Numerical Artifacts Research Articles

The shape of dark matter halos: A new fundamental cosmological invariance

In this article, we focus on the complex relationship between the shape of dark matter (DM) halos and the cosmological models underlying their formation. We have used three realistic cosmological models from the DEUS numerical simulation project. These three models have very distinct cosmological parameters (Ωm, σ8, and w) but their cosmic matter fields beyond the scale of DM halos are quasi-indistinguishable, providing an exemplary framework to examine the cosmological dependence of DM halo morphology. First, we developed a robust method for measuring the halo shapes detected in numerical simulations. This method avoids numerical artifacts on DM halo shape measurements, induced by the presence of substructures depending on the numerical resolution or by any spherical prior that does not respect the triaxiality of DM halos. We then obtain a marked dependence of the halo’s shape both on their mass and the cosmological model underlying their formation. As it is well known, the more massive the DM halo, the less spherical it is and we find that the higher the σ8 of the cosmological model, the more spherical the DM halos. Then, by reexpressing the properties of the shape of the halos in terms of the nonlinear fluctuations of the total cosmic matter field or only of the cosmic matter field which is internal to the halos, we managed to make the cosmological dependence disappear completely. This new fundamental cosmological invariance is a direct consequence of the nonlinear dynamics of the cosmic matter field. As the universe evolves, the nonlinear fluctuations of the cosmic field increase, driving the dense matter halos toward sphericity. The deviation from sphericity, measured by the prolaticity, triaxiality, and ellipticity of the DM halos, is therefore entirely encapsulated in the nonlinear power spectrum of the cosmic field. From this fundamental invariant relation, we retrieve with remarkable accuracy the root-mean-square of the nonlinear fluctuations and, consequently, the power spectrum of the cosmic matter field in which the halos formed. We also recover the σ8 amplitude of the cosmological model that governs the cosmic matter field at the origin of the DM halos. Our results therefore highlight, not only the nuanced relationship between DM halo formation and the underlying cosmology but also the potential of DM halo shape analysis of being a powerful tool for probing the nonlinear dynamics of the cosmic matter field.

Archaeometallurgical characterization of Greco-Roman copper-based and iron nails from Tel Abu Seify, North Sinai, Egypt

The current study focuses on the investigation of a collection of copper alloy and iron nails discovered amid numerous metal artifacts in the archaeological excavations of Tel Abu Seify, North Sinai, Egypt. This site, identified as a shipbuilding and repair facility, dates back to the Greco-Roman era (Circa 332BCE–A.D. 641). Different analytical methods were employed to ascertain the composition of the alloys, manufacturing techniques, and characteristics of the corrosion products in the nails. A range of techniques were utilized to achieve this goal, including optical and metallographic microscopy, X-ray radiography, portable X-ray fluorescence, SEM-EDS, micro-Raman spectroscopy, and X-ray diffraction. The results indicated that 19 of the examined nails were composed of copper alloy, except for two nails made of iron. The analysis revealed that the tin bronze nails were predominantly composed of copper, with a minor presence of tin (4.3 wt%), lead (4.7 wt%), and traces of iron and arsenic. Additionally, the iron nails were made of low-carbon iron alloys. Microscopic examination indicated that the nails were manufactured via cold hammering. The patina observed on the copper nails encompassed cuprite, atacamite, clinoatacamite, antlerite, and cerussite, often interspersed with the soil residues. The rust surfaces of the iron nails comprised hematite, magnetite, goethite, akaganeite, and lepidocrocite. The iron nails and some copper nails exhibited partial or total mineralization, whereas most copper nails remained in good condition, generally retaining their metallic cores.

A Shifted Boundary Method for the compressible Euler equations

The Shifted Boundary Method (SBM) is applied to compressible Euler flows, with and without shock discontinuities. The SBM belongs to the class of unfitted (or immersed, or embedded) finite element methods and avoids integration over cut cells (and the associated implementation/stability issues) by reformulating the original boundary value problem over a surrogate (approximate) computational domain. Accuracy is maintained by modifying the original boundary conditions using Taylor expansions. Hence the name of the method, that shifts the location and values of the boundary conditions. We specifically discuss the advantages the proposed method offers in avoiding spurious numerical artifacts in two scenarios: (a) when curved boundaries are represented by body-fitted polygonal approximations and (b) when the Kutta condition needs to be imposed in immersed simulations of airfoils. An extensive suite of numerical tests is included.

A Systematic Literature Review of Existing Methods and Tools for the Criticality Assessment of Raw Materials: A Focus on the Relations between the Concepts of Criticality and Environmental Sustainability

Critical raw materials have significant economic and social impacts across numerous sectors. Numerous artifacts have been developed to assess their criticality. However, there is no univocity around the factors determining criticality. A systematic literature review was conducted to consider all academic works and official reports on criticality assessment. The review aimed to classify these artifacts to provide a clear picture of the heterogenous literature, with a focus on the relationship between criticality and environmental sustainability. Works proposing or updating criticality assessment artifacts were included according to the eligibility criteria. Academic sources were drawn from the Scopus Database in 2023. Official reports included those considered seminal by academic literature. The risk of bias in the selection and classification of the 162 works was low, as the review sought to be comprehensive. The included artifacts are systematically classified. A mapping of the identified criticality assessment tools and methods has been developed. The review found that while environmental impacts are considered in several works, the theoretical connection between criticality and environmental sustainability is weak. Three perspectives on this relationship are identified and discussed. The main limitation of this study is the inability to analyze undisclosed artifacts. It was conducted under the Horizon Europe Programme (Grant Number 101091490).

Chaotic systems based on higher-order oscillatory equations

This paper discusses the design process toward new lumped chaotic systems that originates in higher-order ordinary differential equations commonly used as description of ideal oscillators. In investigated third-order case, two chaotic oscillators were constructed. These systems are dual in the sense of vector field geometry local to fixed points. The existence of robust chaos was proved by both standard routines of numerical analysis and practical measurement. For the fourth-order oscillatory equation, the concept based on interaction between superinductor and supercapacitor was examined in detail. Since both “superelements” are active, the nonlinearity essential to the evolution of chaos is fully passive. It is demonstrated that complex motion is robust and does not represent long transient behavior or numerical artefact. The existence of chaos was verified using standard quantifiers of the flow, such as the largest Lyapunov exponents, recurrence plots, approximate entropy and sensitivity calculation. A good final agreement between theoretical assumptions and practical results will be concluded, on a visual comparison basis.

Revisiting evolution of domain walls and their gravitational radiation with CosmoLattice

Employing the publicly available 𝒞osmoℒattice code, we conduct numerical simulations of a domain wall network and the resulting gravitational waves (GWs) in a radiation-dominated Universe in the Z2-symmetric scalar field model. In particular, the domain wall evolution is investigated in detail both before and after reaching the scaling regime, using the combination of numerical and theoretical methods. We demonstrate that the total area of closed walls is negligible compared to that of a single long wall stretching throughout the simulation box. Therefore, the closed walls are unlikely to have a significant impact on the overall network evolution. This is in contrast with the case of cosmic strings, where formation of loops is crucial for maintaining the system in the scaling regime. To obtain the GW spectrum, we develop a technique that separates physical effects from numerical artefacts arising due to finite box size and non-zero lattice spacing. Our results on the GW spectrum agree well with refs. [29,30], which use different codes. Notably, we observe a peak at the Hubble scale, an exponential falloff at scales shorter than the wall width, and a plateau/bump at intermediate scales. We also study sensitivity of obtained results on the choice of initial conditions. We find that different types of initial conditions lead to qualitatively similar domain wall evolution in the scaling regime, but with important variations translating into different intensities of GWs.

Echo-planar DWI variants: A comparative study in vertebral marrow pathology.

Single-shot echo-planar imaging (ss-EPI) has limited application in vertebral column imaging due to numerous artifacts. Therefore, we aimed to compare readout-segmented echo-planar imaging (rs-EPI) to ss-EPI and assess its value in the differential diagnosis of vertebral infectious, tumoral infiltrative, and degenerative disorders. Sixty-six adult patients with spondylodiscitis (SD, n = 26), tumoral infiltration (TI, n = 20), or Modic type I degeneration (DE, n = 20) findings on spinal magnetic resonance imaging (MRI) included in this retrospective study. Two radiologists scored images for quality on a 4-point scale (image resolution, degree of geometric distortion, lesion selectivity, and diagnostic reliability) and measured signal intensity (SI), apparent diffusion coefficient (ADC), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). DE and SD groups also united to form the benign group. In all groups, rs-EPI performed better than ss-EPI in image quality, SNR, and CNR (p < .05). The difference between mean pathological ADC (ADCP) in the two sequences was statistically significant (p < .05). There was no significant difference between the groups in terms of ADCP in rs-EPI (p = .229), unlike ss-EPI (p = .025). Pathological SI (SIP) and CNR in rs-EPI were significantly higher in the malignant group than benign group (p = .002, p < .001). In rs-EPI, no significant difference was found between malignant and benign groups' ADCP (p = .13). The rs-EPI is a diffusion-weighted imaging (DWI) method with higher image quality that diminishes motion-induced phase errors and increases resolution through phase corrections. However, the distinction of malignant and benign vertebral bone marrow pathologies is unsatisfactory for rs-EPI compared with ss-EPI.

Oscillation-free implicit pressure explicit concentration discontinuous Galerkin methods for compressible miscible displacements with applications in viscous fingering

The system of compressible miscible displacements is widely adopted to model surfactant flooding in enhanced oil recovery techniques, where a low-viscosity fluid is injected underground to replace the high-viscosity oil. When the mobility ratio of the injected fluid to oil is high, the waterflood front tends to be unstable and exhibits a finger-like growth pattern, known as viscous fingering. Due to its unstable nature, the viscous fingering phenomenon is sensitive to mesh orientation and numerical discretization. Therefore, high-order numerical methods are preferable to reduce numerical artifacts and mesh dependence. In this paper, we propose a high-order discontinuous Galerkin method for the coupled nonlinear system of compressible miscible displacements to simulate the viscous fingering fluid instability in porous media. We adopt the IMplicit Pressure Explicit Concentration time marching approach based on implicit-explicit Runge-Kutta methods to achieve high-order temporal accuracy. Additionally, we introduce an oscillation-free damping term to control the spurious oscillations encountered in the waterflood front due to the large gradient of saturation. We have conducted ample numerical tests in two space dimensions to demonstrate the effectiveness and robustness of the proposed schemes in recovering viscous fingering.

An improved stochastic weighted particle method for boundary driven flows

The stochastic weighted particle method (SWPM) is a generalization of the Direct Simulation Monte Carlo (DSMC) method where particle weights are variable and dynamic. SWPM is backed by a strong theoretical foundation but has not been critically evaluated for problems of practical interest. A thorough assessment of SWPM for boundary-driven flows reveals significant numerical artifacts near the boundary, notably a diverging heat flux. To correct the boundary heat flux, two modifications to SWPM are proposed: separated grouping and a spatially-dependent weight transfer function. To gauge the relative efficiency of SWPM in comparison to DSMC, a high-Mach-number wheel flow which forms a strong density gradient is also simulated.

Coupled Cluster Theory for Nonadiabatic Dynamics: Nuclear Gradients and Nonadiabatic Couplings in Similarity Constrained Coupled Cluster Theory.

Coupled cluster theory is one of the most accurate electronic structure methods for predicting ground and excited state chemistry. However, the presence of numerical artifacts at electronic degeneracies, such as complex energies, has made it difficult to apply the method in nonadiabatic dynamics simulations. While it has already been shown that such numerical artifacts can be fully removed by using similarity constrained coupled cluster (SCC) theory [J. Phys. Chem. Lett. 2017, 8(19), 4801-4807], simulating dynamics requires efficient implementations of gradients and nonadiabatic couplings. Here, we present an implementation of nuclear gradients and nonadiabatic derivative couplings at the similarity constrained coupled cluster singles and doubles (SCCSD) level of theory, thereby making possible nonadiabatic dynamics simulations using a coupled cluster theory that provides a correct description of conical intersections between excited states. We present a few numerical examples that show good agreement with literature values and discuss some limitations of the method.

Population affinities in pre-colonial West Africa: The case of the burial cave Iroungou (Gabon, 14th-15th century CE).

Our knowledge of the populations of sub-Saharan Africa in the periods before European colonization is limited. Few archeological sites containing human remains have been identified, and written sources for these periods are rare. The discovery in 2018 of the Iroungou sepulchral cave (Gabon), whose use predates the arrival of the Portuguese (14th-15th centuries CE), is an exceptional source of information: at least 28 individuals associated with numerous metal artifacts were found there. The anthropobiological remains were left in situ, but the eight best preserved crania were digitized. This study focuses on the population affinities of these crania, whose morphology was described using 237 landmarks. Geometric morphometric analyses were used to compare the eight Iroungou specimens with 154 individuals representing 12 well-defined African populations. After alignment (Generalized Procrustes Analysis), morphological affinity was assessed using Euclidean and Mahalanobis distances, and posterior probabilities of population membership (discriminant analysis). Results indicate that the eight Iroungou crania have, on average, more affinity with Bayaka Pygmy, followed by Central African Bantu. Nevertheless, individually, the Iroungou specimens show an important morphological variation and the eight crania can be separated into different affinity groups: Bayaka and Central African Bantu, KhoeSan, and East-African Bantu. Finally, one individual presents strong affinity with Somalis. This phenetic mapping of the Iroungou sample raises questions about the profile of the individuals deposited in the cave in a geographical area known for the Loango pre-colonial kingdom, which ruling class seemed to have had privileged relationships with the Pygmy populations.

An image processing approach for fatigue crack identification in cellulose acetate replicas

The cellulose acetate replication technique is an important method for studying material fatigue. However, extracting accurate information from pictures of cellulose replicas poses challenges because of distortions and numerous artifacts. This paper presents an image processing procedure for effective fatigue crack identification in plastic replicas. The approach employs thresholding, adaptive Gaussian thresholding, and Otsu binarization to convert gray-scale images into binary ones, enhancing crack visibility. Morphological operations refine object shapes, and Connected Components Analysis facilitates crack identification. Despite limited data, the handcrafted feature extraction algorithm proves robust, addressing challenges. The algorithm shows efficacy in detecting cracks as small as 30 μm, even in the presence of cellulose replication artifacts. The results highlight ability to capture significant cracks’ orientation, length, and growth stages, essential for understanding fatigue mechanisms. Analysis of results, especially evaluation metrics encompassing false positives and false negatives, provides a comprehensive understanding of the algorithm’s strengths and limitations. The proposed tool is available on GitHub.

Solving deep-learning density functional theory via variational autoencoders

In recent years, machine learning models, chiefly deep neural networks, have revealed suited to learn accurate energy-density functionals from data. However, problematic instabilities have been shown to occur in the search of ground-state density profiles via energy minimization. Indeed, any small noise can lead astray from realistic profiles, causing the failure of the learned functional and, hence, strong violations of the variational property. In this article, we employ variational autoencoders (VAEs) to build a compressed, flexible, and regular representation of the ground-state density profiles of various quantum models. Performing energy minimization in this compressed space allows us to avoid both numerical instabilities and variational biases due to excessive constraints. Our tests are performed on one-dimensional single-particle models from the literature in the field and, notably, on a three-dimensional disordered potential. In all cases, the ground-state energies are estimated with errors below the chemical accuracy and the density profiles are accurately reproduced without numerical artifacts. Furthermore, we show that it is possible to perform transfer learning, applying pre-trained VAEs to different potentials.

Lifting relations for a generalized total-energy double-distribution-function kinetic model and their impact on compressible turbulence simulation

Recently, Qi et al. (2022) and Guo et al. (2023) proposed two alternative designs of an efficient mesoscopic method using the total-energy double-distribution-function (DDF) formulation, hereafter referred to as the Qi model and the Guo model. The two models share the same advantage of using only 40 discrete particle velocities to fully reproduce the Navier–Stokes-Fourier (NSF) system. However, the Guo model is based on a more rigorous kinetic consideration, while the Qi model relies on a more general design of the source term to allow for adjustable bulk-to-shear viscosity ratio. In this paper, we derive lifting relations for the Qi model based on two alternative approaches, namely, the Hermite expansion and the Chapman–Enskog expansion, which can be used to construct the boundary and initial conditions for the mesoscopic method. For three-dimensional compressible turbulence simulations, including compressible decaying homogeneous isotropic turbulence and Taylor–Green vortex flows, the derived two sets of lifting relations are applied to the initialization distribution function to study their impacts. Interestingly, for the Qi model, the two sets of lifting relations yield the same results without numerical artifacts, whereas for the Guo model, an appropriate lifting relation must be specified to avoid numerical artifacts resulting from the flow initialization (Qi et al., 2023).

A stabilised Total Lagrangian Element-Free Galerkin method for transient nonlinear solid dynamics

AbstractThis paper presents a new stabilised Element-Free Galerkin (EFG) method tailored for large strain transient solid dynamics. The method employs a mixed formulation that combines the Total Lagrangian conservation laws for linear momentum with an additional set of geometric strain measures. The main aim of this paper is to adapt the well-established Streamline Upwind Petrov–Galerkin (SUPG) stabilisation methodology to the context of EFG, presenting three key contributions. Firstly, a variational consistent EFG computational framework is introduced, emphasising behaviours associated with nearly incompressible materials. Secondly, the suppression of non-physical numerical artefacts, such as zero-energy modes and locking, through a well-established stabilisation procedure. Thirdly, the stability of the SUPG formulation is demonstrated using the time rate of Hamiltonian of the system, ensuring non-negative entropy production throughout the entire simulation. To assess the stability, robustness and performance of the proposed algorithm, several benchmark examples in the context of isothermal hyperelasticity and large strain plasticity are examined. Results show that the proposed algorithm effectively addresses spurious modes, including hour-glassing and spurious pressure fluctuations commonly observed in classical displacement-based EFG frameworks.

LLM‐based Approach to Automatically Establish Traceability between Requirements and MBSE

AbstractTracing requirements specification to design and implementation is an essential part of safety standards, as it allows to ensure that safety goals are met throughout the development process. Manual tracing numerous artifacts produced throughout the development process is error‐prone and takes much time. To address these problems, we proposed a tool (Bonner, M.; Zeller, M.; Schulz, G.; Beyer, D.; Olteanu, M., 2023), which allows to establish links between requirements and Model‐Based Systems Engineering (MBSE) in a semi‐automatic way. The underlying algorithms of our tool are embedding similarity computation and classification approaches based on Large Language Models (LLMs). To assess the performance of underlying algorithm we propose an evaluation, where we compare the recall, the precision, and the F2 score of different approaches applied to our datasets. The goal of our evaluation is to understand how well LLMs perform in automatically generating trace links on different datasets. Our evaluation shows that it is worth to invest time in preprocessing the data and fine‐tuning the LLMs to achieve the better recommendations for engineers, which improves the traceability process.

The Impact of the Explicit Representation of Convection on the Climate of a Tidally Locked Planet in Global Stretched-mesh Simulations

Convective processes are crucial in shaping exoplanetary atmospheres but are computationally expensive to simulate directly. A novel technique of simulating moist convection on tidally locked exoplanets is to use a global 3D model with a stretched mesh. This allows us to locally refine the model resolution to 4.7 km and resolve fine-scale convective processes without relying on parameterizations. We explore the impact of mesh stretching on the climate of a slowly rotating TRAPPIST-1e-like planet, assuming it is 1:1 tidally locked. In the stretched-mesh simulation with explicit convection, the climate is 5 K colder and 25% drier than that in the simulations with parameterized convection(with both stretched and quasi-uniform meshes). This is due to the increased cloud reflectivity—because of an increase in low-level cloudiness—and exacerbated by the diminished greenhouse effect due to less water vapor. At the same time, our stretched-mesh simulations reproduce the key characteristics of the global climate of tidally locked rocky exoplanets, without any noticeable numerical artifacts. Our methodology opens an exciting and computationally feasible avenue for improving our understanding of 3D mixing in exoplanetary atmospheres. Our study also demonstrates the feasibility of a global stretched-mesh configuration for LFRic-Atmosphere, the next-generation Met Office climate and weather model.

Analysis of Varroa Mite Colony Infestation Level Using New Open Software Based on Deep Learning Techniques.

Varroa mites, scientifically identified as Varroa destructor, pose a significant threat to beekeeping and cause one of the most destructive diseases affecting honey bee populations. These parasites attach to bees, feeding on their fat tissue, weakening their immune systems, reducing their lifespans, and even causing colony collapse. They also feed during the pre-imaginal stages of the honey bee in brood cells. Given the critical role of honey bees in pollination and the global food supply, controlling Varroa mites is imperative. One of the most common methods used to evaluate the level of Varroa mite infestation in a bee colony is to count all the mites that fall onto sticky boards placed at the bottom of a colony. However, this is usually a manual process that takes a considerable amount of time. This work proposes a deep learning approach for locating and counting Varroa mites using images of the sticky boards taken by smartphone cameras. To this end, a new realistic dataset has been built: it includes images containing numerous artifacts and blurred parts, which makes the task challenging. After testing various architectures (mainly based on two-stage detectors with feature pyramid networks), combination of hyperparameters and some image enhancement techniques, we have obtained a system that achieves a mean average precision (mAP) metric of 0.9073 on the validation set.

A balanced outflow boundary condition for swirling flows

In open flow simulations, the dispersion characteristics of disturbances near synthetic boundaries can lead to unphysical boundary scattering interactions that contaminate the resolved flow upstream by propagating numerical artifacts back into the domain interior. This issue is exacerbated in flows influenced by real or apparent body forces, which can significantly disrupt the normal stress balance along outflow boundaries and generate spurious pressure disturbances. To address this problem, this paper develops a zero-parameter, physics-based outflow boundary condition (BC) designed to minimize pressure scattering from body forces and pseudo-forces and enhance transparency of the artificial boundary. This “balanced outflow BC” is then compared against other common BCs from the literature using example axisymmetric and three-dimensional open swirling flow computations. Due to centrifugal and Coriolis forces, swirling flows are known to be particularly challenging to simulate in open geometries, as these apparent forces induce non-trivial hydrostatic stress distributions along artificial boundaries that cause scattering issues. In this context, the balanced outflow BC is shown to correspond to a geostrophic hydrostatic stress correction that balances the induced pressure gradients. Unlike the alternatives, the balanced outflow BC yields accurate results in truncated domains for both linear and nonlinear computations without requiring assumptions about wave characteristics along the boundary.

The utilization of wood samples from xylarium in historical wooden statues: improving the separation accuracy non-destructive measurement for using several algorithms

There are numerous wooden historical artifacts in Kyoto and other parts of Japan, including Buddhist statues or Shinto deities. The identification of wood species in these historical artifact is desirable for both repair and maintenance purposes. The most common method of identifying wood species involves examining samples taken from the artifacts. However, intentional sampling from old cultural artifacts is prohibited in Japan. As a result, we attempted to determine the wood species of old statues non-destructively using near-infrared spectroscopy (NIRS). In this article, we developed the softwood and hardwood separation model using NIRS to compare the prediction accuracy for few algorithms. The model was created based on wood samples stored in the xylarium of the Forestry and Forest Products Research Institute (TWTw). We then applied this model to old Buddhist statues in order to classify them as either softwood or hardwood. These Buddhist statues were housed in Nazenji temple and are believed to have been carved during the Heian period (8th–12th century). For the near-infrared (NIR) measurements, we collected diffuse reflectance spectra from TWTw sample and Buddhist statues using same spectrometer. Initially, we used the soft independent modeling of class analogy method (SIMCA), partial least squares discriminant analysis (PLS_DA), and support vector machine to analyze the NIR spectra obtained from the TWTw wood samples. Subsequently, we applied the NIR spectra obtained from several Buddhist statues in Nazenji temple to the aforementioned separation model and determined whether spectra data were classified as the softwood or hardwood. Finally, wood specimens detached naturally from the Buddhist statues over time were observed under microscopic analysis to identify the wood species. As comparing the prediction accuracy of few algorithms, SIMCA had a poor result, but PLS_DA had a good result. PLS_DA had better discrimination because it performed calculations to improve regression from both explanatory variables and objective variables.