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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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Dual Rate Adaptive Control for an Industrial Heat Supply Process Using Signal Compensation Approach

The industrial heat supply process (HSP) is a highly nonlinear cascaded process which uses a steam valve opening as its control input, the steam flow-rate as its inner loop output and the supply water temperature as its outer loop output. The relationship between the heat exchange rate and the model parameters, such as steam density, entropy, and fouling correction factor and heat exchange efficiency are unknown and nonlinear. Moreover, these model parameters vary in line with steam pressure, ambient temperature and the residuals caused by the quality variations of the circulation water. When the steam pressure and the ambient temperature are of high values and are subjected to frequent external random disturbances, the supply water temperature and the steam flow-rate would interact with each other and fluctuate a lot. This is also true when the process exhibits unknown characteristic variations of the process dynamics caused by the unexpected changes of the heat exchange residuals. As a result, it is difficult to control the supply water temperature and the rates of changes of steam flow-rate well inside their targeted ranges. In this paper, a novel compensation signal based dual rate adaptive controller is developed by representing the unknown variations of dynamics as unmodeled dynamics. In the proposed controller design, such a compensation signal is constructed and added onto the control signal obtained from the linear deterministic model based feedback control design. Such a compensation signal aims at eliminating the unmodeled dynamics and the rate of changes of the currently sample unmodeled dynamics. A successful industrial application is carried out, where it has been shown that both the supply water temperature and the rate of the changes of the steam flow-rate can be controlled well inside their targeted ranges when the process is subjected to unknown variations of its dynamics.

Adaptive signal approacg↗
DOE OSTI2023

Microstructure and high temperature properties of tungsten processed via electron beam melting additive manufacturing

There is considerable interest in the adoption of additive manufacturing for processing refractory metals. The layer-wise fabrication approach enables opportunities for producing complex geometries which cannot be otherwise be achieved via powder metallurgy. However, the processing science is still in its nascent stages and structure–property relations are relatively unexplored. Fundamental research is needed to further develop the technology and enable the fabrication of refractory metals for high temperature applications. Here we focus on the processing of pure tungsten using electron beam melting additive manufacturing. Experimentally we develop a suitable processing window for achieving high density crack free material. Microstructural analysis reveals that the microstructure generally consists of a columnar structure with a (111) build direction fiber preference, although, fiber switching was observed. Process induced deformation is believed to drive the formation of subgrains whose boundaries exhibit a high dislocation density. Additionally, high temperature tensile testing reveals that the material exhibits excellent properties closer to that of annealed tungsten. Significant mechanical anisotropy was observed to be present which is likely driven by strong crystallographic texture.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Modeling and analysis of synthetic liquid fuel production from CO 2 and nuclear energy using methanol-to-diesel process

Electrofuels (e-fuels) are synthetic fuels produced from carbon dioxide (CO 2 ) and electricity for blending with or replacing petroleum fuels. Nuclear energy is an attractive energy feedstock for e-fuel production because of its low environmental footprint and its ability to provide steady heat and power essential for e-fuels production. We modeled and evaluated the cost and environmental footprint of e-fuels production in the distillate range for three nuclear power scales, 100, 500, and 1000 MWe, through methanol and olefins intermediates leveraging commercial or high technology readiness level (TRL) processes. Compared to the commonly studied e-fuels from Fischer Tropsch process that has a distillate yield of <70% with the rest being low value naphtha, the proposed process via methanol intermediate increases the product selectivity with distillate yield of 96% and only 4% naphtha. The modeled process has a carbon conversion ratio of 98%, and a process energy efficiency of 56% relative to the total equivalent nuclear electricity input. The e-fuel plant economics and GHG emissions were estimated by considering CO 2 collected from ethanol plants adjacent to nuclear power plants. The estimated minimum fuel selling prices (MFSP) of e-fuel is in the range of $5.7-$9.1/gal depending on e-fuel plant scale, electricity cost, and CO 2 transportation distance. The corresponding e-fuels life cycle GHG emissions is estimated in the range of 5-6 gCO 2 e/MJ of liquid fuel using the R&D Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) model.

10 SYNTHETIC FUELS↗
DOE OSTI2022

Mercury transformation processes in nature: Critical knowledge gaps and perspectives for moving forward

We report the transformation of mercury (Hg) in the environment plays a vital role in the cycling of Hg and its risk to the ecosystem and human health. Of particular importance are Hg oxidation/reduction and methylation/demethylation processes driven or mediated by the dynamics of light, microorganisms, and organic carbon, among others. Advances in understanding those Hg transformation processes determine our capacity of projecting and mitigating Hg risk. Here, we provide a critical analysis of major knowledge gaps in our understanding of Hg transformation in nature, with perspectives on approaches moving forward. Our analysis focuses on Hg transformation processes in the environment, as well as emerging methodology in exploring these processes. Future avenues for improving the understanding of Hg transformation processes to protect ecosystem and human health are also explored.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Physics-informed KNN milling stability model with process damping effects

This paper describes a k-nearest neighbors, or KNN, model for milling stability including process damping effects. A physics-based, frequency domain milling stability solution is used to generate the training data, but does not incorporate process damping effects. The data set is then updated using limited tests to capture the process damping behavior. A “stair step” approach is used to select the test points, where a first spindle speed-axial depth combination is selected based on the physics-based stability map, subsequent tests are defined using the previous test result, and data points are updated by knowledge of process damping behavior and the test results. Furthermore, the KNN modeling approach demonstrates the ability to predict both stable and unstable results, including process damping behavior.

42 ENGINEERING↗
DOE OSTI2025

Creep performance and microstructure of grade 91 steel weldments with integrated welding and thermal processing

Ferritic-Martensitic steel welds typically require post weld heat treatment (PWHT) to restore toughness and high temperature performance. This off-line thermal process reduces disparities between weld and base metal, but can cause distortion, cracking, or simply be impractical due to assembly size and joint non-uniformity. Here we show integrated welding and thermal processing applied to modified 9Cr-1Mo (Grade 91) steel, favored for advanced power generation applications, performed in real time through the addition of a secondary heat source near the primary weld head. Optimal integrated processing reduces weld fusion and heat affected zone hardness by 125 HV, approaching performance of conventional 730 °C, 60 min PWHT processing. Microstructures and mechanical performance are compared for mechanized GTAW welds, with equivalent lifetimes noted in cross-weld creep rupture tests up to 234 MPa at 550 °C, and up to 104 MPa at 650 °C. The integrated process was validated on a Grade 91 pressure vessel with multipass cold wire feed GTAW. After 550 °C, 71.4 bar thermomechanical cyclic testing, the maximum weld hardness is <350 HV.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Process–structure–property relationships in bimodal machined microstructures using robust structure descriptors

Machining is a severe plastic deformation process that subjects materials to high rates of deformation and elevated temperatures. Dynamic recrystallization during severe plastic deformation drives grain refinement into the sub-micron range but the ductility and thermal stability of these structures is poor. In contrast, bimodal microstructures consisting of both fine and coarse grains have been shown to exhibit attractive strength and ductility properties at these temperatures. In this paper, we study the process–structure–property relationships for pure copper subject to a machining process where the cutting speeds are varied. Further, we investigate the role of thermal effects by varying the post-deformation cooling rates. Microstructures generated under these deformation conditions are quantified using angularly resolved chord length statistics. The derived metrics are found to be robust descriptors of the studied microstructures as they automatically capture complex features such as unimodal and bimodal distributions of grain structure, grain constituent length scales, and morphological anisotropy induced by shear deformation. The uniaxial equivalent yield strength of the generated structures are estimated using spherical nanoindentation and inverse modeling techniques. Lastly, we present a methodology for identifying the constrained property-process inverse mapping for machining using a Bayesian framework and the established forward process–structure–property mapping.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Determining processing behaviour of pure Cu in laser powder bed fusion using direct micro-calorimetry

We report copper is challenging to process by laser powder bed fusion (LPBF) given its high reflectivity at common infrared laser diode wavelengths and high thermal conductivity. Successful deposition of copper in a predictable and repeatable fashion relies on understanding the development of the keyhole melting regime, as well as heating, melting, boiling and vapour formation behaviour when interacting with a laser beam within an LPBF environment. In this study, in situ optical absorptivity measurements are used to clarify the complex physics of the laser material interaction. Absorptivity of laser energy is measured using direct micro-calorimetry and compared to melt pool depth in correlation to processing parameters. The measured absorptivity for a 100 μm layer thickness of powder was found to be approximately four times higher than that of the bare polished discs. It was also shown that high laser power above 500 W and scan speed up to 150 mm/s are appropriate for effective melting of the powder layer, with these parameters overcoming the threshold required to achieve keyhole melting. This is explained by multiple reflections withing the powder particles and the lower thermal conductivity of packed powder in comparison to bare discs. Melt pool formation was found to be highly unstable and an explosive behavior was observed when in the keyhole regime, caused by high fluctuations in absorptivity values. This work demonstrates calorimetry can be used to monitor melting behaviour in a real-time fashion during processing for this challenging to process material, thereby avoiding unnecessary parametric optimisation. In addition, the parametric window for optimum processing revealed here can inform future work.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optimizing Bendability and Hardness of Age-Hardenable Aluminum Sheets through Local Thermo-Mechanical Processing

This paper introduces a novel thermo-mechanical process to modify the local mechanical properties of 6xxx aluminum (Al-Mg-Si-Cu) alloy sheets. In this process, two pairs of rollers travel along the length of a sheet while locally bending and unbending it so that the final shape and thickness of the sheet remains unchanged. Room temperature bending/unbending (B/U) produces a deformation gradient through thickness and local hardening in both T4 and T6 sheets (with 41% and 18% greater Vickers hardness, respectively). High temperature bending/unbending performed at ~ 500°C via induction heating, produces significant improvements in local formability as measured by bend testing. Formability levels equivalent to the as-received T4 temper are achieved within the processed zones of T6 sheets with bend angles of ~ 150°, without disturbing the T6 temper in the remainder of the sheet. Finite element simulations and characterization explained the mechanical property improvements and the heterogenous microstructure with weakened Cube texture. Due to its similarity with the roller hemming process, and its compact dimensions, the apparatus developed for B/U has the potential for seamless integration with roller hemming robots to selectively process high strength aluminum sheet materials within mass-production settings.

Efe, Mert [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2025

Operational resilience of additively manufactured parts to stealthy cyberphysical attacks using geometric and process digital twins

Cyberphysical attacks on the digital backbone of Additive Manufacturing (AM) can compromise the printed part’s functionality. They can alter features in the digital geometry to introduce geometric defects (e.g., missing fillets) or alter process parameters to create local defects (e.g., voids). Addressing the downtime, waste, and quality deterioration associated with existing solutions requires operational resilience, i.e., rapid elimination or disruption of defect formation (to retain part function) without production stoppage or part disposal (to retain yield). This need is unmet due to the inherently unpredictable nature of attack-induced alterations, lack of access to the original geometric model for identification of altered geometric features, and in-process imposition of unknown process dynamics via attack-driven alteration of real-time-uncontrolled (or exogenous) parameters. This work establishes the above-mentioned operational resilience for the first time by creating two Digital Twins (DT). The Geometric DT (Geo-DT) is based on a unique physical-field-driven soft sensor and topology optimization method. The Process Digital Twin (Pro-DT) combines local defect quantification with a novel Reinforcement Learning formulation and training method. The importance of these methodological advances and the scalability of our approach are examined on a real AM testbed. It is shown that Geo-DT can correct geometric defects without access to the original digital geometry or explicit knowledge of attack-altered geometric features. Further, Pro-DT can accelerate real-time disruption of local defects despite attack-driven imposition of unknown process dynamics. We discuss how our framework goes beyond the contemporary focus on pre-attack security and in-attack detection towards resilience for AM and beyond.

Additive Manufacturing↗
DOE OSTI2018

Comparison of structure, morphology, and leach characteristics of multi-phase ceramics produced via melt processing and hot isostatic pressing

Melt processing of multi-phase ceramic waste forms offers potential advantages over traditional solid-state synthesis methods given both the prevalence of melters currently in use and the ability to reduce the possibility of airborne radionuclide contamination. In this work, multi-phase ceramics with a targeted hollandite composition of Ba 1.0 Cs 0.3 Cr 1.0 Al 0.3 Fe 1.0 Ti 5.7 O 16 were fabricated by melt processing at 1675 °C and hot isostatic pressing (HIP) at 1250 and 1300 °C. X-ray diffraction analysis (XRD) confirmed hollandite as the major phase in all specimens. Zirconolite/pyrochlore peaks and weaker perovskite reflections were observed after melt processing, while HIP samples displayed prominent perovskite peaks and low-intensity zirconolite reflections. Melt processing produced specimens with large (>50 μm) well-defined hollandite grains, while HIP yielded samples with a more fine-grained morphology. Elemental analysis showed “islands” rich in Cs and Ti across the surface of the 1300 °C HIP sample, suggesting partial melting and partitioning of Cs into multiple phases. Photoemission data revealed multiple Cs 3d spin-orbit pairs for the HIP samples, with the lower binding energy doublets likely corresponding to Cs located in more leachable phases. Among all specimens examined, the melt-processed sample exhibited the lowest fractional release rates for Rb and Cs. However, the retention of Sr and Mo was greater in the HIP specimens.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Thermal analysis of projected molten salt compositions during FFTF and EBR-II used nuclear fuel processing

This work studies the change in liquidus temperature of the salt used in the Mk-IV electrorefiner at the Idaho National Laboratory during processing campaigns of sodium-bonded driver fuels from Experimental Breeder Reactor II and the Fast Flux Test Facility reactor. Modeling and Simulation Tool for Electrochemical Recycling Systems (MASTERS), an INL proprietary pyroprocessing flowsheet simulation tool, was used to simulate the processing campaigns and determine the resulting composition changes of the Mark-IV electrorefiner salt. Surrogate salt samples simulating the Mk-IV electrorefiner salt during the fuel processing campaigns were prepared, and the thermal properties were measured via differential scanning calorimetry. Results from this study indicate that after processing approximately 2,150 kg of uranium metal from used fuel, the liquidus temperature of the molten salt exceeds 520°C, which is a significant increase from 352°C (the melting temperature of eutectic LiCl-KCl). It was also discovered that the liquidus temperature is strongly dependent on the amount of NaCl accumulating in the Mk-IV electrorefiner salt. Thus, the assessment of the liquidus temperature during the subsequent fuel processing campaigns can be simplified by considering the ternary LiCl-KCl-NaCl system only.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

A laboratory-scale process for producing dilithium beryllium tetrafluoride (FLiBe) with dissolved uranium tetrafluoride

Flibe Energy, Incorporated (FEI)'s conceptual Lithium Fluoride Thorium Reactor (LFTR) incorporates a chemical processing facility aimed at recovering uranium and other valuable volatile radionuclides while managing harmful radionuclides from the used fuel. The fuel utilized in this reactor is a combination of dilithium beryllium tetrafluoride (Li 2 BeF 4 or FLiBe) and uranium tetrafluoride (UF 4 ), (FLiBe/U). FEI's plan involves extracting the uranium and other valuable volatile fluoride-forming radionuclides using nitrogen trifluoride (NF 3 ). To facilitate laboratory-scale testing of uranium extraction using NF 3 and address the toxicity and physical hazards associated with beryllium and beryllium fluoride (BeF 2 ), we used a two-step process to prepare the simulated fuel salt. The first step entailed thermally decomposing ammonium beryllium tetrafluoride [(NH 4 ) 2 BeF 4 ] (ABeF) through a nominal 3-step process, combined with appropriate amounts of lithium fluoride (LiF) and UF 4 , resulting in the formation of beryllium fluoride (BeF 2 ). In the second step, the mixture was repeatedly melted and frozen at the melting point of FLiBe to prepare the eutectic FLiBe with dissolved UF 4 . Although the concept appears straightforward, the production of FLiBe/U involved various challenges. These challenges included transporting the gaseous decomposition products of ABeF, hydrogen fluoride (HF) and ammonia (NH 3 ), while preventing the formation of ammonium fluoride (NH 4 F). Additionally, it was necessary to control the reaction between the higher-than-anticipated water content in the commercial ABeF with NH 3 , HF, and the condensed NH 4 F, protect UF 4 from forming an unknown black compound, select suitable structural materials to mitigate fluoride corrosion, address the risks associated with beryllium toxicity through equipment design and operational protocols, and monitor process conditions. This article provides an account of the thermal decomposition chemistry observed in the commercial ABeF, describes the FLiBe/U production apparatus, describes the experiences and process refinements developed to prepare FLiBe/U, and presents our characterizations of prepared FLiBe/U.

Ammonium beryllium fluoride thermal decomposition↗
DOE OSTI2022

Machine learning with knowledge constraints for process optimization of open-air perovskite solar cell manufacturing

Perovskite photovoltaics (PV) have achieved rapid development in the past decade in terms of power conversion efficiency of small-area lab-scale devices; however, successful commercialization still requires further development of low-cost, scalable, and high-throughput manufacturing techniques. One of the critical challenges of developing a new fabrication technique is the high-dimensional parameter space for optimization, but machine learning (ML) can readily be used to accelerate perovskite PV scaling. Herein, we present an ML-guided framework of sequential learning for manufacturing process optimization. We apply our methodology to the Rapid Spray Plasma Processing (RSPP) technique for perovskite thin films in ambient conditions. With a limited experimental budget of screening 100 process conditions, we demonstrated an efficiency improvement to 18.5% as the best-in-our-lab device fabricated by RSPP, and we also experimentally found 10 unique process conditions to produce the top-performing devices of more than 17% efficiency, which is 5 times higher rate of success than the control experiments with pseudo-random Latin hypercube sampling. Our model is enabled by three innovations: (a) flexible knowledge transfer between experimental processes by incorporating data from prior experimental data as a probabilistic constraint; (b) incorporation of both subjective human observations and ML insights when selecting next experiments; (c) adaptive strategy of locating the region of interest using Bayesian optimization first, and then conducting local exploration for high-efficiency devices. Furthermore, in virtual benchmarking, our framework achieves faster improvements with limited experimental budgets than traditional design-of-experiments methods (e.g., one-variable-at-a-time sampling). This framework shows the capability of incorporating researchers’ domain knowledge into the ML-guided optimization loop; therefore, it has the potential to facilitate the wider adoption of ML in scaling to perovskite PV manufacturing.

14 SOLAR ENERGY↗
DOE OSTI2017

Formation and mechanism of nanocrystalline AZ91 powders during HDDR processing

Grain sizes of AZ91 alloy powders were markedly refined to about 15 nm from 100 to 160 μm by an optimized hydrogenation-disproportionation-desorption-recombination (HDDR) process. The effect of temperature, hydrogen pressure and processing time on phase and microstructure evolution of AZ91 alloy powders during HDDR process was investigated systematically by X-ray diffraction, optical microscopy, scanning electron microscopy and transmission electron microscopy, respectively. The optimal HDDR process for preparing nanocrystalline Mg alloy powders is hydriding at temperature of 350 °C under 4 MPa hydrogen pressure for 12 h and dehydriding at 350 °C for 3 h in vacuum. A modified unreacted core model was introduced to describe the mechanism of grain refinement of during HDDR process. - Highlights: • Grain size of the AZ91 alloy powders was significantly refined from 100 μm to 15 nm. • The optimal HDDR technology for nano Mg alloy powders is obtained. • A modified unreacted core model of grain refinement mechanism was proposed.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Fabrication of Al-Zn solid solution via friction stir processing

Highlights: • Thermomechanical nature of FSP was utilized for mechanical alloying. • Zn particles dissolved in Al during FSP to form solid solution. • Second pass of FSP lead to homogenization and partial decomposition of the solid solution. • Processed alloy exhibited improved hardness over base and FSPed metal. • The process can be adopted for site specific property enhancement. - Abstract: The present study demonstrates that friction stir processing (FSP) can be used as a mechanical alloying tool to process solid solution. Zn was incorporated in commercially pure aluminium by multi-pass FSP leading to its dissolution and formation of supersaturated solid solution which was confirmed by X-ray diffraction and scanning electron microscopy. The hardness across the stir zone matched with the distribution of Zn and was significantly improved compared to the base metal. The supersaturated solid solution that formed in the first pass, partially decomposed during the second pass, leading to the formation of fine Al-Zn precipitates. Thermal stability of the microstructure against abnormal grain growth was also improved after the second pass due to the pinning effect of the grain boundary precipitates. FSP also caused grain refinement of the alloy yielding fine equiaxed grains in the range of 4–6 μm with a high fraction (> 67%) of high angle grain boundaries. Such microstructure is conducive for isotropic properties and the fact that the microstructure is stable against thermal cycles make the process suitable for selective alloying for location specific property enhancement.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Accumulative fold-forging (AFF) as a novel severe plastic deformation process to fabricate a high strength ultra-fine grained layered aluminum alloy structure

Highlights: • A novel SPD process named as AFF was introduced. • AFF process is based on the repetitive forging of folded metal foils. • This new method possesses an exceptional capability for fabrication of UFG layered structures. • An AA8006 aluminum alloy layered material with the UFG structure of 200–300 nm was produced. • An enhanced hardness up to ~ 100% was attained owing to the UFG and layered structures. - Abstract: A novel severe plastic deformation (SPD) process termed accumulative fold forging (AFF) is introduced to fabricate a homogenous ultra-fine grained (UFG) layered metal structure by repetitive folding and forging aluminum alloy foil. The present work studies AFF applied to thin foils of AA8006 Al-Fe-Mn aluminum alloy after 26 folding steps to produce a UFG structure containing 67,108,864 layers across a 2 mm thickness. The structure of the layers and grain refinement are studied using X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM) and scanning-transmission electron microscopy (STEM) analysis. The results indicate a well-bonded inter-layer structure with an average grain size of about 200 nm parallel and 250 nm perpendicular to the forging direction, while dislocation density increased to ~ 7.2 × 10{sup 15} m{sup − 2} following AFF. The mechanical strength of the aluminum foil is evaluated in the terms of indentation hardness testing before and after AFF process. The processed UFGed layered material exhibited an average hardness value of ~ 61.5 Vickers as compared to the initial value of ~ 30.4 Vickers for the annealed foil alloy, which indicates an improvement of ~ 100% due to the contributions of grain refinement, work hardening and interfacial strengthening of the bonded layers.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Microstructure and mechanical behavior of hot-work tool steels processed by Selective Laser Melting

Highlights: • H11 and a modified H11 hot work tool steels have been produced by SLM. • As-built alloys are characterized by α-Fe cells surrounded by C-rich γ-Fe regions. • Rapidly solidified structures revealed able to respond to precipitation hardening. • Mechanical behavior of AM H11 is similar to that obtained by conventional processes. - Abstract: The present study is aimed at identifying and testing high-strength alloys for tooling applications featuring suitable processability for laser-based additive manufacturing technologies. The microstructure and mechanical properties of the H11 hot-work tool steel and a leaner version of the same alloy (L-H11) processed by Selective Laser Melting were assessed as a function of specific microstructural conditions obtained by performing different heat treatments. Tempering was performed on quenched alloys or simply from as built material. The rapidly solidified microstructures revealed able to respond directly to precipitation hardening treatment without performing any prior solution annealing. The microstructure of the as-built alloys revealed characterized by α-Fe dendritic cells decorated at boundaries by C-rich γ-Fe regions. Air quenching was responsible for the transformation of the solidification cells into lath martensitic structures and for the formation of the M{sub 3}C phase, which transformed into more complex carbide species on tempering. The hardness of quenched and tempered H11 steel is similar to that obtained by processing the alloy with conventional routes, and the final hardness gap between the two SLM processed H11 and L-H11 alloys treated according to optimal tempered condition was limited to 62 HV.

36 MATERIALS SCIENCE↗