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Ligand-decorated metal surfaces play a pivotal role in various areas of chemistry, particularly in selective catalysis. Molecular dynamics simulations at the molecular mechanics level of theory are best adapted to gain complementary insights to experiments regarding the structure and dynamics of such organic films. However, standard force fields tend to capture only weak physisorption interactions. This is inadequate for ligands that are strongly adsorbed such as carboxylates on metal surfaces. To address this limitation, we employ the Gaussian Lennard-Jones (GLJ) potential, which incorporates an attractive Gaussian potential between the surface and ligand atoms. Here, we develop this approach for the interaction between cobalt surfaces and carboxylate ligands. The accuracy of the GLJ approach is validated through the analysis of the interaction of oxygen with two distinct cobalt surfaces. The accuracy of this method reaches a root mean square deviation (RMSD) of about 3 kcal/mol across all probed configurations, which corresponds to a percentage error of roughly 4%. Application of the GLJ force field to the dynamics of the organic layer on these surfaces reveals how the ligand concentration influences the film order, and highlights differing mobility in the x and y directions, attributable to surface corrugation on Co(11 2 ̄ 0). GLJ is versatile, suitable for a broad range of metal/ligand systems, and can, subsequently, be utilized to study the organic film on the adsorption/desorption of reactants and products during a catalytic process. [ABSTRACT FROM AUTHOR]

Computational simulation of biomolecules can provide important insights into protein design, protein-ligand binding interactions, and ab initio biomolecular folding, among other applications. Accurate treatment of the solvent environment is essential in such applications, but the use of explicit solvents can add considerable cost. Implicit treatment of solvent effects using a dielectric continuum model is an attractive alternative to explicit solvation since it is able to describe solvation effects without the inclusion of solvent degrees of freedom. Previously, we described the development and parameterization of implicit solvent models for small molecules. Here, we extend the parameterization of the generalized Kirkwood (GK) implicit solvent model for use with biomolecules described by the AMOEBA force field via the addition of corrections to the calculation of effective radii that account for interstitial spaces that arise within biomolecules. These include element-specific pairwise descreening scale factors, a short-range neck contribution to describe the solvent-excluded space between pairs of nearby atoms, and finally tanh-based rescaling of the overall descreening integral. We then apply the AMOEBA/GK implicit solvent to a set of ten proteins and achieve an average coordinate root mean square deviation for the experimental structures of 2.0 Å across 500 ns simulations. Overall, the continued development of implicit solvent models will help facilitate the simulation of biomolecules on mechanistically relevant timescales. [ABSTRACT FROM AUTHOR]

We present a new program implementation of the Gaussian process regression adaptive density-guided approach [Schmitz et al., J. Chem. Phys. 153, 064105 (2020)] for automatic and cost-efficient potential energy surface construction in the MidasCpp program. A number of technical and methodological improvements made allowed us to extend this approach toward calculations of larger molecular systems than those previously accessible and maintain the very high accuracy of constructed potential energy surfaces. On the methodological side, improvements were made by using a Δ-learning approach, predicting the difference against a fully harmonic potential, and employing a computationally more efficient hyperparameter optimization procedure. We demonstrate the performance of this method on a test set of molecules of growing size and show that up to 80% of single point calculations could be avoided, introducing a root mean square deviation in fundamental excitations of about 3 cm−1. A much higher accuracy with errors below 1 cm−1 could be achieved with tighter convergence thresholds still reducing the number of single point computations by up to 68%. We further support our findings with a detailed analysis of wall times measured while employing different electronic structure methods. Our results demonstrate that GPR-ADGA is an effective tool, which could be applied for cost-efficient calculations of potential energy surfaces suitable for highly accurate vibrational spectra simulations. [ABSTRACT FROM AUTHOR]

As in the case of a free particle, the initial growth of a broad (relative to lattice spacing) wavepacket placed on an ordered lattice is slow (its time derivative has zero initial slope), and the spread (root mean square displacement) becomes linear in t at a long time. On a disordered lattice, the growth is inhibited for a long time (Anderson localization). We consider site disorder with nearest-neighbor hopping on one- and two-dimensional systems and show via numerical simulations supported by the analytical study that the short time growth of the particle distribution is faster on the disordered lattice than on the ordered one. Such faster spread takes place on time and length scales that may be relevant to the exciton motion in disordered systems. [ABSTRACT FROM AUTHOR]

Effectively modulating the thermal conductivity of materials is critical for meeting the various requirements of thermal-management devices. In this work, the influence of ionization on the phonon-transport properties of stannous oxide (SnO) was systematically investigated using first-principles calculations combined with the Boltzmann transport equation. The results show that ionization has a positive effect on the thermal conductivity of SnO, and this phenomenon can be further enhanced with increased ionization magnitude. Specifically, it was found that the thermal conductivities of SnO along the x (y) and z directions could be increased by 35%/200% and 65%/300% after the removal of four and eight electrons, respectively, from neutral SnO. The phonon mode information implies that the enhancement of thermal conductivity mainly originates from the suppression of anharmonicity in the ionized SnO. This behavior was further demonstrated by analyzing the root mean square displacement and potential-well structure. More in-depth examination suggested that the enhancement of the thermal conductivity of SnO does not originate from the ionization itself, but from the internal strain in the lattice caused by the ionization. The findings presented in this work elucidate how ionization can impact thermal conductivity, providing theoretical guidance for modulating thermal conductivity at the electron level. [ABSTRACT FROM AUTHOR]

Wave–current interaction has always been a challenging topic in fluid mechanics. The research on bimodal waves has received much more attention recently, but their evolutions influenced by underlying currents are not yet clear. This study aims to investigate the effects of co- and counter-propagating currents on spatial evolution using a fully nonlinear wave-current tank based on the high-order spectral method. The process of the wave focus is significantly shortened by the counter-propagating current, resulting in a sharper crest focus, followed by the trough focus. Concurrently, the decrease in the total envelope height and width is accelerated before wave focus and then the increase is decelerated, accompanied by a delay in the envelope profile transition from the backward-leaning to the forward-leaning. The co-propagating current exhibits the opposite phenomenon. The analysis of the spectral energy distribution aids in clarifying the variation of the envelope profile. The energy redistribution, characterized by a downshift of the frequency band, and a decreased energy distribution at the second peak, along with the slightly larger value of the root mean square frequency, indicates that the energy back-flow is obstructed by the counter-propagating current. These findings contribute to our understanding of the current effect on the focused double-wave-group, providing valuable insights for future research and applications in this field. [ABSTRACT FROM AUTHOR]

In this study, the effects of wind barriers on the crosswind environment of vehicle safety on a long-span bridge with a streamlined bridge deck were investigated at different angles of attack (AOA). The profiles of the mean and the root mean square (RMS) of the wind pressure coefficients above different traffic lanes were obtained through synchronous pressure measurements. The mean pressure fields around the bridge decks were investigated by computational fluid dynamics (CFD) simulations. The crosswind environment of vehicle safety between the deck with railings and the deck with wind barriers was compared and analyzed in detail at different AOA. The results showed that the wind barriers produce a thicker separation shear layer above the bridge deck and result in a larger negative pressure region in comparison with the case with railings. This leads to a notable reduction in the mean wind pressure coefficients above the deck. The increase in the AOA enhances the above-mentioned reduction effect. It was also found that the wind barriers significantly increase the RMS of the wind pressure coefficients above the deck compared with the railings. The increase in the AOA inhibits this enhancement effect. The results of the equivalent mean pressure coefficients show that the wind barriers reduce the vehicle sideslipping risk more effectively than the vehicle overturning risk. It was also found that the effect of the wind barriers on the reduction of the overturning risk is more sensitive to the change in AOA than the effect on the reduction of the vehicle sideslipping risk. [ABSTRACT FROM AUTHOR]

Control of combustion instability for a realistic gas-turbine combustor is challenging. This work aims to establish an efficient numerical framework for optimization to improve the combustion stability of a bluff-body combustor. Large eddy simulations of the spray combustion process are conducted, and the experimental measurements are used to evaluate the numerical accuracy of the baseline case. The air preheating temperature, the Sauter mean diameter of fuel droplets, and the location of liquid fuel injection are regarded as input variables. The root mean square of pressure amplitude is regarded as an optimization objective. The Bayesian optimization framework is proposed that includes the sampling process, surrogate model, acquisition function, and genetic algorithm optimizer processes. It is found that PRMS can be reduced by 64% for the optimized case compared to the baseline case using only 17 sample evaluations. This work is promising as it provides an effective optimization framework for the development of next-generation gas-turbine combustors. [ABSTRACT FROM AUTHOR]

In recent years, the lead-free double perovskite Cs2AgBiBr6 has emerged as an appealing alternative to lead-based perovskites due to its nontoxicity and long-term stability. In this study, we employed methyl acetate as an antisolvent and prepared high-quality Cs2AgBiBr6 films by a facile one-step spin-coating method. The prepared films exhibited excellent crystallinity with densely packed crystal grains. The root mean square roughness and average roughness of the obtained Cs2AgBiBr6 perovskite films were 6.69 and 5.43 nm, respectively. Furthermore, the memory device based on the Cs2AgBiBr6 perovskite films exhibited uniform and repeatable bipolar resistive switching performance with an ON/OFF ratio of 15, an endurance of 80 cycles, and a retention time of 104 s. This work showcases a simple and convenient one-step spin-coating method for depositing high-quality Cs2AgBiBr6 thin films while highlighting their potential application in resistive switching memories based on lead-free double perovskites. [ABSTRACT FROM AUTHOR]

In spectral-based ink content measurement, improving the accuracy of the spectral collection system and reducing the algorithm complexity of the ink content measurement model are important aspects of research. This study designs a spectral collection system with an M-type Czerny–Turner optical path structure, uses a third-order polynomial fitting method for calibration analysis, collects the spectral of the standard color card and denoises it through Savitzky–Golay convolution smoothing, and establishes a functional relationship between the spectral and the logarithm of ink content. Uninformative Variable Elimination (UVE) and Competitive Adaptive Reweighting Sampling are used to perform comparative analysis on feature wavelength extraction, and a prediction model for printing ink content is established. Experimental results show that the R2 of ink C, ink M, and ink Y are 0.9981, 0.9975, and 0.9892, respectively, and the root mean square error is 0.0134, 0.0153, and 0.0317, respectively, showing good performance in ink prediction accuracy. [ABSTRACT FROM AUTHOR]

The flow past three square cylinders of unequal size placed in an inline arrangement is studied using the lattice Boltzmann method at different Reynolds numbers [Re = (u∞ d)/ν] within the range of Re = 120, 150, 160, 175, and 200 for various gap spacings (g = s/d), ranging from 1 to 6. This study focused on the symmetric examination of flow behavior for various gap spacing within the three unequal-sized square cylinders. The main objective of this study was to investigate the effects of Reynolds numbers and gap spacing for flow structure mechanism and vortex shedding suppression in between the gap and down-stream position of all three cylinders. Results are obtained in terms of vorticity contours visualization, drag and lift coefficients, Strouhal number, and physical parameters. In vorticity contour visualization, different flow behaviors are observed, known as flow regimes, and are named according to their characteristics, and they are (i) steady flow regime, (ii) shear layer reattachment flow regime (SLR), (iii) fully developed vortex shedding flow regime, (iv) two-row fully developed vortex shedding flow regime, and (v) fully developed irregular vortex shedding flow regime. The present study also includes a discussion on aerodynamic forces, namely the mean drag coefficient (Cdmean), root mean square of the lift coefficient (Clrms), and Strouhal numbers (St) for three cylinders with sizes d = 20, d1 = 15, and d2 = 10, respectively. The maximum value of Cdmean for the first cylinder (C1) is obtained at (Re, g) = (200, 3) that is, 1.5156, where the existing flow regime is the SLR flow regime, while for C2 and C3, the maximum Cdmean values are examined at critical flow behaviors, where the existing flow regime is a fully developed irregular vortex shedding flow regime. Negative values of Cdmean are also examined for cylinders C2 and C3 at some combinations of (Re, g), attributed to the effect of thrust. Furthermore, it is noticed that the values of Strouhal number are increased with an increment in values of gap spacing. The highest value of the Strouhal number for all three cylinders is observed for C1 at (Re, g) = (120, 5), reaching 0.1556 along with a two-row fully developed flow regime. Furthermore, it is investigated from the present problem that the position of unequal sized square cylinders strongly influenced the flow structure mechanism. The information found and discussed in this study could be effective for structure designing arrangement in the case of three square cylinders of unequal size placed in a horizontal arrangement. [ABSTRACT FROM AUTHOR]

Atmospheric temperature is fundamental information for various industries, such as production, life, and scientific research. The temperature error induced by the solar rays can reach 1 °C or even higher. A hemispherical shell-shaped atmospheric temperature measuring instrument that can reduce heat pollution and increase air velocity was designed. First, the instrument was optimized using computational fluid dynamics (CFD) software packages. Then, the CFD software packages were employed to quantify the temperature errors of the instrument with varying situations. A neural network model was employed to develop a temperature error correction model that can be targeted for multi-variable changes. This model provides accurate correction data when the influencing factors change continuously. Finally, field experiments were performed. The experimental data analysis indicates that the mean temperature error and the maximum error of the instrument before correction are 0.08 and 0.25 °C, respectively. The root mean square error, the mean absolute error, and the correlation coefficient between measured temperature errors from experiments and corrected temperature errors from the correction model are 0.099, 0.016, and 0.952 °C, respectively. By utilizing a temperature error correction model, the measuring error of the instrument can be minimized to a range between −0.05 and 0.04 °C. Consequently, the instrument is anticipated to enhance temperature measurement accuracy to ∼0.1 °C. [ABSTRACT FROM AUTHOR]

Solvent effects are notoriously difficult to describe for metallic nanoparticles (NPs). Here, we introduce GAL21 which is the first pairwise additive force field that is specifically designed to modulate the near chemisorption energy of water as a function of the coordination numbers of the metallic atoms. We find a quadratic dependence to be most suitable for capturing the dependence of the adsorption energy of water on the generalized coordination number (GCN) of the metal atoms. GAL21 has been fitted against DFT adsorption energies for Cu, Ag, Au, Ni, Pd, Pt, and Co on 500 configurations and validated on about 3000 configurations for each metal, constructed on five surfaces with GCNs varying from 2.5 to 11.25. Depending on the metals, the root mean square deviation is found between 0.7 kcal mol−1 (Au) to 1.6 kcal mol−1 (Ni). Using GAL21, as implemented in the open-source code CP2K, we then evaluate the solvation energy of Au55 and Pt55 NPs in water using thermodynamic integration. The solvation free energy is found to be larger for Pt than for Au and systematically larger than 200 kcal mol−1, demonstrating the large impact of solvent on the surface energetics of NPs. Still, given that the amorphous NPs are both, the most stable and the most solvated ones, we do not predict a change in the preferred morphology between the gas-phase and in water. Finally, based on a linear regression on three sizes of NPs (from 38 to 147), the solvation energy for Au and Pt surface atoms is found to be −5.2 and −9.9 kcal mol−1, respectively. [ABSTRACT FROM AUTHOR]

This article presents a new reactive potential in the ReaxFF formalism. It aims to include the chlorine element and opens up the fields of use of ReaxFF to the whole class of organochloride compounds including conjugated or aromatic groups. Numerous compounds in this family raise global awareness due to their environmental impact, and such a reactive potential will help investigate their degradation pathways. The new force field, named CHONCl-2022_weak, belongs to the aqueous branch. The force field parameters were fitted against high-level quantum chemistry calculations, including complete active space self-consistent field/NEVPT2 calculations and density functional theory calculations, and their accuracy was evaluated using a validation set. The root means square deviation against quantum mechanics energies is 0.38 eV (8.91 kcal mol−1). From a structural point of view, the root means square deviation is about 0.06 Å for the bond lengths, 11.86° for the angles, and 4.12° for the dihedral angles. With CHONCl-2022_weak new force field, we successfully investigated the regioselectivity for nucleophilic or electrophilic attacks on polychlorinated biphenyls, which are toxic and permanent pollutants. The rotation barriers along the bond linking the two benzene rings, which is crucial in the toxicity of these compounds, are well reproduced by CHONCl-2022_weak. Then, our new reactive potential is used to investigate the chlorobenzene reactivity in the presence of hydroxyl radicals in atmospheric condition or in aqueous solution. The reaction pathways computed with ReaxFF agree with the quantum mechanics results. We showed that, in the presence of dioxygen molecules, in atmospheric condition, the oxidation of chlorobenzene likely leads to the formation of highly oxygenated compounds after the abstraction of hydrogen radicals. In water, the addition of a hydroxyl radical leads to the formation of chlorophenol or phenol molecules, as already predicted from plasma-induced degradation experiments. [ABSTRACT FROM AUTHOR]

We introduce a perturbative approximation to the combined density functional theory and multireference configuration interaction (DFT/MRCI) approach. The method, termed DFT/MRCI(2), results from the application of quasi-degenerate perturbation theory (QDPT) and the Epstein–Nesbet partitioning to the DFT/MRCI Hamiltonian matrix. The application of QDPT obviates the need to diagonalize the large DFT/MRCI Hamiltonian; electronic energies are instead obtained as the eigenvalues of a small effective Hamiltonian, affording an orders of magnitude savings in the computational cost. Most importantly, the DFT/MRCI(2) approximation is found to be of excellent accuracy, furnishing excitation energies with a root mean squared deviation from the canonical DFT/MRCI values of less than 0.03 eV for an extensive test set of organic molecules. [ABSTRACT FROM AUTHOR]

Centrifugal pumps are important equipment in industrial production. At present, vibration signals are often used to diagnose cavitation in centrifugal pumps, but the vibration signals are easy to be disturbed and the fault characteristics are unstable to be detected. In this paper, a single stage centrifugal pump is taken as the study object, and the vibration signals of various parts of the centrifugal pump cavitation state are collected under different flow conditions. The short-time Fourier transform and one-third octave analysis are performed on the filtered signals, and the characteristic frequency of cavitation and the energy near the characteristic frequency with the development of cavitation are obtained. Based on vibration signals, the vibration root mean square (rms) and kurtosis values of different cavitation states are obtained. Flow state, kurtosis, and rms are used as input variables in the double-layer backpropagation neural network model to identify and classify the cavitation states of centrifugal pumps. The results show that the trained neural network model can accurately identify and classify the cavitation state of the centrifugal pump under the conditions of low flow rate, rated flow rate, and large flow rate, and the accuracy is more than 99.5%. This study provides a new technique for diagnosing cavitation in centrifugal pumps. [ABSTRACT FROM AUTHOR]

Scale-adaptive simulations (SAS) of three-dimensional flow around a circular cylinder fitted with a passive version of a novel flow control method (passive Venturi actuator, PVA) are performed at a diameter-based Reynolds number of Re = 28 000. The PVA consists of one or more narrow slits located at the top and/or bottom sides of the cylinder that connected to the throat of the axial Venturi slit in this cylinder. The main purpose of the study is to investigate the influence of divergence angle and narrow slit location relative to the axial Venturi slit on the aerodynamic performance of the cylinder. To this end, four models were designed with various PVAs. Additional models, a plain cylinder (unmodified model) and a cylinder fitted with an axial Venturi slit (model without a narrow slit), were also used for quantitative comparison. SAS predicts that an additional 5% reduction in the time-averaged drag coefficient, ⟨ C D ⟩ , was observed when two narrow slits located on the surface at an angle of ±80° from the front stagnation line were fitted to the cylinder with an axial Venturi slit. Reducing the divergence angle of the PVA leads to improvements in ⟨ C D ⟩ and root mean square of fluctuating force coefficients, C D − rms and C L − rms . It is found that a cylinder with a PVA that has two narrow slits and a divergence angle of 6° can produce a 28.6% reduction in ⟨ C D ⟩ , a 58.5% reduction in C D − rms , and an 81.2% reduction in C L − rms , when compared to the plain cylinder. [ABSTRACT FROM AUTHOR]

The role to which a realistic inflow turbulent boundary layer (TBL) influences transient and mean large-scale pool fire quantities of interest (QoIs) is numerically investigated. High-fidelity, low-Mach large-eddy simulations that activate low-dissipation, unstructured numerics are conducted using an unsteady flamelet combustion modeling approach with mutiphysics coupling to soot and participating media radiation transport. Three inlet profile configurations are exercised for a large-scale, high-aspect rectangular pool that is oriented perpendicular to the flow direction: a time-varying, TBL inflow profile obtained from a periodic precursor simulation, the time-mean of the transient TBL, and a steady power-law inflow profile that replicates the mean TBL crosswind velocity of 10.0 m/s at a vertical height of 10 m. Results include both qualitative transient flame evolution and quantitative flame shape with ground-level temperature and convective/radiative heat flux profiles. While transient fire events, which are driven by burst-sweep TBL coupling, such as blow-off and reattachment are vastly different in the TBL case (contributing to increased root mean square QoI fluctuation prediction and disparate flame lengths), mean surface QoI magnitudes are similar. Quadrant analysis demonstrates that the TBL configuration modifies burst-sweep phenomena at windward pool locations, while leeward recovery is found. Positive fluctuations of convective heat flux correlate with fast moving fluid away from the pool surface due to intermittent combustion events. [ABSTRACT FROM AUTHOR]

We employ molecular flow methods to numerically simulate the supersonic nanoparticles flow in free-molecule regime. To streamline the computational complexity, interaction forces between the gas and solid particles are disregarded. We first develop a discrete phase model (DPM) method that integrates the non-rigid body collision model, enabling an accurate simulation of nanoparticle diffusion under the influence of the drag force and Brownian motion force. The nanoparticles considered in this study have sizes below 10 nm, and the accuracy of the DPM method is verified by comparing its results with experimental data. Subsequently, we theoretically and numerically investigate the transmission probability and number density of N2 molecules flowing through two-dimensional (2D) channels and three-dimensional (3D) tubes by using the angular coefficient (AC) method and the direct simulation Monte Carlo (DSMC) method. The findings indicate that as the diameter of the nanoparticle (dp) decreases to 1 nm, the diffusion coefficient (D) and the root mean square displacement (x) of nanoparticles approach the N2 molecules. The microscopic velocity of most N2 molecules falls within the range of 62–1400 m/s, and the macroscopic velocity of N2 flow falls within the range of Ma = 1.28–1.35. In contrast to the DSMC method, the AC method exhibits enhanced accuracy even with a reduced number of grids and obviates the process for large-scale sampling. Additionally, the solution time required by the AC method is approximately 1/10 and 1/13–1/32 of the DSMC method in 3D cylindrical tubes and 2D channels, respectively. Moreover, the AC method demonstrates superior adaptability when dealing with complex geometries. [ABSTRACT FROM AUTHOR]

The aerodynamic characteristics, flow fields, and flow patterns of the flow around an elliptic cylinder are investigated in this paper using large eddy simulation (LES). The Reynolds number (Re) is fixed at 16 000 in the subcritical regime, and the aspect ratio (AR) of the elliptic cylinder is varied from 0.6 to 1.4 with an increment of 0.2. The numerical model applied is initially validated for the case of AR = 1, showing good agreement with previous studies. The numerical results indicate that both the mean drag coefficient and the root mean square of lift coefficient of the elliptic cylinder decrease with increasing AR. The total drag is decomposed into two components: it indicates that the pressure drag is dominant. The primary separation point of the elliptic cylinder shifts backward with increasing AR within the range of 86.4 ° – 92.3 °. The flow fields are analyzed in detail through the time-averaged velocity profiles along three different axes. Additionally, the two-dimensional (2D) and three-dimensional (3D) visualizations of the wake patterns are also provided to show the different vortex shedding mode and the characteristics of vortex structure for different ARs. This study supplements the basic aerodynamic parameters and details of the flow around an elliptic cylinder and discusses the influence of AR at a moderate Re in the subcritical regime and has a certain significance for further optimization of the simplified model of the human body for efficient aerodynamic testing of sport garments. [ABSTRACT FROM AUTHOR]

Detection of combustion instability is crucial for the safety and reliability of gas turbines. In this paper, the recurrence quantification analysis (RQA) and multi-fractal analysis (MFA) methods are applied to investigate the transition process from combustion noise to combustion instability in an industrial-scale combustor. Based on the dynamic pressure (DP) obtained from high pressure and high temperature tests, a novel method is proposed to construct early detection indicators (EDI) of combustion instability. The method is mainly based on the three-dimensional map of the recurrence rate, Hurst exponent, and root mean square ratio. A regression method and SVM are applied to define the classification boundary. For three test cases, the results showed that the proposed EDI can effectively detect the onset of combustion instability. Compared to the conventional method based on the root mean square levels of dynamic pressure, the EDI has capability to forecast the onset of combustion instability approximately a few hundred milliseconds in advance. [ABSTRACT FROM AUTHOR]

Stability in a Mach 4.5 boundary layer over backward-facing steps (BFSs) is investigated using numerical methods. Two types of cases are considered with different laminar inflow conditions, imposed with single-frequency or broadband-frequency modes, respectively. Compared with the typical K-type transition over a flat plate, the boundary layer transition initiated by 90 kHz-frequency second mode appears to follow the same pattern but with a noticeable delay over the step. A larger step height leads to a better inhibition of the downstream Λ-vortices and thus a later transition, providing the step height is smaller than the local boundary layer thickness. Moreover, both the frequency weighted power spectral density and the root mean square of the streamwise velocity indicate the presence of Kelvin–Helmholtz (K–H) instability when the step height is equivalent to the thickness of the nearby boundary layer. There may exist an optimal step height for suppressing single-frequency (90 kHz) mode without exciting significant K–H modes. Similar to the previous studies on roughness, BFS can act as an amplifier for the low-frequency second modes and a suppressor for the high-frequency second modes. The critical frequency is equal to that of the unstable mode whose synchronization point is exactly located at the step corner. Additionally, the correction effects of the step induce the change of the phase speed of the fast mode, which correspondingly results in the movement of the synchronization point. Generally, the BFS is not able to completely alleviate the transition initiated by the broadband-frequency second modes but can still delay the boundary layer transition in a certain degree by suppressing the high-frequency unstable waves. [ABSTRACT FROM AUTHOR]

Numerical simulations are conducted to analyze flow characteristics around two tandem sharp-edged cylinders with cross sections of square ( b 1 * = 1) for the upstream cylinder and rectangle ( b 2 *) for the downstream cylinder (b * = b / a , where a and b are the sides of the cylinder). This study investigates the effects of Reynolds numbers (Re = 30–150), cross-sectional aspect ratios of the downstream cylinder ( b 2 * = 1 – 4) , and scaled gap-spacing between cylinders ( S * = 1–6) on the flow structure, onset of vortex shedding, hysteresis, and aerodynamic parameters (such as drag coefficient, Strouhal number, root mean square lift and drag coefficients, and so on). The results reveal that increasing b 2 * suppresses the vortex shedding of the upstream cylinder, depending on S * . The suppression is attributed to the interference effect and the adhesion of the shear layers on the downstream cylinder. Three distinct time-mean flow patterns are identified based on the separation and reattachment of shear layers. Flow pattern Ι exhibits parallel flow along the side faces of the upstream cylinder, while the separation bubbles associated with reattachment points are formed in flow pattern II on these faces. For pattern III, no reattachment point is observed, and the separation bubbles cover the upstream cylinder' side faces. Additionally, two instantaneous flow patterns of extended-body and co-shedding are apperceived within the ranges of examined Re and S * . The behaviors of time-mean and varying forces as well as the vortex shedding frequency are correlated with the flow structures. The onset of vortex shedding and hysteresis dependence is discussed comprehensively. The results show that the critical Reynolds numbers for the onset of vortex shedding decrease from 127.5 ± 2.5 to 49.5 ± 2.5 with S * increasing from 1 to 6 ( b 1 * = 1 and b 2 * = 4). The hysteresis limit is found within the range of 3.5 ≤ S * ≤ 4.5 for flow over two tandem cylinders ( b 1 * = 1 and b 2 * = 4) at Re = 150. [ABSTRACT FROM AUTHOR]

Direct numerical simulation combined with a one-way coupled Lagrangian particle tracking technique is employed to investigate dilute particle-laden turbulent flows in open square ducts with a free surface. The focus is on examining the influence of the mean cross-stream secondary flow on particle transport near the wall, free surface, and across the duct cross section. Based on the duct half-width and mean friction velocity, a shear Reynolds number of Reτ = 300 is considered, with the corresponding particle Stokes numbers ranging from St+ = 0.31 to 260. The results reveal that particle concentration near the sidewalls is lower than that near the bottom wall, and the minimum particle concentration is observed at the free surface. Along the bottom wall centerline orientated upward, particle concentration gradually decreases. An exception to this is in the vicinity of the free surface where a slight increase is observed for the heavier particles (St+ ≥ 25), and the amplitude of this increase gradually declines as the Stokes number increases. In the streamwise direction near the free surface, heavier particles tend to preferentially concentrate in regions where the instantaneous transverse secondary flow velocity is negative. As the Stokes number increases, the position of the maximum streamwise velocity for heavier particles is closer to the free surface, and the rotation centers of inner and outer secondary particle motions gradually disappear. The streamwise root mean square velocity for the lightest St+ = 0.31 particles is higher than that for particles with higher inertia in the middle region of the free surface. [ABSTRACT FROM AUTHOR]

Four-dimensional flow magnetic resonance imaging (4D flow MRI) offers a powerful tool for visualizing fluid flows, critical for both diagnosing cardiovascular diseases and analyzing engineering fluid dynamics. Despite its potential in medical research, the clinical applicability of 4D flow MRI often faces challenges due to inherent noise. To mitigate this, we introduce the split-and-overlap singular value decomposition (SOSVD) filter, a distinctive noise reduction approach. Unlike traditional singular value decomposition methods, the SOSVD filter partitions the primary data matrix into overlapping subdomains and then applies singular value decomposition to each subdomain, preserving only the dominant mode for noise attenuation. Evaluations on simulated and experimental flow data within a square duct revealed a significant decrease in root mean square noise metrics. Moreover, when applied to in vivo aortic data, the SOSVD filter enhanced various flow determinants, including divergence, velocity gradients, streamlines, and velocity coherence. Thus, the SOSVD method presents a promising avenue for augmenting noise reduction in 4D flow MRI, potentially elevating diagnostic accuracy and enriching cardiovascular disease research. [ABSTRACT FROM AUTHOR]

We use a novel experimental setup to obtain the vertical velocity and acceleration statistics of snowflakes settling in atmospheric surface-layer turbulence, for Taylor microscale Reynolds numbers (R e λ ) between 400 and 67 000, Stokes numbers (St) between 0.12 and 3.50, and a broad range of snowflake habits. Despite the complexity of snowflake structures and the non-uniform nature of the turbulence, we find that mean snowflake acceleration distributions can be uniquely determined from the value of St. Ensemble-averaged snowflake root mean square (rms) accelerations scale nearly linearly with St. Normalized by the rms value, the acceleration distribution is nearly exponential, with a scaling factor for the (exponent) of −3/2 that is independent of R e λ and St; kurtosis scales with R e λ , albeit weakly compared to fluid tracers in turbulence; gravitational drift with sweeping is observed for St < 1. Surprisingly, the same exponential distribution describes a pseudo-acceleration calculated from fluctuations of snowflake terminal fall speed in still air. This equivalence suggests an underlying connection between how turbulence determines the trajectories of particles and the microphysics determining the evolution of their shapes and sizes. [ABSTRACT FROM AUTHOR]

A superconducting magnet with a warm-bore size of 800 mm and a center magnetic field of 9.4 T for the whole-body magnetic resonance imaging (MRI) system was developed in IEECAS, China. To achieve a highly homogeneous magnetic field over the 400 mm diameter of spherical volume (DSV), both active shimming and passive shimming techniques were employed. This paper mainly focuses on the implementation of passive shimming for the 9.4 T MRI magnet system. After four iterations, we were able to achieve peak-to-peak and root mean square field homogeneities over the DSV at 3.05 and 0.94 ppm, respectively. In addition, this paper analyzes the electromagnetic forces and system errors of passive shimming for ultra-high fields, providing valuable insights into MRI magnet engineering. [ABSTRACT FROM AUTHOR]

In developing solid-state nanopore sensors for single molecule detection, comprehensive evaluation of the nanopore quality is important. Existing studies typically rely on comparing the noise root mean square or power spectrum density values. Nanopores exhibiting lower noise values are generally considered superior. This evaluation is valid when the single molecule signal remains consistent. However, the signal can vary, as it is strongly related to the solid-state nanopore size, which is hard to control during fabrication consistently. This work emphasized the need to report the baseline current for evaluating solid-state nanopore sensors. The baseline current offers insight into several experimental conditions, particularly the nanopore size. Our experiments show that a nanopore sensor with more noise is not necessarily worse when considering the signal-to-noise ratio (SNR), particularly when the pore size is smaller. Our findings suggest that relying only on noise comparisons can lead to inaccurate evaluations of solid-state nanopore sensors, considering the inherent variability in fabrication and testing setups among labs and measurements. We propose that future studies should include reporting baseline current and sensing conditions. Additionally, using SNR as a primary evaluation tool for nanopore sensors could provide a more comprehensive understanding of their performance. [ABSTRACT FROM AUTHOR]

We report a Sagnac-type source based on a MgO:PPLN non-linear crystal pumped with a 532 nm continuous-wave laser, which generates spectrally non-degenerate, polarization-entangled photon pairs of 785 nm signal and 1651 nm idler wavelength, via the type-0 spontaneous parametric downconversion (SPDC) process. We use standard off-the-shelf components; hence, no custom-designed multi-wavelength polarization optics are required. At the same time, long-term phase stability can be achieved due to the geometry of our Sagnac-type design. The source's brightness is 6.17 (4) × 10 6 pairs/sec/mW, which is comparable to the brightest state-of-the-art non-degenerate polarization-entangled photon-pair source. The spectral bandwidth of the single photon is approximately 195 GHz (root mean square). The fidelity of the entangled state is measured to be 96.72 (1) % , the concurrence is 94.7 (2) % , and the Bell-CHSH value S = 2.71 (6). This source has the potential to be applied in long-distance quantum communication using both free-space and fiber links simultaneously. [ABSTRACT FROM AUTHOR]

Sorting of materials at different stages of manufacturing processes is very important to ensure the final product quality. In this paper, the machine learning algorithms are used on the magnetic Barkhausen emission (MBE) signals for the classification of martensitic stainless-steel specimens, which are subjected to different heat treatments. The variation in MBE parameters, such as root mean square, peak height, peak position, and full width at half maximum, was found to be marginal for normalized and quenching and partitioned specimens even though their x-ray diffraction analysis showed distinct microstructural conditions. The conventional MBE parameters are used to train the machine learning models. The performance of decision tree and ensemble learning techniques, such as Bagging, Random Subspace, AdaBoost, RUSBoost, Total Boost, and LP Boost classifiers, is compared and found that the AdaBoost classifier provides the maximum accuracy of 98% in the classification of complex materials. The results showed that the machine learning approach using a limited number of features is sufficiently sensitive toward the classification of specimens that are otherwise indistinguishable in their conventional MBE response. [ABSTRACT FROM AUTHOR]

Many isothermal equations of state lead to numerical problems under tension conditions due to negative bulk modulus. We summarize the properties of four existing models and devise a continuous non-piecewise reference curve to address this issue. The final functional form contains three fitting parameters that are directly related to the bulk modulus and its pressure derivative at the reference state and at infinite pressures. We also include bounds that guarantee the monotonicity of its pressure derivative in all volume space. To demonstrate the qualitative features of each isotherm, we conduct calibrations against experimental data for cyclotetramethylene tetranitramine, magnesium oxide, gold, and platinum. Pressure residuals and root mean square deviations show that the proposed functional form is capable of adequately fitting the data compared to other three-parameter models. [ABSTRACT FROM AUTHOR]

In response to the need for efficient, small-scale power sources for applications such as ocean observation and navigation, this paper presents the design, modeling, fabrication, testing, and analysis of a compact point-absorber wave energy converter (PAWEC) equipped with a mechanical direct-drive power takeoff (PTO) mechanism. The motivation is to address the mismatch between the natural frequencies of conventional PAWECs and dominant ocean wave frequencies, which limits energy capture. The primary objective is to enhance the efficiency of small-scale wave energy converters (WEC) without increasing the buoy size. To achieve this, we introduce a novel design element: an added mass plate (AMP) attached to the buoy. The AMP is devised to increase the WEC added mass and natural period, thereby aligning its natural frequency with dominant ocean wave frequencies. In our case study of a scaled model (1:2.2), the AMP effectively doubled the added mass of the WEC and increased its natural period by 32%. The WEC incorporates a rack and pinion mechanical motion rectifier-type PTO to convert the heave oscillations of the buoy into unidirectional rotation. The scaled model was tested in a wave basin facility with regular waves at zero angle of incidence. The WEC with AMP achieved a maximum root mean square power of 9.34 W, a nearly 30% increase compared to the conventional configuration without AMP, which produced 7.12 W under similar wave conditions. Numerical analysis using the boundary element method in the frequency domain for regular waves confirmed these findings. Finally, it has been derived that the proposed WEC, equipped with an AMP, offers enhanced efficiency in longer wave periods without the need for a larger buoy, establishing its viability as a power source for navigational buoys. This paper also offers a comprehensive guide to experimental techniques for characterizing a PAWEC in a laboratory setting, contributing valuable insights into the wave energy community. [ABSTRACT FROM AUTHOR]

To improve the performance and efficiency of ordinary galloping energy harvesters (GEHs), this paper proposes a GEH with a striped bluff body. The fluid-structure coupling simulation of the bluff body and the oscillator of the energy harvester was carried out using COMSOL Multiphysics. The cloud diagram in the flow field, tip displacement at the tip of the beam, lifting and dragging force, and trace and frequency response of the harvester are analyzed. Simulation results show that the GEH with a striped bluff body has the characteristics of rising frequency and falling peak compared with the ordinary GEH, which can be locked at a fixed peak to form a stable periodic response. Experimental results show that the striped bluff body energy harvester displays better energy harvest performance. The output root mean square voltage can be increased by 119.2% at 2 m/s wind speed, which means that the galloping harvester with a striped bluff body has more stable dynamic characteristics and shows better energy harvest performance. [ABSTRACT FROM AUTHOR]

Three reduced order models are evaluated in their capacity to predict the future state of an unsteady chaotic flow field. A spatially fully developed flow generated in a random packing of cylinders at a solid fraction of 0.1 and a nominal Reynolds number of 50 is investigated. For deep learning (DL), convolutional autoencoders are used to reduce the high-dimensional data to lower dimensional latent space representations of size 16, which were then used for training the temporal architectures. To predict the future states, two DL based methods, long short-term memory and temporal convolutional neural networks, are used and compared to the linear dynamic mode decomposition (DMD). The predictions are tested in their capability to predict the spatiotemporal variations of velocity and pressure, flow statistics such as root mean squared values, and the capability to predict fluid forces on the cylinders. Relative errors between 15% and 20% are evident in predicting instantaneous velocities, chiefly resulting from phase differences between predictions and ground truth. The spatial distribution of statistical second moments is predicted to be within a maximum of 5%–10% of the ground truth with mean error in the range of 1%–2%. Using the predicted fields, instantaneous fluid drag force predictions on individual particles exhibit a mean relative error within 20%, time-averaged drag force predictions to within 5%, and total drag force over all particles to within 1% of the ground truth values. It is found that overall, the non-linear DL models are more accurate than the linear DMD algorithm for the prediction of future states. [ABSTRACT FROM AUTHOR]

A computational study of the blood flow in a stenosed microvessel is presented using coupled discrete ghost-cell and continuous-forcing immersed boundary methods. This study focuses on studying platelet behaviors near the stenosis with deformable red blood cells (RBCs). The influence of varying hematocrit, area blockage, stenosis shape, and driving force on flow characteristics, RBCs, and particle behaviors is considered. Distinct flow characteristics are observed in stenosed microvessels in the presence of RBCs. The motion of RBCs is the major cause of time-dependent oscillations in flow rates, while the contribution of particles to the fluctuations is negligible. However, this effect decreases when the stenosis is elongated in the axial direction. Interestingly, as the hematocrit level increases, downstream particles move closer to the vessel wall due to the enhanced shear-induced lift force resulting from the interaction among RBCs and particles. Furthermore, it is observed that geometrical changes in the stenosis have a more significant impact on the axial profile of particle concentration compared to changes in hematocrit or driving force. An asymmetric stenosis leads to asymmetric profiles in the flow velocity and the distribution of cells and particles due to the geometric focusing effect of the stenosis. There is no significant change in flow rates until a blockage of 0 % – 50 % , but a sudden increase in the root mean square of flow rates occurs at an 80% blockage. This study contributes to our understanding of the rheological behaviors of RBCs and rigid particles in a stenosed microvessel under various hemodynamic conditions. [ABSTRACT FROM AUTHOR]