Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “AMR”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A space-time parallel algorithm with adaptive mesh refinement for computational fluid dynamics

This work describes a space-time parallel algorithm with space-time adaptive mesh refinement (AMR). AMR with subcycling is added to multigrid reduction-in-time (MGRIT) in order to provide solution efficient adaptive grids with a reduction in work performed on coarser grids. This algorithm is achieved by integrating two software libraries: XBraid (Parallel time integration with multigrid. https://computation.llnl.gov/projects/parallel-timeintegration-multigrid) and Chombo (Chombo software package for AMR applications—design document, 2014). The former is a parallel time integration library using multigrid and the latter is a massively parallel structured AMR library. Employing this adaptive space-time parallel algorithm is Chord (Comput Fluids 123:202–217, 2015), a computational fluid dynamics (CFD) application code for solving compressible fluid dynamics problems. For the same solution accuracy, speedups are demonstrated from the use of space-time parallelization over the time-sequential integration on Couette flow and Stokes’ second problem. On a transient Couette flow case, at least a 1.5× speedup is achieved, and with a time periodic problem, a speedup of up to 13.7× over the time-sequential case is obtained. In both cases, the speedup is achieved by adding processors and exploring additional parallelization in time. The numerical experiments show the algorithm is promising for CFD applications that can take advantage of the time parallelism. Future work will focus on improving the parallel performance and providing more tests with complex fluid dynamics to demonstrate the full potential of the algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Scalable and compact magnetocaloric heat pump technology

Magnetocaloric heat pumping (MCHP) promises to be more efficient than traditional vapor compression while also eliminating the deleterious effects of gaseous refrigerants. While MCHP devices have shown the temperature spans and efficiencies needed for different heating and cooling applications, they struggle to become commercially viable due to their large size and mass, and resultant high cost. This paper evaluates a baseline MCHP device and explores methods to boost its system power density (SPD). The key components of the baseline system are the gadolinium packed-particle bed active magnetic regenerator (AMR) and a magnetic source composed of permanent magnets and high permeability magnetic steel. To enhance the SPD, the paper evaluates maximizing the AMR volume, opting for first-order magnetocaloric materials, optimizing the magnet and AMR geometry, and reducing the size of magnets and magnetic steel parts. At larger thermal powers, increasing the AMR diameter and the number of magnetic poles were evaluated. Using finite element models, solid models, and estimates of magnetocaloric material performance, thermal powers ranging from 37 W to 44 kW at a nominal 10 K temperature span were projected, and SPD was estimated to improve from 6 W/kg to 81 W/kg. Neglecting end effects, an upper limit of 114 W/g is estimated. Compared to SPD of off-the-shelf compressors with similar environment temperatures, MCHP power density using gadolinium is competitive up to roughly 200 W of cooling power. This is extended to 1 kW when using LaFeSi alloys and up to 3 kW in the limiting case. In conclusion, these results indicate that the performance and mass of MCHP can match that of compressors, which is a critical step toward cost-competitive magnetocaloric technology.

42 ENGINEERING↗
DOE OSTI2022

A hybrid adaptive multiresolution approach for the efficient simulation of reactive flows

Computational studies that use block-structured adaptive mesh refinement (AMR) approaches suffer from unnecessarily high mesh resolution in regions adjacent to important solution features. This deficiency limits the performance of AMR codes. In this work a novel hybrid adaptive multiresolution (HAMR) approach to AMR-based calculations is introduced to address this issue. The multiresolution (MR) smoothness indicators are used to identify regions of smoothness on the mesh where the computational cost of individual physics solvers may be decreased by replacing direct calculations with interpolation. We suggest an approach to balance the errors due to the adaptive discretization and the interpolation of physics quantities such that the overall accuracy of the HAMR solution is consistent with that of the MR-driven AMR solution. The performance of the HAMR scheme is evaluated for a range of test problems, from pure hydrodynamics to turbulent combustion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Dominant balance-based adaptive mesh refinement for incompressible fluid flows

This work introduces a novel adaptive mesh refinement (AMR) method that utilizes dominant balance analysis (DBA) for efficient and accurate grid adaptation in computational fluid dynamics (CFD) simulations. The proposed method leverages a Gaussian mixture model (GMM) to classify grid cells into active and passive regions based on the dominant physical interactions within the equation space. By modeling truncation error probabilistically from discretized terms, the method identifies regions of high interaction where numerical accuracy is most sensitive to resolution. Unlike traditional AMR strategies, this approach does not rely on heuristic-based sensors or user-defined thresholds, providing a fully automated and problem-independent framework for AMR. Applied to the incompressible Navier-Stokes equations for steady and unsteady flow past a cylinder, the DBA-based AMR method achieves comparable accuracy to high-resolution grids while reducing computational costs by up to 70 %. The validation highlights the method’s effectiveness in capturing complex flow features while minimizing grid cells, directing computational resources toward regions with the most critical dynamics. This modular and scalable strategy is adaptable to a wide range of applications, presenting a promising tool for efficient high-fidelity simulations in CFD and other multiphysics domains.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Carrier confinement and alloy disorder exacerbate Auger–Meitner recombination in AlGaN ultraviolet light-emitting diodes

The quantum efficiency of AlGaN ultraviolet light-emitting diodes declines (droops) at increasing operating powers due to Auger–Meitner recombination (AMR). Using first-principles density-functional theory, we show that indirect AMR mediated by electron–phonon coupling and alloy disorder can induce bulk C coefficients as large as ~10 –31 cm 6 /s. Furthermore, we find that the confinement of carriers by polarization fields within quantum wells severely relaxes crystal-momentum conservation, which exacerbates the rate of AMR over radiative recombination by an order of magnitude relative to the bulk. Furthermore, this results in a striking decrease in quantum efficiency at high power. Suppressing polarization fields and jointly increasing the well width would greatly mitigate AMR and efficiency droop.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A genomic data resource for predicting antimicrobial resistance from laboratory-derived antimicrobial susceptibility phenotypes

Antimicrobial resistance (AMR) is a major global health threat that affects millions of people each year. Funding agencies worldwide and the global research community have expended considerable capital and effort tracking the evolution and spread of AMR by isolating and sequencing bacterial strains and performing antimicrobial susceptibility testing (AST). For the last several years, we have been capturing these efforts by curating data from the literature and data resources and building a set of assembled bacterial genome sequences that are paired with laboratory-derived AST data. This collection currently contains AST data for over 67 000 genomes encompassing approximately 40 genera and over 100 species. In this paper, we describe the characteristics of this collection, highlighting areas where sampling is comparatively deep or shallow, and showing areas where attention is needed from the research community to improve sampling and tracking efforts. In addition to using the data to track the evolution and spread of AMR, it also serves as a useful starting point for building machine learning models for predicting AMR phenotypes. Further, we demonstrate this by describing two machine learning models that are built from the entire dataset to show where the predictive power is comparatively high or low.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Association of Diet and Antimicrobial Resistance in Healthy U.S. Adults

Antimicrobial resistance (AMR) represents a significant source of morbidity and mortality worldwide, with expectations that AMR-associated consequences will continue to worsen throughout the coming decades. Since resistance to antibiotics is encoded in the microbiome, interventions aimed at altering the taxonomic composition of the gut might allow us to prophylactically engineer microbiomes that harbor fewer antibiotic resistant genes (ARGs). Diet is one method of intervention, and yet little is known about the association between diet and antimicrobial resistance. To address this knowledge gap, we examined diet using the food frequency questionnaire (FFQ; habitual diet) and 24-h dietary recalls (Automated Self-Administered 24-h [ASA24 ® ] tool) coupled with an analysis of the microbiome using shotgun metagenome sequencing in 290 healthy adult participants of the United States Department of Agriculture (USDA) Nutritional Phenotyping Study. We found that aminoglycosides were the most abundant and prevalent mechanism of AMR in these healthy adults and that aminoglycoside-O-phosphotransferases (aph3-dprime) correlated negatively with total calories and soluble fiber intake. Individuals in the lowest quartile of ARGs (low-ARG) consumed significantly more fiber in their diets than medium- and high-ARG individuals, which was concomitant with increased abundances of obligate anaerobes, especially from the family Clostridiaceae, in their gut microbiota. Finally, we applied machine learning to examine 387 dietary, physiological, and lifestyle features for associations with antimicrobial resistance, finding that increased phylogenetic diversity of diet was associated with low-ARG individuals. These data suggest diet may be a potential method for reducing the burden of AMR.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

AMRIC: A Novel In Situ Lossy Compression Framework for Efficient I/O in Adaptive Mesh Refinement Applications

As supercomputers advance towards exascale capabilities, computational intensity increases significantly, and the volume of data requiring storage and transmission experiences exponential growth. Adaptive Mesh Refinement (AMR) has emerged as an effective solution to address these two challenges. Concurrently, error-bounded lossy compression is recognized as one of the most efficient approaches to tackle the latter issue. Despite their respective advantages, few attempts have been made to investigate how AMR and error-bounded lossy compression can function together. To this end, this study presents a novel in-situ lossy compression framework that employs the HDF5 filter to improve both I/O costs and boost compression quality for AMR applications. We implement our solution into the AMReX framework and evaluate on two real-world AMR applications, Nyx and WarpX, on the Summit supercomputer. Experiments with 512 cores demonstrate that AMRIC improves the compression ratio by 81X and the I/O performance by 39X over AMReX's original compression solution.

Wang, Daoce↗
DOE OSTI2022

Historical review and proof-of-concept future method demonstration of adaptive mesh refinement in nuclear engineering for increased fidelity and computational efficiency

As the nuclear industry's use of computational tool increases, the need for increased fidelity and computational efficiency is well known. While most approaches to increased fidelity rely on applying a fine mesh over the problem domain, a more efficient method is to apply an adaptive mesh refinement (AMR) algorithm to the mesh definition. In the field of nuclear engineering, AMR has previously been used in conjunction with deterministic methods, including: S{sub N} transport methods, Lattice Boltzmann Methods, and COMSOL. The future of AMR in nuclear engineering is to couple it to a Monte Carlo code with the goal of reducing calculation time. A proof-of-concept example yielded positive results for using the gradient of the flux as a refinement criteria. The refinement criteria was varied from 0.01 to 0.10, which yielded a recommended range of 0.01 to 0.04, and the number of refinement iterations was varied from 0 to 7, with diminishing returns seen after 5 iterations. After the success of the proof-of-concept exercise, work began on creating a full program coupling MCNP6.2 and the AMR algorithm in the deal.II library. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

A global metagenomic map of urban microbiomes and antimicrobial resistance

We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A coupled discontinuous Galerkin-Finite Volume framework for solving gas dynamics over embedded geometries

Herein, we present a computational framework for solving the equations of inviscid gas dynamics using structured grids with embedded geometries. The novelty of the proposed approach is the use of high-order discontinuous Galerkin (dG) schemes and a shock-capturing Finite Volume (FV) scheme coupled via an hp adaptive mesh refinement (hp-AMR) strategy that offers high-order accurate resolution of the embedded geometries. The hp-AMR strategy is based on a multi-level block-structured domain partition in which each level is represented by block-structured Cartesian grids and the embedded geometry is represented implicitly by a level set function. The intersection of the embedded geometry with the grids produces the implicitly-defined mesh that consists of a collection of regular rectangular cells plus a relatively small number of irregular curved elements in the vicinity of the embedded boundaries. High-order quadrature rules for implicitly-defined domains enable high-order accuracy resolution of the curved elements with a cell-merging strategy to address the small-cell problem. The hp-AMR algorithm treats the system with a second-order finite volume scheme at the finest level to dynamically track the evolution of solution discontinuities while using dG schemes at coarser levels to provide high-order accuracy in smooth regions of the flow. On the dG levels, the methodology supports different orders of basis functions on different levels. The space-discretized governing equations are then advanced explicitly in time using high-order Runge-Kutta algorithms. Numerical tests are presented for two-dimensional and three-dimensional problems involving an ideal gas. The results are compared with both analytical solutions and experimental observations and demonstrate that the framework provides high-order accuracy for smooth flows and accurately captures solution discontinuities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Using numerical methods to screen magnetocaloric materials in an active magnetic regenerative cycle

A 2-dimensional numerical model of a room temperature operating Active Magnetic Regenerator (AMR) that comprises of a regenerator, hot and cold heat exchangers, heat transfer fluid is developed. The regenerator is made of a magnetocaloric material (MCM) which heats up upon applying a magnetic field, H, and cools down when the field is removed; thus, making it the most essential part of an AMR. The model takes experimentally measured ΔT ad (H,T) and the C p (H,T) data as input and provides quantitative performance metrics of the magnetic cooling system, such as ΔT span and the cooling load, as output. With this model, it is possible to assess a wide range of MCMs in an AMR. 4 different MCMs were investigated using this model in terms of their ΔT span and the cooling loads—LaFe 10.96 Co 0.97 Si 1.07 , MnFeP (1-x) As (x) and AlFe 2 B 2 and Gd. During the screening of MCMs, all the important operating conditions of the device were fixed such as the fluid flow rate, ambient temperature, cycle duration, magnetic field strength. Our results indicate that Gd exhibits the maximum ΔT span with respectable cooling load, while AlFe 2 B 2 generates the lowest ΔT span . Even though LaFeCoSi compound did not perform as well as Gd, it could be the MCM choice for the realization of magnetic refrigeration on a global scale due to its much lower cost.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A Phage Foundry Framework to Systematically Develop Viral Countermeasures to Combat Antibiotic-Resistant Bacterial Pathogens

At its current rate, the rise of antimicrobial-resistant (AMR) infections is predicted to paralyze our industries and healthcare facilities while becoming the leading global cause of loss of human life. With limited new antibiotics on the horizon, we need to invest in alternative solutions. Bacteriophages (phages)–viruses targeting bacteria–offer a powerful alternative approach to tackle bacterial infections. Despite recent advances in using phages to treat recalcitrant AMR infections, the field lacks systematic development of phage therapies scalable to different applications. We propose a Phage Foundry framework to establish metrics for phage characterization and to fill the knowledge and technological gaps in phage therapeutics. Coordinated investment in AMR surveillance, sampling, characterization, and data sharing procedures will enable rational exploitation of phages for treatments. A fully realized Phage Foundry will enhance the sharing of knowledge, technology, and viral reagents in an equitable manner and will accelerate the biobased economy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Angular-spatial hp -adaptivity for radiative transfer with discontinuous Galerkin spectral element methods

Radiative transfer is important for many science and engineering applications, and numerical simulations of radiative transfer can be challenging. For instance, the radiation field is seven-dimensional – three spatial, two angular, one wavelength, and one temporal – and often features steep gradients. Therefore, memory usage is a key issue. To reduce memory, some past work has investigated the use of adaptive mesh refinement (AMR), typically for either the spatial or angular coordinate, and typically for only h -adaptivity. Here, we propose the use of AMR for the spatial and angular coordinates together, and the use of h - and p -adaptivity together as hp -AMR for the potential for further memory savings. We implemented the proposed method for several test cases in two spatial and one angular dimension, with the discontinuous Galerkin spectral element method. These test cases featured highly anisotropic angular radiation, with or without steep spatial gradients. Our primary findings from these test cases were: (1) Angular hp -adaptivity can deliver the radiation solution with the same accuracy as, and with much less computational memory than, uniform angular h - or p -refinements, or angular h -adaptivity alone. This is most obvious when the incoming radiation is highly anisotropic, in which case the savings can be orders of magnitude. (2) Full spatial-angular hp -adaptivity is more efficient in solution representation, compared to solely spatial or solely angular -adaptivity. This is most evident when steep gradients are present in both the spatial and angular distribution. These results suggest that adaptive spatial- hp angular-refinement may perform well in large-scale seven-dimensional applications.

Adaptive refinement↗
DOE OSTI2020

The success of particular Acinetobacter baumannii clones: accumulating resistance and virulence inside a sugary shield

Abstract Background In Portugal, carbapenem-resistant Acinetobacter baumannii (CRAB) has been associated with ST98, ST103 and ST208 (Oxford Scheme, Oxf) and a clone has usually been associated with a particular period of time. These clonal shifts were primarily explained by an increased antimicrobial resistance profile. Here we explore genomic and biochemical differences among these and more recent clones, which could further explain the diversity and evolution of this species. Methods A total of 116 CRAB isolates (2010–15), together with representatives of a previously described CRAB collection (4 isolates, 2001–06) were characterized by attenuated total reflection Fourier transform infrared spectroscopy (FTIR-ATR) and MLST. Representatives of different FTIR-ATR/MLST clusters were selected for WGS (n = 13), which allowed the in silico extraction of resistance and virulence genes, capsule locus and SNP analysis. Results A. baumannii clonal shifts of OXA-58-producing ST103Oxf (2001–04), OXA-40-producing ST98Oxf (2002–06), OXA-23-producing ST208Oxf (2006–10) and OXA-23-producing ST218Oxf (2010–15) were accompanied by an increase in AMR genes and virulence factors. FTIR-ATR clustering was congruent with sugar composition predicted from the capsular locus: a fucosamine cluster comprising ST98Oxf, ST103Oxf and a single ST218Oxf isolate; a pseudaminic acid cluster of ST208Oxf and ST1557Oxf isolates; and legionaminic acid, resembling the sialic acid from mammalian cells, in a cluster comprising ST218Oxf isolates. The whole-genome phylogenetic tree was congruent with MLST, with isolates presenting 5–28 938 SNPs. ST208Oxf and ST218Oxf presented ∼1900 SNPs while ST103Oxf and ST1557Oxf showed a greater number of SNPs (∼28 000). Conclusions Clonal shifts of CRAB were promoted, in our country, by consecutive virulence and AMR gene pool enlargement, together with features increasing pathogen–host adaptation. Worldwide dominance of ST218Oxf is supported by the combination of high AMR and virulence levels.

Silva, Liliana↗
DOE OSTI2020

Intrinsic Mechanism for Anisotropic Magnetoresistance and Experimental Confirmation in Co{sub x}Fe{sub 1-x} Single-Crystal Fims.

Using first-principles transport calculations, we predict that the anisotropic magnetoresistance (AMR) of single-crystal CoxFe1-x alloys is strongly dependent on the current orientation and alloy concentration. An intrinsic mechanism for AMR is found to arise from the band crossing due to magnetization-dependent symmetry protection. These special k points can be shifted towards or away from the Fermi energy by varying the alloy composition and hence the exchange splitting, thus allowing AMR tunability. The prediction is confirmed by delicate transport measurements, which further reveal a reciprocal relationship of the longitudinal and transverse resistivities along different crystal axes.

Zeng, F. L.↗
DOE OSTI2024

Learning Robust Marking Policies for Adaptive Mesh Refinement

Here in this work, we revisit the marking decisions made in the standard adaptive finite element method (AFEM). Experience shows that a naïve marking policy leads to inefficient use of computational resources for adaptive mesh refinement (AMR). Consequently, using AMR in practice often involves ad-hoc or time-consuming offline parameter tuning to set appropriate parameters for the marking subroutine. To address these practical concerns, we recast AMR as a Markov decision process in which refinement parameters can be selected on-the-fly at run time, without the need for pre-tuning by expert users. In this new paradigm, the refinement parameters are also chosen adaptively via a marking policy that can be optimized using methods from reinforcement learning. We use the Poisson equation to demonstrate our techniques on h- and hp-refinement benchmark problems, and our experiments suggest that superior marking policies remain undiscovered for many classical AFEM applications. Furthermore, an unexpected observation from this work is that marking policies trained on one family of PDEs are sometimes robust enough to perform well on problems far outside the training family. For illustration, we show that a simple hp-refinement policy trained on 2D domains with only a single re-entrant corner can be deployed on far more complicated 2D domains, and even 3D domains, without significant performance loss. For reproduction and broader adoption, we accompany this work with an open-source implementation of our methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

AMReX v2024

The software framework, AMReX, supports the development of block-structured adaptive mesh refinement (AMR) algorithms for solving systems of partial differential equations. AMR reduces the computational cost and memory footprint compared to a uniform mesh while preserving the essential local descriptions of different physical processes in complex multiphysics algorithms. AMR uses a hierarchical representation of the solution at multiple levels of resolution where the solution on each level is defined on the union of data containers at that resolution. These data containers, which represent the solution over a logically rectangular subregion of the domain, can contain field data defined on a mesh, Lagrangian particles or combinations of both. In addition to these basic data types, AMReX supports a multilevel embedded boundary representation of complex geometry; linear solvers for cell-centered and nodal data; asynchronous I/O in a native format readable by ParaView, VisIt and yt; and interfaces to hypre and PETSc solvers. AMReX enables applications to run on distributed memory architectures with multicore CPUs and with GPU accelerators. AMReX uses a lightweight abstraction layer that effectively hides the details of the architecture from the application. The framework currently supports CUDA, HIP and SYCL for GPU acceleration and OpenMP for multi-core CPU architectures.

Almgren, Ann↗