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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Storing Co 2 in Built Infrastructure: Co 2 Carbonation of Precast Concrete Products

The overall objective of the proposed study was to advance the technical understanding of CO 2 incorporation into novel cementitious materials for the development of high value products that provide a net reduction in carbon emissions. This project combined two primary phases of research that addressed technical barriers related to (i) optimizing CO 2 storage capability of cementitious materials, (ii) evaluating and enhancing physical properties of novel carbonated materials, and (iii) assessing the reductions in life cycle CO 2 emissions attributed to CO 2 carbonation of precast cementitious materials. Engineered cementitious composites (ECC) are a class of highly ductile concrete composites that have been shown to be very durable when used in the built environment. CO 2 carbonation of ECC was examined in this study and it was found that precast ECC specimens could sequester up to 35% CO 2 by cement mass after 24 hours of curing at a CO 2 pressure of 0.5 MPa and 23°C and had a strain capacity of 3%. Carbonation conditions were optimized at the bench-scale and then utilized to create full-scale CO 2 -cured ECC railroad ties that were field tested on a train track. Rail ties were selected for this initial assessment of CO 2 storage in precast concrete materials due to the large market for concrete ties in the railroad industry. Although the full-scale rail ties passed all of the required American Railway Engineering and Maintenance-of-Way Association qualifying mechanical tests, on-track testing of the CO 2 -cured ECC rail ties was unsuccessful due to fiber alignment in the ECC the during the rail tie casting process which prevented the material from achieving the expected level of strain capacity. This result highlights the challenge in scaling up bench-scale processes to full-scale product manufacturing and requires additional investigation into the casting process of large-scale infrastructure elements using ECC combined with carbonation curing. Life cycle assessment of a CO 2 -cured ECC rail tie versus a traditional concrete rail tie indicates that the ECC tie can have lifecycle carbon savings of between 11% and 51% depending on how much longer its useful lifetime is compared to traditional concrete rail ties. Both carbon and cost savings are driven by a reduction in the need to replace broken rail ties, so the key factor is the extent to which a CO 2 -cured ECC rail tie will have increased lifetime durability compared to alternative rail ties.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Early-Time (E1) High-Altitude Electromagnetic Pulse Effects on Transient Voltage Surge Suppressors

Determining the effectiveness of surge and pulse protection devices in the United States power grid against effects of a High-Altitude Electromagnetic Pulse (HEMP) is crucial in determining the present state of grid resilience. Transient Voltage Surge Suppressors (TVSS) are used to protect loads in substations from transient overvoltages. Designed to mitigate the effects of lightning, their response to a HEMP event is unknown and was determined. TVSSs were tested in two unique configurations using a pulser that generates pulses in the tens of nanoseconds scale to determine their protective capability as well as to determine their self-resilience against HEMP pulses. Testing concluded that TVSS devices adequately protect against microsecond scale pulses like lightning but do not protect against pulses resembling HEMP events. It suggests that TVSS devices should not be relied upon to mitigate the effects of HEMP pulses.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Experimental investigation of the small-scale prototype of the dew point water recovery system

The article presents experimental investigation of the Dew Point Water Recovery (DPWR) system designed for clean water recovery using the dew point cooling phenomenon. The technology is a novel distillation process which allows for highly efficient water recovery. It is a first distillation technology which allows for water distillation through direct contact with atmospheric air. The authors designed, built, and tested an original prototype of a laboratory-scale DPWR system to verify its basic operating principles and perform performance analysis. It was shown that on average 10 × 10 −6 m 3 of clean water could be recovered from each cubic meter of the supply air with an average GOR of 1.9. Although the operation of the DPWR system requires electricity to drive fans, pumps and other associated equipment, the actual driving force of the system is thermal energy. The average thermal energy demand of the DPWR system was 370 kWh/m 3 , and more than half of this energy was based on the thermodynamic potential of the supply air. Based on experimental data, the mathematical model of the DPWR system was verified and it was found that the average relative discrepancy in predicting air temperature did not exceed 8%, and in predicting air humidity: 5%. In conclusion, the conducted experiments confirmed that the proposed DPWR system is feasible and has the potential to fill the technological gap in terms of a low-energy and easily accessible water recovery method.

42 ENGINEERING↗
DOE OSTI2022

Modernization efforts for the R -Matrix code SAMMY [Abstract]

The R-Matrix code SAMMY is a widely used nuclear data evaluation code focused on the resolved range, which includes corrections for experimental effects. The code is still mostly written in Fortran 77, and uses a memory management system suitable for the time of its initial writing (1984). A modernization effort is under way to bring the code in-line with modern software development practices. A continuous-integration testing framework was added, automating the large existing set of test cases. It is run on every commit. The memory management was updated to current standard practices suitable for modern software analysis tools. The code can be obtained from https://code.ornl.gov/RNSD/SAMMY. The resonance parameters and covariance information are now stored in C++ objects shared by SAMMY and AMPX, the processing code that generates nuclear data libraries for SCALE. This allows for easier maintenance and access to the resonance parameters inside and outside of SAMMY. This feature is already used by accessing and changing parameters in memory in the Bayesian Monte Carlo Evaluation Framework for Cross Sections Nuclear Data and Integral Benchmark Experiments project, Further plans include the switch to the ENDF reading and writing routines in AMPX, as these routines are more robust, easier to maintain, and support more features. Of note here is support for the new GNDS format. Previously it wasn’t easy to share the full covariance matrix for evaluations containing more than one isotope due to limitations on the ENDF format; this is now supported in GNDS. The data are currently available in a binary SAMMY format and can be exported to GNDS to make them more widely available and sharable. The next step will be to use the same resonance processing code at 0K in AMPX and SAMMY as one of the available Reich-Moore R-Matrix formalism. The first step toward this goal is to isolate the reconstruction into a module that takes resonance parameters as its input and does not depend on SAMMY global parameters. This goal has been achieved and it should now be possible to more easily change the resonance formalism and add enhancements as the Phenomenological R-Matrix parameterization of direct, doorway, and compound nuclear reactions discussed elsewhere on this conference. This concerted modernization and enhancement effort provides multiple advantages to the nuclear data community. It will allow parameter optimization using enhanced formalisms, including experimental effects, that better match complex experimental data. Then those evaluated parameters can immediately be passed off to AMPX to be reconstructed with the exact same cross section model and be put into a data library for subsequent testing using SCALE and the Valid Benchmark suite or other suitable benchmark suites.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Low-Cost Recyclable Oxygen Carrier and Novel Process for Chemical Looping Combustion

The University of North Dakota, through its Institute for Energy Studies and Energy & Environmental Research Center, partnered with Envergex LLC, Barr Engineering and Microbeam Technologies to develop a transformational enabling technology for advancement of Chemical Looping Combustion technology. Industrial support was provided by Carbontec Energy Corporation. The project targeted the two biggest challenges to chemical looping combustion: (1) High costs of oxygen carrier replacement/loss due to expensive manufacturing and high replacement rates from physical attrition and/or decrease in reactivity, and (2) Inherently slow fuel char conversion which represents the rate-limiting step for chemical looping combustion and results in very large equipment sizes, and overall lower carbon dioxide capture efficiency. The project activities were addressed in a series of seven tasks. Task 1 extended throughout the entire project and oversaw project management and execution. Task 2 and 3 focused on development and evaluation of the novel oxygen carrier. Task 4 to 7 focused on design of the novel reactor, testing with the novel oxygen carrier and a techno-economic assessment of the process. The list of tasks are: Task 1 – Project management and planning, Task 2 – Laboratory scale oxygen carrier manufacturing and assessment, Task 3 – Modeling and laboratory-scale evaluation of oxygen carrier performance with coal, Task 4 – 10-kilowatt thermal integrated system installation, Task 5 – Scaled-up oxygen carrier manufacturing, Task 6 – 10-kilowatt testing, and Task 7 – Process design and techno-economic analysis.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Testing SUSY GUTs at the Dark Matter and Collider Experiments

We discuss low scale implications of a class of SUSY GUTs with non-universal SSB masses and confront them with the current experimental results from the direct detection of dark matter experiments, as well as the collider experiments of different center of mass energies. This class of SUSY GUTs are expected to be tested soon in direct detection dark matter experiments through the scatterings of Higgsino and Wino-like dark matters at nuclei. Besides, the stop and gluino will be able to be probed and tested up to about 5-6 TeV in the current and future collider experiments. Furthermore, these probe scales are expected to be further when high luminosities are achieved.

Collider↗
DOE OSTI2021

Property enhancement of CoCrNi medium-entropy alloy by introducing nano-scale features

CoCrNi -medium-entropy alloy (MEA) has been widely investigated due to its superior mechanical properties that overcome strength-ductility tradeoff. Here we show further property enhancement of CoCrNi MEA by introducing nano-scale features. Both CoCrNi and oxide dispersion strengthened (ODS) CoCrNi are fabricated by mechanical alloying and spark plasma sintering. Microstructural characterization and mechanical testing of these nanostructured MEAs revealed that the nano-scale features significantly improves the strength of the alloys. In ODS-CoCrNi MEA, Y 2 Ti 2 O 7 oxides with an average diameter of 7.3 ± 3.2 nm are incoherent with the matrix, and a specific orientation relationship exists between Y 2 Ti 2 O 7 and the matrix, which is [011] Y 2 Ti 2 O 7 //[011]Matrix, (400) Y 2 Ti 2 O 7 //(200)Matrix and ($22\bar2$) Y 2 Ti 2 O 7 //($11\bar1$)Matrix. The recrystallization and grain growth processes are effectively suppressed by the introduction of Y 2 Ti 2 O 7 nanoparticles. Strengthening mechanism analyses indicate that the strength improvement of ODS-CoCrNi is mainly ascribed to the precipitation strengthening of Y 2 Ti 2 O 7 .

36 MATERIALS SCIENCE↗
DOE OSTI2025

High-Temperature Cyclic Particle Storage Bin Testing

The High-Temperature Particle Storage Bin Testing project was designed to answer fundamental questions and provide a demonstration for a small-scale particle-based TES system. This was a first-of-its-kind particle-based TES test system that provided experimental observations of a small-scale TES bin for operation over multiple cycles with particle inlet temperatures up to 800 °C.

25 ENERGY STORAGE↗
DOE OSTI2023

The Kimberlina synthetic multiphysics dataset for CO 2 monitoring investigations

Abstract We present a synthetic multi‐scale, multi‐physics dataset constructed from the Kimberlina 1.2 CO 2 reservoir model based on a potential CO 2 storage site in the Southern San Joaquin Basin of California. Among 300 models, one selected reservoir‐simulation scenario produces hydrologic‐state models at the onset and after 20 years of CO 2 injection. Subsequently, these models were transformed into geophysical properties, including P‐ and S‐wave seismic velocities, saturated density where the saturating fluid can be a combination of brine and supercritical CO 2 , and electrical resistivity using established empirical petrophysical relationships. From these 3D distributions of geophysical properties, we have generated synthetic time‐lapse seismic, gravity and electromagnetic responses with acquisition geometries that mimic realistic monitoring surveys and are achievable in actual field situations. We have also created a series of synthetic well logs of CO 2 saturation, acoustic velocity, density and induction resistivity in the injection well and three monitoring wells. These were constructed by combining the low‐frequency trend of the geophysical models with the high‐frequency variations of actual well logs collected at the potential storage site. In addition, to better calibrate our datasets, measurements of permeability and pore connectivity have been made on cores of Vedder Sandstone, which forms the primary reservoir unit. These measurements provide the range of scales in the otherwise synthetic dataset to be as close to a real‐world situation as possible. This dataset consisting of the reservoir models, geophysical models, simulated time‐lapse geophysical responses and well logs forms a multi‐scale, multi‐physics testbed for designing and testing geophysical CO 2 monitoring systems as well as for imaging and characterization algorithms. The suite of numerical models and data have been made publicly available for downloading on the National Energy Technology Laboratory's (NETL) Energy Data Exchange (EDX) website.

58 GEOSCIENCES↗
DOE OSTI2021

Efficient quadrature rules for finite element discretizations of nonlocal equations

Here, in this paper, we design efficient quadrature rules for finite element (FE) discretizations of nonlocal diffusion problems with compactly supported kernel functions. Two of the main challenges in nonlocal modeling and simulations are the prohibitive computational cost and the nontrivial implementation of discretization schemes, especially in three-dimensional settings. In this work, we circumvent both challenges by introducing a parametrized mollifying function that improves the regularity of the integrand, utilizing an adaptive integration technique, and exploiting parallelization. We first show that the “mollified” solution converges to the exact one as the mollifying parameter vanishes, then we illustrate the consistency and accuracy of the proposed method on several two- and three-dimensional test cases. Furthermore, we demonstrate the good scaling properties of the parallel implementation of the adaptive algorithm and we compare the proposed method with recently developed techniques for efficient FE assembly.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Comparative Analyses of Bioequivalence Assessment Methods for In Vitro Permeation Test Data

ABSTRACT For topical, dermatological drug products, an in vitro option to determine bioequivalence (BE) between test and reference products is recommended. In particular, in vitro permeation test (IVPT) data analysis uses a reference‐scaled approach for two primary endpoints, cumulative penetration amount (AMT) and maximum flux ( J max ), which takes the within donor variability into consideration. In 2022, the Food and Drug Administration (FDA) published a draft IVPT guidance that includes statistical analysis methods for both balanced and unbalanced cases of IVPT study data. This work presents a comprehensive evaluation of various methodologies used to estimate critical parameters essential in assessing BE. Specifically, we investigate the performance of the FDA draft IVPT guidance approach alongside alternative empirical and model‐based methods utilizing mixed‐effects models. Our analyses include both simulated scenarios and real‐world studies. In simulated scenarios, empirical formulas consistently demonstrate robustness in approximating the true model, particularly in effectively addressing treatment–donor interactions. Conversely, the effectiveness of model‐based approaches heavily relies on precise model selection, which significantly influences their results. The research emphasizes the importance of accurate model selection in model‐based BE assessment methodologies. It sheds light on the advantages of empirical formulas, highlighting their reliability compared to model‐based approaches and offers valuable implications for BE assessments. Our findings underscore the significance of robust methodologies and provide essential insights to advance their understanding and application in the assessment of BE, employed in IVPT data analysis.

Leon, Sami↗
DOE OSTI2021

Evaluating causal‐based feature selection for fuel property prediction models

Abstract In‐silico screening of novel biofuel molecules based on chemical and fuel properties is a critical first step in the biofuel evaluation process due to the significant volumes of samples required for experimental testing, the destructive nature of engine tests, and the costs associated with bench‐scale synthesis of novel fuels. Predictive models are limited by training sets of few existing measurements, often containing similar classes of molecules that represent just a subset of the potential molecular fuel space. Software tools can be used to generate every possible molecular descriptor for use as input features, but most of these features are largely irrelevant and training models on datasets with higher dimensionality than size tends to yield poor predictive performance. Feature selection has been shown to improve machine learning models, but correlation‐based feature selection fails to provide scientific insight into the underlying mechanisms that determine structure–property relationships. The implementation of causal discovery in feature selection could potentially inform the biofuel design process while also improving model prediction accuracy and robustness to new data. In this study, we investigate the benefits causal‐based feature selection might have on both model performance and identification of key molecular substructures. We found that causal‐based feature selection performed on par with alternative filtration methods, and that a structural causal model provides valuable scientific insights into the relationships between molecular substructures and fuel properties.

Nguyen, Bernard↗
DOE OSTI2026

Metal alloy microparticle tagging of UO 2 fuel pellets for nuclear forensics

A tagging strategy for UO 2 fuel pellets will be discussed which involves the creation of alloyed metal microparticles that can be tuned to create a unique identification (“barcode”) indicating provenance of the pellets. These specialized markers would contain high temperature resistant materials, such as Ti, Mo, and Cr, in small quantities such that they do not interfere with the performance of the pellets but are recoverable by standard analytical techniques. The Amazemet rePowder ultrasonic atomization system was used to manufacture the microparticles, and sample pellets were fabricated and sintered containing these dopants. Various techniques, such as Scanning Electron Microscopy (SEM) and Electron Probe Microanalysis (EPMA), were used to evaluate these sample pellets to determine if particles (and their alloy compositions) were recoverable. Details on how the particles were manufactured and characterized will be detailed, as well as results from their incorporation into test pellets. Next steps will involve the scale of this technique using more conventional mass production methods, as well as the implementation of other alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Dietary uptake of geosmin in rainbow trout ( Oncorhynchus mykiss )

Geosmin is a primary source of muddy/earthy ‘off-flavors’ in farmed fish, which may render their organoleptic quality unacceptable to consumers. Model systems of geosmin uptake typically comprise exposure to waterborne geosmin that is absorbed via the gills. The present research demonstrates dietary exposure as an alternative route of geosmin uptake in Rainbow Trout (Oncorhynchus mykiss) fillets. Trout (average initial weight of 355 g) were stocked in quadruplicate compartmentalized raceways (N = 4 compartments per treatment, n = 50 fish per compartment) supplied with first-use, flow-through water (4.5 complete turnovers per hour). Fish were fed diets containing 0 (control dose), 0.005 (low dose), 0.05 (medium dose), or 0.5 (high dose) mg geosmin/kg feed at 1% body weight/day for four weeks. Fillets (12 fillets/diet/week plus 12 pre-trial fillet samples) and weekly feed and water samples were analyzed via GC–MS to determine geosmin concentrations. Feeding behavior was documented daily according to a four-point scale. ANOVA with post-hoc Tukey tests and polynomial contrast, regression, correlation, and chi-squared statistical analyses were applied to data (α = 0.05 significance level). Palatability of feed did not hinder consumption of the geosmin-spiked feeds: although fish responded positively to all feeds, the most aggressive feeding behavior was observed among those fed medium and high dose feed. Geosmin was effectively imparted into fillets after one week, and no significant temporal effect was found after four weeks. Mean geosmin concentrations significantly increased in fillets from low (mean of 26 ng/kg geosmin) to medium (202 ng/kg) to high (441 ng/kg) dose feed groups during the trial. Polynomial contrasts and regression modeling validated this significant positive effect of dose on geosmin uptake, with an estimated 166 ng/kg rise in fillet-geosmin for every log 10 increase in feed concentration. Waterborne geosmin levels immediately post-feeding were conditionally independent of concentrations in feed and fillets, therefore dietary uptake was affirmed as the predominant mechanism of absorption in the present experimental system. Finally, based on these findings, geosmin-spiked feeds may be used to induce predictable, repeatable levels of this off-flavor compound in fillets and serve as a model system for further investigation of sensory quality and off-flavor mitigation strategies for farm-raised fish.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Online evolutionary neural architecture search for multivariate non-stationary time series forecasting

Time series forecasting (TSF) is one of the most important tasks in data science. TSF models are usually pre-trained with historical data and then applied on future unseen datapoints. However, real-world time series data is usually non-stationary and models trained offline usually face problems from data drift. Models trained and designed in an offline fashion can not quickly adapt to changes quickly or be deployed in real-time. To address these issues, this work presents the Online NeuroEvolution-based Neural Architecture Search (ONE-NAS) algorithm, which is a novel neural architecture search method capable of automatically designing and dynamically training recurrent neural networks (RNNs) for online forecasting tasks. Without any pre-training, ONE-NAS utilizes populations of RNNs that are continuously updated with new network structures and weights in response to new multivariate input data. ONE-NAS is tested on real-world, large-scale multivariate wind turbine data as well as the univariate Dow Jones Industrial Average (DJIA) dataset. These results demonstrate that ONE-NAS outperforms traditional statistical time series forecasting methods, including online linear regression, fixed long short-term memory (LSTM) and gated recurrent unit (GRU) models trained online, as well as state-of-the-art, online ARIMA strategies. Additionally, results show that utilizing multiple populations of RNNs which are periodically repopulated provide significant performance improvements, allowing this online neural network architecture design and training to be successful.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Coal-derived electrically conductive asphalt pavements for snow/ice melting: From laboratory to field

Timely removal of ice and snow from roads is critical to safe, fast, and uninterrupted transportation networks in cold regions. Constructing electrically conductive asphalt pavements to melt the ice and snow on the roads through resistive eating is an emerging alternative technology to traditional snow/ice removal approaches such as utilizing snowplow machines and deicing chemicals. Carbon-based fibers and fillers including carbon fiber and graphite have been widely reported to make electrically conductive hot mix asphalt mixtures for pavement snow/ice-melting applications. This study aimed to develop and demonstrate a novel type of electrically conductive asphalt pavements for snow/ice-melting, which utilizes electrically conductive cold mix asphalt (CMA) mixtures incorporating coal-derived carbon-based coke aggregate as resistive heating elements. Both laboratory experiments and field tests were conducted to investigate the electrical, mechanical, and thermal properties of such electrically conductive asphalt mixtures and pavements. The laboratory experiment results indicated that the electrically conductive CMA mixtures incorporating coke aggregate had sufficiently high electrical conductivity and satisfactory mechanical performance and the pavement prototype slab utilizing a thin layer of such CMA mixtures could successfully raise the pavement surface temperatures to 8.3–11.7 °C rom a low temperature of –5 °C with an input power density of 473 W/m 2 . The field test results showed that the full-scale coal-derived electrically conductive asphalt pavements were able to increase the pavement surface temperatures when electricity was applied, but the magnitude of temperature increase was highly dependent on the power density. Furthermore, it is promising to use coke aggregate to construct coal-derived electrically conductive asphalt pavements for snow/ice melting.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Effective thermal conductivity of insulation materials for cryogenic LH 2 storage tanks: A review

An accurate estimation of the effective thermal conductivity of various insulation materials is essential in the evaluation of heat leak and boil-off rate from liquid hydrogen storage tanks. In this work, we review the existing experimental data and various proposed correlations for predicting the effective conductivity of insulation systems consisting of powders, foams, fibrous materials, and multilayer systems. We also propose a first principles-based correlation that may be used to estimate the dependence of the effective conductivity as a function of temperature, interstitial gas composition, pressure, and structural properties of the material. We validate the proposed correlation using available experimental data for some common insulation materials. Further improvements and testing of the proposed correlation using laboratory scale data obtained using potential LH 2 tank insulation materials are also discussed.

08 HYDROGEN↗
DOE OSTI2022

Numerical study of multi-component flow and mixing in a scaled fission product venting system

Numerical simulation of isothermal multi-component gas flow was conducted to study fluid flow and mixing in a scaled low-pressure, low-temperature test facility for the fission product venting system (FPVS) of a gas cooled fast reactor (GFR). The geometry of FPVS test facility was an open loop including gradual expansion coupling and two 90°pipe elbows. First, the validation of large eddy simulation (LES) wall-adapting local eddy-viscosity (WALE) turbulent model was performed for transitional flow in a circular pipe with gradual expansion. The reactingFOAM solver in OpenFOAM v8 was employed. By introducing appropriate turbulence disturbance at the flow inlet, such as turbulence intensity, the numerical results showed good agreement in (1) the velocity profile downstream of the pipe expansion measured by particle image velocimetry (PIV) in this study, and (2) the reattachment length reported in the literature. Using this validated model, the numerical simulation of flow and component mixing was performed for the FPVS with an inlet flowrate corresponding to a Reynolds number of 2,400 to investigate the flow behavior and component mixing. Standard deviation of the mass fraction of component, referred to as absolute mixing index (AMI), was calculated to quantify the mixing of components, showing that the component mixing length determined by AMI is related to the reattachment length downstream of the expansion. Additionally, this study was able to identify the best location in the FPVS test facility to measure the velocity and concentration profies where multicomponent flow is well mixed.

15 GEOTHERMAL ENERGY↗