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At least 847 records · Page 47

Ultrafast Correlation Energy Estimator

A virtually no-cost method is proposed that can compute the correlation energies of general, covalently bonded, organic, and inorganic molecules (including conjugated π-electron systems) with a well-defined dominant Lewis structure at the accuracy of 99.5% of the near-exact values determined by the coupled-cluster singles, doubles, and perturbative triples [CCSD(T)] in the complete-basis-set (CBS) limit. This Correlation Energy Per Bond (CEPB) method assigns a partial correlation energy to each bond type (characterized by the identities of the two atoms forming the bond and its integer bond order) and to a lone pair, regardless of the bond length, bond angle, sp-hybridization, π-electron conjugation, ionicity, noncovalent interactions, etc. At its current stage, the method is mainly suitable for near-equilibrium geometries. The correlation energies per bond are determined by a fit to the CCSD(T)/CBS benchmarks. It can neither improve the equilibrium structures nor discern conformers or positional isomers, yet its accuracy for reaction energies rivals that of the second-order Møller–Plesset perturbation theory, which is far more expensive. Its promising performance underscores the possibility that surprisingly compact, chemically intuitive molecular fragments exist into which correlation energies can be partitioned, leading to various ultrafast correlation-energy estimators tailored to different purposes.

Binding energy↗

Global Infrared Observations of Roughness Induced Transition on the Space Shuttle Orbiter

High resolution infrared observations made from a mobile ground based optical system captured the laminar-to-turbulent boundary layer transition process as it occurred during Space Shuttle Endeavour's return to earth following its final mission in 2011. The STS-134 imagery was part of a larger effort to demonstrate an emerging and reliable non-intrusive global thermal measurement capability and to complement a series of boundary layer transition flight experiments that were flown on the Shuttle. The STS-134 observations are believed to be the first time that the development and movement of a hypersonic boundary layer transition front has been witnessed in flight over the entire vehicle surface and in particular, at unprecedented spatial resolution. Additionally, benchmark surface temperature maps of the Orbiter lower surface collected over multiple flights and spanning a Mach range of 18 to 6 are now available and represent an opportunity for collaborative comparison with computational techniques focused on hypersonic transition and turbulence modeling. The synergy of the global temperature maps with the companion in-situ thermocouple measurements serve as an example of the effective leveraging of resources to achieve a common goal of advancing our understanding of the complex nature of high Mach number transition. It is shown that quantitative imaging can open the door to a multitude of national and international opportunities for partnership associated with flight-testing and subsequent validation of numerical simulation techniques. The quantitative imaging applications highlighted in this paper offer unique and complementary flight measurement alternatives and suggest collaborative instrumentation opportunities to advance the state of the art in transition prediction and maximize the return on investment in terms of developmental flight tests for future vehicle designs.

Horvath, Thomas J.↗

Progress on Optimizing Wind Farms and Rotor Designs Using Adjoints

Modern wind plants are increasingly tasked with multiple performance objectives. In addition to designing plants that maximize power output and minimize the levelized cost of energy (LCOE), the design and operation of wind plants is increasingly influenced by challenges regarding grid integration of variable generation renewables. This places a growing emphasis on making wind plants more controllable and predictable. WindSE is a Reynolds-averaged Navier-Stokes (RANS) model designed around analytical gradient and adjoint methods, with the ability to capture terrain-induced effects, as shown in Figure 1. The recent addition of an unsteady solver with an actuator line method (ALM) and ongoing work to enable massively parallel optimizations gives it a unique niche to explore coupled plant-level controls and design problems. This code is an open source python package built on the FEniCS framework that utilizes fast, parallel PETSc solvers to model fluid flow throughout wind-farm scale domains. Two recent studies performed using WindSE demonstrate the capability to optimize under a wide variety of flow conditions and objective functions. In the first, we present an optimization focused on modifying the layout of a wind farm with a fixed number of turbines for maximum total power output [1]. This study highlights the ability to quickly perform simulations using the steady Navier-Stokes solver combined with rotors represented as actuator disks while also stressing the importance of capturing terrain-induced effects. Gradient-based optimization using the RANS equations is viable due to the inclusion of efficiently computed adjoint derivatives. We interpret the physical results of the optimal layout and also discuss the computational cost of scaling to larger problems. In the second study, we present the capabilities of the unsteady Navier-Stokes solver, where rotor-blade profiles represented by actuator lines are optimized to enhance wake steering effects and overall power production [2]. We quantify the wind plant performance gains obtained from this type of simultaneous control co-design optimization as compared to optimizing the blade design and yaw independently. Figure 2 shows the differences between a baseline two-turbine system and an optimized system where we fine-tune the blade chord profile. Results and challenges from each study are quickly summarized and used to motivate the current development efforts within WindSE. Current and future work is focused on enabling higher-resolution studies with more degrees of freedom through parallelization of both the simulation and optimization algorithms. We present benchmarking results to show that WindSE performs well in both weak- and strong-scaling tests and further demonstrate that the optimizer obtains the same convergence rates in both shared- and distributed-memory environments. Using larger wind farms, we can study deep-array effects within an optimization context, allowing the use of objective functions that have been previously unstudied. As an example, we present ongoing work on a blockage metric which characterizes the loss of available kinetic energy due to wake effects from multiple upstream turbines.

adjoint optimization↗

Portable Programming Model Exploration for LArTPC Simulation in a Heterogeneous Computing Environment: OpenMP vs. SYCL

The evolution of the computing landscape has resulted in the proliferation of diverse hardware architectures, with different flavors of GPUs and other compute accelerators becoming more widely available. To facilitate the efficient use of these architectures in a heterogeneous computing environment, several programming models are available to enable portability and performance across different computing systems, such as Kokkos, SYCL, OpenMP and others. As part of the High Energy Physics Center for Computational Excellence (HEP-CCE) project, we investigate if and how these different programming models may be suitable for experimental HEP workflows through a few representative use cases. One of such use cases is the Liquid Argon Time Projection Chamber (LArTPC) simulation which is essential for LArTPC detector design, validation and data analysis. Following up on our previous investigations of using Kokkos to port LArTPC simulation in the Wire-Cell Toolkit (WCT) to GPUs, we have explored OpenMP and SYCL as potential portable programming models for WCT, with the goal to make diverse computing resources accessible to the LArTPC simulations. In this work, we describe how we utilize relevant features of OpenMP and SYCL for the LArTPC simulation module in WCT. We also show performance benchmark results on multi-core CPUs, NVIDIA and AMD GPUs for both the OpenMP and the SYCL implementations. Comparisons with different compilers will also be given where appropriate.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Loschmidt-echo approach to error estimation in Krylov-subspace approximation

The Krylov subspace method is a traditional approach to approximate quantum evolution, allowing us to treat systems with large Hilbert spaces. Despite its popularity, current bounds typically overestimate the error, which translates into more expensive simulation routines. Here, in this paper, we tackle this problem by realizing that the error can be understood as a Loschmidt echo in a one-dimensional (1D) noninteracting tight-binding Hamiltonian. We show that the different time regimes of the approximation can be understood using simple physical ideas. More importantly, we obtain computationally cheap error bounds that describe with high precision the actual error in the approximation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Crystalline materials for quantum computing: Semiconductor heterostructures and topological insulators exemplars

Abstract High-purity crystalline solid-state materials play an essential role in various technologies for quantum information processing, from qubits based on spins to topological states. New and improved crystalline materials emerge each year and continue to drive new results in experimental quantum science. This article summarizes the opportunities for a selected class of crystalline materials for qubit technologies based on spins and topological states and the challenges associated with their fabrication. We start by describing semiconductor heterostructures for spin qubits in gate-defined quantum dots and benchmark GaAs, Si, and Ge, the three platforms that demonstrated two-qubit logic. We then examine novel topologically nontrivial materials and structures that might be incorporated into superconducting devices to create topological qubits. We review topological insulator thin films and move onto topological crystalline materials, such as PbSnTe, and its integration with Josephson junctions. We discuss advances in novel and specialized fabrication and characterization techniques to enable these. We conclude by identifying the most promising directions where advances in these material systems will enable progress in qubit technology.

Scappucci, G. (ORCID:0000000325120079)↗

Understanding the chemical bonding of ground and excited states of HfO and HfB with correlated wavefunction theory and density functional approximations

Knowledge of the chemical bonding of HfO and HfB ground and low-lying electronic states provides essential insights into a range of catalysts and materials that contain Hf–O or Hf–B moieties. Here, we carry out high-level multi-reference configuration interaction theory and coupled cluster quantum chemical calculations on these systems. We compute full potential energy curves, excitation energies, ionization energies, electronic configurations, and spectroscopic parameters with large quadruple-ζ and quintuple-ζ quality correlation consistent basis sets. We also investigate equilibrium chemical bonding patterns and effects of correlating core electrons on property predictions. Differences in the ground state electron configuration of HfB(X 4 Σ - ) and HfO(X 1 Σ + ) lead to a significantly stronger bond in HfO than HfB, as judged by both dissociation energies and equilibrium bond distances. We extend our analysis to the chemical bonding patterns of the isovalent HfX (X = O, S, Se, Te, and Po) series and observe similar trends. We also note a linear trend between the decreasing value of the dissociation energy (D e ) from HfO to HfPo and the singlet–triplet energy gap (ΔE S–T ) of the molecule. Finally, we compare these benchmark results to those obtained using density functional theory (DFT) with 23 exchange–correlation functionals spanning multiple rungs of “Jacob’s ladder.” When comparing DFT errors to coupled cluster reference values on dissociation energies, excitation energies, and ionization energies of HfB and HfO, we observe semi-local generalized gradient approximations to significantly outperform more complex and high-cost functionals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

ANALYSIS OF THE MSL/MEDLI ENTRY DATA WITH COUPLED CFD AND MATERIAL RESPONSE.

The Mars Science Laboratory (MSL) was protected during its atmospheric entry by an instrumented heat-shield using NASA's Phenolic Impregnated Carbon Ablator (PICA) material. PICA is a lightweight carbon fiber/polymeric resin material that offers out-standing performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of material response and atmospheric entry. MEDLI recorded, among other things, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP). The objective of this work is to showcase and analyze the coupling between the material response and the aerothermal environment. As shown in Figure 1, the workflow is divided into the following steps. First, the aerothermal properties are computed in the Data Parallel Line Relaxation (DPLR) code [3] and used with the Nonequilibrium air radiation (NEQAIR) program [8] to compute radiative heating. Second, the thermal response inside the material is computed in the Porous material Analysis Toolbox based on Open-FOAM (PATO) using a fixed blowing correction parameter. Third, the pyrolysis gases computed in PATO are used as inputs to a blowing boundary condition within DPLR. Fourth, the new environment properties from DPLR are used in NEQAIR to provide an updated solution, then both the updated aerothermal environment and radiative heating are used in PATO without blowing correction. The third and fourth steps are then repeated until convergence in surface temperature is obtained. Convergence in the radiative heating is generally achieved before surface temperature, at which point the radiative heating is no longer updated. Char mass loss rates are forced to zero to produce a non-receding surface condition. For early time points in the trajectory, where flow around the MSL aeroshell is rarefied, the Direct Simulation Monte Carlo (DSMC) code, SPARTA, is used to compute the aerothermal environment. Iteration between PATO and SPARTA is not performed due to the computational cost of DSMC simulations. Preliminary results of the coupling between PATO and DPLR for the MSL heatshield atmospheric entry model are presented in Figures 2-4 at 65 seconds after entry interface. Figure 2 shows the surface temperature results from an uncoupled simulation in PATO with the blowing correction parameter applied (left) along with the coupled surface temperature after iteration (right). Figure 3 shows the surface temperature along the centerline from windward to leeward for easier comparison. Figure 4 shows the coupled and uncoupled pyrolysis gas blowing rate. Mars 2020 used a similar heatshield consisting of PICA for thermal protection during entry, descent, and landing. In preparation for Mars 2020 post-flight analysis, the predictive material response capability is benchmarked against flight data from MEDLI. This work represents an important milestone toward the development of validated predictive capabilities for designing thermal protection systems for planetary probes.

Mars Science Laboratory↗

Analysis of MSL/MEDLI Entry Data with Coupled CFD and Material Response

The Mars Science Laboratory (MSL) was protected during its atmospheric entry by an instrumented heatshield using NASA's Phenolic Impregnated Carbon Ablator (PICA) material [1]. PICA is a lightweight carbon fiber/polymeric resin material that offers outstanding performances for protecting probes during planetary entry. The Mars Entry Descent and Landing Instrument (MEDLI) suite on MSL offers unique in-flight validation data for models of material response and atmospheric entry. MEDLI recorded, among other things, time-resolved in-depth temperature data of PICA using thermocouple sensors assembled in the MEDLI Integrated Sensor Plugs (MISP) [2]. The objective of this work is to showcase and analyze the coupling between the material response and the aerothermal environment. As shown in Figure 1, the workflow is divided into the following steps. First, the aerothermal properties are computed in the Data Parallel Line Relaxation (DPLR) code [3] and used with the Nonequilibrium air radiation (NEQAIR) program [8] to compute radiative heating. Second, the thermal response inside the material is computed in the Porous material Analysis Toolbox based on OpenFOAM (PATO) [4,5,6] using a fixed blowing correction parameter. Third, the pyrolysis gases computed in PATO are used as inputs to a blowing boundary condition within DPLR. Fourth, the new environment properties from DPLR are used in NEQAIR to provide an updated solution, then both the updated aerothermal environment and radiative heating are used in PATO without blowing correction. The third and fourth steps are then repeated until convergence in surface temperature is obtained. Convergence in the radiative heating is generally achieved before surface temperature, at which point the radiative heating is no longer updated. Char mass loss rates are forced to zero to produce a non-receding surface condition. For early time points in the trajectory, where flow around the MSL aeroshell is rarefied, the Direct Simulation Monte Carlo (DSMC) code, SPARTA [7], is used to compute the aerothermal environment. Iteration between PATO and SPARTA is not performed due to the computational cost of DSMC simulations. Preliminary results of the coupling between PATO and DPLR for the MSL heatshield atmospheric entry model are presented in Figures 2-4 at 65 seconds after entry interface. Figure 2 shows the surface temperature results from an uncoupled simulation in PATO with the blowing correction parameter applied (left) along with the coupled surface temperature after iteration (right). Figure 3 shows the surface temperature along the centerline from windward to leeward for easier comparison. Figure 4 shows the coupled and uncoupled pyrolysis gas blowing rate. Mars 2020 used a similar heatshield consisting of PICA for thermal protection during entry, descent, and landing. In preparation for Mars 2020 post-flight analysis, the predictive material response capability is benchmarked against flight data from MEDLI. This work represents an important milestone toward the development of validated predictive capabilities for designing thermal protection systems for planetary probes.

Thermal Protection Systems↗

The effects of Reynolds number, rotor incidence angle, and surface roughness on the heat transfer distribution in a large-scale turbine rotor passage

A combined experimental and computational program was conducted to examine the heat transfer distribution in a turbine rotor passage geometrically similiar to the Space Shuttle Main Engine (SSME) High Pressure Fuel Turbopump (HPFTP). Heat transfer was measured and computed for both the full-span suction and pressure surfaces of the rotor airfoil as well as for the hub endwall surface. The primary objective of the program was to provide a benchmark-quality data base for the assessment of rotor passage heat transfer computational procedures. The experimental portion of the study was conducted in a large-scale, ambient temperature, rotating turbine model. Heat transfer data were obtained using thermocouple and liquid-crystal techniques to measure temperature distributions on the thin, electrically-heated skin of the rotor passage model. Test data were obtained for various combinations of Reynolds number, rotor incidence angle and model surface roughness. The data are reported in the form of contour maps of Stanton number. These heat distribution maps revealed numerous local effects produced by the three-dimensional flows within the rotor passage. Of particular importance were regions of local enhancement produced on the airfoil suction surface by the main-passage and tip-leakage vortices and on the hub endwall by the leading-edge horseshoe vortex system. The computational portion consisted of the application of a well-posed parabolized Navier-Stokes analysis to the calculation of the three-dimensional viscous flow through ducts simulating the a gas turbine passage. These cases include a 90 deg turning duct, a gas turbine cascade simulating a stator passage, and a gas turbine rotor passage including Coriolis forces. The calculated results were evaluated using experimental data of the three-dimensional velocity fields, wall static pressures, and wall heat transfer on the suction surface of the turbine airfoil and on the end wall. Particular attention was paid to an accurate modeling of the passage vortex and to the development of the wall boundary layers including crossflow.

Blair, Michael F.↗

Comparison of Corcos-based and experimentally-derived coherence factors for BFFs estimation

In this paper, high-spatial-resolution unsteady Pressure Sensitive Paint (uPSP) data are utilized to compare two methods for panel Buffet Forcing Functions (BFF) estimation for the Space Launch System (SLS). Such methods are based on discrete pressure measurements within a panel but employ coherence factors to account for partially-correlated fluctuating pressures across the whole panel. In one method, coherence factors are derived based on the Corcos model, whereas the second method utilizes experimentally-derived coherence factors. To simulate discrete measurements using uPSP data, suitable subsets of the data are extracted. When full uPSP resolution is retained, uPSP data provide a benchmark to assess discrete-measurements-based methods. The analysis focuses on the peak SLS buffet environment located downstream of the Forward Attachment Hardware (FAH) between the core stage and solid rocket boosters. Trends of Corcos-based and experimentally-derived coherence factors are in reasonable agreement with the benchmark. However, at certain frequencies, experimentally-derived coherence factors are sensitive to the separation distance between pressure measurements utilized to compute coherence lengths. Such sensitivity originates from deviation of the experimental-based coherence function from an exponential decay assumption. On the other hand, the present implementation of the Corcos model fails to capture certain non-turbulent boundary layer related environments, such as a subharmonic of FAH vortex-shedding. For all methods presented in this paper, at near transonic conditions, increased pressure coherence and spatial nonuniformity lead to BFF overestimation and sensitivity to the pressure measurement location within the panel.

transonic buffet↗

Comparison of Corcos-Based and Experimentally-Derived Coherence Factors for Buffet Forcing Functions Estimation

In this paper, high-spatial-resolution unsteady Pressure Sensitive Paint (uPSP) data are utilized to compare two methods for panel Buffet Forcing Functions (BFF) estimation for the Space Launch System (SLS). Such methods are based on discrete pressure measurements within a panel but employ coherence factors to account for partially-correlated fluctuating pressures across the whole panel. In one method, coherence factors are derived based on the Corcos model, whereas the second method utilizes experimentally-derived coherence factors. To simulate discrete measurements using uPSP data, suitable subsets of the data are extracted. When full uPSP resolution is retained, uPSP data provide a benchmark to assess discrete-measurements-based methods. The analysis focuses on the peak SLS buffet environment located downstream of the Forward Attachment Hardware (FAH) between the core stage and solid rocket boosters. Trends of Corcos-based and experimentally-derived coherence factors are in reasonable agreement with the benchmark. However, at certain frequencies, experimentally-derived coherence factors are sensitive to the separation distance between pressure measurements utilized to compute coherence lengths. Such sensitivity originates from deviation of the experimental-based coherence function from an exponential decay assumption. On the other hand, the present implementation of the Corcos model fails to capture certain nonturbulent boundary layer related environments, such as a subharmonic of FAH vortex-shedding. For all methods presented in this paper, at near transonic conditions, increased pressure coherence and spatial nonuniformity lead to BFF overestimation and sensitivity to the pressure measurement location within the panel.

buffet↗

Comparison of Corcos-Based and Experimentally-Derived Coherence Factors for Buffet Forcing Function Estimation

In this paper, high-spatial-resolution unsteady Pressure Sensitive Paint (uPSP) data are utilized to compare two methods for panel Buffet Forcing Function (BFF) estimation for the Space Launch System (SLS). Such methods are based on discrete pressure measurements within a panel but employ coherence factors to account for partially-correlated fluctuating pressures across the whole panel. In one method, coherence factors are derived based on the Corcos model, whereas the second method utilizes experimentally-derived coherence factors. To simulate discrete measurements using uPSP data, suitable subsets of the data are extracted. When full uPSP resolution is retained, uPSP data provide a benchmark to assess discrete-measurement-based methods. The analysis focuses on the peak SLS buffet environment located downstream of the Forward Attachment Hardware (FAH) between the core stage and solid rocket boosters. Trends of Corcos-based and experimentally-derived coherence factors are in reasonable agreement with the benchmark. However, at certain frequencies, experimentally-derived coherence factors are sensitive to the separation distance between pressure measurements utilized to compute coherence lengths. Such sensitivity originates from deviation of the experimentally-based coherence function from an exponential decay assumption. On the other hand, the present implementation of the Corcos model fails to capture certain nonturbulent boundary layer related environments, such as a subharmonic of FAH vortex-shedding. For all methods presented in this paper, at near transonic conditions, increased pressure coherence and spatial nonuniformity lead to BFF overestimation and sensitivity to the pressure measurement location within the panel.

transonic buffet↗

Mastering the Cryogenic Frontier: Predicting Sloshing in Cryogenic Propellant Tanks

In recent years, NASA has undertaken the development and validation of computation fluid dynamic (CFD) models for predicting cryogenic two-phase sloshing within propellant tanks. These models have been rigorously anchored against cryogenic ground tests that induce sloshing, as well as limited microgravity tests. The primary focus of these models is to accurately predict the two-phase condensation and, at times, evaporation within the cryogenic propellant. This approach is important for estimating the required autogenous and/or helium pressurant for completing propulsion system burns or ensuring adequate pressure for in-space propellant transfers. Unlike in hypergolic propulsion systems, where the propellant is stored at room temperature, cryogenic propellant is highly volatile. Therefore, ensuring the accurate estimation of pressurant necessitates the precise modeling of two-phase interfacial heat and mass transfer processes. This paper aims to provide an overview of NASA’s continuing efforts in developing and validating these CFD models, with particular emphasis on benchmark cases with sloshing that enhances phase change, tracing their historical development, and demonstrating their predictive accuracy when compared to test results.

low-gravity fluid modeling↗

Linear solvers for power grid optimization problems: A review of GPU-accelerated linear solvers

The linear equations that arise in interior methods for constrained optimization are sparse symmetric indefinite, and they become extremely ill-conditioned as the interior method converges. These linear systems present a challenge for existing solver frameworks based on sparse LU or LDL T decompositions. Here, we benchmark five well known direct linear solver packages on CPU- and GPU-based hardware, using matrices extracted from power grid optimization problems. The achieved solution accuracy varies greatly among the packages. None of the tested packages delivers significant GPU acceleration for our test cases. For completeness of the comparison we include results for MA57, which is one of the most efficient and reliable CPU solvers for this class of problem.

97 MATHEMATICS AND COMPUTING↗

Scalable Experimental Bounds for Entangled Quantum State Fidelities

Estimating the state preparation fidelity of highly entangled states on noisy intermediate-scale quantum (NISQ) devices is important for benchmarking and application considerations. Unfortunately, exact fidelity measurements quickly become prohibitively expensive, as they scale exponentially as O(3 N for N-qubit states, using full state tomography with measurements in all Pauli bases combinations. However, Somma et al.established that the complexity could be drastically reduced when looking at fidelity lower bounds for states that exhibit symmetries, such as Dicke states and GHZ states. These bounds must still be tight enough for larger states to provide reasonable estimations on NISQ devices. For the first time and more than 15 years after the theoretical introduction, we report meaningful lower bounds for the state preparation fidelity of all Dicke states up to N=10 and all GHZ states up to N=20 on Quantinuum H1 ion-trap systems using efficient implementations of recently proposed scalable circuits for these states. Our achieved lower bounds match or exceed previously reported exact fidelities on superconducting systems for much smaller states. Furthermore, we provide evidence that for large Dicke states |$D^{N}_{N/2}\rangle$, we may resort to a GHZ-based approximate state preparation to achieve better fidelity. This work provides a path forward to benchmarking entanglement as NISQ devices improve in size and quality.

97 MATHEMATICS AND COMPUTING↗

Benchmarking image processing techniques for porosity measurement in polymer additive manufacturing: Review and experimental analysis

An image processing workflow is proposed for porosity measurement in polymer additive manufacturing. Various techniques, including global and local thresholding, region growing, and K-means clustering, were applied to microscopic images of carbon fiber reinforced acrylonitrile butadiene styrene (CF-ABS) and benchmarked for their ability to accurately measure porosity. Global methods included Otsu, minimum error, iterative, and entropy-based thresholding, while local methods included Niblack, Bernsen, Sauvola, and Bradley-Roth algorithms. Artificial uneven illumination was introduced to test local adaptive thresholds. Results showed significant differences in porosity values across methods. Otsu, region growing, and K-means clustering excelled under uniform illumination, while Sauvola and Bradley-Roth performed better with uneven illumination. Comparison with X-ray computed tomography (XCT) revealed slightly lower porosity values (2.55 %) than optimized methods (2.73–2.79 %) due to XCT's lower resolution excluding smaller pores. While XCT offers finer pore detection, it limits sample volume and underestimates porosity due to spatial variation. Validation using artificial grayscale images with 5 % porosity confirmed that Otsu, Bradley-Roth, region growing, and Sauvola algorithms produced accurate results. Although tested on a single material system, these methods can be adapted to others with optimization. In conclusion, given XCT's high computational and time costs, this study highlights suitable image processing techniques as cost-effective alternatives for porosity analysis in polymer composites.

Additive manufacturing↗

Particle collisionality in scaled kinetic plasma simulations

Kinetic plasma processes, such as magnetic reconnection, collisionless shocks, and turbulence, are fundamental to the dynamics of astrophysical and laboratory plasmas. Simulating these processes often requires particle-in-cell (PIC) methods, but the computational cost of fully kinetic simulations can necessitate the use of artificial parameters, such as a reduced speed of light and ion-to-electron mass ratio, to decrease expense. While these approximations can preserve overall dynamics under specific conditions, they introduce nontrivial impacts on particle collisionality that are not yet well understood. In this work, we develop a method to scale particle collisionality in simulations employing an artificial speed of light and/or an artificial ion-to-electron mass ratio. By introducing species-dependent scaling factors, we independently adjust inter- and intra-species collision rates to better replicate the collisional properties of the physical system. Our approach maintains the fidelity of electron and ion transport properties while preserving critical relaxation rates, such as energy exchange timescales, within the limits of weakly collisional plasma theory. Furthermore, we demonstrate the accuracy of this scaling method through benchmarking tests against theoretical relaxation rates and connecting to fluid theory, highlighting its ability to retain key transport properties. Existing collisional PIC implementations can be easily modified to include this scaling, which will enable deeper insights into the behavior of marginally collisional plasmas across various contexts.

Totorica, S. R. [Princeton Univ., NJ (United State↗