Boundary Conditions Research Articles

Treatment of asymptotic non-adiabatic couplings with higher order reprojection method in the diabatic representation.

The problem of asymptotic non-adiabatic couplings in heavy particle collisions is treated using the reprojection method. The mixing matrix that mixes the asymptotic solutions of the coupled states to obtain appropriate boundary conditions is here derived to second order, yielding a faster convergence of the cross section. In addition, the reprojection method is implemented in a diabatic representation and applied to inelastic scattering of Li + Na and H + H collisions and to mutual neutralization in H+ + H- collisions.

Kiphynet: an online network simulation tool connecting cellular kinetics and physiological transport.

Human metabolism is sustained by functional networks that operate at diverse scales. Capturing local and global dynamics in the human body by hierarchically bridging multi-scale functional networks is a major challenge in physiological modeling. To develop an interactive, user-friendly web application that facilitates the simulation and visualization of advection-dispersion transport in three-dimensional (3D) microvascular networks, biochemical exchange, and metabolic reactions in the tissue layer surrounding the vasculature. To help modelers combine and simulate biochemical processes occurring at multiple scales, KiPhyNet deploys our discrete graph-based modeling framework that bridges functional networks existing at diverse scales. KiPhyNet is implemented in Python based on Apache web server using MATLAB as the simulator engine. KiPhyNet provides the functionality to assimilate multi-omics data from clinical and experimental studies as well as vascular data from imaging studies to investigate the role of structural changes in vascular topology on the functional response of the tissue. With the network topology, its biophysical attributes, values of initial and boundary conditions, parameterized kinetic constants, biochemical species-specific transport properties such as diffusivity as inputs, a user can use our application to simulate and view the simulation results. The results of steady-state velocity and pressure fields and dynamic concentration fields can be interactively examined. KiPhyNet provides barrier-free access to perform time-course simulation experiments by building multi-scale models of microvascular networks in physiology, using a discrete modeling framework. KiPhyNet is freely accessible at http://pallab.cds.iisc.ac.in/kiphynet/ and the documentation is available at https://deepamahm.github.io/kiphynet_docs/ .

Computational insights into the structure and decomposition behaviors of 2,4,6-triamino-5-nitropyrimidine-1,3-dioxide under high pressure up to 10 GPa.

Inspired by the recent successful synthesis of the energetic compound 2,4,6-triamino-5-nitropyrimidine-1,3-dioxide (ICM-102), which displayed a good balance between high energy and sensitivity, the response of the structure and decomposition behaviors of ICM-102 to high pressure was systematically investigated using first principle calculations. ICM-102 exhibited a graphite-like layer structure, with the c-axis and the a-axis mainly contributing to the distance between the molecular planes. As the pressure increased from 1atm to 10 GPa, this distance decreased from 3.166 to 2.689 Ǻ. The hydrogen bonds had the most contribution to the non-covalent interactions within the same molecular planes, resulting in the b-axis discontinuity. However, van der Waals interactions gradually appeared between molecular planes as the pressure increased to 2.5 GPa. Based on the analysis of crystal orbitals, the distribution of π bonds and the Laplacian bond order (LBO), it was determined that the generation mechanism of H2O molecules involved the cleavage of N-Oc (coordinated oxygen atoms), followed by intermolecular hydrogen transfer reactions, and ultimately the formation of H2O molecules through competition with H atoms in the amino groups within the same molecules. More importantly, the pressure dependence of LBO values for N-Oc revealed that high pressure could inhibit the ICM-102 decomposition process due to reinforcing hydrogen bonds and van der Waals interactions. This work will deepen our understanding of the stability of ICM-102 under high pressure and provide a helpful reference for its potential detonation applications. All simulations, including geometry optimization and vibration analysis under quasi-hydrostatic pressure, were conducted using the CP2K code. The PBE function and the Goldk-Teter-Hutter (GTH) pseudopotential with the double-ζ-with-polarization (DZVP) basis set were employed. Additionally, the semiempirical dispersion correction D3 (BJ) was used to account for the intermolecular dispersion force. The simulations were performed under periodic boundary conditions, with a finest grid level cutoff set to 400 Ry for the Γ point. The Broyden-Flecher-Goldfarb-Shanno (BFGS) optimization method was used, with tighter convergence criteria applied for the subsequent calculations of infrared spectra. Finally, the wave-function analysis, such as non-covalent interaction and LBO, was conducted using the Multiwfn and VMD packages.

Layered Heterostructure of Graphene and TiO2 as a Highly Sensitive and Stable Photoassisted NO2 Sensor.

As an atomically thin electric conductor with a low density of highly mobile charge carriers, graphene is a suitable transducer for molecular adsorption. In this study, we demonstrate that the adsorption properties can be significantly enhanced with a laser-deposited TiO2 nanolayer on top of single-layer CVD graphene, whereas the effective charge transfer between the TiO2-adsorbed gas molecules and graphene is retained through the interface. The formation of such a heterostructure with optimally a monolayer thick oxide combined with ultraviolet irradiation (wavelength 365 nm, intensity <1 mW/mm2) dramatically enhances the gas-sensing properties. It provides an outstanding sensitivity for detecting NO2 in the range of a few ppb to a few hundred ppb-s in air, with response times below 30 s at room temperature. The effect of visible light (436 and 546 nm) was much weaker, indicating that the excitations due to light absorption in TiO2 play an essential role, while the characteristics of gas responses imply the involvement of both photoinduced adsorption and desorption. The sensing mechanism was confirmed by theoretical simulations on a NO2@Ti8O16C50 complex under periodic boundary conditions. The proposed sensor structure has significant additional merits, such as relative insensitivity to other polluting gases (CO, SO2, NH3) and air humidity, as well as long-term stability (>2 years) in ambient air. The results pave the way for an emerging class of gas sensor structures based on stacked 2D materials incorporating highly charge-sensitive transducer and selective receptor layers.

Numerical study of laser-induced cavitation bubble with consideration of chemical reactions

Cavitation generated during injector jetting can significantly affect fuel atomization. Laser-induced cavitation bubble is an important phenomenon in laser induced plasma ignition technology. Limited by the difficulties in experimental measurements, numerical simulations have become an important tool in the study of laser-induced cavitation bubble, but most previous numerical models used to study the dynamics of laser-induced cavitation bubble usually ignore the effect of chemical reactions. In this study, the finite volume method is used to solve the compressible two-dimensional reynolds averaged Navier–Stokes equation by considering the heat and mass transfer as well as the chemical reactions within the cavitation bubble. The effects of overall reaction and elementary reactions on the cavitation bubble are evaluated, respectively. It is found that by additionally considering chemical reactions within the numerical model, lower maximum temperatures and higher maximum pressures are predicted within the bubble. And the generated non-condensable gases produced by the chemical reactions enhance the subsequent expansion process of the cavitation bubble. Besides, the effect of the one-sided wall boundary condition on cavitation bubble is compared with the infinite boundary condition. Influenced by the wall boundary, the cavitation bubble forms a localized high pressure on the side of the bubble away from the wall during the collapse process, which causes the bubble to be compressed into a ”crescent” shape. The maximum pressure and temperature inside the bubble are lower due to localized losses caused by the wall.

On quasi-linear reaction diffusion systems arising from compartmental SEIR models

The global existence and boundedness of solutions to quasi-linear reaction-diffusion systems are investigated. The system arises from compartmental models describing the spread of infectious diseases proposed in Viguerie et al. (Appl Math Lett 111:106617, 2021); Viguerie et al. (Comput Mech 66(5):1131–1152, 2020), where the diffusion rate is assumed to depend on the total population, leading to quasilinear diffusion with possible degeneracy. The mathematical analysis of this model has been addressed recently in Auricchio et al. (Math Methods Appl Sci 46:12529–12548, 2023) where it was essentially assumed that all sub-populations diffuse at the same rate, which yields a positive lower bound of the total population, thus removing the degeneracy. In this work, we remove this assumption completely and show the global existence and boundedness of solutions by exploiting a recently developed Lp\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L^p$$\\end{document}-energy method. Our approach is applicable to a larger class of systems and is sufficiently robust to allow model variants and different boundary conditions.

Unveiling the impact of the congruence between artificial intelligence and explorative learning on supply chain resilience

PurposeDrawing upon socio-technical system theory, this study intends to investigate the effects of the congruence and incongruence between artificial intelligence (AI) and explorative learning on supply chain resilience as well as the moderating role of organizational inertia.Design/methodology/approachUsing survey data collected from 170 Chinese manufacturing firms, we performed polynomial regression and response surface analyses to test our hypotheses.FindingsWe find that the congruence between AI and explorative learning enhances firms’ supply chain resilience, while the incongruence between these two factors impairs their supply chain resilience. In addition, compared with low–low congruence, high–high congruence between AI and explorative learning improves supply chain resilience to a greater extent. Moreover, organizational inertia attenuates the positive influence of the congruence between AI and explorative learning on supply chain resilience, while it aggravates the negative influence of the incongruence between these two factors on supply chain resilience.Originality/valueOur study expands the literature on supply chain resilience by demonstrating that the congruence between a firm’s AI (i.e. technical aspect) and explorative learning (i.e. social aspect) boosts its supply chain resilience. More importantly, our study sheds new light on the role of organizational inertia in moderating the congruent effect of AI and explorative learning, thereby extending the boundary condition for socio-technical system theory in the supply chain resilience literature.

Existence of positive solutions for a class of p-Laplacian fractional differential equations with nonlocal boundary conditions

This article is devoted to proving the uniqueness of positive solutions for p-Laplacian equations with Caputo and Riemann-Liouville fractional derivative. The uniqueness result and the dependence of the solution on a parameter are established based on the fixed point point theorem of mixed monotone operators. In the end, a numerical simulation is given to verify the main results.

Privacy? What’s that? Differences in privacy boundaries

PurposeWhile research on privacy concerns is rich in understanding and depth, there is still not a clear understanding of why people express having privacy concerns, but do not behave consistently with their concern. We propose that this misalignment derives from a diverse set of privacy boundaries, depending on the user. This research builds on prior Communication Privacy Management Theory research to further define individual privacy boundaries. Beyond that, we evaluate the relationship between the privacy boundaries people set, and their ability to protect themselves.Design/methodology/approachA survey was conducted to assess how private individuals find twenty items. Along with measuring the sensitivity of information, we collected responses on the Online Privacy Information Literacy test to measure differences in sensitivity based on privacy knowledge. 285 participant’s responses were evaluated using exploratory factor analysis and K-means clustering.FindingsWe identify five different groups of privacy indicators. Our findings also suggest that users have limited understanding of how to keep data private, even if they have high privacy concerns.Originality/valueWe contribute to theory by offering guidance on how to better apply theoretical understanding, based on our results. More explicitly, we offer analysis that suggests boundary conditions might be absent from current theoretical understanding. Practically, we offer guidance for understanding privacy differences, which is important to understanding how to implement privacy protection laws.

Klein-Gordon potential in characteristic coordinates

Abstract By the Klein-Gordon potential, we call a convolution-type integral with a kernel, which is the fundamental solution of the Klein-Gordon equation and also a solution of the Cauchy problem to the same equation. An interesting question having several important applications (in general) is what boundary condition can be imposed on the Klein-Gordon potential on the boundary of a given domain so that the Klein-Gordon equation with initial conditions complemented by this “transparent” boundary condition would have a unique solution within that domain still given by the Klein-Gordon potential. It amounts to finding the trace of the Klein-Gordon potential to the boundary of the given domain. In this article, we analyze this question and construct a novel initial boundary-value problem for the Klein-Gordon equation in characteristic coordinates.

Biophysical fluid dynamics in a Petri dish

The humble Petri dish is perhaps the simplest setting in which to examine the locomotion of swimming organisms, particularly those whose body size is tens of microns to millimeters. The fluid layer in such a container has a bottom no-slip surface and a stress-free upper boundary. It is of fundamental interest to understand the flow fields produced by the elementary and composite singularities of Stokes flow in this geometry. Building on the few particular cases that have previously been considered in the literature, we study here the image systems for the primary singularities of Stokes flow subject to such boundary conditions—the Stokeslet, rotlet, source, rotlet dipole, source dipole, and stresslet—paying particular attention to the far-field behavior. In several key situations, the depth-averaged fluid flow is accurately captured by the solution of an associated Brinkman equation whose screening length is proportional to the depth of the fluid layer. The case of hydrodynamic bound states formed by spinning microswimmers near a no-slip surface, discovered first using the alga , is reconsidered in the geometry of a Petri dish, where the power-law attractive interaction between microswimmers acquires unusual exponentially screened oscillations. Published by the American Physical Society 2024

An Aero Engine Disk Sizing and Weight Estimation Approach with Improved Temperature Profiles

Abstract During the predesign phase of an aero engine, interdisciplinary parametric studies are crucial for identifying an optimum engine. As innovative engine concepts emerge, it is essential to study trends aiming to minimize climate impact and one of its key contributors, fuel burn. The comparatively heavy disks, subjected to high thermal and mechanical loads, are central to this analysis due to their high impact on the overall module mass. This paper proposes an approach to achieve a first lightweight mechanical design of disks in the predesign phase. Based on a performance and aerodynamic baseline, the design space and physical boundary conditions are set. Firstly, an initial mass optimized disk is derived using simplified temperature profiles and stress calculations under the Mechanical Design Point conditions. Subsequently, all the module disks are considered and an estimation for each bore temperature is achieved through a novel loop over the entire module and all available operating points. By evaluating the temperature and stress profiles across various operating conditions, the lowcyclefatigue life of each disk can be studied. As part of a highly modular engine predesign framework, this method allows for zooming capabilities of single disk calculations by prescribing individual boundary conditions. The proposed approach already yields an initial assessment of the rotors within a short runtime, facilitating simple iterations with the succeeding design phases due to method and tool commonalities. While the primary focus of the current work is on compressor design, the principles presented are adaptable and expandable to turbine disk applications as well.

Analysis of Caputo Sequential Fractional Differential Equations with Generalized Riemann–Liouville Boundary Conditions

This paper delves into a novel category of nonlocal boundary value problems concerning nonlinear sequential fractional differential equations, coupled with a unique form of generalized Riemann–Liouville fractional differential integral boundary conditions. For single-valued maps, we employ a transformation technique to convert the provided system into an equivalent fixed-point problem, which we then address using standard fixed-point theorems. Following this, we evaluate the stability of these solutions utilizing the Ulam–Hyres stability method. To elucidate the derived findings, we present constructed examples.

Unsupervised deep learning bias correction of CMIP6 global ensemble precipitation predictions with cycle generative adversarial network

Abstract Climate change significantly impacts agricultural production, ecosystem stability, and socioeconomic development. Global climate models (GCMs) serve as the primary tool for simulating historical and future precipitation patterns. However, due to issues such as coarse resolution, boundary condition, and parameterization, model outputs require bias correction (BC). With the evolution of deep learning techniques, supervised convolutional neural network (CNN) frameworks have gained popularity in the area of climate model BC but face limitations in spatial correlation assumptions and data sparsity, particularly for extreme precipitation This study proposed an unsupervised learning approach using cycle generative adversarial network (CycleGAN) to correct the ensemble mean bias of models and compare its performance with CNN and Quantile Mapping methods. The results demonstrate that the proposed CycleGAN approach outperforms both CNN and Quantile Mapping in ensemble mean BC. It effectively learns the overall distribution of precipitation through an adversarial process and yields better extreme precipitation predictions.

Correlations of mixed convection in a double lid‐driven shallow rectangular cavity: The case of non‐Newtonian power‐law fluids

AbstractThis work provides an analytical and numerical assessment, complete with correlations, of mixed convection in a double lid‐driven shallow rectangular enclosure, which confines non‐Newtonian fluids of the Ostwald–de Waele type and which a uniform thermal flux heats. The finite volume method with the SIMPLER algorithm is the numerical method used to solve the governing partial differential equations along with the boundary conditions, where the parallel flow concept is the analytical approach. In the limits of the explored values of the governing parameters of this study, which are the Rayleigh number, the Peclet number, and the behavior index, the results obtained by these approaches appear to be in good harmony. On the basis of the results obtained by these approaches, we established helpful correlating relations between the governing parameters to realize the contribution of mixed convection to heat transfer. This leads to the finding that the ratio Ra/Pe2+n is the mixed convection parameter, which is the key to distinguishing the three convective flow modes. On the basis of this parameter, which allows the transition from one regime to another, it is possible to identify the zones that designate the predominance of natural, forced, and mixed convection. The limits of these latter depend on the behavior index, n, which is diversified from 0.6 to 1.4 to account for shear thinning (0 &lt; n &lt; 1, low apparent viscosity, high fluid flow, and high heat transfer rate), Newtonian (n = 1), and shear thickening (n &gt; 1, high apparent viscosity, slow fluid flow, and low heat transfer rate) fluids. On the other hand, the study presents and interprets the influences of the steering factors on heat transfer and fluid flow.

One‐dimensional consolidation analysis of layered soil with exponential flow under continuous drainage boundary

AbstractTo comprehensively consider the influence of boundary conditions, non‐Darcy flow, load forms, and soil stratification on soil consolidation, a one‐dimensional soil consolidation equation is established. By subdividing the soil layer and employing time discretization, the nonlinear consolidation equation is linearized, resulting in an analytical solution for layered soil foundation at any given time. Subsequently, an iterative approach for time solution is employed to obtain a semi‐analytical solution. The correctness of the solution is verified by comparison with solutions based on Darcy's flow and the semi‐analytical method under traditional drainage boundary conditions. Subsequently, the influence of interface parameters, loading conditions, flow index, and other factors on consolidation characteristics is analyzed. The results indicate that higher interface parameter values for continuous drainage boundaries correspond to faster average consolidation rates for stratified soil foundations, while these parameters have little effect on the time required for complete consolidation of the soil layers. Improved boundary drainage performance amplifies the influence of exponential flow on pore water pressure and average consolidation degree. Conversely, poor boundary drainage performance diminishes the impact of exponential flow on soil consolidation, rendering it negligible. Moreover, faster loading rates accentuate the influence of the flow index on the average consolidation degree defined by pore pressure.

The Visual Scene Network and Hippocampus Represent Spatial Boundary Structures for Temporal Episodic Memory Organization.

Crossing a spatial boundary such as a doorway plays an important role in the temporal organization of episodic memory. However, despite the wealth of evidence showing that visual boundary structures in scenes affect our representation of space, no studies have tested the possibility that they also function as event boundaries even without active navigation. In this study, we used a nonnavigational scene-based memory task that required participants to remember a sequence of objects moving to various baskets in a scene. In the boundary condition, there was a freestanding boundary in the middle of the room, low enough to see the rest of the room beyond it. We found that the additional boundary within the scene was sufficient to trigger a larger response in the cortical visual scene network, the hippocampus, and their coordinated activity. These results suggest that active navigation across a spatial boundary such as a doorway into another room is not necessary to form an event boundary and that a visual representation of boundaries is sufficient to influence the organization of a hippocampal episodic memory.

Induction heating simulation for aircraft RTM toolings

Aircraft CFRP parts as sharklets are produced in resin transfer molding (RTM) tooling. The parts need to be heated up homogenously over the whole area with a constant temperature. The complex shape and accessibility of the tooling make it hard to introduce a common heating system. In addition, the heat must be transferred through the Invar metal tooling structure onto the CFRP. Infrared lamp, air fan and microwave heating are concepts in development. Electrical heating layer mats and cages are laborious in applying. Induction has the advantage of contact-less, efficient, and fast heating. Induction heating was tested for the structural bonding of CFRP frames and stringers showing high bonding strengths. To apply this technology for the RTM tooling, the placement and distance of the induction coils is important. Simulation can help to find the right adjustments and power needed for induction heating. With the program COMSOL the surface and the coils are modeled, and the numerically structured net is divided in small tetrahedron and quadratic sub elements. Since there is no magnetic streamline in the middle of the coil-section, a symmetric halving of the structure is applied as a boundary condition. The temperature-time development and the distance of the coils are simulated in 2D and 3D. Due to the material properties of the magnetic flux concentrator (MFC), higher flux concentration of the magnetic field occurred only in 2D. The results are validated by experiments and are in good agreement.

Splitting probabilities as optimal controllers of rare reactive events.

The committor constitutes the primary quantity of interest within chemical kinetics as it is understood to encode the ideal reaction coordinate for a rare reactive event. We show the generative utility of the committor in that it can be used explicitly to produce a reactive trajectory ensemble that exhibits numerically exact statistics as that of the original transition path ensemble. This is done by relating a time-dependent analog of the committor that solves a generalized bridge problem to the splitting probability that solves a boundary value problem under a bistable assumption. By invoking stochastic optimal control and spectral theory, we derive a general form for the optimal controller of a bridge process that connects two metastable states expressed in terms of the splitting probability. This formalism offers an alternative perspective into the role of the committor and its gradients in that they encode force fields that guarantee reactivity, generating trajectories that are statistically identical to the way that a system would react autonomously.

Large deviations in the symmetric simple exclusion process with slow boundaries: A hydrodynamic perspective

We revisit the one-dimensional model of the symmetric simple exclusion process slowly coupled with two unequal reservoirs at the boundaries. In its non-equilibrium stationary state, the large deviations functions of density and current have been recently derived using exact microscopic analysis by Derrida, Hirschberg and Sadhu in [J. Stat. Phys. 182, 15 (2021)]. We present an independent derivation using the hydrodynamic approach of the macroscopic fluctuation theory (MFT). The slow coupling introduces additional boundary terms in the MFT-Action, which modifies the spatial boundary conditions for the associated variational problem. For the density large deviations, we explicitly solve the corresponding Euler-Lagrange equations using a simple local transformation of the optimal fields. For the current large deviations, our solution is obtained using the additivity principle. In addition to recovering the expression of the large deviations functions, our solution describes the most probable path for these rare fluctuations.