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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Sample Preparation Method for Low-Level Total 129 I Measurements by ICP-MS

Trace-level measurements of iodine’s isotopic ( 129 I and 127 I) and chemical species distributions are needed for an accurate understanding of radioiodine migration in the Hanford subsurface. Pacific Northwest National Laboratory (PNNL) previously developed a novel analytical method for iodine characterization that uses ion chromatography (IC) coupled to inductively coupled mass spectrometry (ICP-MS). While the method can measure speciated forms of 129 I at levels below the drinking water standard, an interference from molybdenum (Mo) prevents the assay from quantifying the $\underline{total}$ 129 I concentration in many Hanford sample matrices. In this work, solvent extraction was evaluated as a sample preparation method for eliminating the Mo interference. A series of 10 experiments was conducted in which solutions containing known amounts of iodate or iodide were treated by solvent extraction, and the extracted solutions were analyzed for total iodine concentrations by ICP MS. Several extraction parameters such as reagent concentrations and chemical reaction times were systematically adjusted in attempts to optimize the extraction process. While solvent extraction was shown to be effective at removing Mo, there was a consistent inability to recover more than approximately 75% of the total iodine in most experiments. This would reduce the ability to detect 129 I at levels near the drinking water standard. Additionally, the extraction efficiencies in several experiments were highly variable, suggesting that solvent extraction could add significant uncertainty to radioiodine measurements. We recommend evaluating ion exchange as an alternative sample preparation approach in fiscal year (FY) 2024.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Uncertainty analysis for techno-economic and life-cycle assessment of wet waste hydrothermal liquefaction with centralized upgrading to produce fuel blendstocks

Wet waste hydrothermal liquefaction is a promising technology for producing transportation fuels with much lower greenhouse gases emissions than petroleum-based fuels. However, its techno-economic and life cycle assessment are primarily based on laboratory scale testing data, subject to considerable uncertainties, and even bias, due to knowledge gaps. Here, a preliminary uncertainty analysis of key economic measures was conducted based on the 2019 state-of-technology model for biocrude production. Building on the preliminary analysis, this work presents a comprehensive uncertainty analysis in both economic and environmental measures of the entire supply chain of wet waste hydrothermal liquefaction to fuel blendstocks including biocrude upgrading based on the 2021 state-of-technology model. The analysis includes the most recent developments in hydrothermal liquefaction and biocrude upgrading technologies and Monte Carlo simulation based on an integrated model system including an improved reactor yield model, reduced-order process model, discounted cash flow economic model and simplified life-cycle assessment model. The estimated biocrude yield ranges from 42.2% to 52.4% with a median of 47.3%. The estimated fuel yield ranges from 34.7% to 42.7% with a median of 38.7%. The estimated minimum fuel selling price ranges from $\$ $2.28/gge to $\$ $3.45/gge with a median of $\$ $2.80/gge. Relative to petroleum-derived diesel, the estimated reduction in supply chain greenhouse gas emissions ranges from 73.4% to 81.8% with a median of 77.7%. Compared to the 2019 state-of-technology analysis, a significant improvement in biocrude selectivity and economic measures and reduction in uncertainties were achieved due to the incorporation of additional continuous experimental data sets, technology development and de-risking, and improvement in model accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Directional dependence of equilibrated TLD-400 chips in multiple radiation fields

Fielding of thermoluminescent dosimeters (TLDs) for measurement of photon radiation dose in experiments is the standard practice for γ-irradiation facilities, pulsed power x-ray facilities, and reactor facilities at Sandia National Laboratories (SNL). Due to the high-dose experimental conditions and the mixed ( 1 n, γ) fields in these facilities, SNL radiation metrologists have historically used CaF 2 :Mn TLDs (also known as TLD-400). Recent inquiries to the radiation metrology staff have raised concerns that the aluminum-equilibrated TLD-400 chips may exhibit a directionally dependent response. The metrologists were asked whether the dose measured by the chip may be impacted by the angle of incidence on the equilibrated TLD. To provide a thorough answer to this query, a set of adjoint Monte Carlo radiation transport calculations was performed for three different equilibrated TLDs as well as bare TLD chips using the Integrated Tiger Series (ITS) code. The key feature of the adjoint calculations performed in this study is that each photon escaping the modeled geometry was tallied into angular bins to provide information on both the energy and angular dependence of the equilibrated chip. After the adjoint Monte Carlo calculations were completed, the resulting energy-dependent response function for each angular bin was convolved with multiple photon energy spectra representing various radiation facilities at SNL. The radiation facilities selected for analysis span a range of photon energies from approximately 1 keV up to approximately 20 MeV. Thus, the presented results are applicable to a wide variety of radiation facilities around the world. Although the bare TLD-400 chip was expected to display the largest variation due to the photon angle of impact on the dosimeter, the dosimeter with the thinnest aluminum equilibrator (SNL thin equilibrated TLD-400) was determined to have the biggest differential between the impact angle with the maximum dose ( D max ) and the impact angle with the minimum dose ( D min ). However, the SNL normal equilibrated TLD-400 chip demonstrated a dramatic reduction in that differential between maximum and minimum dose angles. The reduction in this differential is one of the dominant factors in experimenters’ choice to field these dosimeters at SNL radiation facilities. The results from the PNNL (Hanford) energy-flattening field capsule are consistent with the previous publications. The differential dose responses due to the photon impact angle indicate that experimenters should strive to field their TLD-400 dosimeters in a consistent manner to avoid additional uncertainty in the measurements based on dosimeter orientation.

Adjoint radiation transport↗
DOE OSTI2024

Shock compression experiments using the DiPOLE 100-X laser on the high energy density instrument at the European x-ray free electron laser: Quantitative structural analysis of liquid Sn

X-ray free electron laser (XFEL) sources coupled to high-power laser systems offer an avenue to study the structural dynamics of materials at extreme pressures and temperatures. The recent commissioning of the DiPOLE 100-X laser on the high energy density (HED) instrument at the European XFEL represents the state-of-the-art in combining x-ray diffraction with laser compression, allowing for compressed materials to be probed in unprecedented detail. Here, we report quantitative structural measurements of molten Sn compressed to 85(5) GPa and ~3500 K. The capabilities of the HED instrument enable liquid density measurements with an uncertainty of ~1% at conditions which are extremely challenging to reach via static compression methods. We discuss best practices for conducting liquid diffraction dynamic compression experiments and the necessary intensity corrections which allow for accurate quantitative analysis. We also provide a polyimide ablation pressure vs input laser energy for the DiPOLE 100-X drive laser which will serve future users of the HED instrument.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Predicting System Response at Unmeasured Locations

Traditional techniques to derive dynamic specification for components have a great deal of uncertainty. One of the major sources of uncertainty is that the number of response measurements in the operational system environment is insufficient to determine the component motion. This inadequacy is due to logistical limitations for data recording in field testing and space limitations for accelerometers, strain gages and associated wiring. Available measurements are often some distance from the component and therefore do not represent component motion. Typical straight-line envelopes of these unrepresentative measurements guarantee an increase in the uncertainty. In this paper multiple methods are attempted to expand a sparse set of field test measurements on a system to responses of interest that cannot be measured in the field due to the limitations. Proof of concept is demonstrated on the Modal Analysis Test Vehicle (MATV). The responses of interest, known as “truth responses”, are measured in a system vibration environment along with an optimized sparse set of 30 field responses. Methods to expand the field responses to the truth responses are demonstrated by comparing the acceleration spectral density of the expanded response to the measured response. Two methods utilize a validated finite element model of the MATV. One is developed from purely experiment based frequency response functions of a laboratory pre-test. Finally, these approaches are designed to drastically reduce the uncertainty of the component in-service motion as a basis for developing specifications that are guaranteed to be conservative with a known (instead of unknown) conservatism.

42 ENGINEERING↗
DOE OSTI2023

Impedance‐matching model‐in‐the‐loop simulation

Abstract Impedance matching is a novel approach to executing model‐in‐the‐loop (MIL) simulations. The concept, key features, and sample applications of this approach have been described in a series of publications. This paper advances theory and implementation for impedance‐matching MIL by: (1) developing a feedback linearization technique for implementing MIL for nonlinear virtual systems, (2) systematically characterizing MIL performance‐stability tradeoffs using three design‐oriented criteria—performance: defined as closeness of the controlled‐actuator impedance to the virtual‐boundary impedance;control effort: low controller response at high frequencies to reduce sensitivity to measurement noise and uncertainties in the actuator model; andstability: pursued using passivity of the controlled actuator system, and (3) assessing, through experimentation, the robustness of two ways to estimate feedback reaction force from the test article. These fundamental advancements to MIL are described using a one‐dimensional configuration consisting of a fluid‐filled cylindrical vessel as the physical test article and a uniaxial hydraulic shake table controlled to imitate different seismic isolation systems at the base of the vessel.

Engineering↗
DOE OSTI2026

Improvement of Drop‐Hammer Impact Testing for Safety Assessment of High Explosives Using 10‐mg Samples

Here, in this study, we established an improved method for drop-hammer impact testing of small quantities of high explosives (10 mg). We performed about seven hundred impact tests under various experimental conditions (e.g., sandpaper vs bare anvil, different sample masses, drop-weights, and striker diameters) to determine an optimal set of conditions and reaction detection methods (e.g., gas analysis, video, and sound recordings) that give the most statistically reliable results with 10 mg samples. We used both Frequentist and Bayesian statistical approaches to compare estimates of the drop height (DH50) that initiates a reaction 50% of the time, and to quantify the associated uncertainty. Gas analysis proved to be the most reliable reaction detection method, showing unambiguous rises in HE decomposition products (e.g., CO 2 ) even when the other indicators (e.g., sound, video) were inconclusive. The impact tests performed with a bare anvil showed much better reproducibility than those conducted with sandpaper, reducing the largest uncertainty observed in the data sets by a factor of 1.7. The DH 50 values obtained from three different sample masses (10, 20, and 35 mg) fell within the uncertainties of the measurements. We demonstrated the improved procedure (i.e., 10-mg samples, gas analysis, bare anvil, and Bayesian approach) on a variety of PETN samples having different surface areas and thermal histories.

PETN↗
DOE OSTI2020

Isospin-violating contributions to ϵ'/ϵ

The known isospin-breaking contributions to the K → ππ amplitudes are reanalyzed, taking into account our current understanding of the quark masses and the relevant non-perturbative inputs. We present a complete numerical reappraisal of the direct CP-violating ratio ϵ'/ϵ, where these corrections play a quite significant role. We obtain the Standard Model prediction Re (ϵ'/ϵ) = (14 ± 5) · 10 -4 , which is in very good agreement with the measured ratio. The uncertainty, which has been estimated conservatively, is dominated by our current ignorance about 1/N C -suppressed contributions to some relevant chiral-perturbation-theory low-energy constants.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

An International Round-Robin Study on Thermoelectric Module Testing and Development of Standard Power Generation Modules

An international round-robin study on thermoelectric power generation modules was conducted with nine participating laboratories. Two types of commercially available bismuth telluride modules, 30 mm × 30 mm and 40 mm × 40 mm, were used. A test protocol was followed with five temperature set points from 50°C to 150°C. Graphite sheets were used as thermal interface materials with test pressure at 100 psi (0.69 MPa). The results showed large lab-to-lab variations and the key source of uncertainty for module efficiency was identified as the heat flux measurement. In the meantime, significant uncertainty was also found in maximum electrical power (P max ) measurements. As a result of the round-robin, a “standard module” with 4 × 4 legs on a 20 mm × 20 mm platform was suggested. A skutterudite module and a half-Heusler module were produced with identical geometry and 4 mm × 4 mm × 8 mm legs. All transport properties to calculate the figure-of-merit, zT, were measured from ambient temperature to 500°C. Module performance was measured by two laboratories. Two finite-element-analysis (FEA)-based models were developed independently to simulate and predict the module performance. In conclusion, the standard modules eliminated significant test uncertainties and are aimed at assisting device design and achieving more accurate performance predictions.

Round-robin↗
DOE OSTI2022

Physical and dynamical characterization of hyperbolic comet C/2017 U7 (PANSTARRS)

Here we present here a dynamical and observational study of the comet C/2017 U7 (PANSTARRS). This comet was discovered in 2017 and found to have a hyperbolic orbit. Our dynamical analysis shows that the object has probably originated in the Oort cloud, however an interstellar origin cannot be discarded. The observations were obtained in 2018 and 2019 using the Goodman High Throughput Spectrograph (GHTS) at the SOAR telescope. We obtained visible spectra covering the wavelength range of 0.5 - 0.9 μm and also images in the SDSS filters system. Both the low-resolution reflectance spectrum and the reflectance spectra derived from the SDSS filters show an atypical band at ~ 0.595 μm. We conducted a comparative study of the colors and reflectance spectra of different small body populations (e.g., comets, Centaurs, and trans-Neptunian objects or TNOs) from the literature and concluded that the spectra and the colors of this comet are atypical, showing only some overlap with those of some known members of the TNOs and Centaurs, within the large uncertainties of the measurements of those populations. It is found that the feature and overall spectral shape can be reproduced by laboratory spectra of kerite, a template for aliphatic-rich hydrocarbons that has been previously identified in NIR cometary spectra absorptions. It is tentatively proposed that the unusual spectral shape is the result of a particle size distribution of dust grains in the coma or on the surface that has arisen due to a low grain ejection velocity from the surface and large nucleus size.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Development and formulation of physics based metallic fuel models and comparison to integral irradiation data

Metallic fuel has an important historical significance in the development of nuclear reactors and continues to be relevant to the progression of advanced test and power reactors. A number of models, ranging from empirical to mechanistic, have been developed and implemented in various fuel performance codes to describe U-Zr and U-Pu-Zr fuel and typical fast reactor cladding materials. One challenge of using these models to simulate fuel performance is the inevitable tangling of coupled phenomena that can cloud proper implementation, calibration, and eventual utilization of new models. Here in an effort to provide a baseline capability that will facilitate the use of advanced models, new capabilities have been implemented into the fuel performance code BISON specific to metallic fuel simulations, ranging from materials properties, fission gas release and swelling calculations, coolant channel models, and cladding correlations. These models have been applied to the X441/X441A EBR-II experimental assembly data, a set of irradiated metallic UPuZr fuel rods of varying pin designs. The models implemented in BISON are able to capture the general trend of the expected response of the fuel and cladding to irradiation in EBR-II, especially when considering the spread in experimental measurements and the uncertainties inherited from the historical material models. Ultimately, the models outlined here provide the baseline capabilities on which new models can build upon in order to improve the prediction of metallic fuel performance simulations in off-normal designs or operations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Critical statistical assessment of data in metal additive manufacturing

Obtaining high quality data reflecting the relationships between the additive manufacturing (AM) process parameters, material microstructure and mechanical properties is crucial for the use of machine learning in AM. A database of over 4,000 data entries of metal AM was created thanks to a large number of literature studies on key process parameters and indicators of build quality. Meta-analysis reveals critical biases in the literature. Firstly, majority of studies report only high quality builds, these imbalances in reporting result in weak correlation between process parameters, properties and consolidation, limiting the ability of machine learning models to generalize beyond optimized conditions. Nevertheless, the trained models accurately predict yield strength ($R^2 = 0.85$), suggesting that certain process–property relationships are effectively captured within these models. Secondly, quantitative microstructural data are largely absent, limiting the learning of the microstructure-mechanical properties relationships. Finally, current process window identification is based largely on the consolidation, despite significant uncertainty in its measurement. It is important to identify the process map on the basis of not only the consolidation, but also mechanical behaviour under loading. Such a identification shows that 316 L and Inconel have much larger process map (i.e. highly printable) in comparison to the AlSi10Mg and Ti6Al4V.

Additive manufacturing↗
DOE OSTI2024

Applying U.S. metal fuel experience to new fuel designs for fast reactors

With the increasing interest in small modular reactors or microreactors, developers are working to design and submit licensing approval requests of U–10Zr-fueled fast reactors. The developers and their proponents cite prior metal fuel experience (worldwide, but U.S. experience in particular for many developers) as the motivation and justification for their reactor concepts. The experience with metal fuel deployment in sodium-cooled fast reactors as well as the underlying irradiation testing database, provide a suitable basis for analytically justifying the use of metal fuel in new reactors. The evolution of metal fuel design and capability illustrates the importance of key fuel design parameters to consider in new applications of the prior experience: fuel smeared density, plenum-to-fuel volume ratio, the ratio of cladding radius to thickness, fuel composition, and cladding and duct materials. In-service operating and deployment conditions to be considered include fuel linear heat generation rate, fuel temperature, cladding temperature, peak burnup and peak fast fluence. Fuel designs and in-service conditions that are bounded by the database and experience are most easily addressed, but deviations from those previous parameters and conditions can be addressed by considering impacts on previously established behavior and applying other mitigating conservatisms, as appropriate. Here, the authors recommend any new deployment proceed with fuel surveillance and monitoring to mitigate risk, application of conservative measures to address uncertainties, and a fuel qualification program that addresses a range of in-service operating conditions with production fuel. The work reported should be of interest to students and regulators unfamiliar with metal fuel in fast reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Development of Heterogeneous Ice Nucleation Rate Coefficient Parameterizations From Ambient Measurements

Ice nucleating particles (INPs) are a rare subset of particles that can have an outsized impact relative to their prevalence. To simulate INP variability, models require parameterizations for the most important sources of INPs. Most parameterizations in the literature were developed from laboratory experiments that used proxies for ambient particles. Whether these laboratory models effectively represent ambient aerosol is still not well understood and parameterizations developed from field measurements may be more atmospherically relevant. Expanding on previous work in which we used an ice chamber and a single-particle mass spectrometer (SPMS) to characterize INP composition, we calculate heterogeneous ice nucleation rate coefficients for ambient particles. We find good agreement between our dust and previous measurements of airborne dust. We also use a Monte Carlo approach to assess the relative contribution of each measurement to the uncertainty and find that the biggest source is the sampling efficiency of the SPMS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Bayesian Deep Learning Approach to Near-Term Climate Prediction

Since model bias and associated initialization shock are serious shortcomings that reduce prediction skills in state-of-the-art decadal climate prediction efforts, we pursue a complementary machine-learning-based approach to climate prediction. The example problem setting we consider consists of predicting natural variability of the North Atlantic sea surface temperature on the interannual timescale in the pre-industrial control simulation of the Community Earth System Model. While previous works have considered the use of recurrent networks such as convolutional LSTMs and reservoir computing networks in this and other similar problem settings, we currently focus on the use of feedforward convolutional networks. In particular, we find that a feedforward convolutional network with a Densenet architecture is able to outperform a convolutional LSTM in terms of predictive skill. Next, we go on to consider a probabilistic formulation of the same network based on Stein variational gradient descent and find that in addition to providing useful measures of predictive uncertainty, the probabilistic (Bayesian) version improves on its deterministic counterpart in terms of predictive skill. Finally, we characterize the reliability of the ensemble of machine learning models obtained in the probabilistic setting by using analysis tools developed in the context of ensemble numerical weather prediction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Characterizing Greater Houston's Aerosol by Air Mass During TRACER

During the TRacking Aerosol and Convection interaction ExpeRiment (TRACER), a suite of aerosol and cloud measurements were made using the Texas A&M Rapid Onsite Atmospheric Measurement Van (ROAM-V) mobile instrument platform. Joint ROAM-V/radiosonde deployments focused on sampling polluted marine and continental air masses to understand summertime convection along and across the sea-breeze front as it propagated through Houston. The polluted marine air mass at Seawolf Park, Galveston, TX was defined by two characteristic aerosol populations. Although the background total particle concentrations averaged 2,500 cm −3 , the air mass was also influenced by frequent but irregular periods of ship emission with significantly higher aerosol concentrations at times exceeding 34,000 cm −3 . Ship emission influenced periods, typically lasting <10 min, contained smaller, less hygroscopic particles resulting in a 69% relative decline in cloud condensation nuclei (CCN) activated fraction at 1% supersaturation compared to background periods. Measurements in continental air masses northwest of Houston revealed an average aerosol concentration of 5,208 cm −3 with a κ value near 0.1 reasonably describing the CCN population, independent of particle size. In continental air masses, substantial differences in particle size and CCN activation over small distances (<42 miles between sites) suggest considerable site-to-site variability in addition to the expected day-to-day differences. This small-scale variability makes it difficult to generalize continental air mass aerosol properties. Both coastal and inland locations had effective ice nucleating particles, but inland deployments observed the warmest nucleation temperature at −15.6°C compared to −17.8°C close to the coast. These measurements can reduce uncertainties in regional convection allowing models to improve understanding of aerosol-cloud interactions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

An assessment of China’s methane mitigation potential and costs and uncertainties through 2060

Abstract China, the world’s largest methane emitter, is increasingly focused on methane mitigation in support of its climate goals, but gaps exist in the understanding of key methane sources, as well as mitigation opportunities and their associated uncertainties. We use a bottom-up modeling approach with updated methane emission projections and abatement cost analysis to account for additional sources, uncertainties, and mitigation measures in China’s energy and agricultural sectors. Here we show the significant cost-effective potential for reducing methane emissions in China by 2030, with 660 million tonnes of carbon dioxide equivalent possible with average negative abatement costs of US$6.40 per tonne CO 2 e. Most of this potential exists in the energy sector, particularly coal mining, but the greater potential will shift towards agriculture by 2060. Aquaculture and biochar applications in rice cultivation have net economic benefits but need greater support for deployment, while new mitigation measures will be needed for remaining emissions from enteric fermentation, rice cultivation, and wastewater.

Science & Technology - Other Topics↗