Sensitivity Study Research Articles

A Study of Loss Model Parameter Sensitivity in Compressor Unsteady Flow Simulations

Abstract This article presents results from a comprehensive sensitivity analysis focused on loss models used in a recently developed compressor unsteady mean line flow model for a transonic axial-centrifugal compressor. The mean line flow model treats flow through rotors and stators in their respective reference frames (rotating or stationary), and the compressor performance is determined by the kinetic energy addition and various physics-based loss models in relative frames. In this paper, we describe the modeling approach of the compressor flow model, as well as the loss models that are used to obtain a relatively good match against test data. Sensitivity studies of selected loss model parameters are presented to show the effect of individual loss model parameters on the overall compressor characteristics in the entire speed range. The effects of losses on unsteady flow transients are assessed by comparing the transient responses when a step reduction of throttle area is applied. The comparisons show that the change in loss magnitude has weak effects on transient response if the change of loss does not significantly change the system stability.

The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators

Abstract. Supercooled liquid clouds are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We take advantage of the Macquarie Island Cloud and Radiation Experiment (MICRE) to perform an analysis of observed and simulated cloud processes over the Southern Ocean in a region and season dominated by supercooled liquid clouds. Using a single-column version of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS), we compare two different cloud microphysical schemes to ground-based observations of cloud, precipitation, and radiation over a 2.5-month period (1 January–17 March 2017). Both schemes are able to reproduce aspects of the cloud and radiation observations during MICRE to within the uncertainty of the data when the thermodynamic profile is prescribed with relaxation. There are differences in water mass and representation of reflectivity between the schemes. A sensitivity study of the cloud microphysics schemes, one a bulk one-moment scheme and the other a two-moment scheme with prediction of mass and number, indicates that several key processes create differences between the schemes. Surface radiative fluxes and total water path are highly sensitive to the formation and fall speed of precipitation. The prediction of hydrometeor number with the two-moment scheme yields a better comparison with observed reflectivity and radiative fluxes, despite predicting higher liquid water contents than observed. With the two-moment scheme, we are also able to test the sensitivity of the results to the input of liquid cloud condensation nuclei (CCN) and ice nuclei (IN). The cloud properties and resulting radiative effects are found to be sensitive to the CCN and IN concentrations. More CCN and IN increase liquid and ice water paths, respectively. Thus, both the dynamic environment and aerosols, integrated through the cloud microphysics, are important for properly representing Southern Ocean cloud radiative effects.

A Phase 2 Sensitivity and Selectivity Study of High-Dose 5-Aminolevulinic Acid in Adult Patients Undergoing Resection of a Newly Diagnosed or Recurrent Glioblastoma

BACKGROUND AND OBJECTIVES: The utility of oral 5-aminolevulinic acid (5-ALA)/protoporphyrin fluorescence for the resection of high-grade gliomas is well documented, but the problem of false-negative observations remains. This study compares high-grade glioma visualization with low/standard dose 5-ALA (<30 mg/kg) to high-dose 5-ALA (>40 mg/kg) to see if by using this higher dose, it is possible to reduce the rate of false-negative observations without increasing the rate of false-positive (FP) observations and therefore increase the sensitivity. METHODS: This is a prospective study of consecutive patients with radiological evidence of presumed high-grade glioma. We reviewed the data from patients who received preoperative low/standard doses and patients who received a preoperative high dose of 5-ALA. Adverse events, dose to observation time, intensity of tumor fluorescence, and results of biopsies in areas of tumor and tumor bed under deep blue light were recorded. RESULTS: A total of 22 patients with high-grade glioma received a dose >40 mg/kg (high-dose) and 9 patients received <30 mg/kg (low/standard dose). There were no serious adverse events related to 5-ALA in any subject. There was a very high sensitivity and specificity of 5-ALA for the presence of tumor in both groups. There were no FP observations (fluorescence with no tumor) in either group. The specificity and the positive predictive value were 100% in both groups. The sensitivity and the negative predictive value were 53.3% and 30.0% in the low/standard dose group and 59.5% and 31.8% in the high-dose group, respectively. CONCLUSION: High-dose oral 5-aminolevulinic/protoporphyrin fluorescence is a safe and effective aid to the intraoperative detection of high-grade gliomas with high sensitivity and specificity. False-negative observations with a high dose do not seem to be less than that with a low/standard dose. The rate of FP observations with both groups remains very low.

A Sensitive Frequency Band Study for Distributed Acoustical Sensing Monitoring Based on the Coupled Simulation of Gas–Liquid Two-Phase Flow and Acoustic Processes

The sensitivity of gas and water phases to DAS acoustic frequency bands can be used to interpret the production profile of horizontal wells. DAS typically collects acoustic signals in the kilohertz range, presenting a key challenge in identifying the sensitive frequency bands of the gas and water phases in the production well for accurate interpretation. In this study, a gas–water two-phase flow–acoustic coupling model for a horizontal well is developed by integrating a gas–water separation flow model with a pipeline acoustic model. The model simulates the sound pressure level (SPL) and amplitude variations of acoustic waves under different flow patterns, spatial locations, and gas–water ratio schemes. The results demonstrate that within the same flow pattern, an increase in the gas–water ratio significantly elevates acoustic amplitude and SPL peaks within the 5–50 Hz frequency band. Analysis of oil field DAS data reveals that the amplitude response range for stages with a lower gas–water ratio falls within 5–10 Hz, whereas stages with a higher gas–water ratio exhibit an amplitude response range of 10–50 Hz.

Generation of 10 kT axial magnetic fields using multiple conventional laser beams: A sensitivity study for kJ PW-class laser facilities

Strong multi-kilotesla magnetic fields have various applications in high-energy density science and laboratory astrophysics, but they are not readily available. In our previous work [Y. Shi et al., Phys. Rev. Lett. 130, 155101 (2023)], we developed a novel approach for generating such fields using multiple conventional laser beams with a twist in the pointing direction. This method is particularly well-suited for multi-kilojoule petawatt-class laser systems like SG-II UP, which are designed with multiple linearly polarized beamlets. Utilizing three-dimensional kinetic particle-in-cell simulations, we examine critical factors for a proof-of-principle experiment, such as laser polarization, relative pulse delay, phase offset, pointing stability, and target configuration, and their impact on magnetic field generation. Our general conclusion is that the approach is very robust and can be realized under a wide range of laser parameters and plasma conditions. We also provide an in-depth analysis of the axial magnetic field configuration, azimuthal electron current, and electron and ion orbital angular momentum densities. Supported by a simple model, our analysis shows that the axial magnetic field decays owing to the expansion of hot electrons.

A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2

Abstract. Recent studies have suggested that injection of solid particles such as alumina and calcite particles for stratospheric aerosol injection (SAI) instead of sulfur-based injections could reduce some of the adverse side effects of SAI such as ozone depletion and stratospheric heating. Here, we present a version of the global aerosol–chemistry–climate model SOCOL-AERv2 and the Earth system model (ESM) SOCOLv4 which incorporate a solid-particle microphysics scheme for assessment of SAI of solid particles. Microphysical interactions of the solid particle with the stratospheric sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code (RTC) for the first time within an ESM. Therefore, the model allows simulation of heterogeneous chemistry at the particle surface as well as feedbacks between microphysics, chemistry, radiation and climate. We show that sulfur-based SAI results in a doubling of the stratospheric aerosol burden compared to the same mass injection rate of calcite and alumina particles with a radius of 240 nm. Most of the sulfuric acid aerosol mass resulting from SO2 injection does not need to be lifted to the stratosphere but is formed after in situ oxidation and subsequent water uptake in the stratosphere. Therefore, to achieve the same radiative forcing, larger injection rates are needed for calcite and alumina particle injection than for sulfur-based SAI. The stratospheric sulfur cycle would be significantly perturbed, with a reduction in stratospheric sulfuric acid burden by 53 %, when injecting 5 Mt yr−1 (megatons per year) of alumina or calcite particles of 240 nm radius. We show that alumina particles will acquire a sulfuric acid coating equivalent to about 10 nm thickness if the sulfuric acid is equally distributed over the whole available particle surface area in the lower stratosphere. However, due to the steep contact angle of sulfuric acid on alumina particles, the sulfuric acid coating would likely not cover the entire alumina surface, which would result in available surface for heterogeneous reactions other than the ones on sulfuric acid. When applying realistic uptake coefficients of 1.0, 10−5 and 10−4 for H2SO4, HCl and HNO3, respectively, the same scenario with injections of calcite particles results in 94 % of the particle mass remaining in the form of CaCO3. This likely keeps the optical properties of the calcite particles intact but could significantly alter the heterogeneous reactions occurring on the particle surfaces. The major process uncertainties of solid-particle SAI are (1) the solid-particle microphysics in the injection plume and degree of agglomeration of solid particles on the sub-ESM grid scale, (2) the scattering properties of the resulting agglomerates, (3) heterogeneous chemistry on the particle surface, and (4) aerosol–cloud interactions. These uncertainties can only be addressed with extensive, coordinated experimental and modelling research efforts. The model presented in this work offers a useful tool for sensitivity studies and incorporating new experimental results on SAI of solid particles.

A time-relaxation reduced order model for the turbulent channel flow

Regularized reduced order models (Reg-ROMs) are stabilization strategies that leverage spatial filtering to alleviate the spurious numerical oscillations generally displayed by the classical Galerkin ROM (G-ROM) in under-resolved numerical simulations of turbulent flows. In this paper, we propose a new Reg-ROM, the time-relaxation ROM (TR-ROM), which filters the marginally resolved scales. We compare the new TR-ROM with the two other Reg-ROMs in current use, i.e., the Leray ROM (L-ROM) and the evolve-filter-relax ROM (EFR-ROM) and one eddy viscosity model, the mixing-length model, in the numerical simulation of the turbulent channel flow at Reτ=180 and Reτ=395 in both the reproduction and the predictive regimes. For each Reg-ROM, we investigate two different filters: (i) the differential filter (DF), and (ii) the higher-order algebraic filter (HOAF). In our numerical investigation, we monitor the Reg-ROM performance with respect to the ROM dimension, N, and the filter order. We also perform sensitivity studies of the three Reg-ROMs with respect to the time interval, relaxation parameter, and filter radius. The numerical results yield the following conclusions: (i) All three Reg-ROMs are significantly more accurate than the G-ROM. (ii) All three Reg-ROMs are more accurate than the ROM projection in terms of Reynolds stresses. (iii) With the optimal parameter values, the new TR-ROM yields more accurate results than the L-ROM and the EFR-ROM in all tests. (iv) The new TR-ROM is more accurate than the mixing-length ROM. (v) For most N values, DF yields the most accurate results for all three Reg-ROMs. (vi) The optimal parameters trained in the reproduction regime are also optimal for the predictive regime for most N values, demonstrating the Reg-ROM predictive capabilities. (vii) All three Reg-ROMs are sensitive to the filter order and the filter radius, and the EFR-ROM and the TR-ROM are sensitive to the relaxation parameter. (viii) The optimal range for the filter radius and the effect of relaxation parameter are similar for the two Reτ values.

Study of Etiopathological Factors, Clinical Parameters and Culture Sensitivity of Patients Suffering from Diabetic Foot Ulcer

Study of Etiopathological Factors, Clinical Parameters and Culture Sensitivity of Patients Suffering from Diabetic Foot Ulcer

Study of mesh sensitivity and temporal discretization influence on the generation of realistic irregular waves through the WaveMIMO methodology

Study of mesh sensitivity and temporal discretization influence on the generation of realistic irregular waves through the WaveMIMO methodology

A novel computer vision and point cloud-based approach for accurate structural analysis of a tall irregular timber structure

Wood material has been widely used in critical heritage structures such as pagodas, totem poles, and large-scale sculptures. Conducting rigorous structural analysis is crucial to protect these structures in high-seismic regions. Typically, these types of structures are modeled using an equivalent finite element (FE) model which used simple cylinder with a constant cross section equal to the average of the top and bottom cross section. However, simplified equivalent FE models may not accurately consider the irregularities and complexities of these structures. In this paper, advanced computer vision and point cloud techniques were adopted to accurately and rapidly construct a FE model of a 30-meter irregular timber sculpture. This was achieved using video scans, computer vision-aided 3D reconstruction, point cloud processing, and mesh to solid element conversion. The refined FE model was used to conduct capacity check, mesh sensitivity study, pushover analysis, and response spectrum analysis. The results of the refined FE model were compared to an equivalent FE model. The results show: 1) the proposed numerical modeling methodology for structural analysis can efficiently and accurately measure the dimension of the irregular sculpture up to 98.2 % accuracy; 2) the lateral stiffnesses of the 30-meter irregular sculpture vary significantly (up to 42.6 %) from one direction to the other; 3) the equivalent FE model overestimated the shear and moment capacities by 20.6 % and 13.2 %, respectively; 4) on average, the equivalent FE model overestimated the shear and moment demands by 8.9 % and 5.5 %, respectively. Overall, the proposed application has demonstrated a fast, economical and accurate method to conduct seismic evaluation and design for irregular structures.

4E analysis and optimization comparison of solar, biomass, geothermal, and wind power systems for green hydrogen-fueled SOFCs

Integrating renewable energies with hydrogen production via electrolysis and utilizing hydrogen as a fuel for solid oxide fuel cells (SOFCs) presents a synergistic approach towards sustainable energy generation. This coupling offers enhanced flexibility, allowing for efficient energy storage and distribution, thereby addressing intermittency issues associated with renewable sources. Additionally, the utilization of hydrogen in SOFCs enables high-efficiency power generation with reduced emissions, contributing to the transition towards a cleaner energy landscape. In the present study, four types of renewable energies, namely solar, biomass, geothermal, and wind, produce hydrogen by coupling power generation units and a proton exchange membrane electrolyzer (PEME). Then, the produced hydrogen is stored and used for later utilization in an SOFC subsystem. A 4E (energy, exergy, exergy-economic, and environmental) study is conducted for the proposed systems through a sensitivity study and design optimization. In the best output performance mode, the best exergy efficiency is obtained by the biomass-based system, which is equal to 9.40%, and the lowest values for total cost rate and unit cost of outputs are achievable by the geothermal-based system, with values of 27.72 $/h and 43.23 $/GJ.

Study Explores Fracture-Driven Interaction Mitigation Strategies for Field Development

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper URTeC 4055561, “Numerical Investigation of Fracture-Driven-Interaction Mitigation Strategies and Field Development Optimization,” by Ruiting Wu, SPE, Xiaolong Liu, and Lili Xu, Chevron, et al. The paper has not been peer reviewed. _ Numerical modeling of fracture-driven interactions (FDI) using a coupled hydraulic-fracturing-propagation, reservoir-flow, and geomechanics tool has been conducted. The numerical study showed that, for the basins studied, FDI and some mitigation strategies have minimal effect on long-term parent-well productions. Parent depletion (volume and areal extent), well spacing, and child-fracture asymmetry, however, greatly affect child-well production as the result of FDI. Introduction Interwell FDI, also known as frac hits, has garnered recent attention given that more than 60% of new wells drilled in US unconventional reservoirs are infill drilling. Whereas uncontrollable parameters, such as natural fractures and matrix permeability, do contribute to the effect of FDI on well production, the authors’ primary focus lies on controllable factors. Field observations have shown that tighter well spacing and smaller completion sizes tend to result in fewer negative effects on both parent- and child-well production. Additionally, fracture-fluid injection rates, the number of clusters, and cluster spacing all influence FDI effects. Simulation Tool and Workflow A coupled hydraulic-fracture, reservoir, and wellbore simulator was used to simulate the fracturing and production stage of the parent and child wells and related fracture-driven well interaction. The simulator simultaneously solves the equations of fluid flow, proppant transport, water/solute transport, fracture mechanics, and poroelasticity in the well, fracture, and matrix domains. Fracture propagation is calculated using the multilayer-tip-elements algorithm. Fracture elements are represented by uniformly sized rectangles. Fracture-to-fracture stress shadow is calculated with the 3D displacement discontinuity method, and the poroelastic stress responses during fracture propagation and depletion are calculated with a finite-volume method. The tool is designed to simulate the entire life cycle of the FDI interaction. The modeling workflow also includes calibration with field observations of fracture geometry, the pressure response at the parent well during fracturing of the child well, the water cut change at the parent well as the result of FDI, and production performance. Field Case Study: Permian Basin The primary objective of this study is to identify the key parameters that contribute to FDI and mitigate the negative effects of FDI. Two field case studies were conducted in two basins, the Permian Basin and the DJ Basin. In both field studies, a history match of parent and child well performance was first conducted. Then, a sensitivity study was performed on various key parameters to understand their effects on the production performance at both parent and child wells. Both field case studies are focused on the lateral FDI. The first case study is included in this synopsis.

Analytical model for CO2-water displacement with rate-dependent phase permeability for geological storage

Analytical modelling is an effective tool for predicting reservoir behaviour under high uncertainties, like CO2 storage in aquifers, where multiple simulation runs are necessary for stochastic modelling and risk assessment. This paper formulates the Buckley-Leverett problem with x-dependent fractional flow. We derive a new analytical model for displacement of brine by CO2 accounting for (i) rate-dependent phase permeability during radial flows and (ii) radial flows of Forchheimer’s high-rate gas injection; this analytical model is also valid for (iii) linear flows during flooding in micro heterogeneous or composite cores and (iv) CO2-water flow upscaling in reservoir where layering is perpendicular to flux direction. An exact solution of the flow equation is based on the observation that the flux of each phase conserves along the characteristic trajectories. We discuss S-shape fractional flow function, which is typical for reservoir rocks. The solution includes formulae for phase saturations and fluxes and trajectories of the displacement CO2-water front and of the forward and rear mixture zone boundaries. Fast analytical model can be used for multivariate sensitivity study and sweep efficiency prediction.

Auroral 3D structure retrieval from the Juno/UVS data

Context. Jovian auroras, the most powerful in the Solar System, result from the interaction between the magnetosphere and atmosphere of Jupiter. While the horizontal morphology of these phenomena has been widely studied, their vertical structure, determined by the penetration depth of the magnetospheric electron into the auroral regions, remains relatively unexplored. Previous observations, including those from the Hubble Space Telescope (HST), have addressed this question to a limited extent. Aims. In this study we aim to map the vertical structure of Jovian auroral emissions. Methods. Using observations from Juno’s UltraViolet Spectrograph (UVS), we examined the vertical structure of the auroral emissions. Building on a recent study of auroral energy mapping based on UVS observations that mapped the average energy of precipitating electrons in the Jovian auroral regions, we find a relationship between this average energy and the volume emission rate (VER) of H2 for two types of electron energy distributions: monoenergetic and a kappa distribution with κ = 2.5. Results. Using brightness maps, we derived the 3D VER structure of Jovian auroras in both northern and southern regions, across multiple spacecraft perijoves (PJs). By considering the example of PJ11, we find that the average altitude of the VER peak in the polar emission region is approximately ~250 km for the monoenergetic distribution case and ~190 km for kappa distribution case. In the main emission region, we find that the average altitude of the VER peak is approximately ~260 km for the case of monoenergetic distribution and ~197 km for kappa distribution case. For the other PJs, we obtained results that are very similar to those of PJ11. Conclusions. Our findings are, on average, consistent with measurements from the Galileo probe and the HST observations. This study contributes to a better understanding of the complexity of Jovian auroras and highlights the importance of using Juno observations when probing their vertical structure. Considering the variability in the κ parameter in the auroral region, we also studied the impact of this variability on the vertical structure of the auroral emission. This sensitivity study reveals that the influence of the κ parameter on our results was very weak. However, the impact of the κ variability on the VER amplitude shows that there is an influence on the thermal structure and chemical composition of the atmosphere in the auroral regions.

Investigating secondary ice production in a deep convective cloud with a 3D bin microphysics model: Part I - Sensitivity study of microphysical processes representations

Secondary ice production (SIP) is a crucial phenomenon for explaining the formation of ice crystal clouds, especially when addressing the discrepancies between observed ice crystal number concentrations and ice nucleating particles (INPs). In this study, we investigate parameterizations of three SIP processes (Hallett-Mossop, fragmentation of freezing drops, and fragmentation due to ice–ice collision) by simulating a deep convective cloud observed during the HAIC/HIWC campaign with the 3D bin microphysics scheme DESCAM (DEtailed SCAvening and Microphysics model). The simulated mean cloud properties, including particle size distributions and ice crystal number concentration are compared with in situ probe observations obtained during the campaign. Simulation excluding SIP show a large underestimation of small ice crystals (< 1 mm diameter) for temperatures warmer than ‐30∘C. In our results, incorporating Hallett-Mossop and fragmentation due to ice–ice collision processes leads to ice crystal number concentrations close to observed values, thereby reducing discrepancies by two orders of magnitude. Our simulations also indicates that fragmentation of freezing drops affect minimally the properties of the cloud at its mature stage. Furthermore, we investigate the impact of fragments sizes resulting from SIP processes and show that the size of fragments generated from fragmentation due to ice–ice collision significantly influences the shape of ice particle size distribution. Employing various parameterizations of the ice crystal sticking efficiency reveals a notable impact on cloud properties. This study shows that SIP mechanisms are important and have to be considered for cold and mixed-phase clouds. However their parameterization lack reliability, highlighting the need for better quantifying these mechanisms. The companion paper, investigates the effects of SIP processes on the formation and the evolution of the deep convective system.

Experimental analysis of a hybrid thermochemical cycle driven by intermediate grade heat sources for energy storage and combined cold and work productions

This paper presents an experimental study of a hybrid thermochemical cycle for the simultaneous cogeneration of cold and mechanical power, and thermal storage based on medium temperature sources. This concept is based on the integration of an expander machine on the reactive gas flow between the evaporator and the reactor to allow mechanical work production. The paper shows the proof of concept of this hybridization by continuous mechanical production and cold during the whole production phase: 68.33 kJ mechanical energy and 15.18 MJ cold, stable pressure ratio at the expander (around 1.3) and stable rotational speed (around 400 rpm). The prototype conception and design are detailed. The integration of the expander creates a pressure difference between the evaporator and the reactor (contrary to a classical thermochemical cycle), and thus an experimental sensitivity study investigating the effect of the cold production temperature at the evaporator (which defines the inlet pressure of the expander) on the mechanical production of the prototype and its dynamics is done. This allowed to analyze the strong coupling between the reactor and the expander in different operating conditions, experimentally and from a theoretical point of view. Indeed, the identified limitations of these two main components, it is worth mentioning that this is the first hybrid thermochemical prototype with stable output productions. The prototype works properly by providing continuous mechanical production during the whole production phase under different cold temperatures and constant electrical load, in comparison with what was found in the literature.

Integrating complexity in population modelling: From matrix to dynamic models

Matrix models are widely used in population ecology studies and are valuable for analysing population dynamics, although they are limited in the use of time-varying parameters. This limitation can be overcome by dynamic models. In this study, we revisit a previously published study on a matrix model of a population of the box jellyfish Carybdea marsupialis (L. 1758) in the Western Mediterranean. A dynamic model integrating the transition matrix of the original model is developed in STELLA Architect with the following improvements: (1) Sensitivity study of the reliability of the methodology for calculating the transition matrix and estimation of the errors of the fitting parameters; (2) Closure of the jellyfish life cycle by adding the polyp stage. This will make it possible to simulate scenarios of ecological interest over several years such as a decline in food supply, jellyfish removal strategies, changes in drift currents and changes in substrate availability for planulae to settle. (3) The inclusion of more biological reality. In particular, a temporal pattern of strobilation is added, which improves the fit of the model to the field data.

Sensitivity study of heat transfer in a Jeffrey ferro-hybrid nanofluid bioconvective squeezing flow with inclined MHD and higher-order chemical reaction: entropy analysis

Abstract The present investigation concentrates on analyzing heat transfer and entropy formation in a time-reliant bioconvective flow of a blood-based Jeffrey hybrid nanofluid via a squeezing channel that is suctioned or injected at the lower plate. Cu nanoparticles and Fe3O4 ferro-nanoparticles are suspended in base-fluid blood. Adding ferro-nanoparticles to a flow process allows for better control of the external magnetic field and improved heat transmission. Noble integration of an aligned magnetic field, Joule's heating, thermal radiation, and higher-order chemical reactions is taken into account in the flow in a porous media. An appropriate choice of similarity variables leads to the non-dimensionalization of the governing equations, that are subsequently solved by the homotopy analysis method (HAM), yielding a semi-analytical solution. An innovative feature of this research is the optimization of heat transfer by the application of the response surface methodology (RSM) technique. Additionally, sensitivity analysis was carried out to identify the most influential parameter. The study's findings indicate that increased suction reduces both velocity and temperature distributions in both the nanofluid and hybrid nanofluid models. In terms of thermal performance, the Blood/Fe3O4 - Cu hybrid nanofluid surpasses the Blood/Fe3O4 nanofluid. The rate of thermal energy transfer is highly sensitive to variations in the Eckert number, while thermal radiation has a relatively lesser impact. Moreover, elevated levels of the magnetic parameter, Eckert number, and nanoparticle concentration lead to augmented entropy formation. This mathematical model is effective for analyzing drug transport mechanisms throughout the human body and presents extensive potential applications in the fields of biology and healthcare.

Surface Strain Measurement for Non-Intrusive Internal Pressure Evaluation of a Cannon

Abstract Recent cutting-edge designs for gun barrels, projectiles, and propellants require testing, such as measuring the internal pressure during firing. However, there are concerns with the current drilling method to mount pressure transducers near the breech and chamber of the gun barrel where pressure is highest. To address this challenge, the team hereby presents an alternative, nonintrusive strain measurement method. This method focuses on determining the feasibility and accuracy of relating tangential strain along the sidewall of a gun barrel to the drastic internal pressure rise created during combustion. A transient structural, numerical model of a 155 mm gun barrel was created using ansys. The pressure was derived using the outline in Interior Ballistics of High Velocity Guns, version 2, and the model was validated using published experimental tangential strain testing data from a gun of the same caliber. The model was then used to demonstrate the ideal location for strain measurement along the sidewall of the chamber. Furthermore, three different pressure ranges were simulated in the model. The behavior of the tangential strain in each case indicates a similar trend to the internal pressure rise and oscillation due to a dominant frequency of the barrel. A method to predict internal pressure from external tangential strain was developed. The internal pressure predicted is within 4% of the pressure applied in the model. In the sensitivity study, the thickness and elastic modulus of the gun barrel were found to be the primary factors affecting tangential strain. Overall, this work helps to understand tangential strain behavior on the sidewall of a large-caliber gun barrel and lays the ground for an accurate prediction of internal pressure from external tangential strain.

Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions

Abstract. Urban air quality is an important part of human well-being, and its detailed and precise modeling is important for efficient urban planning. In this study the potential sources of errors in large eddy simulation (LES) runs of the PALM model in stable conditions for a high-traffic residential area in Prague, Czech Republic, with a focus on street canyon ventilation, are investigated. The evaluation of the PALM model simulations against observations obtained during a dedicated campaign revealed unrealistically high concentrations of modeled air pollutants for a short period during a winter inversion episode. To identify potential reasons, the sensitivities of the model to changes in meteorological boundary conditions and adjustments of model parameters were tested. The model adaptations included adding the anthropogenic heat from cars, setting a bottom limit of the subgrid-scale turbulent kinetic energy (TKE), adjusting the profiles of parameters of the synthetic turbulence generator in PALM, and limiting the model time step. The study confirmed the crucial role of the correct meteorological boundary conditions for realistic air quality modeling during stable conditions. Besides this, the studied adjustments of the model parameters proved to have a significant impact in these stable conditions, resulting in a decrease in concentration overestimation in the range 30 %–66 % while exhibiting a negligible influence on model results during the rest of the episode. This suggested that the inclusion or improvement of these processes in PALM is desirable despite their negligible impact in most other conditions. Moreover, the time step limitation test revealed numerical inaccuracies caused by discretization errors which occurred during such extremely stable conditions.