Domain Of Validity Research Articles

A Novel Historical Landslide Detection Approach Based on LiDAR and Lightweight Attention U-Net

Rapid and accurate identification of landslides is an essential part of landslide hazard assessment, and in particular it is useful for land use planning, disaster prevention, and risk control. Recent alternatives to manual landslide mapping are moving in the direction of artificial intelligence—aided recognition of these surface processes. However, so far, the technological advancements have not produced robust automated mapping tools whose domain of validity holds in any area across the globe. For instance, capturing historical landslides in densely vegetated areas is still a challenge. This study proposed a deep learning method based on Light Detection and Ranging (LiDAR) data for automatic identification of historical landslides. Additionally, it tested this method in the Jiuzhaigou earthquake-hit region of Sichuan Province (China). Specifically, we generated a Red Relief Image Map (RRIM), which was obtained via high-precision airborne LiDAR data, and on the basis of this information we trained a Lightweight Attention U-Net (LAU-Net) to map a total of 1949 historical landslides. Overall, our model recognized the aforementioned landslides with high accuracy and relatively low computational costs. We compared multiple performance indexes across several deep learning routines and different data types. The results showed that the Multiple-Class based Semantic Image Segmentation (MIOU) and the F1_score of the LAU-Net and RRIM reached 82.29% and 87.45%, which represented the best performance among the methods we tested.

Heat transfer coefficient correlations of water subatmospheric vaporization in a channel of a smooth plate heat exchanger, based on Vaschy-Buckingham theorem

Water as an environmentally friendly, safe and cheap natural refrigerant (R-718) requires vaporization conditions at sub-atmospheric pressures (∼1 kPa). At these pressure ranges, studies on the specific vaporization of water are scarce and insufficient. For this reason, the engineering of heat exchangers using R-718 as working fluid remains empirical. The aim of this paper is thus to provide correlations to estimate water pool boiling and falling film evaporation heat transfer coefficient under subatmospheric pressure. Correlations developed are believed to be more widely used by providing dimensionless numbers consistent with phase-change phenomena occurring at sub and at-mospheric pressure. To develop these correlations, heat transfer phenomena during water vaporization at pressures ranging from 0.7 to 1.7 kPa in a scale-lab size (0.2 m wide × 0.5 m high) vertical smooth plate evaporator channel are studied. Filling ratio vary from 1/2 to 1/10 of the total channel height, canal thicknesses are set to 2 mm, 4 mm or 6 mm. Thus, raw experimental data from 139 tests performed under various operating conditions of a thermosyphon loop mimicking a sorption system are exploited. Each test consists of more than 1200 values. A graphical and statistical comparison between the heat transfer coefficient (HTC) obtained from the experimental database and the HTC estimated by empirical correlations from the literature is made, calculating the percentage of predicted data within an error band of ±30% (τ30), the mean absolute error (MAE), the mean relative error (MRE) and the correlation coefficient (r). Two methodical correlations for predicting the HTC of pool boiling and liquid film evaporation, are developed. They predict 86% (with MAE = 19%, MRE = 3%, r=0.79) and 83% (with MAE = 18%, MRE = 2%, r=0.84) of the experimental data in τ30 respectively. To extend their validity domains, the proposed correlations are evaluated using independent experimental data from the literature. Giving satisfactory results, it constitutes a first step towards the development of tools used for the sizing and the optimization of the design of two-phase heat exchangers.

Characterizing the calibration domain of remote sensing models using convex hulls

• We used a convex hull approach to assess model validity domain. • Convex hulls allow identifying unreliable model predictions. • At low sampling intensity, higher proportion of extrapolation are observed. • Prediction biases increase with extrapolation distances from the calibration domain. • This approach could help model development, as a complementary tool used in model quality assessment. The ever-increasing availability of remote sensing data allows production of forest attributes maps, which are usually made using model-based approaches. These map products are sensitive to various bias sources, including model extrapolation. To identify, over a case study forest, the proportion of extrapolated predictions, we used a convex hull method applied to the auxiliary data space of an airborne laser scanning (ALS) flight. The impact of different sampling efforts was also evaluated. This was done by iteratively thinning a set of 487 systematic plots using nested sub-grids allowing to divide the sample by two at each level. The analysis were conducted for all alternative samples and evaluated against 56 independent validation plots. Residuals of the extrapolated validation plots were computed and examined as a function of their distance to the model calibration domain. Extrapolation was also characterized for the pixels of the area of interest (AOI) to upscale at population level. Results showed that the proportion of extrapolated pixels greatly reduced with an increasing sampling effort. It reached a plateau (ca. 20% extrapolation) with a sampling intensity of ca. 250-calibration plots. This contrasts with results on model’s root mean squared error (RMSE), which reached a plateau at a much lower sampling intensity. This result emphasizes the fact that with a low sampling effort, extrapolation risk remains high, even at a relatively low RMSE. For all attributes examined (i.e. , stand density, basal area, and quadratic mean diameter) estimations were generally found to be biased for validation plots that were extrapolated. The method allows an easy identification of map pixels that are out of the calibration domain, making it an interesting tool to evaluate model transferability over an area of interest (AOI). It could also serve to compare “competing” models at a variable selection phase. From a model calibration perspective, it could serve a posteriori , to evaluate areas (in the auxiliary space) that merit further sampling efforts to improve model reliability.

Analytical strain localization analysis of isotropic and anisotropic damage models for quasi-brittle materials

Strain and damage localization are usually precursors of rupture. We present a three-dimensional method dedicated to quasi-brittle materials based on the works of Bigoni & Hueckel, and Jirásek and coworkers, aiming at simplifying the analysis of the localization properties of continuous damage models of a general form, and possibly anisotropic. The method reformulates the localization problem as a two-variable polynomial maximization problem, a strategy commonly used in softening plasticity models, but not so much in Continuum Damage mechanics. The quasi-brittle hypothesis is exploited to render the problem solvable in a fully analytical way, and a post-analysis criterion for the validity of the analysis is also exhibited. In this work, the method is fully established from a theoretical viewpoint, and examples illustrating its use are provided. Multiaxial calculations are performed for four continuous damage models (two isotropic and two anisotropic ones). The method applies to induced anisotropy and constitutive models representing isotropic linear elasticity before damage growth, and remains accurate when models display immediate softening after the elastic limit (and thus to multiaxial tensile cases). The analytical method is, however, entirely general and allows for the calculation of (i) the orientation of a potential localization plane, (ii) the mode angle of the weak discontinuity, and (iii) the validity domain of such a simplified analysis.

Accurate Numerical Treatment on a Stochastic SIR Epidemic Model with Optimal Control Strategy

In this paper, a numerical study has been undertaken on the susceptible-infected-recovered (SIR) epidemic model that encompasses the mechanisms of the evolution of disease transmission; a prophylactic vaccination strategy in the susceptible populations, depending on the infective individuals. We furnish numerical and graphical simulation combined with explicit series solutions of the proposed model using the New Iterative Method (NIM) and Modified New Iterative Method (MNIM). The analytic-numeric New Iterative Method failed to deliver accurate solution for the large time domain. A new reliable algorithm based on NIM, the coupling of the Laplace transforms, and the New Iterative method is called Modified New Iterative Method (MNIM) which is presented to enhance the validity domain of NIM techniques. The convergence analysis of the MNIM has also been illustrated. The simulation results show that the vaccination strategy can slow down the spread of the epidemic rapidly. Numerical results illustrate the excellent performance of the MNIM and show that the modified method is much more accurate than the NIM.

High-frequency permeability of porous media with thin constrictions. I. Wedge-shaped porous media

In this series of publications, the high-frequency behavior of the dynamic permeability of porous media with thin constriction is investigated. In Part I, the classical theory of Johnson et al. [“Theory of dynamic permeability and tortuosity in fluid saturated porous media,” J. Fluid Mech. 176, 379 (1987)] for soft-curved pore geometries is recalled. For wedge-shaped pore geometries, numerical computations (by finite element method) and analysis by Cortis et al. [“Influence of pore roughness on high-frequency permeability,” Phys. Fluids 15, 1766 (2003)] are revisited and confirmed, while leading to important new conclusions. Because the electric field is singular at the tip of wedges, the original model developed by Johnson et al., which links the viscous fluid flow problem to the electrical conduction problem, is inappropriate for describing the high-frequency behavior of the viscous fluid flow through wedge-shaped porous media. In particular, in the case of small wedge angles, we show that the real part of the dynamic permeability behaves in the high-frequency regime as ℜ(k(ω))∝ω−(3/2)(ln (ω)+constant), which differs from the predictions of the Johnson et al. model [ℜ(k(ω))∝ω−(3/2)]. However, our results show that the classical Johnson et al. high frequency limit can be a good approximation of the viscous fluid flow if the electrical conduction problem is solved over a fluid domain truncated by a boundary layer having a thickness comparable to the viscous skin depth. In Part II, we consider foam with perforated membranes involving different microstructural characteristic lengths: pore size, membrane aperture size, and membrane thickness. We assess the validity domain of the Johnson et al. approximation and test our modified high-frequency approximation for such porous materials.

High-frequency permeability of porous media with thin constrictions. II. Porous media containing thin holed membranes

In this series of publications, the high-frequency behavior of the dynamic permeability of porous media with thin constriction is investigated. In Paper I, the classical theory of Johnson et al. [J. Fluid Mech. 176, 379 (1987)] for soft-curved pore geometries is recalled. For wedge-shaped pore geometries, numerical computations (by the finite element method) and analysis by Cortis et al. [Phy. Fluids 15, 1766 (2003)] are revisited and confirmed, while leading to important new conclusions. Because the electric field is singular at the tip of wedges, the original model developed by Johnson et al., which links the viscous fluid flow problem to the electrical conduction problem, is inappropriate for describing the high-frequency behavior of the viscous fluid flow through wedge-shaped porous media. In particular, in the case of small wedge angles, we show that the real part of the dynamic permeability behaves in the high-frequency regime as ℜ(k(ω))∝ω−(3/2)(ln (ω)+constant), which differs from the predictions of the Johnson et al. model [ℜ(k(ω))∝ω−(3/2)]. However, our results show that the classical Johnson et al. high frequency limit can be a good approximation of the viscous fluid flow if the electrical conduction problem is solved over a fluid domain truncated by a boundary layer having a thickness comparable to the viscous skin depth. In Paper II, we consider foam with perforated membranes involving different microstructural characteristic lengths: pore size, membrane aperture size, and membrane thickness. We assess the validity domain of the Johnson et al. approximation and test our modified high-frequency approximation for such porous materials.

Diagnostische validiteit van het concept Pathological Demand Avoidance: een systematische literatuurreview

Title: Diagnostic validity of the concept Pathological Demand Avoidance: a systematic review Background: Much is to be discussed about the evidence, positioning and usefulness of the concept Pathological Demand Avoidance (PDA). The concept of PDA envelopes a behavioural pattern of resistance to meet ordinary demands of life and the usage of manipulative strategies in order to achieve this; a superficial sociability, lability of mood, obsessive behaviour and fallback into role play as a coping strategy. Until now, the validity of this concept has not been systematically reviewed. Method: This review researches the different aspects of validity based on the five phases by Robins and Guze and a supplementary section about treatment guidelines. A systematic search has been conducted to find relevant studies concerning the validity of PDA using the following databases: Pubmed, Embase, Medline, Cochrane Library, Web of Science and Google Scholar. Full articles with a study design or case reports, published in a peer-reviewed journal were included. Results: 12 relevant study designs and 6 case reports were found. Regarding the two common symptomatic descriptions of PDA no operationalization nor cluster analytic studies were found. Two PDA-related measurement instruments are described. They demonstrated a good internal consistency, but are not validated by research in an independent clinical population. The PDA-dimension correlates with other dimensions of psychopathology (ASD, personality factors and ADHD). However, the positioning of PDA (within the Autism spectrum, as a combination of comorbid factors or as a unique diagnosis) remains unclear. Regarding other domains of validity, as regarding treatment response, insufficient conclusive research has been conducted. Conclusion: Insufficient arguments have been found in the current literature to perceive PDA as a valid concept. At first, cluster analytic studies about the symptoms need to be conducted. A valid definition and delineation regarding PDA is critical to conduct further research to other domains of validity.

Psychometric Evaluation of Glaucoma Quality of Life Item Banks (GlauCAT) and Initial Assessment Using Computerized Adaptive Testing.

PurposeTo evaluate the psychometric properties of glaucoma-specific quality of life (QoL) item banks (GlauCAT) and assess their performance using computerized adaptive testing (CAT) simulations.MethodsIn this cross-sectional study, 293 participants with glaucoma (mean age ± SD, 70.7 ± 13.2 years; 45% female) answered 342 items in 12 QoL item banks (IBs): Activity Limitation (AL); Driving (DV); Convenience (CV); Economic (EC); Emotional (EM); General Symptoms (GS); Health Concerns (HC); Lighting (LT); Mobility (MB); Ocular Surface Symptoms (OS); Social (SC); and Visual Symptoms (VS). These IBs were assessed using Rasch analysis, and CAT simulations with 1000 simulated respondents were utilized to determine the average number of items to be administered to achieve moderate and high precision levels.ResultsThe AL, DV, EM, HC, LT, MB, EC, OS, SC, and VS IBs required relatively minor amendments to achieve satisfactory psychometric fit. To resolve multidimensionality, we split CV into Treatment Convenience (TCV) and General Convenience (GCV). Due to poor measurement precision, the GS IB was not pursued further. This resulted in 12 total IBs. In CAT simulations, an average of 3.7 and 7.3 items per IB were required to attain measurement at moderate and high precision, respectively.ConclusionsFollowing rigorous psychometric assessment, we developed 12 valid glaucoma-specific QoL domains that can obtain highly precise person measure estimates using a small number of items.Translational RelevanceGlauCAT will enable researchers and clinicians to quickly and comprehensively assess the impact of glaucoma and its associated interventions across a range of QoL domains.

Preservice Physics Teachers’ Conceptual Profile of Time

Time is a concept of historical, social, cultural, philosophical, artistic, economic, technological, scientific relevance. Time assumes different meanings in the Sciences, especially in Physics, acquiring fundamental importance in different physical contexts. However, in both high school and college Physics courses in Brazil, time is usually treated as an abstract mathematical parameter to the detriment of recognizing its different meanings, domains of validity, and historicity concerning its genesis. Such treatment of the concept of time leads us to believe that these more particular notions would probably be present in the conceptions within the complex conceptual profile of future Physics teachers in training. We interviewed preservice physics teachers to investigate this hypothesis in physics teacher education. To categorize students’ conceptual profile zones, we developed the Concept Polysemy Organization Matrix (POM) based on the dimensions of the complex conceptual profile model and the genetic scales of Vygotsky. As a result, we start to structure future Physics teachers’ conceptual profile of time, identifying a myriad of meanings of time through POM. Beyond that, we verified that future physics teachers’ dominant meaning of time is numerical since their main formation activity in physics teacher education reinforces abstract mathematical-physical problem-solving.

Homogenized constitutive equations for porous single crystals plasticity

Ductile fracture through void growth to coalescence occurs at the grain scale in numerous metallic alloys encountered in engineering applications. Classical models used to perform numerical simulations of ductile fracture, as the Gurson–Tvergaard–Needleman model and its extensions, are relevant for the case of large voids compared to the grain size, in which a homogenization of the material behavior over a large number of grains is used. Such modeling prevents assessing the effects of microstructure on both crack path and crack propagation resistance. Therefore, homogenized constitutive equations for porous single crystals plasticity are proposed, featuring void growth and void coalescence stages, hardening and void shape evolution. An original numerical implementation based on the coupling of Newton–Raphson and fixed point algorithms is described. In order to assess the accuracy of the proposed model as well as another one described recently in the literature, an extended database of porous unit-cell simulation results is gathered, investigating the effect of crystallographic orientations and hardening behavior for a FCC material. Strengths and weaknesses of both models are detailed with respect to the reference simulations, leading to the definition of the validity domain of the current model and to pinpoint necessary refinements.

Analytic expressions for the moving infinite line source model

Groundwater flow can have a significant impact on the thermal response of ground heat exchangers. The moving infinite line source model is thus widely used in practice as it considers both conductive and advective heat transfert processes. Solution of this model involves a relatively heavy numerical quadrature. Contrarily to the infinite line source model, there is currently no known first-order approximation that could be useful for many practical applications. In this paper, known analytical expressions of the Hantush well function and generalized incomplete gamma function are first revisited. A clear link between these functions and the moving infinite line source model is then established. Then, two new exact and integral-free analytical expressions are proposed, along with two new first-order approximations. The new analytical expressions proposed take the form of convergent power series involving no recursive evaluations. It is shown that relative errors less than 1% can be obtained with only a few summands. The convergence properties of the series, their accuracy and the validity domain of the first-order approximations are also presented and discussed.

Integrating advanced soft computing techniques with experimental studies for pore structure analysis of Qingshankou shale in Southern Songliao Basin, NE China

Evaluating pore structure of unconventional shale reservoirs enables us to determine their productivity, allowing for better operational decisions. Despite extensive studies in this field, considering the complexity of shale plays, pore structure analysis of such formations still requires novelties and further research. In this study, 10 samples from the Qingshankou Formation (from 5 wells) were analyzed with X-ray diffraction (XRD), programmed pyrolysis, N2 adsorption, and mercury intrusion capillary pressure (MICP). In the next step, several modern intelligent smart models including multilayer perceptron (MLP), radial basis function (RBF), generalized regression neural network (GRNN), cascaded forward neural network (CFNN), and least squares support vector machine (LSSVM), that were optimized by levenberg-marquardt (LM), Bayesian regularization (BR), genetic algorithm (GA), ant colony optimization (ACO), particle swarm optimization (PSO), and differential evolution (DE) algorithms were employed, to estimate the volumes of N2 adsorbed and desorbed based on the mineralogy and geochemical properties of the samples. Results show that samples are mainly composed of clay (up to 42.3 wt%) and quartz (up to 34.6 wt%), low in total organic carbon (TOC) (up to 2.89%) and in the oil generation window. Complexity of smaller pores was found higher compared to medium and larger ones. In addition, deconvolution of N2 adsorption pore size distribution (PSD) curve revealed that samples are composed of up to three families in the range of macropore size and different families in mesopore size. We found that LSSVM with applicability to the entire input dataset, outperformed all other models in predicting the amount of nitrogen adsorption and desorption with an average absolute percent relative error (AAPRE) value of 1.94%. Ultimately, clay minerals and potash feldspar had the greatest effect on increasing and decreasing the amount of nitrogen adsorbed and desorbed, respectively. The Leverage technique's findings demonstrate that more than 97% of total data points in the LSSVM model are in the valid domain. This study proves that smart methods if used properly, would enable us to study a large group of samples independent from exhaustive, time consuming and expensive experimental methods.

A Novel Methodology for Human Plasma Protein Binding: Prediction, Validation, and Applicability Domain

Background: Plasma protein binding is a key component in drug therapy as it affects the pharmacokinetics and pharmacodynamics of drugs. Objectives: This study aimed to predict the fraction of plasma protein binding. Methods: A quantitative structure-activity relationship, convolutional neural network, and feed-forward neural network (QSAR-CNN-FFNN) methodology was used. CNN was used for feature selection, which is known as a difficult task in QSAR studies. The values of the descriptors acquired without the preprocessing procedures were rearranged into matrices, and features from a deep fully connected layer of a pre-trained CNN (ALEXNET) were extracted. Then, the latest features learned from the CNN layers were flattened out and passed through an FFNN to make predictions. Results: The external accuracy of the validation set (Q2=0.945, RMSE=0.085) showed the performance of this methodology. Another extremely favorable circumstance of this method is that it does not take a lot of time (only a few minutes) compared to the QSAR-Wrapper-FFNN method (days of hard work and concentration) and it automatically gives us the characteristics that are the best representations of our input. Conclusion: We can say that this model can be used to predict the fraction of human plasma protein binding for drugs that have not been tested to avoid chemical synthesis and reduce expansive laboratory tests.

Editorial

Last year, Applied AI Letters announced the formation of its Associate Editorial Board. The purpose of this body was to provide a platform for rising stars in the field of applied AI, to enable them to have a voice in the world of publishing, and so to ensure that Applied AI Letters was a venue which maintained its close connection to the community from which it was born. As part of their role on the Associate Editorial Board, these talented practitioners were asked to go out into the community and find research works, which they felt were particularly exciting and bring them to Applied AI Letters for wider publication and dissemination. Today, I am proud to write this Editorial announcing the first fruit of this effort. In this issue, we can highlight two of these carefully selected pieces of research, chosen by two of our Associate Editorial Board members, Dr Helge Spieker and Dr Philippe Schwaller. Helge is a postdoctoral researcher at Simula Research Laboratory in Norway, whose research interests are in the applications of artificial intelligence and machine learning, especially in the domains of validation and verification of software-based autonomous systems, industrial robotics, and sports. He also maintains an interest in the integration of machine learning and symbolic AI methods, such as constraint programming, to enable robust hybrid intelligent systems that are reliable and robust. Helge has commissioned an article entitled ‘Deep learning to predict power output from respiratory inductive plethysmography data’.1 As we move into an age where our own personal health data are becoming increasingly important to personalise our lifestyles, including exercise regimes, there is a new scrutiny being placed on the equipment, which is required to generate these data. A reliance on expensive equipment could drive inequalities between those who are financially able to partake in this monitoring and those who cannot. This work takes the case of measuring power output, a common metric used to define exercise intensity. Traditional technologies require expensive equipment, which must also be embedded into the technology, which limit usage. In this paper, an AI model based upon respiratory inductive plethysmography (a non-invasive method for monitoring breathing) and heart rate was built and tested against standard sensor-based power output measurements. The model was able to function with low error and provides evidence of the potential for AI methods to democratise data gathering in this field. Philippe Schwaller is an assistant professor at EPFL (Swiss Federal Institute of Technology Lausanne), having previously worked at IBM Research – Europe, in Zurich. He completed a PhD in Chemistry and Molecular Sciences at the University of Bern, an MPhil in Physics at the University of Cambridge, and an MSc in Materials Science & Engineering at EPFL. His main research focus is on accelerating the discovery and synthesis of novel materials and molecules using AI techniques. Philippe has commissioned an article entitled ‘Generative model-enhanced human motion prediction’.2 Generative models are sometimes referred to as computational creativity agents, as they are adept at identifying and plausibly filling in the white space in data. Whilst we are commonly used to seeing these models in technologies such as deep fakes, as part of a generative adversarial network, this paper uses this family of techniques to augment a human motion data set. These data sets are often prone to building models, which have weaknesses to rare events, and for them to be useful in the ‘real world’, it is necessary to build some robustness to these out of distribution events. In this paper, this robustness is achieved by using generative models to enhance the data set with data which more closely represents the true generating distribution. This work shows that this approach can dramatically improve model robustness without a significant performance penalty. I hope that you enjoy these articles, we will continue this series in the next issue with some more articles championed by our associate editors.

Chemistry without the Born-Oppenheimer approximation.

Chemistry without the Born-Oppenheimer approximation.

A transfer learning-based digital twin for detecting localised torsional friction in deviated wells

Digital twins seek to replicate a physical structure in a digital domain. For a digital twin to have close correspondence to its physical twin, data are required. However, it is not always possible, or cost-effective, to collect a complete set of data for a structure in all configurations of interest. It is nonetheless useful to repurpose data to help validate predictions for different configurations and scenarios. This statement is true in drilling applications, where, for example, the length of the drill string is altered throughout operation. This paper demonstrates how transfer learning, in the form of three domain-adaptation methods, — transfer component analysis (TCA), maximum independence domain adaptation (MIDA) and geodesic flow kernel (GFK) — can be used to construct a digital twin for localising torsional friction in deviated wells under structural changes (e.g., when the drill column gets longer). The method uses a physics-based torsional model to train a machine-learning classifier that can localise torsional friction for a given drill string length and diameter, where friction localisation labels are known (source). As the length or diameter of the drill string are altered in the field, transfer learning is utilised to map the classifier from the labelled (source) scenario onto these unlabelled (target) scenarios. As a result, transfer learning improves the performance of the classifier when applied to the target data, and increases the domain of validity for the classifier. The performance of the classifier, and therefore its suitability to new drill-string configurations, is estimated by utilising two different distance metrics between the source and a proposed target dataset.

Possibility for survival of macroscopic turbulence in porous media with high porosity

The direct numerical simulation (DNS) study by Jin et al. (J. Fluid Mech, vol. 766, 2015, pp. 76–103) shows that the turbulent structures are generally restricted in size to the pore scale, leading to the pore-scale prevalence hypothesis (PSPH). Although the PSPH has been validated under most conditions, it might become invalid as the porosity approaches unity. In order to investigate the valid domain of the PSPH, we have studied the turbulent flows in porous matrices which have one or two length scales using DNS and macroscopic simulation methods. The large porous elements are made of staggered arrays of square cylinders, which might stimulate strong macroscopic (large-scale) turbulence. The small porous elements are made of aligned arrays of spheres or cubes, which suppress the macroscopic turbulence. The analyses are performed for various values of the Reynolds number, Darcy number, pore-scale ratio and porosity. Turbulent two-point correlations, integral length scales and premultiplied energy spectra are calculated from the DNS and macroscopic simulation results to determine the length scale of the turbulent structures. Our numerical results show that the flow becomes turbulent when the Reynolds number is sufficiently large. However, the length scale of turbulence is not considerably affected by the Reynolds number, Darcy number and pore-scale geometry. The PSPH is valid when the porosity has small or medium values. At a sufficiently large Reynolds number, large-scale turbulence survives if the porosity is larger than a critical value. Our DNS and macroscopic simulation results show that this critical value is in the range 0.93–0.98 for porous matrices with large Darcy numbers (0.3–1.26 using the definition in this study). The dependence of the critical porosity on the pore-scale geometry still needs to be further investigated.

Quantum Hotspots: Mean Fields, Open EFTs, Nonlocality and Decoherence Near Black Holes

AbstractEffective theories describing black hole exteriors resemble open quantum systems inasmuch as many unmeasurable degrees of freedom beyond the horizon interact with those we can see. A solvable Caldeira‐Leggett type model of a quantum field that mixes with many unmeasured thermal degrees of freedom on a shared surface was proposed in arXiv:2106.09854 to provide a benchmark against which more complete black hole calculations might be compared. We here use this model to test two types of field‐theoretic approximation schemes that also lend themselves to describing black hole behaviour: Open EFT techniques (as applied to the fields themselves, rather than Unruh‐DeWitt detectors) and mean‐field methods. Mean‐field methods are of interest because the effective Hamiltonians to which they lead can be nonlocal; a possible source for the nonlocality that is sometimes entertained as being possible for black holes in the near‐horizon regime. Open EFTs compute the evolution of the field state, allowing discussion of thermalization and decoherence even when these occur at such late times that perturbative methods fail (as they often do). Applying both of these methods to a solvable system identifies their domains of validity and shows how their predictions relate to more garden‐variety perturbative tools.

Graded Hilbert spaces, quantum distillation and connecting SQCD to QCD

The dimension of the Hilbert space of QFT scales exponentially with the volume of the space in which the theory lives, yet in supersymmetric theories, one can define a graded dimension (such as the supersymmetric index) that counts just the number of bosonic minus fermionic ground states. Can we make this observation useful in non-supersymmetric QFTs in four dimensions? In this work, we construct symmetry graded state sums for a variety of non-supersymmetric theories. Among the theories we consider is one that is remarkably close to QCD: Yang-Mills theory with Nf = Nc fundamental Dirac fermions and one adjoint Weyl fermion, QCD(F/adj). This theory can be obtained from SQCD by decoupling scalars and carry exactly the same anomalies. Despite the existence of fundamental fermions, the theory possess an exact 0-form color-flavor center (CFC) symmetry for a particular grading/twist under which Polyakov loop is a genuine order parameters. By a two-loop analysis, we prove that CFC-symmetry remains unbroken at small β due to grading. Chiral symmetry is spontaneously broken within the domain of validity of semi-classics on ℝ3 × S1 in a pattern identical to Nf = Nc SQCD on ℝ4 and the two regimes are adiabatically connected. The vacuum structures of the theory on ℝ4 and ℝ3 × S1 are controlled by the same mixed ’t Hooft anomaly condition, implying a remarkable persistent order.