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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Evaluation of Additively Manufactured Materials for Nuclear Plant Components

Powder bed fusion Direct Metal Laser Melting (DMLM) is an evolving additive manufacturing (AM) fabrication technology that is providing high performance parts to many industries. This technology has significant promise for use in building components for nuclear power plants. Implementation of materials produced using this and similar processes offer a potential step change in efficiency for complex parts production and hence a potential for innovative design as well as cost savings for components in the future. Properties of AM Type 316L have been reported in previous work, showing properties that match wrought properties. The fine grain structure may even lead to better environmental resistance. However, there is a need to confirm the behavior of these innovative materials after exposure to radiation if this innovative technology is to be used in current and future nuclear applications. This paper discusses new efforts being explored via a joint program between GE Hitachi (GEH) and INL (Idaho National laboratory) aimed at developing corresponding un-irradiated and irradiated data for AM materials. This paper will present data for both Type 316L stainless steel, a single-phase alloy, and Ni-base Alloy 718, a precipitation hardened alloy, manufactured using AM. This paper, serving as a progress report, will present the mechanical property and microstructural data for both Type 316L and 718 AM alloys to assess their correspondence to wrought alloy data and establish a baseline for future comparison to irradiated properties. The paper will end by discussing the requirements for using these and other additively manufactured materials in future reactor component applications where irradiated data is not available.

316 Stainless Steel↗
DOE OSTI2019

Build optimization of fiber-reinforced additively manufactured components

Additive manufacturing (AM) is enabling the fabrication of artifacts with unprecedented geometric and material complexity. The focus of this paper is on the build the optimization of short fiber reinforced polymers (SFRP) AM components. Specifically, we consider optimization of the build direction, topology, and fiber orientation of SFRP components. All three factors have a significant impact on the functional performance of the printed part. While significant progress has been made on optimizing these independently, the objective of this paper is to consider all three factors simultaneously and explore their interdependency, within the context of thermal applications. Towards this end, the underlying design parameters are identified, appropriate sensitivity equations are derived, and a formal optimization problem is posed as an extension to the popular Solid Isotropic Material with Penalization (SIMP). Results from several numerical experiments are presented, highlighting the impact of build direction, topology, and fiber orientation on the performance of SFRP components.

42 ENGINEERING↗
DOE OSTI2018

Engineering Analysis of Thermal-Load Components in the Process of Heating of Pet Preforms

The influence of thermal-load components (convection, collimated and uncollimated components of infrared radiation) in the process of production of PET packaging on the heating of PET preforms has been assessed. It has been established that the collimated component of infrared radiation ensures most (up to 70%) of the thermal energy in the process of heating of a PET preform.

42 ENGINEERING↗
DOE OSTI2025

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗
DOE OSTI2018

Near Critical Preferential Attachment Networks have Small Giant Components

Preferential attachment networks with power law exponent τ>3 are known to exhibit a phase transition. There is a value ρ{sub c}>0 such that, for small edge densities ρ≤ρ{sub c} every component of the graph comprises an asymptotically vanishing proportion of vertices, while for large edge densities ρ>ρ{sub c} there is a unique giant component comprising an asymptotically positive proportion of vertices. In this paper we study the decay in the size of the giant component as the critical edge density is approached from above. We show that the size decays very rapidly, like exp (−c/√(ρ−ρ{sub c})) for an explicit constant c>0 depending on the model implementation. This result is in contrast to the behaviour of the class of rank-one models of scale-free networks, including the configuration model, where the decay is polynomial. Our proofs rely on the local neighbourhood approximations of Dereich and Mörters (Ann Probab 41(1):329–384, 2013) and recent progress in the theory of branching random walks (Gantert et al. in Ann Inst Henri Poincaré Probab Stat 47(1):111–129, 2011).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Investigation of the Window Variance Noise Component of Multicomponent Signals

Signal partitioning or signal segmentation allows to perform data classification, prediction of signals’ behavior, and profound interpretation of obtained data. In accordance with the signal model some distribution characteristics of the window variance noise component are investigated. It was shown that when all true underlying signal components remain unchanged, the window variance noise component is gamma distributed. Applying window variance to multicomponent signal (i.e., pharmacokinetic curve), it was shown that the window variance allows to split visually the signal record into phases due to prevalent processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Interaction between the emerging components of online shopping and in-person activities: insights from a behavioral survey

The rise of technological advancements has led to the commonplace practice of online shopping for retail, grocery, and food. However, little research has been conducted on the interplay of these components in burdened communities (BCs) that face issues of marginalization and limited access to digital resources. Here, this study aims to provide a comprehensive understanding of travel behavior changes by analyzing the interconnectedness of the emerging components of online shopping (retail, grocery, and food) and in-person activities in both BCs and non-BCs. A unique household-level database is created by linking the 2021 Puget Sound Household Travel Survey and the US Department of Transportation’s burdened community databases, and a conditional mixed process model is estimated to account for unobserved endogeneity. The findings suggest households living in BCs are less likely to order online retail goods and groceries compared to non-BC households. Additionally, the probability of making more restaurant trips decreases for households living in BCs. The study highlights the digital divide that exists in BCs and the differences in online and in-person shopping activities across socioeconomic levels. Policymakers may address these disparities to promote better access to goods and services for all. Besides, planners may need to improve the travel demand models by accounting for the emerging components of online shopping and the trip frequencies by purpose in BCs.

Digital Divide↗
DOE OSTI2019

A Reaction Between High Mn–High Al Steel and CaO-SiO{sub 2}-Type Molten Mold Flux: Reduction of Additive Oxide Components in Mold Flux by Al in Steel

The interfacial reaction between high-Mn–high-Al steel and CaO-SiO{sub 2}-type mold flux was investigated, with particular emphasis on the reduction of additive oxide components by Al. Typical additive oxide components (B{sub 2}O{sub 3}, Na{sub 2}O) could be reduced by Al, thereby losing their initial role in the flux. It is proposed to consider the chemical stability of the additive components in the flux in addition to the physico-chemical properties of the flux when developing the mold flux chemistry.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A New Efficient Quantitative Multi-component Phase Field: Lattice Boltzmann Model for Simulating Ti6Al4V Solidified Dendrite Under Forced Flow

Ti6Al4V is a widely used, multi-component alloy in additive manufacturing, during which the fluid flow in the molten pool significantly affects the solidified dendrites. To predict and further control the microstructure, modeling and simulating the microstructure evolution play a critical role. In this study, a newly developed, efficient, quantitative multi-component phase-field (PF) model is coupled with a lattice Boltzmann (LB) model to simulate Ti6Al4V solidified dendrite evolution under fluid flow. The accuracy and convergence behavior of the model is validated by the Gibbs–Thomson relation at the dendrite tip. Single and multiple two-dimensional (2D) equiaxed dendrite evolution cases under forced flow were simulated. Results show that the dendrite pattern is influenced remarkably by the fluid flow. Underlying mechanisms of the asymmetrical evolution are revealed by discussing the interaction among the flow, composition distribution and dendrite morphology, quantitatively. The dendrite kinetics are also derived, which ascertains the relationship between tip velocity and undercooling and inlet velocity and is the foundation for larger-scale simulation. We believe that the coupled quantitative multi-component PF–LB framework employed in this study helps in investigating the solidified dendrite morphology evolution in a deep and quantitate manner.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multimodal Defect Imaging of Pure Tungsten Components Fabricated via Electron Beam Powder Bed Fusion

The utilization of additive manufacturing (AM) techniques for refractory materials in high-temperature environments has significantly expanded because of the ability to fabricate geometrically complex components. Electron beam powder bed fusion (EB-PBF), which provides lower residual stress, a cleaner vacuum environment, and better efficiency for high melting point, is one of the best-suited AM methods to produce advanced refractory components. However, the property variation attributed to the heterogeneous microstructure and process-induced defects has hindered the widespread adoption of EB-PBF-produced material like tungsten. While numerous in-situ monitoring and defect detection methods have been demonstrated for EB-PBF, a workflow that compares and evaluates process-induced abnormalities from different imaging perspectives is still limited. This study examines a feature-embedded tungsten component manufactured via the EB-PBF process to demonstrate the defect detection capabilities of a multimodal defect imaging workflow. The predefined and process-induced defects are evaluated by harnessing various imaging techniques, including in-situ electron imaging, layerwise near-infrared (NIR) imaging, post-build high-energy x-ray computed tomography (CT), and conventional destructive metallography. The results highlight the strengths and limitations of distinctive defect imaging techniques concerning specific defect types, sizes, and conditions. It was found that electron imaging can provide more abnormal detection capabilities while maintaining a higher measuring accuracy, against the conventional metallography in this case study, compared with NIR and CT imaging techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2018

An Improved Sub-component Fatigue Testing Method for Material Characterization

In this paper an improved sub-component fatigue testing method is proposed, in which structural optimization is used to obtain specimens in which fatigue failure is precipitated in the designated area away from the boundaries, i.e., load application and fixture points. This is achieved by optimizing the nonlinear beam taper and the dynamic excitation. The major requirement for accurate material characterization through sub-component tests concerns unbiased stress states in the gauge section. However, empiricism shows that many sub-component high-cycle fatigue testing methods suffer from failure in the boundaries rather than the gauge section, which causes bias. The common practice for reinforcing those regions only shifts the issue into new areas of local discontinuities where failure is still caused remotely from the gauge section. An experimental proof of concept demonstrates that optimization of the beam taper can be used to obtain unbiased fatigue test data.

42 ENGINEERING↗
DOE OSTI2016

Interpreting and designing microbial communities for bioprocess applications, from components to interactions to emergent properties

Interest in microbial communities for bioprocessing has surged in recent years based on the potential to optimize multiple tasks simultaneously and to enhance process productivity and stability. The presence and magnitude of these desirable system properties often result from interactions between functionally distinct community members. The importance of interactions, while appreciated by some disciplines for decades, has gained interest recently due to the development of ‘omics techniques, polymicrobial culturing approaches, and computational methods which has made the systems-level analysis of interacting components more tractable. This review defines and categorizes natural and engineered system components, interactions, and emergent properties, as well as presents three ecological theories relevant to microbial communities. Case studies are interpreted to illustrate components, interactions, emergent properties and agreement with theoretical concepts. A general foundation is laid to facilitate interpretation of current systems and to aid in future design of microbial systems for the next generation of bioprocesses.

community↗
DOE OSTI2012

Sulfate Storage and Stability on Common Lean NOx Trap Components

Components found in a commercial lean NO{sub x} trap have been studied in order to determine their impact on sulfate storage and release. A micro-reactor and a diffuse reflectance infrared Fourier transform spectrometer (DRIFTS) were used to compare components MgAl{sub 2}O{sub 4}, Pt/MgAl{sub 2}O{sub 4}, Pt/Al{sub 2}O{sub 3}, Pt/Ba/Al{sub 2}O{sub 3}, Pt/CeO{sub 2}-ZrO{sub 2}, and Pt/Ba/CeO{sub 2}-ZrO{sub 2}, as well as physical mixtures of Pt/Al{sub 2}O{sub 3} + MgAl{sub 2}O{sub 4} and Pt/Ba/CeO{sub 2}-ZrO{sub 2} + MgAl{sub 2}O{sub 4}. Desulfation temperature profiles as well as DRIFTS NO{sub x} and SO{sub x} storage spectra are presented for all components. This systematic approach highlighted the ability of the underlying support to impact sulfate stability, in particular when Ba was supported on ceria-zirconia rather than alumina the desulfation temperature decreased by 60-120 C. A conceptual model of sulfation progression on the ceria-zirconia support is proposed that explains the high uptake of sulfur and low temperature release when it is employed. It was also determined that the close proximity of platinum is not necessary for much of the sulfation and desulfation chemistry that occurs, as physical mixtures with platinum dispersed on only one phase displayed similar behavior to samples with platinum dispersed on both phases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

The AAA-ATPase NVL2 is a telomerase component essential for holoenzyme assembly

Highlights: Black-Right-Pointing-Pointer Identification of the AAA-ATPase NVL2 as a novel hTERT-interacting protein. Black-Right-Pointing-Pointer NVL2 associates with catalytically active telomerase via an interaction with hTERT. Black-Right-Pointing-Pointer NVL2 is a telomerase component essential for holoenzyme assembly. Black-Right-Pointing-Pointer ATP-binding activity of NVL2 is required for hTERT binding and telomerase assembly. -- Abstract: Continued cell proliferation requires telomerase to maintain functional telomeres that are essential for chromosome integrity. Although the core enzyme includes a telomerase reverse transcriptase (TERT) and a telomerase RNA component (TERC), a number of auxiliary proteins have been identified to regulate telomerase assembly, localization, and enzymatic activity. Here we describe the characterization of the AAA-ATPase NVL2 as a novel hTERT-interacting protein. NVL2 interacts and co-localizes with hTERT in the nucleolus. NLV2 is also found in association with catalytically competent telomerase in cell lysates through an interaction with hTERT. Depletion of endogenous NVL2 by small interfering RNA led to a decrease in hTERT without affecting the steady-state levels of hTERT mRNA, thereby reducing telomerase activity, suggesting that NVL2 is an essential component of the telomerase holoenzyme. We also found that ATP-binding activity of NVL2 is required for hTERT binding as well as telomerase assembly. Our findings suggest that NVL2, in addition to its role in ribosome biosynthesis, is essential for telomerase biogenesis and provides an alternative approach for inhibiting telomerase activity in cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Molecular identification of BrHAB2a, one of the two AtHAB2-like proteins in Brassica rapa, is an important component of ABA signaling

Highlights: • Fourteen putative PP2C-A-like phosphatases were identified in Brassica rapa. • BrHAB2a was verified as a putative negative regulator of ABA signaling. • The inhibition of BrHAB2a by ABA and its receptors was successfully recapitulated. Abscisic acid (ABA) signaling is a vital physiological step that is used by many land plants to fight against environmental stress. As components of the linear ABA signaling pathway, clade A protein phosphatases type 2C (PP2C-As) are mainly inhibited by PYRABACTIN RESISTANCE1/PYR1-LIKE/REGULATORY COMPONENTS OF ABA RECEPTORS (PYLs)-type receptors upon their binding to ABA. Here, we show that the genome of Brassica rapa encodes 14 putative clade A PP2C-like proteins (BrPP2C-As). Two of these BrPP2C-As, Bra025964 and Bra016595, show high similarity to the HAB2 (Homology to ABI2) protein in Arabidopsis. RNAseq data reveal that nearly all BrPP2C-As, like BrHAB2a (Bra025964) and BrHAB2b (Bra016595), were highly expressed in at least one tissue. Overexpression of BrHAB2a conferred ABA insensitivity to Arabidopsis thaliana seedlings. Furthermore, the phosphatase activity of BrHAB2a could be inhibited by AtPYL1 or BrPYL1 in the presence of ABA. Overall, these results suggest that BrHAB2a is a functional PP2C-A like protein phosphotase and a key component of ABA signaling in Brassica rapa.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Measurement and prediction of through-section residual stresses in the manufacturing sequence of bearing components

Through-section residual stresses in an asymmetric, thin-walled tapered bearing component were non-destructively studied via neutron diffraction after soft machining, heat treatment and hard turning. Two-dimensional area maps revealed non-uniform distributions of stress fields in both the thinnest and thickest sections of the component, indicating that the entire processing sequence plays a vital role — not only in distortion, but in the final stress state as well. Here, a computational model was developed to further understand the extent of the distortion induced in bearing components as a result of process variables in the manufacturing sequence.

36 MATERIALS SCIENCE↗
DOE OSTI2010

Quantitative planar laser-induced fluorescence imaging of multi-component fuel/air mixing in a firing gasoline-direct-injection engine: Effects of residual exhaust gas on quantitative PLIF

A study of in-cylinder fuel-air mixing distributions in a firing gasoline-direct-injection engine is reported using planar laser-induced fluorescence (PLIF) imaging. A multi-component fuel synthesised from three pairs of components chosen to simulate light, medium and heavy fractions was seeded with one of three tracers, each chosen to co-evaporate with and thus follow one of the fractions, in order to account for differential volatility of such components in typical gasoline fuels. In order to make quantitative measurements of fuel-air ratio from PLIF images, initial calibration was by recording PLIF images of homogeneous fuel-air mixtures under similar conditions of in-cylinder temperature and pressure using a re-circulation loop and a motored engine. This calibration method was found to be affected by two significant factors. Firstly, calibration was affected by variation of signal collection efficiency arising from build-up of absorbing deposits on the windows during firing cycles, which are not present under motored conditions. Secondly, the effects of residual exhaust gas present in the firing engine were not accounted for using a calibration loop with a motored engine. In order to account for these factors a novel method of PLIF calibration is presented whereby 'bookend' calibration measurements for each tracer separately are performed under firing conditions, utilising injection into a large upstream heated plenum to promote the formation of homogeneous in-cylinder mixtures. These calibration datasets contain sufficient information to not only characterise the quantum efficiency of each tracer during a typical engine cycle, but also monitor imaging efficiency, and, importantly, account for the impact of exhaust gas residuals (EGR). By use of this method EGR is identified as a significant factor in quantitative PLIF for fuel mixing diagnostics in firing engines. The effects of cyclic variation in fuel concentration on burn rate are analysed for different fuel injection strategies. Finally, mixture distributions for late injection obtained using quantitative PLIF are compared to predictions of computational fluid dynamics calculations. (author)

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

A new chemical kinetic method of determining RON and MON values for single component and multicomponent mixtures of engine fuels

A new method of using chemical kinetic reaction modeling to predict the Research Octane Number (RON) and Motor Octane Number (MON) of single component fuels and fuel mixtures is described and illustrated via comparisons between computed and experimental values obtained using the well-established ASTM test procedures in a Cooperative Fuels Research (CFR) engine. Comparisons include predictions of RON and MON for a large variety of neat fuels, studies determining the RON and MON of mixtures of primary reference fuels (PRF) and toluene, and studies of RON and MON for mixtures of single-component and multiple-component gasoline surrogate mixtures with ethanol. Advantages in costs, time, and experimental complexity of the kinetic modeling approach compared to the existing engine test procedures are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗