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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Spherical Indentation and Implementation of S 3 /P for yield stress determination of brittle materials

Here, a mathematically transparent and robust experimental method has been developed to estimate the yield stress of brittle materials through the analysis of depth-sensing spherical indentation. Employing Hertzian contact mechanics, an elastically invariant ratio based on the simple equation S 3 / P = 6RE r 2 , (where S and P are contact stiffness and indentation load, respectively) has been derived that enables more accurate and confident determination of the transition from elastic to inelastic deformation; a transition that the yield stress dictates and represents. Using two diamond spheres with radii of 3.2 and 8.6 μm, the indentation test method and analyses are applied to two vitreous silicates: Corning's HPFS 7980® fused silica and Vitro's Starphire® soda lime silicate. The estimated yield strengths are 8.15 GPa ± 2.5% for the fused silica and 6.1 GPa ± 3.3% for the soda-lime silicate, and both were independent of indenter radius. Verification of this new experimental method is demonstrated with an as-drawn titanium by showing equivalence of measured yield stress by its spherical indentation and that from uniaxial compression testing. This method will enable easier and more confident estimation of yield stress in brittle materials - a property that historically has been elusive to measure for these materials using common laboratory mechanical test methods.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Preface to Special Issue on Neutron Scattering for Catalysis

In the pursuit of understanding the chemical transformations of catalytic reactions and the structural evolution of catalysts at the molecular level, a suite of advanced experimental methods has been developed in the studies of catalysis science. Furthermore, among these methods, neutron scattering not only gives catalytic information that is highly complementary to other microscopic scattering techniques such as electrons (microscopy and diffraction) and photons from visible light to synchrotron X-rays, but also frequently provides unique insights into catalysis regarding the structure and chemical nature of light elements such as hydrogen and oxygen that are either not possible or difficult to study with other approaches.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

New approach to precisely measure γ-ray intensities for long-lived fission products, with results for the decay of 95 Zr

For many fission products, the rays emitted following decay provide an easily-detectable signature that can be used to identify their quantities and distributions in a sample. As a result, γ-ray spectroscopy is often exploited to study fission-product yields, provided sufficiently accurate information on the γ-ray intensity is available. However, in many cases, the uncertainties in the existing nuclear data are large enough that they compromise the precision achievable for modern experiments and applications. To address this need, we have developed a new experimental method that is well suited to precisely measure absolute γ-ray intensities in the β decay of long-lived fission products. The approach involves the production of a radiopure sample by implantation of a mass-separated ion beam from the CAlifornium Rare Isotope Breeder Upgrade (CARIBU) facility on a thin carbon foil. The emitted β-decay radiation is detected with a 4π gas proportional counter and a meticulously efficiency-calibrated high-purity germanium (HPGe) detector. As a first measurement to demonstrate the approach, we studied the absolute γ-ray intensities of the strongest transitions following the β decay of 95 Zr and its decay-daughter 95 Nb, and determined them to fractional precisions of better than 1–2%. In addition, with a larger sample of activity produced through neutron irradiation of an isotopically-enriched Zr foil, we performed a high-precision measurement of the relative γ-ray intensities following the decay of 95 Zr with just the HPGe detector. Here, the sample-production method at CARIBU and the coincidence detection approach demonstrated here can be applied to study fission products with half-lives longer than a day, which includes isotopes important not only for nuclear-energy and national-security applications, but also for medical-isotope research and environmental monitoring.

4π↗
DOE OSTI2024

Reliable edge machine learning hardware for scientific applications

Extreme data rate scientific experiments create massive amounts of data that require efficient ML edge processing. This leads to unique validation challenges for VLSI implementations of ML algorithms: enabling bit-accurate functional simulations for performance validation in experimental software frameworks, verifying those ML models are robust under extreme quantization and pruning, and enabling ultra-fine-grained model inspection for efficient fault tolerance. We discuss approaches to developing and validating reliable algorithms at the scientific edge under such strict latency, resource, power, and area requirements in extreme experimental environments. We study metrics for developing robust algorithms, present preliminary results and mitigation strategies, and conclude with an outlook of these and future directions of research towards the longer-term goal of developing autonomous scientific experimentation methods for accelerated scientific discovery.

Baldi, Tommaso↗
DOE OSTI2020

Accuracy of HVAC Load Predictions: Validation of EnergyPlus and DOE-2 using FLEXLAB Measurements

The aim of the project reported here was to better understand the level of accuracy of three building energy simulation (BES) engines (‘engines’) — EnergyPlus™, DOE-2.1e, and DOE-2.2 — by identifying and investigating significant deviations between the performance predicted by these engines and actual performance as measured in the FLEXLAB® test facility at Lawrence Berkeley National Laboratory (LBNL). The specific test conditions included some of those prescribed in ANSI/ASHRAE Standard 140 - Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs. Detailed measurements of FLEXLAB performance, including indoor temperatures and heat fluxes and air-flow and water flow rates and temperatures in the Heating, Ventilating and Air Conditioning (HVAC) system, together with hourly weather data, were recorded and used in analyzing the simulation results from EnergyPlus v8.8, DOE-2.2 v3.65 and DOE-2.1e v127. These engines are commonly used in the United States for building energy code compliance, federal, state, and utility incentives programs, as well as energy efficient design of new buildings and energy retrofit of existing buildings. Seven conventional overhead mixing ventilation scenarios were tested and each engine was found to have a similar level of agreement with the measurements of space-level heating and sensible cooling loads. These results provide useful information regarding the accuracy of these engines in predicting the cooling and heating load elements of whole building energy performance. This information is intended for practitioners who are concerned about transitioning between simulation tools with different engines and for managers of utility programs leveraging these tools for evaluating and/or projecting measure savings to be incentivized under their programs. The results of the comparisons of simulated and measured performance indicate that the predictions from all three engines are not significantly different. The 24-hour average value of the absolute mean bias indicates the likely magnitude of the error in any particular case. The average mean bias is reduced by cancelation of overprediction in one case by underprediction in another. The daytime absolute mean biases, which may be more important for both energy performance and occupant comfort, are ~6%, presumably because of the greater complexity involved in simulating in the presence of solar radiation. EnergyPlus typically overpredicts the cooling load and/or underpredicts the heating load by ~1.5% and the DOE-2 engines typically underpredict the cooling load by approximately the same amount. The Root Mean Square Error is relatively more sensitive to shorter term variations in the difference between predicted and measured loads; the three engines have similar values, ~10%, suggesting that the uncertainties in their predictions of peak loads may also be similar in magnitude. The implication of these results is that users, both designers and program analysts, can use EnergyPlus, DOE-2.1e, or DOE-2.2 to model conventional commercial buildings equipped with overhead mixing ventilation with a similar level of confidence. Further work is required to better understand the variability in the level of agreement between the engine predictions and FLEXLAB measurements, where a particular engine will agree well with FLEXLAB in some cases and not so well in others and another engine will agree or disagree in different cases. As the sources of this variability are identified and eliminated or reduced significantly, it is recommended that the experimental capabilities and methods developed in the study reported here should be applied to validating heating and cooling load calculations for spaces with different types of furniture and miscellaneous loads. These methods should then be applied to low energy space conditioning systems in EnergyPlus including, in particular, radiant slab and radiant ceiling panel cooling and heating systems and ‘mixed mode’ systems that combine mechanical cooling and natural ventilation systems, focusing on controls, including control of thermal mass. The work reported here addresses the conventional method of heating and cooling occupied spaces; other methods, such as the use of radiant heating and cooling systems have the potential to provide equivalent occupant comfort, or better, with lower energy consumption. These systems are addressed more explicitly in EnergyPlus but there is a need for empirical validation to give users the same level of confidence in modeling these systems that they have, or should have, in modeling conventional systems, based on the results presented here.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Determination of γ-ray branching ratios for ⁹⁵Zr and ¹⁴⁷Nd

For many fission products, the γ rays emitted following decay provide an easily-detectable signature that can be used to identify their quantities and distributions in a sample. As a result, γ-ray spectroscopy is often exploited to study fission-product yields (FPYs), provided sufficiently accurate information on the γ-ray branching ratio is available. However, in many cases, the uncertainties in the existing nuclear data are large enough that they compromise the precision achievable for modern experiments and applications. To address this need, we have developed a new experimental method that is well suited to precisely measure the γ-ray branching ratios in the decay of long-lived fission products. The approach involves the production of a radiopure sample by implantation of a mass-separated ion beam from the CAlifornium Rare Isotope Breeder Upgrade (CARIBU) facility on a thin carbon foil. The emitted β -decay radiation is detected with a 4π gas proportional counter and a meticulously efficiency-calibrated high-purity germanium (HPGe) detector. As a first measurement to demonstrate the approach, we studied the γ-ray branching ratios of the strongest transitions following the decay of ⁹⁵Zr and decay-daughter ⁹⁵Nb and determined these branching ratios to fractional precisions of 1%. We then applied this approach to determine the γ-ray branching ratios for the β decay of ¹⁴⁷Nd. The results for the γ-ray branching ratios are presented here and compared to previous results and evaluations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Active Reduction of Apparent Cable Capacitance

This paper presents a method for reducing apparent cable capacitance seen by sensors. The proposed method is designed for sensing in extreme environments including ultra-high temperatures, but can be applied in benign environments as well. By reducing the cable capacitance, high speed signals can be transmitted over longer distances, allowing the application of advanced control systems that require high bandwidth data for stable operation. A triaxial cable with an associated guard circuit is developed that actively reduces cable capacitance while also rejecting extraneous electric and magnetic interference on the signal. The active capacitance reduction method developed is tested experimentally and shown to reduce apparent cable capacitance to two percent of the static value.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Novel Magnetron Operation and Control Methods for Superconducting RF Accelerators

High power magnetrons designed and optimized for industrial heating, being injection-locked, have been suggested to power superconducting RF cavities for accelerators due to lower cost and higher efficiency. However, standard operation methods do not provide high efficiency with wideband control suppressing microphonics. We have developed and experimentally verified novel methods of operating and controlling the magnetron that provide stable RF generation with higher efficiency and lower noise than other RF sources. By our method the magnetrons operate with the anode voltage notably lower than the self-excitation threshold improving its performance. This is also a promising way to increase tube reliability and longevity. A magnetron operating with the anode voltage lower than the self-excitation threshold, in so-called stimulated coherent generation mode has special advantage for pulse operation with a gated injection-locking signal. This eliminates the need for expensive pulsed HV modulators and additionally increases the magnetron RF source efficiency due to absence of losses in HV modulators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Binder jetting additive manufacturing of silicon carbide ceramics: Development of bimodal powder feedstocks by modeling and experimental methods

A limitation of binder jetting additive manufacturing is the low density of fabricated parts. Mixing powders with different sizes is a promising approach to increase powder bed packing density and, hence, printed part density. However, in previous studies mixed powder feedstock was prepared by trial and error method. In this research, both modeling and experimental methods were used to prepare the bimodal powder feedstocks. Analytical packing model was introduced for irregular powders. A bimodal powder was prepared by mixing two different-sized silicon carbide powders (i.e. coarse and fine) using ball mill, and their tap densities were measured. Silicon carbide plates were printed using the coarse and bimodal powders by a commercial binder jetting system. Results showed that the modeling method could predict the tap density of bimodal powders with high accuracy. The printed parts from bimodal powder achieved higher green densities than those from the unimodal powder.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Development and experimental evaluation of new building air leakage measurement methods: measurement of interior air leaks and comparison to conventional methods

Building air leaks (both through exterior and interior surfaces) can have a significant impact on energy consumption, indoor air quality, fire safety, and moisture accumulation affecting structural durability. Blower door testing has been used to measure leaks in buildings, but commonly used testing methods do not directly measure interior leaks. In this paper, new testing methods (guarded interior test and zonal multipoint pressure testing method) are presented that directly measure these interior leaks, utilizing common blower door equipment for both single and multi-point testing. Furthermore, these new methods are compared to conventional methods in terms of the information provided, limitations and time/effort needed. In addition, building leak measurement results are analyzed to reveal a) coupling between power law model values (exponent and coefficient) for an ensemble of buildings, b) the error in using single point testing when estimating low pressure leakage, and c) how building power law models vary from low to high pressure ranges.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2026

Advancing Building Air Leakage Measurement and Modeling: Measurement of Interior Air Leaks, Experimental Comparison to Conventional Methods, and Building Modeling Characteristics

This report, Advancing Building Air Leakage Measurement and Modeling: Measurement of Interior Air Leaks, Experimental Comparison to Conventional Methods, and Building Modeling Characteristics, developed two new building air leakage measurement methods, experimentally evaluated the performance in comparison to conventional methods, experimentally evaluated the behavior of leaks for specific crack structures, and identified testing constraints and model implications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Radioactive Material Dynamics @ NSLS-II [Slides]

RMD @ NSLS-II helps pave the path to a DMMSC: Developing expertise in techniques and experimental methods for DMMSC science; Improving capabilities for models to become microstructurally aware; Workforce training and development; Help refine DMMSC scientific requirements; Complementary to DMMSC XFEL science (EDXD/EXAFS)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Lessons Learned in Employing Data Analytics to Predict Oxidation Kinetics and Spallation Behavior of High-Temperature NiCr-Based Alloys

Machine learning (ML) can offer many advantages in predicting material properties over traditional materials development methods based solely on limited experimental investigations or physical-based simulations with the capability to reduce development cost, risk, and time. However, so far, limited efforts have been made to predict alloy oxidation kinetics and spallation behavior via ML due to the lack of consistently measured and sufficient experimental data and the inherent complexity in oxidation behavior of multicomponent high-temperature alloys. A previous study reported the ability of ML to predict oxidation kinetics of NiCr-based alloys as a function of alloy composition and operating conditions. Here, the performance of a ML model in predicting rate constants and spallation probability was evaluated in light of the roles of the data distribution of the experimental dataset (data analytics), the alloy composition, the exposure environment and the chosen oxidation approach to extracting kinetic values from the measured mass changes (but using either a simple parabolic law or a statistical cyclic oxidation model). Potential strategies to improve the predictions and enhance the extrapolative capability of the previously trained model will be discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Photoporomechanics: An Experimental Method to Visualize the Effective Stress Field in Fluid-Filled Granular Media

Effective stress governs the mechanical behavior of porous media. In this study, we use photoelasticimetry to visualize the evolving effective stress field in fluid-filled granular media in processes that couple fluid flow and mechanical deformation. We refer to this experimental method as photoporomechanics. We develop a fabrication process to produce millimeter-scale residual-stress-free photoelastic spheres with high geometric accuracy. We use color to quantify the forces acting on the particles over a wide range of forces, while using light intensity for a small range of forces. We then provide an application of photoporomechanics to illustrate the evolution of effective stress during one-dimensional consolidation: a process by which the stresses caused by a sudden load are gradually transmitted through a fluid-filled granular pack as the fluid drains and excess pore pressures dissipate. We report our technique provides a powerful experimental model system to study the grain-scale underpinning of coupled solid-fluid processes in granular media.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Optimized pulsed sideband cooling and enhanced thermometry of trapped ions

Resolved sideband cooling is a standard technique for cooling trapped ions below the Doppler limit to near their motional ground state. Yet the most common methods for sideband cooling implicitly rely on low Doppler-cooled temperatures and tightly confined ions and they cannot be optimized for different experimental conditions. Here we introduce a framework which calculates the fastest possible pulsed sideband cooling sequence for a given number of pulses and set of experimental parameters and we verify its improvement compared to traditional methods using a trapped 171 Yb + ion. After extensive cooling, we find that the ion motional distribution is distinctly nonthermal and thus not amenable to standard thermometry techniques. We therefore develop and experimentally validate an improved method to measure ion temperatures after sideband cooling. These techniques will enable more efficient cooling and thermometry within trapped-ion systems, especially those with high initial temperatures or spatially extended ion wave packets.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Understanding Isomeric Effects on Properties of Aviation Fuels via a Group Contribution Method: Preprint

The molecular composition of aviation fuels, including conventional and sustainable aviation fuels (SAFs), significantly influences their performance, safety, and environmental impact. This study examines the effect of isomeric variation for compounds with the same carbon number and chemical family on key fuel properties, focusing on compounds commonly found in conventional jet fuels and SAFs. A group contribution method (GCM) is employed to predict thermophysical and combustion properties, providing an efficient analytical approach to evaluate the contributions of individual compounds to overall fuel mixture behavior. As part of this work, we introduce FuelLib, an open-source Python tool built around the GCM, to calculate individual compound and fuel mixture properties using various mixing rules. Our work evaluates whether the GCM can capture isomeric effects, that are often overlooked in traditional fuel property estimation. This is particularly important for SAFs, which often are composed of a more limited set of compound classes than conventional fuels, making isomeric differences more critical. Two-dimensional gas chromatography (GCxGC) data, which can be obtained from small fuel samples, provides weight percentages of compounds grouped by chemical family and carbon number rather than detailed information about individual compounds. As a result, assumptions must be made when decomposing GCxGC data into functional groups for GCM applications. Using GCxGC data, we show that the FuelLib tool can be used to predict the fuel properties of conventional jet fuels, with validation against experimental data. The provided tool enables researchers to predict fuel properties of candidate fuels and supports the design of new SAFs at both the component and mixture levels. This capability provides a foundation for studying fuel and combustion properties during SAF development, reducing reliance on costly experimental methods and advancing progress toward certification of new SAFs.The molecular composition of aviation fuels, including conventional and sustainable aviation fuels (SAFs), significantly influences their performance, safety, and environmental impact. This study examines the effect of isomeric variation for compounds with the same carbon number and chemical family on key fuel properties, focusing on compounds commonly found in conventional jet fuels and SAFs. A group contribution method (GCM) is employed to predict thermophysical and combustion properties, providing an efficient analytical approach to evaluate the contributions of individual compounds to overall fuel mixture behavior. As part of this work, we introduce FuelLib, an open-source Python tool built around the GCM, to calculate individual compound and fuel mixture properties using various mixing rules. Our work evaluates whether the GCM can capture isomeric effects, that are often overlooked in traditional fuel property estimation. This is particularly important for SAFs, which often are composed of a more limited set of compound classes than conventional fuels, making isomeric differences more critical. Two-dimensional gas chromatography (GCxGC) data, which can be obtained from small fuel samples, provides weight percentages of compounds grouped by chemical family and carbon number rather than detailed information about individual compounds. As a result, assumptions must be made when decomposing GCxGC data into functional groups for GCM applications. Using GCxGC data, we show that the FuelLib tool can be used to predict the fuel properties of conventional jet fuels, with validation against experimental data. The provided tool enables researchers to predict fuel properties of candidate fuels and supports the design of new SAFs at both the component and mixture levels. This capability provides a foundation for studying fuel and combustion properties during SAF development, reducing reliance on costly experimental methods and advancing progress toward certification of new SAFs.

33 ADVANCED PROPULSION SYSTEMS↗