Computational Setup Research Articles

Minimizing Communication Overhead in Decentralized Deep Neural Networks

Minimizing communication overhead in decentralized deep neural network (DNN) training has become a critical challenge, particularly with the increasing adoption of distributed systems for large-scale machine learning tasks. This paper introduces advanced techniques that leverage gradient compression, adaptive sparsification, and hybrid aggregation to optimize communication efficiency while maintaining model accuracy and convergence rates. Experimental results on benchmark datasets such as CIFAR-10 and ImageNet show that the proposed methods reduce communication costs by up to 70% compared to standard approaches while achieving comparable or superior model accuracy. Additionally, scalability tests on diverse neural network architectures highlight the robustness of the approach, demonstrating efficient performance across varying network sizes and computational setups. These findings underscore the potential of the proposed strategies to enable faster, cost-effective, and sustainable decentralized deep learning systems.

Experimental and numerical study of solid needle insertions into human stomach tissue

PurposeOral drug delivery is the Holy Grail in the field of drug delivery. However, poor bioavailability limits the oral intake of macromolecular drugs. Oral devices may overcome this limitation, but a knowledge gap exists on the device-tissue interaction. This study focuses on needle insertion into the human stomach experimentally and numerically. This will guide early stages of device development. MethodsNeedle insertions were done into excised human gastric tissue with sharp and blunt needles at velocities of 0.0001 and 0.1 m/s. Parameters for constitutive models were determined from tensile visco-hyperelastic biomechanical tests. The computational setup modeled four different needle shape indentations at five velocities from 0.0001 to 5 m/s. ResultsFrom experiments, peak forces at 0.1 and 0.0001 m/s were 0.995 ± 0.296 N and 1.281 ± 0.670 N (blunt needle) and 0.325 ± 0.235 N and 0.362 ± 0.119 N (sharp needle). The needle geometry significantly influenced peak forces (p < 0.05). A Yeoh-Prony series combination was fitted to the tensile visco-hyperelastic biomechanical data and used for the numerical model with excellent fit (R2 = 0.973). Both needle geometry and insertion velocity influenced the stress contour and displacement magnitudes as well as energy curves. ConclusionThis study contributes to a better understanding of needle insertion into the stomach wall. The numerical model demonstrated agreement with experimental data providing a good approach to early device iterations. Findings in this study showed that insertion velocity and needle shape affect tissue mechanical outcomes.

Leveraging graph neural networks to predict Hammett’s constants for benzoic acid derivatives

The Hammett constants, σm and σp, reflect the electron-withdrawing and electron-donating abilities of substituents on aromatic compounds, and have been successfully used in various structure-activity relationship studies. However, determining these constants experimentally is both resource-intensive and time-consuming approach. In this study, we explore the use of graph neural networks (GNNs) to predict Hammett constant parameters using graph-based features. This innovative approach aims to provide rapid and efficient predictions of σm and σp values, eliminating the need for extensive computational and experimental setups. By leveraging the power of GNNs, we hope to streamline the process of obtaining these critical parameters, thereby facilitating more efficient reaction design and enhancing the applicability of linear free energy relationship studies in chemical research.

How to simulate dissociative chemisorption of methane on metal surfaces.

The dissociation of methane is not only an important reaction step in catalytic processes, but also of fundamental interest. Dynamical effects during the dissociative chemisorption of methane on metal surfaces cause significant differences in computed reaction rates, compared to what is predicted by typical transition state theory (TST) models. It is clear that for a good understanding of the catalytic activation of methane dynamical simulations are required. In this paper, a general blueprint is provided for performing dynamical simulations of the dissociative chemisorption of methane on metal surfaces, by employing either the quasi-classical trajectory or ring polymer molecular dynamics approach. If the computational setup is constructed with great care-since results can be affected considerably by the setup - chemically accurate predictions are achievable. Although this paper concerns methane dissociation, the provided blueprint is, so far, applicable to the dissociative chemisorption of most molecules.

Pore collapse, shear bands, and hotspots using atomistics-consistent continuum models for RDX (1,3,5-trinitro-1,3,5-triazinane): Comparison with molecular dynamics calculations

Shock-induced energy localization is a crucial mechanism for determining shock sensitivity of energetic materials (EMs). Hotspots, i.e., localized areas of elevated temperature, arise when shocks interact with defects (cracks, pores, and interfaces) in the EM microstructure. The ignition and growth of hotspots in a shocked energetic material contribute to rapid chemical reactions that can couple with the passing shock wave, potentially leading to a self-sustained detonation wave. Predictive models for shock-to-detonation transition must correctly capture hotspot dynamics, which demands high-fidelity material models for meso-scale calculations. In this work, we deploy atomistics-guided material models for the energetic crystal RDX (1,3,5-trinitro-1,3,5-triazinane) and perform tandem continuum and all-atom molecular dynamics (MD) simulations. The computational setup for the continuum and MD simulations are nearly identical. The material models used for the calculations are derived from MD data, particularly the equations of state, rate-dependent Johnson–Cook strength model, and pressure-dependent shear modulus and melting temperature. We show that a modified Johnson–Cook model that accounts for shear-induced localization at the pore surface is necessary to represent well—relative to MD as the ground truth—the inelastic response of the crystal under a range of shock conditions. A head-to-head comparison of continuum and atomistic calculations across several metrics of pore collapse and energy deposition demonstrates that the continuum calculations are in good overall agreement with MD. Therefore, this work provides improved RDX material models to perform physically accurate meso-scale simulations, to enhance understanding of hot spot formation, and to use meso-scale hot spot data to inform macro-scale shock simulations.

Towards Hydraulic Design Optimization of Shaft Hydropower Plants: A 3D-CFD Application Based on Physical Models

The shaft hydropower plant (SHPP) is a novel hydraulic concept for low-head hydropower sites with several environmental and operational advantages over conventional layouts. However, the first two projects implementing this concept have shown comparatively high construction costs and project risks. Therefore, further optimization is required to increase economic attractiveness and enable broader market adoption. Initial model tests recommend a square-shaped shaft inlet with a three-sided approach flow for low-loss and fish-friendly inflow conditions. Yet, this design requires significant space for structural implementation and may be unsuitable for use with multiple shafts or as an extension of non-powered dams and weirs. This research paper presents the application of a computational fluid dynamics simulation setup to evaluate the hydraulic performance of various design configurations, especially alternative design layouts with a one-sided approach flow without further physical model tests. The simulation setup is calibrated against observations including head loss and velocity measurements from the physical model tests, and its satisfactory performance enables the analysis of alternative design layouts. This study aims to derive the most significant design parameters for achieving the desired hydraulic conditions at the intake. Increasing the flow depth before the intake and enlarging the inlet area have the most significant impact, while increasing the overflow of the front gate has the least significant effect. The chosen CFD application is deemed suitable for hydraulic design optimization and provides guidance on the key parameters to focus on for tailored site-specific design development.

High-fidelity numerical simulation of longitudinal thermoacoustic instability in a high-pressure subscale rocket combustor

A detailed analysis of thermoacoustic combustion instability in a subscale rocket combustor at high pressure is reported in this paper using the high-fidelity large-eddy simulation (LES). Self-sustained longitudinal combustion instability is observed in the experiments for this combustor configuration. The computational setup follows the past experimental study of a rig called the Continuously Variable Resonance Combustor (CVRC). In this combustor, both stable combustion and unstable combustion dynamics have been observed by varying the oxidizer injector length. A combustor configuration with an oxidizer injector length of 12 cm is chosen for this study based on the experimental evidence of longitudinal combustion instability. An autonomous meshing using the modified cut-cell Cartesian grid generation approach, coupled with on-the-fly Adaptive Mesh Refinement (AMR) is employed in this study. Chemical reactions during turbulent combustion in this configuration are modeled by solving the species transport equations with a detailed chemistry solver using a kinetic mechanism with 21 species and 84 steps. Similar to the findings of the experiments, we observe a self-sustained combustion instability in the present study, which is characterized by a limit cycle behavior of the acoustic fluctuations. The spectral analysis of these acoustic fluctuations shows good agreement with experimental data for the frequency of the three dominant modes. We further analyze the features of time-averaged and instantaneous reacting flow to study the effects of combustion instability on the flame holding dynamics, vortex shedding, mixing, and combustion regime due to flame movement along the longitudinal direction of the combustor during a limit cycle. These phenomena are effectively captured through the integration of AMR with complex chemistry in the present study. A particular focus of the study is on understanding the role of minor species (OH, HO2, and CH2O) in the physical and state-space in sustaining the flame during the combustion instability. Additionally, the physical mechanisms responsible for the production and dissipation of enstrophy are examined to demonstrate that their contribution can create significant fluctuations in the reacting flow field, which can assist in sustaining the combustion instability.

Correction to the Paper “Branch and Price for the Time-Dependent Vehicle Routing Problem with Time Windows”

The aim of this erratum is to correct an error in the computer implementation of the algorithm proposed by Dabia, Ropke, and van Woensel [Dabia S, Ropke S, van Woensel T (2013) Branch and price for the time-dependent vehicle routing problem with time windows. Transportation Sci. 47(3):295–454]. Section 6 , “Computational Results,” from the original paper is rewritten to reflect the corrected implementation, the new computational setup, and the updated results.

The effects of wellbore stone materials and fluid density on the shock wave induced by plasma pulse system propagation in rock: An analytical and experimental study.

A pulsed plasma system is a highly efficient tool for linking wells to reservoirs to repair near-wellbore damage and restore production. This research aims to create a computational model and experimental setup to delve into the generation and spread of shock waves from electrical discharge. It also explores the influence of different stone wall materials such as limestone, sandstone, and dolomite, along with varied fluid densities such as saline water and drilling mud. Results show that when an electrical current passes through a metal wire, the wire explosively disintegrates, creating a plasma pulse that applies pressure shock to the stone walls, leading to crack formation. It is important to note that the explosion's energy can be increased by raising the capacitor's energy and modifying the circuit's inductance. Analyzing the impact of fluid density on the shock wave reveals that enhancing the plasma pulse system and attaining higher energy levels can be achieved by using materials with higher viscosity. In terms of stone wall materials, limestone demonstrates superior mechanical stability, dolomite exhibits moderate stability, and sandstone shows relatively lower stability in crack growth.

Shear strengthening of damaged reinforced concrete beams with iron-based shape memory alloy (Fe-SMA) strips: numerical and parametric analysis

Shape memory alloys (SMAs) are metallic materials that are characterized by their ability to restore their original shape after large deformation when activated by heating. This unique property renders SMAs appealing for various civil engineering applications. Iron-based SMAs (Fe-SMAs), including alloys like Fe–Mn–Si, stand out due to their cost-effectiveness and high strength. The primary focus of this research lies in the computational modeling of Fe-SMA strips utilized to reinforce damaged concrete structures. To achieve this, details from an experimental test are leveraged for the computational simulation of real-scale reinforced concrete beams that were first loaded to some level of damage, then released and strengthened, and subsequently retested. The strengthening approach involves the application of external Fe-SMA strips wrapping around the beams. This paper presents an original computational modeling setup that incorporates a switch option for the Fe-SMA material. This feature enables one to use a single simulation platform for the whole process. The significance of this method originates from its capacity to ensure a robust analysis that includes all simulation steps-testing unstrengthened beams, installing and heating Fe-SMA strips, and testing both damaged and strengthened beams—in a single, multi-step analysis. The computational simulation results were compared with the outcomes of the experimental test, revealing an acceptable level of agreement. The findings indicate a substantial increase in both shear strength and ductility as a result of the application of Fe-SMA strips. Additionally, parametric and mesh sensitivity studies were conducted. These aimed to investigate the mesh dependency of the model and to identify the optimal mesh size. Furthermore, variations in the details of the Fe-SMA strips, including thickness, width, quantity, and effect of applied temperature were explored to compare the outcomes of different applications of these strips.

TORO Indexer: a PyTorch-based indexing algorithm for kilohertz serial crystallography.

Serial crystallography (SX) involves combining observations from a very large number of diffraction patterns coming from crystals in random orientations. To compile a complete data set, these patterns must be indexed (i.e. their orientation determined), integrated and merged. Introduced here is TORO (Torch-powered robust optimization) Indexer, a robust and adaptable indexing algorithm developed using the PyTorch framework. TORO is capable of operating on graphics processing units (GPUs), central processing units (CPUs) and other hardware accelerators supported by PyTorch, ensuring compatibility with a wide variety of computational setups. In tests, TORO outpaces existing solutions, indexing thousands of frames per second when running on GPUs, which positions it as an attractive candidate to produce real-time indexing and user feedback. The algorithm streamlines some of the ideas introduced by previous indexers like DIALS real-space grid search [Gildea, Waterman, Parkhurst, Axford, Sutton, Stuart, Sauter, Evans & Winter (2014). Acta Cryst. D70, 2652-2666] and XGandalf [Gevorkov, Yefanov, Barty, White, Mariani, Brehm, Tolstikova, Grigat & Chapman (2019). Acta Cryst. A75, 694-704] and refines them using faster and principled robust optimization techniques which result in a concise code base consisting of less than 500 lines. On the basis of evaluations across four proteins, TORO consistently matches, and in certain instances outperforms, established algorithms such as XGandalf and MOSFLM [Powell (1999). Acta Cryst. D55, 1690-1695], occasionally amplifying the quality of the consolidated data while achieving superior indexing speed. The inherent modularity of TORO and the versatility of PyTorch code bases facilitate its deployment into a wide array of architectures, software platforms and bespoke applications, highlighting its prospective significance in SX.

High-fidelity simulation of the interaction between a blade cascade and an ingested vortex

The aim of this research is to analyze the flow generated by the interaction between a simplified linear blade cascade adapted from an industrial aircraft engine demonstrator and an ingested vortex with the aerodynamic characteristics of a ground vortex observed in experiments. Due to the lack of availability of experimental and high-fidelity numerical studies of this phenomenon in the literature, a representative academic test case with a high-fidelity hybrid RANS/LES resolution of turbulence, namely the Zonal Detached Eddy Simulation (ZDES) technique, is performed. After the description of the computational setup and the numerical parameters used, the instantaneous topology of this complex flow is discussed, especially the interaction of the compressor cascade with the dynamics of the vortex. The simulation shows the chopping of the vortex, its destabilization and its dislocation into turbulent structures downstream the blade cascade. Turbulence is finely resolved in the blade wake and in the chopped vortex by ZDES technique at a moderate computational cost thanks to the RANS treatment of attached boundary layers with an applicative value of Reynolds number (5⋅106). A URANS simulation is also performed and allows a good representation of the averaged vortical structures inside the vortex close to the phase-averaged reference simulation. Spectral analyses are performed on unsteady velocity signals from probes located inside and outside the vortex chopped by the blades, highlighting more intense axial velocity fluctuations from turbulent structures inside the transformed vortex than in the wake of the blades, these structures being convected downstream in the direction of the Outlet Guide Vane (OGV).

Mastering the complex time-scale interaction during Stress Corrosion Cracking phenomena through an advanced coupling scheme

Stress corrosion cracking (SCC) failure is a multi-physics phenomena and is usually modelled at the microstructural level, which includes mechanical, chemical, and electrochemical contributions. In aggressive corrosive environments, materials prone to localized corrosion, can suffer heavy pitting corrosion. Subsequently, pit-to-crack transition events might be initiated. Respective mechanical assisted pitting corrosion propagation processes are determined by mechanical, chemical, and electrochemical properties as well as transport properties of ions at grain boundaries. Variations in the electrolyte exposure conditions (including the kinetics at the solid–liquid interface), different mechanical loading scenarios, grain-specific crystal anisotropies, and other local factors combine to produce a highly complex SCC-type interaction scenario at various time and length scales. Since corrosion is a slow process whereas brittle fracture is a rapid failure mechanism, the individual domain discretization-based solvers need to use distinct time steps and appropriate solver settings to become capable to accurately simulate such coupled events. In order to address the issues that arise while accounting for scaling effects in both time and space, and retaining coupled mechanistic interplay and including the aspects specified earlier, a sophisticated modelling method is necessary for the analysis of structural failure by SCC. In this work, a partitioned multi-physics computational approach is presented, using two separate single physics solvers coupled by the open-source coupling library preCICE. In the proposed computational setup, two separate software environments are used, with dedicated solver settings and different time steps, to simulate the mechanical fracture and dissolution-driven pitting corrosion for various loading and corrosion conditions, while also taking into account the effects of microstructural anisotropy. For a 2D polycrystalline model representing face-centered-cubic (fcc) material systems, selected numerical experiments are conducted that predict the evolution of fracture and crack path resulting from SCC. The framework has been further extended to simulate 3D problems as well. The corresponding results are evaluated to show the applicability of the proposed methodology.

Errors and uncertainties in CFD validation for non-equilibrium turbulent boundary layer flows at high Reynolds numbers

NATO AVT-RTG-349 was dedicated to the validation of computational fluid dynamics (CFD) methods based on the Reynolds-Averaged Navier-Stokes (RANS) equations and statistical turbulence models for non-equilibrium turbulent-boundary-layer flows at high Reynolds numbers. This paper describes and discusses the errors and uncertainties arising in the comparison of RANS simulation results with experimental data from wind-tunnel experiments. These errors and uncertainties are associated with the CFD grid and the discretization, the physical modelling, the measurement accuracy, and the differences in the flow conditions between the experimental facility and the computational set-up. The results show the need for a grid-convergence study using systematically-refined families of CFD grids. The two major sources of errors are the RANS turbulence model and the uncertainty originating from the differences between the computational set-up and the wind-tunnel. Then two possible paths for future research are described: future CFD mesh generation, and future validation experiments at high Reynolds numbers.

Thermodiffusively unstable laminar hydrogen flame in a sufficiently large 3D computational domain – Part II: NOx formation mechanism and flamelet modeling

In this work, the NOx formation mechanism in three-dimensional (3D) thermodiffusively unstable premixed hydrogen flames is investigated through direct numerical simulations (DNS) and a reaction path analysis based on the DNS dataset. In part I of this study (Wen et al., 2024), the characteristic patterns of the instabilities were studied using the same dataset. Here, first, the effects of the computational setup (2D vs. 3D) and curvature on the flux ratio of nitrogen atom are quantified. In addition, the composition space model (CSM) proposed in previous works is extended to account for the NOx chemical reaction mechanism to predict NOx formation in thermodiffusively unstable premixed hydrogen flames. The flamelet solutions are obtained from the premixed flamelet equations in composition space so that the wide range of curvatures associated with the strongly corrugated flame front can be considered. The performance of the CSM in predicting the NOx species and the important radicals involved in the NOx formation pathways is evaluated through an a priori analysis. To investigate the effects of curvature on the NOx formation pathways and the performance of the composition space model, the positively- and negatively-curved regions in the DNS are studied separately. The results show that different from the 2D simulation, the NNH reaction pathway becomes dominant in the 3D simulation due to the increased range of curvature, which promotes the accumulation of the highly diffusive H radical in the positively-curved regions. The NNH reaction pathway is dominant in the positively-curved regions, while the N2O reaction pathway is more important in the negatively-curved regions. The flamelet model based on the composition space solutions that consider the effects of curvature yields accurate predictions for the radicals that are sensitive to the effects of curvature.Novelty and significance statementThe novelty of the present work includes the following aspects,(i) Analysis of NOx formation mechanism based on the large-scale 3D DNS dataset of a laminar fuel-lean premixed hydrogen flame on a sufficiently large domain;(ii) Quantification of the effects of computational setup (2D and 3D) and curvature on the NOx formation pathways;(iii) Extension of the previous composition space model (CSM) by incorporating the NOx chemical reaction mechanism to consider the effects of curvature on the NOx formation.

Space–time computations of exactly time-periodic flows past hydrofoils

The computation of periodic flows is typically conducted over multiple periods. First, a number of periods is used to develop periodic characteristics, and afterwards statistics are collected from averages over multiple periods. As a consequence, it is uncertain whether the numerical results are exactly time-periodic, and additionally, the time domain might be needlessly long. In this article, we circumvent these concerns by using a time-periodic function space. Consequently, the boundary conditions and solutions are exactly periodic. We employ the isogeometric analysis framework to achieve higher-order smoothness in both space and time. The discretization is performed using residual-based variational multiscale modeling and weak boundary conditions are adopted to enhance the accuracy near the moving boundaries of the computational domain. We enforce the time-periodic boundary condition within the isogeometric discretization spaces, which converts the two-dimensional time-dependent problem into a three-dimensional boundary value problem. Furthermore, we determine the boundary velocities of moving hydrofoils directly from the computational mesh and use a conservation methodology for force extraction. Application of the computational setup to heaving and pitching hydrofoils displays very accurate and exactly periodic results for lift and drag.

On identifying suitable hydrogen power plant location under [formula omitted]-spherical fuzzy hypersoft matrix structures

In recent decades, the prime objective of the energy sector has been to replace conventional energy sources with renewable energy sources such as hydrogen power, solar energy, etc. The objective of the present communication is to computationally locate the best site for the establishment of the hydrogen power plant given the various uncertainty parameters in terms of inexact and incomplete information. The uncertainty components of the information are well dealt with by the incorporation of T-spherical fuzzy hypersoft information. In accordance, we present the new concept of T-spherical fuzzy hypersoft matrix (TSFHSM) with different matrix-theoretic structured possibilities having useful computational setups. Some standard matrix operations with their algebraic properties have also been studied. Next, the structure of the proposed matrix has been utilized in presenting two new methodologies for the decision-making selection problems — one with the help of choice/weighted choice T-spherical fuzzy hypersoft matrices and the other with the value & score T-spherical fuzzy hypersoft matrices. Further, an illustrative example where the set of sites for the selection of hydrogen power plants has been computationally studied with the help of the presented novel algorithms given the available criteria. The efficacy of the proposed algorithms and their implementations have been discussed along with a comparative analysis, advantages and a characteristic comparison table.

Altering flight stability characteristics of a high-performance aircraft through wing strake modification

AbstractChanges in flight stability characteristics at the advanced stage of aircraft design are complex and require thorough investigations. This paper examines the impact of wing strake modification on high-performance aircraft using computational fluid dynamics (CFD). The dynamic behaviour is calculated using the forced oscillation technique, while the effect of geometric variation on longitudinal stability characteristics is extensively studied. Steady-state experimental data is utilised to validate the computational setup. Static aerodynamic coefficients, dynamic stability derivatives and the positions of aerodynamic and pressure centres are employed to quantify the changes. Furthermore, the alterations in stability characteristics are correlated with flow physics. The results indicate a reduction in longitudinal static and dynamic stability at various flight conditions due to the proposed modification. This deliberate reduction was necessary to accommodate the installation of a fly-by-wire system. The discussed design changes have been effectively implemented on an in-service aircraft.

Evaluating speech-in-speech perception via a humanoid robot.

Underlying mechanisms of speech perception masked by background speakers, a common daily listening condition, are often investigated using various and lengthy psychophysical tests. The presence of a social agent, such as an interactive humanoid NAO robot, may help maintain engagement and attention. However, such robots potentially have limited sound quality or processing speed. As a first step toward the use of NAO in psychophysical testing of speech- in-speech perception, we compared normal-hearing young adults' performance when using the standard computer interface to that when using a NAO robot to introduce the test and present all corresponding stimuli. Target sentences were presented with colour and number keywords in the presence of competing masker speech at varying target-to-masker ratios. Sentences were produced by the same speaker, but voice differences between the target and masker were introduced using speech synthesis methods. To assess test performance, speech intelligibility and data collection duration were compared between the computer and NAO setups. Human-robot interaction was assessed using the Negative Attitude Toward Robot Scale (NARS) and quantification of behavioural cues (backchannels). Speech intelligibility results showed functional similarity between the computer and NAO setups. Data collection durations were longer when using NAO. NARS results showed participants had a relatively positive attitude toward "situations of interactions" with robots prior to the experiment, but otherwise showed neutral attitudes toward the "social influence" of and "emotions in interaction" with robots. The presence of more positive backchannels when using NAO suggest higher engagement with the robot in comparison to the computer. Overall, the study presents the potential of the NAO for presenting speech materials and collecting psychophysical measurements for speech-in-speech perception.

Type-I antiferromagnetic Weyl semimetal InMnTi2

Topological materials have been a main focus of studies in the past decade due to their protected properties that can be exploited for the fabrication of new devices. Among them, Weyl semimetals are a class of topological semimetals with nontrivial linear band crossings close to the Fermi level. The existence of such crossings requires the breaking of either time-reversal (T) or inversion (I) symmetry and is responsible for the exotic physical properties. In this work we identify the full-Heusler compound InMnTi2, as a promising, easy to synthesize, T- and I-breaking Weyl semimetal. To correctly capture the nature of the magnetic state, we employed a novel DFT+U computational setup where all the Hubbard parameters are evaluated from first principles; thus preserving a genuinely predictive character of the theory. We demonstrate that this material exhibits several features that are comparatively more intriguing with respect to other known Weyl semimetals: the distance between two neighboring nodes is large enough to observe a wide range of linear dispersions in the bands, and only one kind of such node's pairs is present in the Brillouin zone. We also show the presence of Fermi arcs stable across a wide range of chemical potentials. Finally, the lack of contributions from trivial points to the low-energy properties makes the materials a promising candidate for practical devices. Published by the American Physical Society 2024