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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

AMR Magnetic Sensors in Flux Expulsion Studies

Magnetic flux expulsion properties of the superconducting material such as bulk niobium, widely used for the radio-frequency cavity fabrication, substantially affect the performance characteristics of the cavities. The quality factor of the SRF resonators can be significantly compromised due to the presence of the trapped flux vortices causing additional RF energy losses in the material. Large number of experiments have been carried out by different research groups to establish the correlation of the flux trapping in niobium cavities with the presence of impurities in niobium as well as various surface treatment methods. Majority of these experiments utilize commercially available cryogenic fluxgate magnetic sensors to measure the field before and after the niobium transition to the superconducting state to quantify the amount of flux trapped. One disadvantage of the typically used fluxgates is the size of the sensing volume. As an example, the Barting-ton F and G type cryogenic fluxgates have a sensing core length of about 30mm, which is comparable to the curvature radius of the cavity walls and hence the magnetic field lines curvature radius after the expulsion. Thus, the measured field value needs to be corrected to account for the sensor effective averaging over the sensing volume. In case of the sharper geometries, for instance if the flux expulsion to be measured on the edge of the rectangular niobium flat sheet with a thickness of ~5mm, the use of the fluxgate would be impractical.

Netepenko, A.↗
DOE OSTI2023

Review AMR 2023 Presentation

Provide a an overall outline of the project for durable low-cost pressure vessels for bulk hydrogen storage. Includes project objectives, benefits, task, results and concluding remarks.

25 ENERGY STORAGE↗
DOE OSTI2022

Proteomic Signatures of Antimicrobial Resistance in Yersinia pestis and Francisella tularensis

Antimicrobial resistance (AMR) is a well-recognized, widespread, and growing issue of concern. With increasing incidence of AMR, the ability to respond quickly to infection with or exposure to an AMR pathogen is critical. Approaches that could accurately and more quickly identify whether a pathogen is AMR also are needed to more rapidly respond to existing and emerging biological threats. We examined proteins associated with paired AMR and antimicrobial susceptible (AMS) strains of Yersinia pestis and Francisella tularensis, causative agents of the diseases plague and tularemia, respectively, to identify whether potential existed to use proteins as signatures of AMR. We found that protein expression was significantly impacted by AMR status. Antimicrobial resistance-conferring proteins were expressed even in the absence of antibiotics in growth media, and the abundance of 10–20% of cellular proteins beyond those that directly confer AMR also were significantly changed in both Y. pestis and F. tularensis. Most strikingly, the abundance of proteins involved in specific metabolic pathways and biological functions was altered in all AMR strains examined, independent of species, resistance mechanism, and affected cellular antimicrobial target. We have identified features that distinguish between AMR and AMS strains, including a subset of features shared across species with different resistance mechanisms, which suggest shared biological signatures of resistance. These features could form the basis of novel approaches to identify AMR phenotypes in unknown strains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Investigation on the two-stage active magnetic regenerative refrigerator for liquefaction of hydrogen

An active magnetic regenerative refrigerator (AMRR) is expected to be useful for hydrogen liquefaction due to its inherent high thermodynamic efficiency. Because the temperature of the cold end of the refrigerator has to be approximately liquid temperature, a large temperature span of the active magnetic regenerator (AMR) is indispensable when the heat sink temperature is liquid nitrogen temperature or higher. Since magnetic refrigerants are only effective in the vicinity of their own transition temperatures, which limit the temperature span of the AMR, an innovative structure is needed to increase the temperature span. The AMR must be a layered structure and the thermophysical matching of magnetic field and flow convection effects is very important. In order to design an AMR for liquefaction of hydrogen, the implementation of multi-layered AMR with different magnetic refrigerants is explored with multi-staging. In this paper, the performance of the multi-layered AMR using four rare-earth compounds (GdNi{sub 2}, Gd{sub 0.1}Dy{sub 0.9}Ni{sub 2}, Dy{sub 0.85}Er{sub 0.15}Al{sub 2}, Dy{sub 0.5}Er{sub 0.5}Al{sub 2}) is investigated. The experimental apparatus includes two-stage active magnetic regenerator containing two different magnetic refrigerants each. A liquid nitrogen reservoir connected to the warm end of the AMR maintains the temperature of the warm end around 77 K. High-pressure helium gas is employed as a heat transfer fluid in the AMR and the maximum magnetic field of 4 T is supplied by the low temperature superconducting (LTS) magnet. The temperature span with the variation of parameters such as phase difference between magnetic field and mass flow rate of magnetic refrigerants in AMR is investigated. The maximum temperature span in the experiment is recorded as 50 K and several performance issues have been discussed in this paper.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

An accurate and interpretable model for antimicrobial resistance in pathogenic Escherichia coli from livestock and companion animal species

Understanding the microbial genomic contributors to antimicrobial resistance (AMR) is essential for early detection of emerging AMR infections, a pressing global health threat in human and veterinary medicine. Here we used whole genome sequencing and antibiotic susceptibility test data from 980 disease causing Escherichia coli isolated from companion and farm animals to model AMR genotypes and phenotypes for 24 antibiotics. We determined the strength of genotype-to-phenotype relationships for 197 AMR genes with elastic net logistic regression. Model predictors were designed to evaluate different potential modes of AMR genotype translation into resistance phenotypes. Our results show a model that considers the presence of individual AMR genes and total number of AMR genes present from a set of genes known to confer resistance was able to accurately predict isolate resistance on average (mean F 1 score = 98.0%, SD = 2.3%, mean accuracy = 98.2%, SD = 2.7%). However, fitted models sometimes varied for antibiotics in the same class and for the same antibiotic across animal hosts, suggesting heterogeneity in the genetic determinants of AMR resistance. We conclude that an interpretable AMR prediction model can be used to accurately predict resistance phenotypes across multiple host species and reveal testable hypotheses about how the mechanism of resistance may vary across antibiotics within the same class and across animal hosts for the same antibiotic.

Chung, Henri C.↗
DOE OSTI2016

An Adaptive Mesh Algorithm: Mesh Structure and Generation

The purpose of Adaptive Mesh Refinement is to minimize spatial errors over the computational space not to minimize the number of computational elements. The additional result of the technique is that it may reduce the number of computational elements needed to retain a given level of spatial accuracy. Adaptive mesh refinement is a computational technique used to dynamically select, over a region of space, a set of computational elements designed to minimize spatial error in the computational model of a physical process. The fundamental idea is to increase the mesh resolution in regions where the physical variables are represented by a broad spectrum of modes in k-space, hence increasing the effective global spectral coverage of those physical variables. In addition, the selection of the spatially distributed elements is done dynamically by cyclically adjusting the mesh to follow the spectral evolution of the system. Over the years three types of AMR schemes have evolved; block, patch and locally refined AMR. In block and patch AMR logical blocks of various grid sizes are overlaid to span the physical space of interest, whereas in locally refined AMR no logical blocks are employed but locally nested mesh levels are used to span the physical space. The distinction between block and patch AMR is that in block AMR the original blocks refine and coarsen entirely in time, whereas in patch AMR the patches change location and zone size with time. The type of AMR described herein is a locally refi ned AMR. In the algorithm described, at any point in physical space only one zone exists at whatever level of mesh that is appropriate for that physical location. The dynamic creation of a locally refi ned computational mesh is made practical by a judicious selection of mesh rules. With these rules the mesh is evolved via a mesh potential designed to concentrate the nest mesh in regions where the physics is modally dense, and coarsen zones in regions where the physics is modally sparse.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Whole-Genome Sequence Analysis of Antimicrobial Resistance Genes in Streptococcus uberis and Streptococcus dysgalactiae Isolates from Canadian Dairy Herds

The objectives of this study are to determine the occurrence of antimicrobial resistance (AMR) genes using whole-genome sequence (WGS) of Streptococcus uberis (S. uberis) and Streptococcus dysgalactiae (S. dysgalactiae) isolates, recovered from dairy cows in the Canadian Maritime Provinces. A secondary objective included the exploration of the association between phenotypic AMR and the genomic characteristics (genome size, guanine–cytosine content, and occurrence of unique gene sequences). Initially, 91 isolates were sequenced, and of these isolates, 89 were assembled. Furthermore, 16 isolates were excluded due to larger than expected genomic sizes (>2.3 bp × 1,000 bp). In the final analysis, 73 were used with complete WGS and minimum inhibitory concentration records, which were part of the previous phenotypic AMR study, representing 18 dairy herds from the Maritime region of Canada (1). A total of 23 unique AMR gene sequences were found in the bacterial genomes, with a mean number of 8.1 (minimum: 5; maximum: 13) per genome. Overall, there were 10 AMR genes [ANT(6), TEM-127, TEM-163, TEM-89, TEM-95, Linb, Lnub, Ermb, Ermc, and TetS] present only in S. uberis genomes and 2 genes unique (EF-TU and TEM-71) to the S. dysgalactiae genomes; 11 AMR genes [APH(3'), TEM-1, TEM-136, TEM-157, TEM-47, TetM, bl2b, gyrA, parE, phoP, and rpoB] were found in both bacterial species. Two-way tabulations showed association between the phenotypic susceptibility to lincosamides and the presence of linB (P = 0.002) and lnuB (P < 0.001) genes and the between the presence of tetM (P = 0.015) and tetS (P = 0.064) genes and phenotypic resistance to tetracyclines only for the S. uberis isolates. The logistic model showed that the odds of resistance (to any of the phenotypically tested antimicrobials) was 4.35 times higher when there were >11 AMR genes present in the genome, compared with <7 AMR genes (P < 0.001). The odds of resistance was lower for S. dysgalactiae than S. uberis (P = 0.031). When the within-herd somatic cell count was >250,000 cells/mL, a trend toward higher odds of resistance compared with the baseline category of <150,000 cells/mL was observed. When the isolate corresponded to a post-mastitis sample, there were lower odds of resistance when compared with non-clinical isolates (P = 0.01). The results of this study showed the strength of associations between phenotypic AMR resistance of both mastitis pathogens and their genotypic resistome and other epidemiological characteristics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Preliminary Analysis of a Fully Solid State Magnetocaloric Refrigeration

Magnetocaloric refrigeration is an alternative refrigeration technology with significant potential energy savings compared to conventional vapor compression refrigeration technology. Most of the reported active magnetic regenerator (AMR) systems that operate based on the magnetocaloric effect use heat transfer fluid to exchange heat, which results in complicated mechanical subsystems and components such as rotating valves and hydraulic pumps. In this paper, we propose an alternative mechanism for heat transfer between the AMR and the heat source/sink. High-conductivity moving rods/sheets (e.g. copper, brass, iron, graphite, aluminum or composite structures from these) are utilized instead of heat transfer fluid significantly enhancing the heat transfer rate hence cooling/heating capacity. A one-dimensional model is developed to study the solid state AMR. In this model, the heat exchange between the solid-solid interfaces is modeled via a contact conductance, which depends on the interface apparent pressure, material hardness, thermal conductivity, surface roughness, surface slope between the interfaces, and material filled in the gap between the interfaces. Due to the tremendous impact of the heat exchange on the AMR cycle performance, a sensitivity analysis is conducted employing a response surface method, in which the apparent pressure, effective surface roughness and grease thermal conductivity are the uncertainty factors. COP and refrigeration capacity are presented as the response in the sensitivity analysis to reveal the important factors influencing the fully solid state AMR and optimize the solid state AMR efficiency. The performances of fully solid state AMR and traditional AMR are also compared and discussed in present work. The results of this study will provide general guidelines for designing high performance solid state AMR systems.

Abdelaziz, Omar↗
DOE OSTI2021

Predicting Antimicrobial Resistance Using Partial Genome Alignments

Antimicrobial resistance (AMR) is an important global health threat that impacts millions of people worldwide each year. Developing methods that can detect and predict AMR phenotypes can help to mitigate the spread of AMR by informing clinical decision making and appropriate mitigation strategies. Many bioinformatic methods have been developed for predicting AMR phenotypes from whole-genome sequences and AMR genes, but recent studies have indicated that predictions can be made from incomplete genome sequence data. In order to more systematically understand this, we built random forest-based machine learning classifiers for predicting susceptible and resistant phenotypes for Klebsiella pneumoniae (1,640 strains), Mycobacterium tuberculosis (2,497 strains), and Salmonella enterica (1,981 strains). We started by building models from alignments that were based on a reference chromosome for each species. We then subsampled each chromosomal alignment and built models for the resulting subalignments, finding that very small regions, representing approximately 0.1 to 0.2% of the chromosome, are predictive. In K. pneumoniae, M. tuberculosis, and S. enterica, the subalignments are able to predict multiple AMR phenotypes with at least 70% accuracy, even though most do not encode an AMR-related function. We used these models to identify regions of the chromosome with high and low predictive signals. Finally, subalignments that retain high accuracy across larger phylogenetic distances were examined in greater detail, revealing genes and intergenic regions with potential links to AMR, virulence, transport, and survival under stress conditions. IMPORTANCE Antimicrobial resistance causes thousands of deaths annually worldwide. Understanding the regions of the genome that are involved in antimicrobial resistance is important for developing mitigation strategies and preventing transmission. Machine learning models are capable of predicting antimicrobial resistance phenotypes from bacterial genome sequence data by identifying resistance genes, mutations, and other correlated features. They are also capable of implicating regions of the genome that have not been previously characterized as being involved in resistance. In this study, we generated global chromosomal alignments for Klebsiella pneumoniae, Mycobacterium tuberculosis, and Salmonella enterica and systematically searched them for small conserved regions of the genome that enable the prediction of antimicrobial resistance phenotypes. In addition to known antimicrobial resistance genes, this analysis identified genes involved in virulence and transport functions, as well as many genes with no previous implication in antimicrobial resistance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Comparison Study of Conventional and Adaptive Mesh Refinement in Organic Material Decomposition Models

This study compares conventional mesh refinement techniques, specifically Uniform Mesh Refinement (UMR), with a new Adaptive Mesh Refinement (AMR) method, applied to Organic Material Decomposition (OMD) models. The proposed benefit of AMR is that only areas that require refinement, based on minimizing a specific field gradient, are refined thus decreasing model wall time compared to conventional UMR methods. This work specifically focuses on comparing UMR and AMR methods on decomposing (both No-Flow and Porous-Flow material models) Polymeric Methylene Diisocyanate (PMDI) polyurethane foam. Throughout the work, the geometry increased in complexity to assess the refinement methods performance at varying levels geometric intricacy. While AMR has been shown to work well in a variety of applications, the UMR approach proved to be computationally faster, for many of the geometries and foam decomposition models, than AMR. However, it was observed that at higher levels of refinement, greater than 3 UMR, AMR begins to be computationally better. Additionally, the settings used to perform AMR greatly impact its performance, and lessons learned, in terms of OMD models, are shared. Due to physics involved in material decomposition, specifically the evolution of state variables, these problems don’t fully benefit from the advantages of AMR.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Magnetic refrigeration system with separated inlet and outlet flow

An active magnetic regenerative (AMR) refrigerator apparatus can include at least one AMR bed with a first end and a second end and a first heat exchanger (HEX) with a first end and a second end. The AMR refrigerator can also include a first pipe that fluidly connects the first end of the first HEX to the first end of the AMR bed and a second pipe that fluidly connects the second end of the first HEX to the first end of the AMR bed. The first pipe can divide into two or more sub-passages at the AMR bed. The second pipe can divide into two or more sub-passages at the AMR bed. The sub-passages of the first pipe and the second pipe can interleave at the AMR bed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Propane Liquefaction with an Active Magnetic Regenerative Liquefier

Magnetic refrigeration is a cooling technique that uses the magnetocaloric e?ect (MCE). The active magnetic regenerator (AMR) cycle is a regenerative cycle that employs the MCE and consists of four steps: adiabatic magnetization with no heat transfer gas flow; heat transfer gas flow at constant high field; demagnetization with no heat transfer gas flow; and heat transfer gas flow at constant low field. The first heat transfer gas cold-to-hot flow step rejects heat from the magnetized regenerator to a hot sink and the second reverse heat transfer gas hot-to-cold flow step add heat from a cold source into the demagnetized regenerator. Our primary research and development objective is to use the MCE for more efficient liquefaction of much colder cryogens, to help identify problems of effective coupling of cold heat transfer gas of a single-stage reciprocating magnetic refrigerator to a process gas, we have used a single-stage active magnetic regenerative refrigerator (AMRR) with Gd refrigerant to liquefy pure propane gas at two different supply pressures. The high-purity propane was supplied from a small regulated lecture bottle at 295 K via a 1.6 mm o.d. stainless-steel tube into the helium-cooled coiled-fin tube heat exchanger at 49 psia or 27 psia, to liquefy propane at 262 K or 246 K, respectively. Propane liquefied until the small collection vessel and the coiled fin tube heat exchanger were filled at which the flow from the open lecture bottle stopped. The measured rate of liquefaction and the elapsed time for each case were measured and used to determine the volume of propane collected and the cooling power of the AMRR at the liquefaction temperatures. These cooling power results were compared to the cooling power results obtained from the curve of cool-down temperature vs. time data and agreement was excellent after the duty cycle of each cooling process was properly treated.

propane, liquefaction, active magnetic regenerator↗
DOE OSTI2017

A numerical analysis of a magnetocaloric refrigerator with a 16-layer regenerator

A numerical analysis was conducted to study a room temperature magnetocaloric refrigerator with a 16-layer parallel plates active magnetic regenerator (AMR). Sixteen layers of LaFeMnSiH having different Curie temperatures were employed as magnetocaloric material (MCM) in the regenerator. Measured properties data was used. A transient one dimensional (1D) model was employed, in which a unique numerical method was developed to significantly accelerate the simulation speed of the multi-layer AMR system. As a result, the computation speed of a multi-layer AMR case was very close to the single-layer configuration. The performance of the 16-layer AMR system in different frequencies and utilizations has been investigated using this model. To optimize the layer length distribution of the 16-layer MCMs in the regenerator, a set of 137 simulations with different MCM distributions based on the Design of Experiments (DoE) method was conducted and the results were analyzed. The results show that the 16-layer AMR system can operate up to 84% of Carnot cycle COP at a temperature span of 41 K, which cannot be obtained using an AMR with fewer layers. Here, the DoE results indicate that for a 16-layer AMR system, the uniform distribution is very close to the optimized design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Systematic evaluation of magnetic sensitivities of anisotropic magnetoresistive sensors at liquid helium temperature for superconducting cavities

Trapped magnetic flux in bulk superconductors reduces the quality factor Q in superconducting radio-frequency (SRF) cavities. However, the mechanisms underlying flux trapping and radio-frequency loss are not well understood. Detailed observation of the magnetic distributions is important for understanding such phenomena. Magnetic field mapping is useful for observing the magnetic field distribution around SRF cavities. Measuring the change in the magnetic field around the cavity elucidates the flux trapping behavior. Anisotropic magnetoresistive (AMR) sensors are inexpensive and small devices that can detect magnetic flux density. The magnetic sensitivities of AMR sensors need to be evaluated at liquid helium temperature for the magnetic field mapping of SRF cavities. In this study, a test stand was constructed to calibrate the magnetic sensitivities of AMR sensors in liquid helium, and 110 AMR sensors were tested using this stand. The magnetic sensitivities were evaluated systematically. A solenoid coil was used to control the uniform external magnetic field and to measure the magnetic sensitivity at low temperatures. All AMR sensors exhibited suitable sensitivities to the magnetic field around the SRF cavity. The variation in these sensitivities in all AMR sensors was ~1%. Further, the AMR sensors were found to have sufficient sensitivity for mapping the magnetic field around the exterior surface of the SRF cavity.

43 PARTICLE ACCELERATORS↗