thermal field and distortion predicted by the thermomechanical model were verified using experimentally derived data. The model predicts in-plane compressive strains in the order of 10-3. Differences in the inherent strain were found at different locations in the component, consistent with differences in the macroscale thermal field. The proposed method is general and may also be applied to the laser powder bed fusion (L-PBF) process.

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This study conducts a numerical comparison of the thermal performance of three distinct working fluids (pure water, TiO2, and SiO2 water-based nanofluids) within an evacuated tube solar collector using Computational Fluid Dynamics. The study evaluates thermohydraulic performance alongside global and local entropy generation rates, while considering variations in solar radiation values and inlet mass flow rates. Results indicate that nanofluids demonstrate superior performance under low solar radiation, exhibiting higher outlet temperatures, velocities, thermal efficiency, and exergy efficiency compared to pure water. However, at the higher solar radiation level, the efficiency of SiO2 water-based nanofluid diminishes due to its impact on specific heat. Furthermore, the entropy generation analysis reveals significant reductions with TiO2 water-based nanofluid in all the phenomena considered (up to 79 %). The SiO2 nanofluid performance aligns closely with pure water under high radiation value. This investigation offers valuable insights into the utilization of nanofluids in solar collectors across diverse operating conditions, emphasizing their pivotal role in enhancing overall performance.

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Peatlands are recognized as crucial greenhouse gas sources and sinks and have been extensively studied. Their emissions exhibit high spatial heterogeneity when measured on site using flux chambers. However, the mechanism by which this spatial variability behaves on a very fine scale remains unclear. This study investigates the fine-scale spatial variability of greenhouse gas emissions from a subantarctic Sphagnum peatland bog. Using a recently developed skirt chamber, methane emissions and ecosystem respiration (as carbon dioxide) were measured at a submeter scale resolution, at five specific 3 × 3 m plots, which were examined across the site throughout a single campaign during the Austral summer season. The results indicated that methane fluxes were significantly less homogeneously distributed compared with ecosystem respiration. Furthermore, we established that the spatial variation scale, i.e., the minimum spatial domain over which notable changes in methane emissions and ecosystem respiration occur, was <0.56 m2. Factors such as ground height relative to the water table and vegetation coverage were analyzed. It was observed that Tetroncium magellanicum exhibited a notable correlation with higher methane fluxes, likely because of the aerenchymatous nature of this species, facilitating gas transport. This study advances understanding of gas exchange patterns in peatlands but also emphasizes the need for further efforts for characterizing spatial dynamics at a very fine scale for precise greenhouse gas budget assessment.

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Seawater intrusion (SI) has become a global issue exacerbated by intense anthropogenic activities and climate change. It is imperative to seek a synergistic strategy to reconcile environmental and economic benefits in the coastal regions. However, the intricate SI process and data scarcity present formidable challenges in dynamically assessing the coastal groundwater vulnerability. To address the challenge, this study proposed a novel framework that integrates the existing vulnerability assessment method (GALDIT) and variable-density groundwater model (SEAWAT). The future scenarios from 2019 to 2050 were investigated monthly under climate change (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and human activities (80 % and 50 % of current groundwater abstraction) in Longkou city, China, a typical coastal region subject to extensive SI, compared with the status quo in 2018. Results indicated that by 2050, the high vulnerability area, is in a narrow buffer within 1.2 km from the shoreline and exhibits minor changes while the salt concentration here increased by about 2700 mg/L compared with the current situation. The moderate vulnerability zone expands by about 30 km2, and the low vulnerable area decreases proportionally. The groundwater over-abstraction is identified as a more critical factor compared to the regional precipitation under climate change. When groundwater abstraction is reduced to 80 % of the current scale, the expansion rate of the moderate-vulnerable area slows down significantly, with an expansion area of only 18 km2 by 2050. Further reducing groundwater abstraction to 50 % of the current scale shifts the evolution trend of the medium-vulnerable area from expansion to contraction, with the area shrinking by about 11 km2 by 2050. The integrated vulnerability assessment framework can be applied not only in the similar coastal regions but also provides insights into other natural hazards.

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The accumulation of lead (Pb) in soil resulted from industrialization and urbanization poses a threat to human health and the ecosystem. This study proposes a mathematical model for Pb migration and transformation in soil porous media, aiming to guide the design of electrokinetic remediation schemes for Pb-contaminated soils. To improve the validity of the model, the chemical reactions considered in the model are all based on chemical reaction kinetics, which were usually overlooked for model simplification. The model quantitatively describes various physical and chemical processes of Pb at the soil-pore fluid interface and in the pore fluid, including diffusion, electromigration, electroosmosis, electrolytic water reaction, precipitation, adsorption/desorption, protonation/deprotonation reaction, and water self-ionization reaction. The numerical results show that the pH value is a key factor affecting the distribution of Pb in the soil and determining the removal efficiency of Pb. The effects of different enhancement methods on Pb concentration distribution and removal efficiency were evaluated with this model. It was found that placing a cation exchange membrane at the cathode boundary while using 0.01 M nitric acid as anode electrolyte can effectively improve Pb removal efficiency from 3.9% to 93.6%. The developed model can be used to guide the design of the enhanced electrokinetic remediation schemes.

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Human surrogates have long been employed to simulate human behaviour, beginning in the automotive industry and now widely used throughout the safety framework to estimate human injury during and after accidents and impacts. In the specific context of blunt ballistics, various methods have been developed to investigate wound injuries, including tissue simulants such as clays or gelatine ballistic, physical dummies and numerical models. However, all of these surrogate entities must be biofidelic, meaning they must accurately represent the biological properties of the human body. This paper provides an overview of physical and numerical surrogates developed specifically for blunt ballistic impacts, including their properties, use and applications. The focus is on their ability to accurately represent the human body in the context of blunt ballistic impact.

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OBJECTIVES: Aortic valve repair requires the creation of a normal geometry of cusps and aortic root. Of the different dimensions, geometric cusp height is the most difficult to change while annular and sinotubular dimensions can be easily modified. The objective of this study was to investigate, by computer simulation, ideal combinations of annular and sinotubular junction size for a given geometric height. METHODS: Based on a literature review of anatomical data, a computational biomechanics model was generated for a tricuspid aortic valve. We aimed to determine the ideal relationships for the root dimensions, keeping geometric height constant and creating different combinations of the annular and sinotubular junction dimensions. Using this model, 125 virtual anatomies were created, with 25 different combinations of annulus and sinotubular junction. Effective height, coaptation height and mechanical cusp stress were calculated with the valves in closed configuration. RESULTS: Generally, within the analysed range of geometric heights, changes to the annular diameter yielded a stronger impact than sinotubular junction diameter changes for optimal valve configuration. The best results were obtained with the sinotubular junction being 2-4 mm larger than the annulus, leading to higher effective height, normal coaptation height and lower stress. Within the range tested, stenosis did not occur due to annular reduction. CONCLUSIONS: In tricuspid aortic valves, the geometric height can be used to predict ideal post-repair annular and sinotubular junction dimensions for optimal valve configuration. Such an ideal configuration is associated with reduced cusp stress.

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Organic contaminants have a tendency to accumulate in low-permeability aquifers, making their removal challenging and creating a bottleneck in groundwater remediation efforts. The use of ozone micro-nano bubbles, due to their smaller size compared to traditional macrobubbles, shows potential for efficient penetration into the low-permeability aquifer and effective oxidization of contaminants. This study conducted batch experiments, column studies, and 2D tank experiments to systematically investigate the remediation efficiency of toluene in a heterogeneous aquifer using ozonated water (OW), ozone micro-bubble water (OMBW), and encapsulated ozone micro-nano bubble water (EOMBW) with rhamnolipid. Experimental results showed that rhamnolipid effectively increased the densities and reduced the sizes of micro-nano bubbles, leading to improved ozone preservation and enhanced toluene degradation. Nanobubbles exhibited higher mobility compared to microbubbles in porous media, while rhamnolipid increased the density of penetrated nanobubbles by 9.6 times. EOMBW demonstrated superior efficiency in oxidizing toluene in low-permeability aquifers, and a numerical model was developed to successfully simulate the ozone and toluene concentration. The model revealed that the increased oxidation rate by EOMBW was attributed to the preservation of ozone in micro-nano bubbles and the enhanced toluene oxidation rate. These findings contribute significantly to the application of EOMBW in heterogeneous aquifer remediation.