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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.

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At least 487 records · Page 27

An iterative dynamic chemical stiffness removal method for reacting flow simulations

Abstract An iterative dynamic chemical stiffness removal method (IDCSR) based on quasi-steady-state approximation (QSSA) is proposed. The IDCSR method is built on a previously developed non-iterative method which has proved to work well for small timestep sizes. A novel iterative procedure is designed in IDCSR to enable explicit time integration of stiff chemistry at relatively large timestep sizes relevant to practical reacting flow simulations. The effectiveness of the iterative procedure is first demonstrated with a toy problem and homogeneous auto-ignition with fixed integration step sizes, showing that larger timestep sizes can be allowed for explicit time integration using IDCSR compared with the previous non-iterative method. IDCSR is then compared with existing explicit chemistry solvers for simulations of homogeneous auto-ignition and shows similar or lower computational cost but significantly higher accuracy across a wide range of timestep sizes. IDCSR is further combined with an automatic adaptive time-stepping scheme for simulations of 0-D homogeneous auto-ignition and a 2-D laminar lifted n -dodecane jet flame. For the 0-D auto-ignition simulations, IDCSR is shown to reduce both the error (by 43%–90%) and computational cost (by 6–15 times) compared with existing explicit solvers, while achieving speed-up factors of up to 400 compared with VODE for a wide range of timestep sizes and reaction mechanisms. For the 2-D jet flame simulations, speed-up factors of 15 and 31 for chemistry integration, and 5 and 9 for overall simulation, are achieved by IDCSR compared with CVODE with and without analytic Jacobian, respectively.

Xu, Chao (ORCID:0000000153074159)↗

The dual-electron cyclotron emission based measurement of 3D structures on DIII-D tokamak

The measurements of the locked mode and other 3D magnetohydrodynamic modes are essential for real-time control of plasma stability in future fusion reactors. Current magnetic measurements present non-negligible challenges for the application on fusion pilot plants (FPPs) due to neutron radiation and pose challenging design issues. In this paper, we discuss an alternative solution with microwave-based measurements. The dual-electron cyclotron emission (ECE) method has been developed and applied on DIII-D. The dual-ECE measurement method demonstrates clear identification of magnetic islands compared to single ECE, which is highly beneficial for locked mode feedback control on the FPPs. Toroidally separated ECE measurements provide accurate three-dimensional structure of magnetic islands and tearing modes. This technique also offers deeper physical insights into the penetration of resonant magnetic perturbations. Numerical calculations indicate that small locked modes (magnetic island width > 2 cm) can be detected using the dual-ECE measurement method in ITER plasma. This will enhance measurement capabilities for the safe operation of FPP plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Arrayed in vivo barcoding for multiplexed sequence verification of plasmid DNA and demultiplexing of pooled libraries

Sequence verification of plasmid DNA is critical for many cloning and molecular biology workflows. To leverage high-throughput sequencing, several methods have been developed that add a unique DNA barcode to individual samples prior to pooling and sequencing. However, these methods require an individual plasmid extraction and/or in vitro barcoding reaction for each sample processed, limiting throughput and adding cost. Here, we develop an arrayed in vivo plasmid barcoding platform that enables pooled plasmid extraction and library preparation for Oxford Nanopore sequencing. This method has a high accuracy and recovery rate, and greatly increases throughput and reduces cost relative to other plasmid barcoding methods or Sanger sequencing. We use in vivo barcoding to sequence verify >45 000 plasmids and show that the method can be used to transform error-containing dispersed plasmid pools into sequence-perfect arrays or well-balanced pools. In vivo barcoding does not require any specialized equipment beyond a low-overhead Oxford Nanopore sequencer, enabling most labs to flexibly process hundreds to thousands of plasmids in parallel.

59 BASIC BIOLOGICAL SCIENCES↗

De novo Materials Design of Catalytic Surface Motifs for Water-Gas-Shift (Final Progress Report DOE Grant DE-SC0019281)

This project was aimed at developing innovative theoretical methods and models to understand essential catalysis-relevant issues such as CO 2 conversion, fuel cells, and lithium batteries. Through collaborations with experimentalists, we strive to develop new quantum and machine learning methods for the understanding of surface and interfacial chemistry that can empower the design of energy and sustainability systems. Overall, our work under this grant brings cross-disciplinary insights into catalytic materials, microenvironments, and other conditions, which can serve to provide design rules for the next generation of catalysts.

25 ENERGY STORAGE↗

An ICP-OES method for the precise and accurate quantification of rare earth elements in natural water: A comparative study from mine waste sites in New Mexico, USA

Inductively coupled plasma techniques such as ICP-OES and ICP-MS are routinely used to determine the concentrations of rare earth elements (REE) in water samples. However, their performance for the determination of REE concentration in mine drainage waters from epithermal vein and porphyry copper mining districts has not been evaluated extensively. In this work, we develop an REE analysis method on an Agilent 5900 ICP-OES instrument and assess the accuracy and precision for the quantification of REE in the natural waters collected from mine adits and an acid seep of mine sites in the Steeple Rock and Hillsboro mining districts, New Mexico, USA. The total REE concentrations in the water samples were measured using the methods we developed for both ICP-OES and ICP-MS. The power of the new ICP-OES method lies in routine analysis of μg/L level concentrations normally analyzed using ICP-MS, including a U.S. Geological Survey standard reference sample, laboratory blank samples spiked with a National Institute of Standards and Technology traceable standard, and surface water samples from mine waste sites. This ICP-OES method achieves low quantification limits ranging from 0.2 to 5 μg/L and excellent analytical accuracy and precision for REE analysis. The precision of light (La-Gd) and heavy (Tb-Lu) REE analysis using this method are better than 5% at average concentrations above 5 ± 4 μg/L and 3 ± 2 μg/L, respectively, and 3% at average concentrations above 10 ± 9 μg/L and 5 ± 4 μg/L, respectively. This method also shows excellent sensitivity and reproducibility for our laboratory and field samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Synthetic Control of Water-Stable Hybrid Perovskitoid Semiconductors

Hybrid metal-halide perovskites and their derived materials have emerged as the next-generation semiconductors with a wide range of applications, including photovoltaics, light-emitting devices, and other optoelectronics. Over the past decade, numerous single-crystalline perovskite derivatives have been synthesized and developed. However, the synthetic methods for these derivatives mainly rely on acidic crystallization conditions. This approach leads to crystals comprising metal halide building blocks, which show problematic stability when directly exposed to water. In this study, a methodology is developed for synthesizing hybrid metal-halide compounds using lead iodide and the zwitterionic bifunctional molecule cysteamine (CYS), to form various perovskitoid structures under a broad pH range. Interestingly, the different pH conditions alter the coordination environment of lead halides, leading to lead-sulfide and lead-nitride covalent bond formation. This modification significantly enhances their stability when in direct contact with water, lasting for months. Photoluminescence measurements and first principal density functional theory (DFT) calculations reveal that the perovskitoids synthesized under basic and acidic pH conditions exhibit a direct bandgap nature, while those synthesized under neutral conditions display an indirect bandgap. This approach opens new avenues for manipulating synthetic methods to develop water-stable hybrid semiconductors suitable for a wide range of applications, such as solid-state light emitters.

36 MATERIALS SCIENCE↗

Structure-aware annotation of leucine-rich repeat domains

Protein domain annotation is typically done by predictive models such as HMMs trained on sequence motifs. However, sequence-based annotation methods are prone to error, particularly in calling domain boundaries and motifs within them. These methods are limited by a lack of structural information accessible to the model. With the advent of deep learning-based protein structure prediction, existing sequenced-based domain annotation methods can be improved by taking into account the geometry of protein structures. We develop dimensionality reduction methods to annotate repeat units of the Leucine Rich Repeat solenoid domain. The methods are able to correct mistakes made by existing machine learning-based annotation tools and enable the automated detection of hairpin loops and structural anomalies in the solenoid. The methods are applied to 127 predicted structures of LRR-containing intracellular innate immune proteins in the model plant Arabidopsis thaliana and validated against a benchmark dataset of 172 manually-annotated LRR domains.

Xu, Boyan↗

An Open-Source Coupling for Depletion During Fuel Cycle Modeling

Fuel depletion is an important aspect of fuel cycle modeling, allowing a user to account for how loaded fuel compositions affect in-core and spent fuel compositions and their related fuel cycle metrics. Therefore, multiple methods have been developed to account for depletion within fuel cycle simulations. This work adds to that list of methods by introducing an open-source coupling between C$\scriptsize{YCLUS}$ and OpenMC to perform fuel depletion during a fuel cycle simulation, called OpenMCyclus. This work explains the methodology of OpenMCyclus and presents a benchmark comparison between the performance of OpenMCyclus and another C$\scriptsize{YCLUS}$ archetype that uses recipes to define spent fuel compositions. In conclusion, the development of this coupling expands the functionalities possible through C$\scriptsize{YCLUS}$ by providing real-time fuel depletion that is reactor agnostic and open source.

C$\scriptsize{YCLUS}$↗

Using Filter Methods to Guide Convergence for ADMM, with Applications to Nonnegative Matrix Factorization Problems

Nonconvex, nonlinear optimization problems arise naturally in parameter fitting and machine learning. While augmented Lagrangian methods have demonstrated robust convergence for classes of these problems, their convergence for block updates has been relatively unexplored outside of the context of the alternating direction method of multipliers (ADMM). ADMM has seen extensive use in these applications, but may exhibit uncertain convergence behavior in many practical nonconvex settings, and struggles with general nonlinear constraints. In contrast, filter methods have proved effective in enforcing convergence for sequential quadratic programming methods and interior point methods with feasibility criteria. We develop an ADMM-filter method for highly nonlinear and nonconvex problems. Here, we show convergence under mild assumptions for several types of coordinate descent schemes, and demonstrate our algorithm on nonnegative matrix factorization and completion problems in imaging and chemical spectrum analysis.

Nonconvex optimization↗

Recent Developments in DFTB+, a Software Package for Efficient Atomistic Quantum Mechanical Simulations

DFTB+ is a flexible, open-source software package developed by its community, designed for fast and efficient atomistic quantum mechanical simulations. It employs various methods that approximate density functional theory (DFT), such as density functional-based tight binding (DFTB) and the extended tight binding (xTB) approach allowing simulations of large systems over extended time scales with reasonable accuracy, while being significantly faster than traditional ab initio methods. In recent years, several new extensions of the DFTB method have been developed and implemented in the DFTB+ program package in order to improve the accuracy and generality of the available simulation results. In this paper, we review those enhancements, show several use case examples and discuss the strengths and limitations of its features.

36 MATERIALS SCIENCE↗

Functional Data Analysis in Wearable Body Sensor Networks

Improving response time of indirect room-size calorimeters is still an outstanding problem in metabolic research. Accurate estimates of instantaneous rates of gaseous exchange require numerical differentiation of measured gaseousgas concentrations. We propose a new method to estimate the instantaneous gaseousgas exchange rates in indirect calorimetry. In contrast to the previously developed techniques, the method addresses the problem of differentiation of gaseous concentrations as an ill-posed problem. By applying the method of regularization, the problem of differentiation is converted into a well-posed problem resulting in smooth and consistent gaseous exchange rates. The validity of the method is tested on a large dataset of calorimeter experiments which included 313 human experiments along with 231 alcohol combustion experiments. It is demonstrated that the method is able to reliably differentiate between the “unphysiological” process of alcohol combustion and physiological variations produced by human metabolism. The method also allowed unraveling the previously unreported relative kinetics of O2 consumption and Respiratory Quotient (RQ) in humans. It was found that the kinetics of oxidative fuel selection lags behind the energy expenditure in humans exhibiting some sort of oxidative inertia. The time lag varies from 2-3 min up to 30 min, depending on particular individual. No such lag was found in alcohol combustion experiments. In addition to the relative kinetics of substrate oxidation, two statistical indexes reflecting variability of minute-by-minute RQ were estimated. The indexes were the RQ’s standard deviation and RQ’s first-order derivative. Both indexes showed statistically significant difference between human experiments and alcohol combustion experiments. We conclude that the proposed method can consistently extract physiologically-relevant information from noisy calorimetry data and the aforesaid information can provide additional insights into the mechanism of metabolic fuel selection in humans.

54 ENVIRONMENTAL SCIENCES↗

Functional Data Analysis in Wearable Body Sensor Networks

Improving response time of indirect room-size calorimeters is still an outstanding problem in metabolic research. Accurate estimates of instantaneous rates of gaseous exchange require numerical differentiation of measured gaseousgas concentrations. We propose a new method to estimate the instantaneous gaseousgas exchange rates in indirect calorimetry. In contrast to the previously developed techniques, the method addresses the problem of differentiation of gaseous concentrations as an ill-posed problem. By applying the method of regularization, the problem of differentiation is converted into a well-posed problem resulting in smooth and consistent gaseous exchange rates. The validity of the method is tested on a large dataset of calorimeter experiments which included 313 human experiments along with 231 alcohol combustion experiments. It is demonstrated that the method is able to reliably differentiate between the “unphysiological” process of alcohol combustion and physiological variations produced by human metabolism. The method also allowed unraveling the previously unreported relative kinetics of O2 consumption and Respiratory Quotient (RQ) in humans. It was found that the kinetics of oxidative fuel selection lags behind the energy expenditure in humans exhibiting some sort of oxidative inertia. The time lag varies from 2-3 min up to 30 min, depending on particular individual. No such lag was found in alcohol combustion experiments. In addition to the relative kinetics of substrate oxidation, two statistical indexes reflecting variability of minute-by-minute RQ were estimated. The indexes were the RQ’s standard deviation and RQ’s first-order derivative. Both indexes showed statistically significant difference between human experiments and alcohol combustion experiments. We conclude that the proposed method can consistently extract physiologically-relevant information from noisy calorimetry data and the aforesaid information can provide additional insights into the mechanism of metabolic fuel selection in humans.

60 - APPLIED LIFE SCIENCES↗

Molten Salt Reactor Safety Assessment - Three Approaches to A Common Objective

Safety adequacy assessment is central to nuclear power plant (NPP) licensing. Either NPP accident mitigation or prevention can result in adequate safety. Accident prevention, along with the the prevention of accident escalation, can be evaluated using either deterministic or probabilistic methods. Acceptable means to develop principal design criteria (PDCs) via probabilistic methods are provided in NRC Regulatory Guide 1.233 while advanced reactor design criteria are provided in NRC Regulatory Guide 1.232 (RG 1.232). Accident mitigation-based regulatory guidance for non-power reactors is provided in NUREG 1537. While RG 1.232 included class specific guidance for both sodium-cooled fast reactors and modular high-temperature gas-cooled reactors, it did not provide molten salt reactor (MSR) class specific guidance. Class specific design criteria more closely align with reactors in their class so will require less effort to employ to develop design specific PDCs. The American Nuclear Society has recently released a liquid-fueled MSR design safety standard (ANSI/ANS-20.2-2023) that provides class specific design criteria.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Electron-impact ionization from excited states method

We present a distorted-wave with exchange (DWE) formulation for computing electron-impact ionization (EII) cross sections within the recently developed excited states method (ESM) for plasmas. The ESM provides a self-consistent quantum-mechanical description of both bound and continuum electronic states in dense plasmas, incorporating finite-temperature and screening effects absent in isolated-atom approaches. Using this framework, we calculate EII cross sections for lithium across a wide range of temperatures and densities. We show that the ESM reproduces the isolated-atom limit at low densities while capturing strong plasma effects, such as pressure ionization and shape resonances, at solid density. Comparisons with isolated-atom DWE and average-atom (AA) calculations reveal that, although AA cross sections can approximate configuration average behavior, the ESM provides more accurate, state-resolved answers. In conclusion, these results demonstrate that the ESM allows one to obtain rate coefficients for collisional-radiative modeling of plasmas out of local thermodynamical equilibrium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Unified Analytical Method Greenness Score ( uAMGS ) Quantifies How Microscopic Imaging Is Greener Than Conventional Liquid Chromatography

Green chemistry is a set of principles for assessing, developing, and implementing methods that are safer, more efficient, and less detrimental to the environment. The analytical method greenness score (AMGS) is one of many metrics that attempt to evaluate traditional liquid chromatography (LC) based on the energy consumption of the instrument and the safety, health risks, and environmental impact of the solvents employed. Unfortunately, in practice, the AMGS is primarily focused on traditional separation methods in the pharmaceutical industry and is not amenable to cutting-edge separation science, including miniaturization. To broaden this scope, the unified Analytical Method Greenness Score (uAMGS) is presented here, which clarifies and expands on the underlying mathematics and incorporates both dimensional and uncertainty analysis, enabling its application to a broader range of analytical techniques. The uAMGS is used to compare the greenness of two distinct methods: single-molecule microscopy (SMM) and high-performance liquid chromatography (HPLC), which were used to collect equivalent data. uAMGS determines that SMM is significantly greener than HPLC due primarily to decreased solvent consumption. Overall, the uAMGS should allow chemists ranging from undergraduates to industrial PhDs to assess the greenness of a wide range of separations.

chemical separations↗

Method for Real-Time Salt Aerosol Concentration and Size Measurements for Molten Salt Reactor Safety Assessments

Licensing a new nuclear reactor involves evaluating credible accident scenarios by developing models that simulate accident progression to predict possible outcomes and their impact on safety. The formation of radionuclide-bearing aerosols in the respirable size range can significantly affect dose consequence and threaten human health and is therefore a focus of nuclear reactor safety assessments. Recent reviews of the literature identified a lack of existing experimental data describing the mechanisms of formation and properties (size, concentration, and composition) of radionuclide-bearing aerosols that may be produced from molten salt reactor (MSR) facilities during postulated accident scenarios. Experiments on aerosol formation from molten salt systems are a high priority need that will support MSR licensing by indicating the radiological consequences of aerosol formation and providing the data required for model development and validation. The evolving conditions that occur during a MSR accident, such as a spill of molten fuel salt, may affect aerosol formation mechanisms and aerosol properties over time. There is a need to conduct experiments that simulate credible MSR accidents in a laboratory to generate aerosols with realistic characteristics and behaviors and a need to measure these aerosols in real time under accident-relevant conditions. This report describes the development of a method that can be used to quantify the size and concentration of salt aerosol particles that form from molten salt systems in real time. This method will be employed in future integral effects tests that are conducted at an engineering scale to simulate realistic MSR accidents and in future separate effects tests that will provide mechanistic insight into aerosol formation and properties to support process model development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗