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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 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Integrating helicoid channels for passive control of fiber alignment in direct-write 3D printing

3D printing of fiber-reinforced composites has been receiving increasing attention as an efficient additive approach enabling lightweight, functional, and high-performance components required for industrial applications. The properties of fiber composites significantly depend on internal microstructures, including fiber orientation, distribution, and degree of alignment. Although multiple strategies have been introduced for controlling the fiber composites microstructures, these strategies are mostly active approaches relying on additional control of mechatronics parts, external forces, or intentionally introduced unstable flows inside narrow nozzles. These methods suffer from higher risk of nozzle clogging and requiring extra parts in 3D printing. Here, we introduce helicoid channels into extrusion system as a passive approach to control the fiber alignment without any additional moving parts in direct-write 3D printing. The helicoid channels automatically guide the composite inks and align fibers before flowing into narrow nozzle space, avoiding clogging and improving printability. The analyses indicate that both helicoid surface to volume ratio and helix angle affect the pre-alignment of fibers, leading to tunable mechanical properties of printed fiber-reinforced composites with increased stiffness and strength up to 77.6% and 47.8%, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Mica filled polyetherketoneketones for material extrusion 3D printing

Polyetherketoneketone (PEKK) has superior physical properties to most available thermoplastics compatible with material extrusion-based 3D printing, including analogs in the polyaryletherketone (PAEK) family. To date, the performance of fused filament fabrication (FFF) compatible PEKK has been detailed primarily as a function of varying the isomer ratios composing the co-polymer structure. The strategy to form blends or composites with PEKK for FFF is attractive for further tailoring of performance in application, yet has received limited attention. Here, we report the integration of three grades of mica platelets into PEKK at 10% and 30% mass loadings to generate an array of filament feedstocks that were then used to print objects with a simple FFF machine. The effects of mica coating chemistry and surface treatment on the compatibility with PEKK and resulting properties are described. Mica fillers at both loadings have only subtle influence on the FFF relevant melt rheological properties inherent to PEKK. Pigment micas at high loadings can lower the melting temperature of PEKK (up to 19 ºC) without shifting its glass transition temperature and inhibit much of the undesirable crystallization occurring during processing with unfilled PEKK. The printed composites were effectively cold crystallized post-printing, affording crystalline fractions up to 90% relative to unfilled PEKK with increased dimensional stabilities. All micas, when used as fillers in low and high relative PEKK crystallinities, significantly increased the tensile modulus (as high as 126% or to 7.31 GPa) of parts in correlation to the loading. Furthermore, the underlying microstructural features of a printed composite were compared to unfilled PEKK by use of a high-resolution helical micro-computed tomography instrument. Practically, pigment micas can confer a wide range of rich colors to 3D-printed PEKK.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ThermoPore: Predicting part porosity based on thermal images using deep learning

Part qualification is often a critical and labor-intensive process in additive manufacturing, particularly in the detection of defects such as porosity, which stands to benefit significantly from advancements in machine learning. We present a deep learning approach for quantifying and localizing ex-situ porosity within Laser Powder Bed Fusion fabricated samples utilizing in-situ thermal image monitoring data. Our goal is to build the real time porosity map of parts based on thermal images acquired during the build. The quantification task builds upon the established Convolutional Neural Network model architecture to predict pore count and the localization task leverages the spatial and temporal attention mechanisms of the novel Video Vision Transformer model to indicate areas of expected porosity. Our model for porosity quantification achieved a R 2 score of 0.57 and our model for porosity localization produced an average Intersection over Union (IoU) score of 0.32 and a maximum of 1.0. This work is setting the foundations of part porosity “Digital Twins” based on additive manufacturing monitoring data and can be applied downstream to reduce time-intensive post-inspection and testing activities during part qualification and certification. In addition, we seek to accelerate the acquisition of crucial insights normally only available through ex-situ part evaluation by means of machine learning analysis of in-situ process monitoring data.

Deep learning↗
DOE OSTI2025

Formation mechanisms of Sn-rich δ phase and its role in strengthening Cu-10Sn manufactured by laser powder bed fusion

Cu-Sn alloys produced via laser powder bed fusion (L-PBF) additive manufacturing (AM) have gained significant attention because they combine the advantages of AM relevant to intricate component design with outstanding combinations of strength, ductility, and resistance to wear and corrosion. However, a detailed understanding of the microstructure that contributes to the enhancement of the mechanical properties of L-PBF Cu-10Sn alloys remains unclear. In particular, there is a lack of understanding of the formation mechanisms of the Sn-rich δ phase commonly observed in Cu-10Sn. This study reveals two distinct variants of the δ phase possessing unique morphological characteristics. These characteristics are attributed to the local solidification conditions inherent to the melt pool boundaries versus those at the interiors of melt pools. A phase transformation pathway that elucidates the origin of the morphological variants of the δ phase from the Sn-rich metastable phases during the cyclic heating of the AM process is proposed. We report superior mechanical properties in L-PBF Cu-10Sn compared to those of conventionally manufactured counterparts due to the synergistic contributions from grain boundaries, dislocations, and the δ phase. Notably, the δ phase alone contributes approximately 22 % to the overall strength observed in the L-PBF Cu-10Sn alloy. The discovery of two types of distinct Sn-rich δ phase offers key insights into precise microstructural control in AM Cu-Sn alloys to enhance mechanical properties, providing practical strategies for improving material performance for diverse applications in automotive, aerospace, and machinery industries.

36 MATERIALS SCIENCE↗
DOE OSTI2025

A mechanistic study on environment gas in laser powder bed fusion

A variety of protective or reactive environmental gases have recently gained growing attention in laser-based metal additive manufacturing (AM) technologies due to their unique thermophysical properties and the potential improvements they can bring to the build processes. However, much remains unclear regarding the effects of different gas environments on critical phenomena in laser AM, such as rapid cooling, energy coupling, and defect generation. Through simultaneous high-speed synchrotron x-ray imaging and thermal imaging, we identify distinct effects of two environmental gases in laser AM and gained a deeper understanding of the underlying mechanisms. Compared to the commonly used protective gas, argon, it is found that helium has a negligible effect on cooling the part. However, helium can suppress unstable keyholes by decreasing effective energy absorption, thus mitigating keyhole porosity generation and reducing pore size under certain processing conditions. In conclusion, these observations provide guidelines for the strategic use of environmental gases in laser AM to produce parts with improved quality.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A dynamic data-driven method for dealing with model structural error in soil moisture data assimilation

Attributing to the flexibility in considering various types of observation error and model error, data assimilation has been increasingly applied to dynamically improve soil moisture modeling in many hydrological practices. However, accurate characterization of model error, especially the part caused by defective model structure, presents a significant challenge to the successful implementation of data assimilation. Model structural error has received limited attention relative to parameter and input errors, mainly due to our poor understanding of structural inadequacy and the difficulties in parameterizing structural error. In this paper, we present a dynamic data-driven approach to estimate the model structural error in soil moisture data assimilation without the need for identifying error generation mechanism or specifying particular form for the error model. The error model is based on the Gaussian process regression and then integrated into the ensemble Kalman filter (EnKF) to form a hybrid method for dealing with multi-source model errors. Two variants of the hybrid method in terms of two different error correction manners are proposed. The effectiveness of the proposed method is tested through a suit of synthetic cases and a real-world case. Results demonstrate the potential of the proposed hybrid method for estimating model structural error and providing improved model predictions. Compared to the traditional EnKF without explicitly considering the model structural error, parameter compensation issue is obviously reduced and soil moisture retrieval is substantially improved.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Using the red chromatic coordinate to characterize the phenology of forest canopy photosynthesis

Vegetation phenology has received increasing attention in climate change research. Near-surface sensing using digital repeat photography has proven to be useful for ecosystem-scale monitoring of vegetation phenology. However, our understanding of the link between phenological metrics derived from digital repeat photography and the phenology of forest canopy photosynthesis is still incomplete, especially for evergreen plant species. Using 49 site-years of digital images from the PhenoCam Network from eight evergreen needleleaf forest (ENF) and six deciduous broadleaf forest (DBF) sites in North America, we explored the potential of the green chromatic (GCC) and red chromatic coordinates (RCC) in tracking forest canopy photosynthesis by comparing camera-derived start- and end-of-growing season (SOS and EOS, respectively) with corresponding estimates derived from eddy covariance-derived daily gross primary productivity (GPP). We found that for DBF sites, both GCC and RCC performed comparable in capturing SOS and EOS. However, similar to earlier studies, GCC had limited potential in capturing GPP-based SOS or EOS for ENF sites. In contrast, we found RCC was a better predictor of both GPP-based SOS and EOS for ENF sites. Environmental and ecological explanations were both provided that phenological transitions derived from RCC were highly correlated with spring and autumn meteorological conditions, as well as having overall higher correlations with phenology based on LAI, a critical variable for describing canopy development. Our results demonstrate that RCC is an underappreciated metric for tracking vegetation phenology, especially for ENF sites where GCC failed to provide reliable estimates for GPP-based SOS or EOS. Our results improve confidence in using digital repeat photography to characterize the phenology of canopy photosynthesis across forest types.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Comparative energetics of carbon storage molecules in green algae

Several members of the green algae possess the ability to produce lipids and/or high value compounds in significant quantities. While for several of these green algal species induction of increased lipid production has been shown, and cultivation of species for high value molecules occurs at production scale, the molecular mechanisms governing over-accumulation of molecules synthesized from isoprenoid precursors, carotenoids, for example, have received far less attention. Here, we present a calculation of the required ATP equivalencies per carbon atom and reducing power equivalencies as NADH/NADPH (NAD(P)H) per carbon atom for the isoprenoid molecules ..beta..-carotene (C40), astaxanthin (C40), and squalene (C30). We compared energetic requirements of carbohydrates, triacylglycerol, and isoprenoid molecules under a gradient of conditions of cellular stress. Our calculations revealed slightly less ATP and NAD(P)H equivalency per carbon atom between triacylglycerol and the three isoprenoid molecules. Based on our results, we propose that the driving force for differences in accumulation patterns of carotenoids vs. triacylglycerols in algal cells under stress is largely dependent on the presence and regulation of bypass mechanisms at metabolic junction bottlenecks, like pyruvate dehydrogenase (PDH), within particular species. We provide a discussion of several molecular mechanisms that may influence carbon partitioning within different groups of green algae, including metabolic inhibition through accumulation of specific substrates related to ATP and reducing equivalent production (NAD(P)H) as well as cellular compartmentalization. This work contributes to the ongoing discussion of cellular homeostatic regulation during stress, as well as the potential mechanisms driving long-term carbon storage as it relates to energy and redox states within the algal cell.

09 BIOMASS FUELS↗
DOE OSTI2019

Mitigation of variable seasonal productivity in algae biomass through blending and ensiling: An assessment of compositional changes in storage

Microalgae biomass has gained considerable attention in recent years as an attractive feedstock for biofuel production. However, seasonal variability in algae growth presents a challenge to delivering a consistent feedstock supply to a conversion facility. Drying is one approach to preserving algae produced in productive summer months for conversion in winter, but is energy intensive and costly. Ensiling is an alternative to drying that preserves algae in wet anaerobic conditions in the presence of organic acids. We have previously demonstrated that dry matter loss of algae:corn stover blends can be limited to 8% over 35 days using this approach. However, longer storage durations will be required to maintain a consistent feedstock supply to a biorefinery. Furthermore, the impacts to biomass quality that occur during storage are unknown. A Box-Behnken design of experiment was conducted to determine the influence of moisture, soluble sugar, and algae content on dry matter loss of algae:corn stover blends in wet anaerobic storage over a 30-day period. Using one-way analysis of variance (ANOVA) moisture and soluble sugar content were found to significantly affect dry matter loss in storage. The results of experimental design were then used to inform the initiation of a 180 day storage study that evaluated the storage performance and biomass composition of algae:corn stover blends containing 5, 20 or 40% algae. After 180 days of storage dry matter loss ranged from 6 – 17%. A relative increase in nitrogen content of stored blends indicates that protein content was unaffected by storage, while the carbohydrate fraction was most impacted, decreasing by 5 – 15%. For each stored blend the oxygen content decreased in storage resulting increased higher heating values (HHV). As a result, the impact that changes to biochemical and elemental composition of algae:corn stover blends has on biomass conversion to fuels and chemicals is discussed.

09 BIOMASS FUELS↗
DOE OSTI2026

The Energy Costs of Dewatering Feedstock Microalgae Species Using Conventional Implementations of Ultrasonic and Crossflow Filtration Technologies

The use of microalgae as a feedstock for biofuels and other products continues to be explored, but large-scale biomass production faces persistent high costs. One major cost contributor is the energy required for harvesting and dewatering, a challenge resulting from the dilute nature of microalgae cultures as well as the properties of microalgae cells. This study investigated the energy demands of concentrating three diverse microalgae species (Nannochloropsis salina, Scenedesmus obliquus, and Chlorella luteoviridis) exhibiting different settling velocities, a key harvesting property, using conventional ultrasonic and crossflow membrane filtration. Membrane-free ultrasonic filtration removed 60-80% of the microalgae largely in steady-state operations, increasing concentrations 20-100 times, while consuming 1-6 kWh/m3 - similar to centrifugation. In contrast, crossflow membrane filtration retained nearly 100% of the microalgae, increasing concentrations over 20-fold, but consumed 158 kWh/m3 - over 10 times the energy of centrifugation. Both approaches exceeded the 10% energy target suggested in the 2010 National Algal Biofuel Technology Roadmap. This study also highlights potential sources of energy savings. For ultrasonic filtration, attention to an innovative, dynamic property of the ultrasonic chamber called the Energy Efficiency Factor, could lead to energy reductions by no more than 10-fold and improve the favorability of two of the microalgae species studied. For membrane filtration, a dead-end configuration could reduce energy consumption by no more than 1000-fold, making it favorable for all three species. This study not only highlights the need to further increase the energy content of microalgae cultures, but also the critical importance of continued development of ultrasonic filtration and other harvesting technologies to achieve low-cost, energy-sustainable algal biofuels.

09 BIOMASS FUELS↗
DOE OSTI2018

An angular biasing method using arbitrary convex polyhedra for Monte Carlo radiation transport calculations

This paper presents a new method for performing angular biasing in Monte Carlo radiation transport codes using arbitrary convex polyhedra to define regions of interest toward which to project particles (DXTRAN regions). The method is derived and is implemented using axis-aligned right parallelepipeds (AARPPs) and arbitrary convex polyhedra. Attention is also paid to possible numerical complications and areas for future refinement. A series of test problems are executed with void, purely absorbing, purely scattering, and 50% absorbing/50% scattering materials. For all test problems tally results using AARPP and polyhedral DXTRAN regions agree with analog and/or spherical DXTRAN results within statistical uncertainties. In cases with significant scattering the figure of merit (FOM) using AARPP or polyhedral DXTRAN regions is lower than with spherical regions despite the ability to closely fit the tally region. This is because spherical DXTRAN processing is computationally less expensive than AARPP or polyhedral DXTRAN processing. Thus, it is recommended that the speed of spherical regions be considered versus the ability to closely fit the tally region with an AARPP or arbitrary polyhedral region. It is also recommended that short calculations be made prior to final calculations to compare the FOM for the various DXTRAN geometries because of the influence of the scattering behavior.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Phenomena Identification and Ranking Table (PIRT) study for metallic structural materials for advanced High-Temperature reactor

The Fluoride High-Temperature Reactor (FHR) technology promises many benefits including passive safety, proliferation-resistant waste forms, and improved economics. However, selection of reliable structural materials and identification of the possible degradation mechanisms for these is important for the licensure and the safe operation of FHRs. In order to address this task, the Georgia Tech led Integrated Research Project (IRP) hosted a Phenomena Identification and Ranking Table (PIRT) panel of experts to address degradation mechanisms and other materials related issues of importance to the FHRs. Futhermore, materials, ones that come in contact with FLiBe or FLiNaK molten salts or other related environments like high temperature steam etc., were considered in this PIRT. Focus of this PIRT was the metallic alloys, especially the ones that are permitted for the construction of elevated temperature Class A components by the ASME code. Degradation mechanisms considered in this PIRT included chemical degradation, mechanical degradation, radiation degradation, and synergistic effect of these mechanisms that may negatively impact operations or cause some safety concerns for the major structural components of FHRs. Main components which were considered included vessel and primary piping, primary heat exchangers, steam generator vessel, steam generator tubes, intermediate loop piping, valves and pumps. Welds in all structural components were identified as an important class of material, which varies in composition and properties, and needs more attention. Importance of impurity control in molten fluorides considered for FHR was highlighted throughout PIRT panel discussions. As a result, this paper gives a summary of important results from the PIRT panel discussions and report.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Coupled fuel performance calculations in VERA and demonstration on Watts Bar unit 1, cycle 1

As the core simulator capabilities in the Virtual Environment for Reactor Applications (VERA) have become more mature and stable, increased attention has been focused on coupling Bison to provide fuel performance simulations. This technique has been a very important driver for the pellet-clad interaction challenge problem being addressed by the Consortium for Advanced Simulation of Light Water Reactors (CASL). Here, two coupling approaches are demonstrated on quarter core problems based on Watts Bar Nuclear Plant Unit 1, Cycle 1: (1) an inline approach in which a one-way coupling is used between neutronics/thermal hydraulics (through MPACT/CTF) and fuel performance (through Bison) but no fuel temperature information is passed back to MPACT/CTF, and (2) a two-way approach (coupled) in which the fuel temperature is passed from Bison to MPACT/CTF. In both approaches, power and temperature distributions from MPACT/CTF are used to inform the Bison simulations for each rod in the core.The demonstrations presented here are the first integrated fuel performance simulations in VERA, which opens many possibilities for future work, including applications to accident-tolerant fuel efforts and transient simulations, which are of critical importance to CASL. These demonstrations also highlight the potential to move away from the current Bison-informed fuel temperature lookup table approach, which is the default in MPACT/CTF simulations, if performance improvements are made in the near future.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Conceptual core design of the molten metal fueled microreactor with self-regulating capability

The microreactor concept has received significant attention in the United States for its lower capital investment, siting flexibility and high mobility. A microreactor aims to provide reliable electricity in remote communities, mining areas, or isolated islands, which will save the high fuel transportation cost. Thus, minimizing the staff level for operating and maintaining a microreactor is desirable. The objective of the study is to design a self-regulated Molten Metal fueled microReactor core (MMR) and to demonstrate the self-regulating capability of the MMR core. The control of the reactor is solely relying on reactivity feedbacks from fuel temperature perturbation. Molten UMn (liquid form at the temperature over 720°C) was utilized as the fuel material in MMR due to the larger thermal expansion coefficient compared to the conventional solid fuel. The MMR core has a fast neutron spectrum, which corresponds to a small burnup reactivity swing. The core design parameters were selected based on DAKOTA, REBUS, and ANLHTP calculations. The MMR is designed to run for 10 years at a power level of 15 MWth. Furthermore, no refueling is needed during the reactor lifetime. The system dynamic analyses were performed, and it was found that the reactor can be self-regulating within a temperature range of 800 ± 80°C for a loss of heat sink transient.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Pre-trained network-based transfer learning: A small-sample machine learning approach to nuclear power plant classification problem

Some research topics belonging to classification problems in the nuclear industry, such as fault diagnosis and accident identification, can be solved by feature extraction and subsequent application of statistical machine learning classifiers. Recently, deep neural network-based methods with automatic feature extraction and high accuracy have gained wide attention. They usually require large-scale training data, however, plant fault or accident data are scarce or difficult to obtain. Here this paper proposes a convolutional network (CNN)-based transfer learning method to solve this problem. The network's shallow layer is derived from a pre-trained CNN based on the ImageNet database to automatically extract features, and the deep layer is customized to match the classification problem. Data in non-image formats are converted to image formats and subsequently used to train the network. Case studies of rotating machines fault diagnosis show that the proposed method requires only limited training data to achieve high accuracy.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2013

Measurement-induced disturbance and thermal negativity in 1D optical lattice chain

We study the measurement-induced disturbance (MID) in a 1D optical lattice chain with nonlinear coupling. Special attention is paid to the difference between the thermal entanglement and MID when considering the influences of the linear coupling constant, nonlinear coupling constant and external magnetic field. It is shown that MID is more robust than thermal entanglement against temperature T and external magnetic field B, and MID may reveal more properties about quantum correlations of the system, which can be seen from the point of view that MID can be nonzero when there is no thermal entanglement and MID can detect the critical point of quantum phase transition at finite temperature. - Highlights: Black-Right-Pointing-Pointer The nonlinear coupling constant can strengthen the quantum correlation. Black-Right-Pointing-Pointer MID is more robust than entanglement against temperature and magnetic field. Black-Right-Pointing-Pointer MID exhibits more information about quantum correlation than entanglement. Black-Right-Pointing-Pointer MID can detect the critical point of quantum phase transition at finite temperature.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

Scalar–vector–pseudoscalar Cornell potential for a spin-1/2 particle under spin and pseudospin symmetries: 1+1 dimensions

The Cornell potential consists of Coulomb and linear potentials, i.e. −a/x+bx, that has received a great deal of attention in particle and nuclear physics. In this paper, we present exact solutions of the Dirac equation with the mixed scalar–vector–pseudoscalar Cornell potential under spin and pseudospin symmetry limits. The corresponding eigenfunctions are given in the form of the biconfluent Heun polynomials. -- Highlights: •We investigate the Dirac equation with the scalar–vector–pseudoscalar Cornell potential. •The solutions are discussed in view of spin and pseudospin symmetry limits. •The energy levels and the wave function are presented in Heun biconfluent equations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗