Search NASA⌕ Search

SEARCH · Search NASA

Results for “experimental methods development”

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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

X-Ray Phase Contrast Imaging for Dynamic Material Mix Experiments, LAO-003-17, Year 3 of 3

X-ray phase contrast imaging with transmission gratings for density profile measurements has been developed and tested for dynamic experimental applications. Talbot-Lau x-ray deflectometry is a new method of measuring x-ray refraction in addition to attenuation and ultrasmall-angle scattering that has recently been developed for static imaging, primarily for medical and industrial applications. To obtain density profiles from fast-evolving systems, we must use a flash x-ray source with a spot size much larger than the continuous microfocus sources of static imaging systems, and we can obtain only a single exposure. The challenges to measuring electron density profiles of two mixed elements from a single-image, low spatial resolution system are addressed, and initial results from the first dynamic experiments with one such system, conducted on a gas launcher at the end of FY 2018 and beginning of FY 2019, are presented. In FY 2019, we designed and built a new deflectometer designed for detonator experiments to test new techniques to improve the sensitivity and reliability of the diagnostic.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Determining HPGe Total Detection Efficiency Using γ–γ Coincidence

Abstract Both the peak and total detection efficiencies are generally needed in order to calculate sample activity from a gamma spectroscopic measurement, except in the case of isotope specific calibration. This is particularly true when the sample is in close proximity to the detector and corrections for cascade summing effects are required to avoid significant inaccuracy in the result. These corrections use the total detection efficiency to correct for summing-in and summing-out events, and the extent of the correction depends on both the geometry and the gamma cascade for the isotope in question. Experimentally determining the total efficiency is a labor intensive endeavor requiring multiple measurements with a set of single-gamma-emitting standards. Modeling the total efficiency vs. energy may be less time consuming, but is also likely to produce less confidence in the final result. Pacific Northwest National Laboratory's Radiation Detection and Nuclear Sciences group has constructed a low background 14-crystal HPGe array for sample measurement; in all measurements, samples will be in close proximity to the germanium crystals. This close geometry and the sheer number efficiency calibrations required for the system have led us to investigate methods to simplify the efficiency calibration procedure. One method we are developing uses the Y-Y coincidence plane to isolate Compton scattering event populations, allowing experimental determination of total detection efficiency values from the measurement of a single mixed isotope standard. A description of the analysis and experimental results of this method are presented.

low background HPGe High Purity Germanium detector↗
DOE OSTI2024

Probing and Understanding the Spatial and Energy Distributions of Plasmonic Hot Carriers via Single-Molecule Quantum Transport

The generation of hot carriers in plasmonic nanostructures offers new transformative opportunities for a range of applications, including solar energy harvesting, photochemistry, and photodetection. To better understand such phenomena, this project aims to develop an experimental approach to study and understand hot carrier distributions in photoexcited plasmonic nanostructures. The developed experimental approach, combining scanning probe-based single-molecule quantum transport measurements with plasmonic excitation methods, leverages nanoscopic single molecules as quantum energy filters to selectively access hot carriers in a variety of plasmonic nanostructures. This report summarizes the key outcomes, impacts, and lessons learned in the first two years of the project. Over the past two years, important progress was made in achieving the project's goals, including the development of the scanning probe-based experimental platform, fabrication of plasmonic nanostructures, and design and synthesis of the desired molecular candidates. Insights from this research will pave the path toward the development of technologies that will improve the way we harvest solar energy and drive chemical reactions and ultimately help transition the U.S. to a clean and sustainable society.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2019

CHARMM-GUI Glycan Modeler for modeling and simulation of carbohydrates and glycoconjugates

Characterizing glycans and glycoconjugates in the context of three-dimensional structures is important in understanding their biological roles and developing efficient therapeutic agents. Computational modeling and molecular simulation have become an essential tool complementary to experimental methods. In this work, we present a computational tool, Glycan Modeler for in silico N–/O –glycosylation of the target protein and generation of carbohydrate-only systems. In our previous study, we developed Glycan Reader , a web-based tool for detecting carbohydrate molecules from a PDB structure and generation of simulation system and input files. As integrated into Glycan Reader in CHARMM-GUI, Glycan Modeler (Glycan Reader & Modeler) enables to generate the structures of glycans and glycoconjugates for given glycan sequences and glycosylation sites using PDB glycan template structures from Glycan Fragment Database (http://glycanstructure.org/fragment-db). Our benchmark tests demonstrate the universal applicability of Glycan Reader & Modeler to various glycan sequences and target proteins. We also investigated the structural properties of modeled glycan structures by running 2-μs molecular dynamics simulations of HIV envelope protein. The simulations show that the modeled glycan structures built by Glycan Reader & Modeler have the similar structural features compared to the ones solved by X-ray crystallography. We also describe the representative examples of glycoconjugate modeling with video demos to illustrate the practical applications of Glycan Reader & Modeler . Glycan Reader & Modeler is freely available at http://charmm-gui.org/input/glycan.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Multiscale atomistic simulation of metal-oxygen surface interactions: Methodological development, theoretical investigation, and correlation with experiment

The purpose of this grant is to develop the multi-scale theoretical methods to describe the nanoscale oxidation of metal thin films, as the PI (Yang) extensive previous experience in the experimental elucidation of the initial stages of Cu oxidation by primarily in situ transmission electron microscopy methods. Through the use and development of computational tools at varying length (and time) scales, from atomistic quantum mechanical calculation, force field mesoscale simulations, to large scale Kinetic Monte Carlo (KMC) modeling, the fundamental underpinings of the initial stages of Cu oxidation have been elucidated. The development of computational modeling tools allows for accelerated materials discovery. The theoretical tools developed from this program impact a wide range of technologies that depend on surface reactions, including corrosion, catalysis, and nanomaterials fabrication.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Measurement of the sound speed in dense fluid deuterium along the cryogenic liquid Hugoniot

Many experimental studies, spanning several decades of research and using various dynamic compression schemes, have been conducted to investigate cryogenic liquid deuterium under strong shock compression. The consensus emerging from these studies is that of a progressive dissociation of the D 2 molecules into an electrically conducting, atomic plasma, when subjected to shock pressures exceeding ~50 GPa. While state-of-the-art numerical simulations based on density-functional-theory or quantum Monte-Carlo techniques capture this behavior quite well, subtle differences subsist between these simulations and the available experimental data regarding the pressure-density compressibility. Here, leveraging a recently developed analysis method for high-resolution Doppler interferometric velocity data, we present Eulerian sound speed measurements in compressed deuterium to shock pressures between 50 and 200 GPa. These results, extracted from laser-driven shockwave experiments, are found to agree with several of the most accurate equation of state models for deuterium at those conditions up to ~150 GPa. However, the data indicate that these models fail to reproduce the experimentally observed sound speed at higher pressures, approaching 200 GPa. In particular, we unveil a discrepancy between the experimental results and the equation of state model that is most commonly used in inertial confinement fusion at the National Ignition Facility.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Device-Centric Firmware Malware Detection for Smart Inverters using Deep Transfer Learning

Since future power grids are inverter-dominant grids and inverters are getting smarter by incorporating remote access and seamless firmware update, it is anticipated that malware attackers will directly target smart inverters. However, malware threats targeting smart inverters have been less studied yet. This paper explores potential malware attacks targeting smart inverters and proposes a deep transfer-learning (DTL)-based malware detection framework for smart inverters. The proposed DTL method can significantly reduce development time and efforts for an artificial intelligence-based malware detection algorithm while improving detection accuracy. The experimental result shows that the proposed method achieves 98% of firmware malware detection accuracy. Furthermore, this approach will be transformative to other smart grid devices enabling seamless firmware update.

artificial intelligence↗
DOE OSTI2020

Thermal Image Processing for Feature Extraction from Encapsulated Phase Change Materials

Encapsulated inorganic particles with high melting points (>300 °C) are desired as high-temperature Phase Change Materials (PCMs) for next-generation Latent Heat Thermal Energy Storage (LHTES) systems. One of the many challenges during the development of PCMs is to achieve a high throughput that in turn depends on accurately modeling the relation between process parameters and geometric & thermal properties of the PCMs particle. During the production of the PCMs, a high-speed infrared camera is used to acquire images of the encapsulated material under controlled illumination conditions. This research article focuses on the development of image processing techniques for both geometric and thermal feature extraction during the development of the PCMs. A user-friendly GUI has been designed in MATLAB and preliminary experimental results have demonstrated that the method is fast, accurate and reliable for a high throughput production. The extracted features will be used to develop Machine Learning (ML) models to predict the geometric and thermal properties of the PCM based on the process parameter settings. The ML model will accelerate the search for the optimized process settings to boost the throughput of the production.

25 ENERGY STORAGE↗
DOE OSTI2018

Improvement of the Processes of Liquid-Phase Epitaxial Growth of Nanoheteroepitaxial Structures

We have revealed the shortcomings of equipment and technological approaches in growing nanoheteroepitaxial structures with quantum dots by liquid-phase epitaxy. We have developed and fabricated a new vertical barreltype cassette for growing quantum dots and epitaxial layers of various thicknesses in one technological process. A physico-mathematical simulation has been carried out of the processes of liquid-phase epitaxial growth of quantumdimensional structures with the use of the program product SolidWorks (FlowSimulation program). Analysis has revealed the presence of negative factors influencing the growth process of the above structures. The mathematical model has been optimized, and the equipment has been modernized without additional experiments and measurements. The flow dynamics of the process gas in the reactor at various flow rates has been investigated. A method for tuning the thermal equipment has been developed. The calculated and experimental temperature distributions in the process of growing structures with high reproducibility are in good agreement, which confirms the validity of the modernization made.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

PhaseT3M: 3D imaging at 1.6 Å resolution via electron cryo-tomography with nonlinear phase retrieval

Electron cryo-tomography (cryo-ET) enables 3D imaging of complex, radiation-sensitive structures with molecular detail. However, image contrast from the interference of scattered electrons is nonlinear with atomic density and multiple scattering further complicates interpretation. These effects degrade resolution, particularly in conventional reconstruction algorithms, which assume linearity. Particle averaging can reduce such issues but is unsuitable for heterogeneous or dynamic samples ubiquitous in biology, chemistry, and materials sciences. Here, we develop a phase retrieval-based cryo-ET method, PhaseT3M. We experimentally demonstrate its application to an approximately 7 nm Co3O4 nanoparticle on an approximately 30 nm carbon substrate, achieving a maximum resolution of 1.6 Å, surpassing conventional limits using standard cryo-TEM equipment. PhaseT3M uses a multislice model for multiple scattering and Bayesian optimization for alignment and computational aberration correction, with a positivity constraint to recover ‘missing wedge’ information. Applied directly to biological particles, it enhances reconstruction quality and reduces artifacts, establishing a standard for routine 3D imaging with phase contrast.

Biophysics↗
DOE OSTI2019

Going large(r): General Discussion

With the introduction of new ion sources and advanced mass-spectrometric techniques coupled to spectroscopy, ever larger complexes are being probed. This increase in size is coupled with an increase in complexity requiring new methodologies (both experimental and theoretical) but also providing new opportunities. This session will primarily focus on the application of ion spectroscopy of non-covalent interactions in clusters and biological systems. These include solvent clusters, secondary and tertiary structure of proteins, and weakly-bound molecular clusters. Topics covered will include: structural probes for weak interactions; advances in action spectroscopy; and conformationally selective spectroscopy. A key discussion point will concern the marriage of mass-spectrometery with optical spectroscopy. The interpretation of experimental data obtained for these larger systems demands concomitant developments in theoretical methods, and the session will provide an opportunity for comparative discussions of new theoretical approaches in this field.

Ahmed, Musahid↗
DOE OSTI2012

Comparative analysis of LWR and FBR spent fuels for nuclear forensics evaluation

Some interesting issues are attributed to nuclide compositions of spent fuels from thermal reactors as well as fast reactors such as a potential to reuse as recycled fuel, and a possible capability to be manage as a fuel for destructive devices. In addition, analysis on nuclear forensics which is related to spent fuel compositions becomes one of the interesting topics to evaluate the origin and the composition of spent fuels from the spent fuel foot-prints. Spent fuel compositions of different fuel types give some typical spent fuel foot prints and can be estimated the origin of source of those spent fuel compositions. Some technics or methods have been developing based on some science and technological capability including experimental and modeling or theoretical aspects of analyses. Some foot-print of nuclear forensics will identify the typical information of spent fuel compositions such as enrichment information, burnup or irradiation time, reactor types as well as the cooling time which is related to the age of spent fuels. This paper intends to evaluate the typical spent fuel compositions of light water (LWR) and fast breeder reactors (FBR) from the view point of some foot prints of nuclear forensics. An established depletion code of ORIGEN is adopted to analyze LWR spent fuel (SF) for several burnup constants and decay times. For analyzing some spent fuel compositions of FBR, some coupling codes such as SLAROM code, JOINT and CITATION codes including JFS-3-J-3.2R as nuclear data library have been adopted. Enriched U-235 fuel composition of oxide type is used for fresh fuel of LWR and a mixed oxide fuel (MOX) for FBR fresh fuel. Those MOX fuels of FBR come from the spent fuels of LWR. Some typical spent fuels from both LWR and FBR will be compared to distinguish some typical foot-prints of SF based on nuclear forensic analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Measuring thermal profiles in high explosives using neural networks

We present a new method for calculating the temperature profile of high explosive (HE) material using a Convolutional Neural Network (CNN). To train/test the CNN, we have developed a hybrid experiment/simulation method for collecting acoustic and temperature data. We experimentally heat cylindrical containers of HE material until detonation/deflagration, where we continuously measure the acoustic bursts through the HE using multiple acoustic transducers lined around the exterior container circumference. However, measuring the temperature profile in the HE in an experiment would require inserting a large number of thermal probes, which would disrupt the heating process. Thus, we use two thermal probes, one at the HE center and one at the wall. We then use numerical simulation of the heating process to calculate the temperature distribution and correct the simulated temperatures based on the experimental center and wall temperatures. We calculate temperature errors on the order of 15 °C, which is ∼12% of the range of temperatures in the experiment. We also investigate how the algorithm’s accuracy is affected by the number of acoustic receivers used to collect each measurement and the resolution of the temperature prediction. This work provides a means of assessing the safety status of HE material, which cannot be achieved using existing temperature measurement methods. In addition, it has implications for a range of other applications where internal temperature profile measurements would provide critical information. These applications include detecting chemical reactions, observing thermodynamic processes such as combustion, monitoring metal or plastic casting, determining the energy density in thermal storage capsules, and identifying abnormal battery operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Implementing Arbitrary/Common Concurrent Writes of CRCW PRAM

The Parallel Random Access Machines (PRAM) abstraction is the simplest and most elegant algorithmic model for the design and analysis of parallel algorithms. It consists of different models categorized based on the underlying memory access mode used, the most powerful of which is the Concurrent Read Concurrent Write (CRCW) model. A PRAM algorithm describes a series of rounds, each of which consists of a collection of operations that can be executed concurrently within the same time step. However, the lack of support for concurrent memory accesses and the prevalence of asynchronous programming models led to the belief that implementing CRCW PRAM algorithms is unattainable and prompted many to avoid this model except for theoretical studies of optimal performance.In this work, we study the arbitrary and common concurrent writes in the CRCW PRAM model and explore implementation challenges on general-purpose systems. Moreover, we examine current practices for implementing common/arbitrary concurrent writes and propose a new efficient lightweight and thread-safe method to implement concurrent writes through leveraging atomic instructions. To demonstrate the efficacy of our method, we developed OpenMP kernels for classical CRCW PRAM algorithms and provide experimental results and comparisons based on run time performance measured over the x86 multicore architecture. Our results show a performance speedup compared to current practices up to 4.5x across all our benchmarks.

Ghanim, Fady↗
DOE OSTI2012

Experimental Test Plan DOE Tidal and River Reference Turbines

Our aim is to provide details of the experimental test plan for scaled model studies in St. Anthony Falls Laboratory (SAFL) Main Channel at the University of Minnesota, including a review of study objectives, descriptions of the turbine models, the experimental set-up, instrumentation details, instrument measurement uncertainty, anticipated experimental test cases, post-processing methods, and data archiving for model developers.

acoustic Doppler profiler↗
DOE OSTI2013

Predictive Science Panel, LLNL Meeting, August 20–22, 2013 (Unclassified Report)

The Predictive Science Panel (PSP) met at LLNL on August 20–22, 2013. The Panel appreciated the frank discussions of the four deep-dive topics: • Primary Physics Certification Issues with Remanufacture and Reuse, • Statistical Filtering Approaches to UQ Science, • Theoretical and Experimental Considerations for Accessing Low-Z EOS, and • Advanced Hydrodynamics Methods Development. Significant progress was demonstrated in each area. Panel suggestions of fruitful directions for further work are described in our classified report. In this unclassified report we offer the following summaries.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Compressor is A Sensor: A Universal Refrigerant Charge Fault Detection and Diagnostics Method Based on Pump Down Operation

The primary goal of this report is to develop a universal charge fault detection method that requires only a few experimental data with high prediction accuracy. Currently, pump-down operations is typical practices by HVAC technicians when they need to open the refrigerant circuit to make a repair. In addition, compressors have a built-in low-pressure cut-off protection function, and the compressor performance maps are commonly available from manufacturers. The new charge fault detection and diagnostics method innovatively utilizes the typical pump down operation, the compressor’s low-pressure cut-off protection, and the compressor performance map. It does not require any geometry information of heat exchangers, refrigerant lines, or charge buffers.

42 ENGINEERING↗
DOE OSTI2024

Measuring thermal profiles in high explosives using neural networks

We present a new method for calculating the temperature profile of high explosive (HE) material using a Convolutional Neural Network (CNN). To train/test the CNN, we have developed a hybrid experiment/simulation method for collecting acoustic and temperature data. We experimentally heat cylindrical containers of HE material until detonation/deflagration, where we continuously measure the acoustic bursts through the HE using multiple acoustic transducers lined around the exterior container circumference. However, measuring the temperature profile in the HE in an experiment would require inserting a large number of thermal probes, which would disrupt the heating process. Thus, we use two thermal probes, one at the HE center and one at the wall. We then use numerical simulation of the heating process to calculate the temperature distribution and correct the simulated temperatures based on the experimental center and wall temperatures. We calculate temperature errors on the order of 15 °C, which is ~12% of the range of temperatures in the experiment. We also investigate how the algorithm’s accuracy is affected by the number of acoustic receivers used to collect each measurement and the resolution of the temperature prediction. This work provides a means of assessing the safety status of HE material, which cannot be achieved using existing temperature measurement methods. In addition, it has implications for a range of other applications where internal temperature profile measurements would provide critical information. These applications include detecting chemical reactions, observing thermodynamic processes such as combustion, monitoring metal or plastic casting, determining the energy density in thermal storage capsules, and identifying abnormal battery operations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗