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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Heat Transfer Experiments of a 1st Stage Blade Cascade for Supercritical CO2 Oxy-Combustion Turbine Application

The results of internally cooled 1st stage blade (S1B) cascade testing in a supercritical CO2 environment is presented. The turbine blade design has been previously established for the end application of an oxy-combustion turbine operating in the Allam-Fetvedt cycle with turbine inlet conditions of 305 bar and 1150°C. The internally cooled blade features leading edge (LE) region impingement cooling, mid-section ribbed serpentine passages, and a pin-finned trailing edge (TE) region before cooling ejection holes. The geometry for the tested blade cascade has a cooled central blade with un-cooled blades on either side to match flowpath areas of the actual turbine. The flowpath reuses internal components previously employed for mid-section region ribbed serpentine passage experiments that established Nusselt number enhancement ratios over a range of Reynolds numbers from 100,000-400,000. New components include flow conditioning plates upstream and downstream of the blade cascade to adequately represent the flow field and blade external heat transfer coefficient profiles for the actual turbine. The cooled central blade utilizes uniform crystal temperature sensors (UCTS) with six sensors each on the blade pressure and suction surfaces distributed radially and from LE to TE. The post-processed UCTS quantified the maximum wall temperature seen at each installed sensor location. The test procedure consisted of establishing supercritical CO2 cooling flow temperature and flow rate and maintaining it throughout the test. The flow rate aims to match that for the actual in-service turbine blade design and is maintained through an orifice restriction to keep the pressure differential between internal cooling flow and external hot flow nearly constant. For the sCO2 flow path external to the blade, temperatures were ramped throughout the test via control of the test loop’s natural gas burner heater. The maximum temperature seen was 468°C and held constant for a duration of 10 minutes at which the blade metal temperature was predicted to be at its maximum before ramping down. For the turbine blade design for service inlet conditions, external flow path computational fluid dynamics (CFD) results and an internal cooling 1-D thermal and hydraulic flow network model using experimentally validated correlations served as thermal finite element (FE) boundary conditions to predict blade metal temperatures. These predicted temperatures were subsequently utilized in a structural FE model to predict blade life ratings dictated by Haynes 282 creep strength data, having a strong dependence on temperature. The boundary conditions experienced during testing are used in the same workflow and compared to the experimental results, with the goal of validating the analysis methodology and providing insight on the uncertainty in local metal temperature predictions.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2026

Affine Transformations to Enable Machine Learning for Semi-Quantitative EDS Analysis

Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Affine Transformations to Correlate Experimental and Simulated EDS Spectra for Multi-Element Systems

Energy Dispersive X-ray Spectroscopy (EDS) is an essential technique for determining elemental concentrations and distributions within microstructures, critical for materials discovery, optimization, and qualification. However, most published EDS data is qualitative because current quantitative EDS analysis methods require extensive calibration and post-processing, limiting their practicality and widespread adoption. This work seeks to establish a framework for accelerated EDS characterization and spectrum analysis that can leverage ML to analyze correlations between various elemental compositions and resulting EDS spectra. The complex physics and data result in a high-dimensional problem that grows exponentially with the number of elements in the system and the complexity of the spectrum analysis. ML provides a way to compute and optimize the results of this highly dimensional problem in a flexible way to tailor it to the user’s specific needs and material system. However, the framework emphasizes transparency through a strictly mathematical affine transformation, so the analysis remains understandable and reviewable to facilitate adoption by the scientific community. While currently implemented methods are simplistic and unvalidated, further development and demonstration of this framework could enable high-throughput, accurate, and accessible EDS characterization.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2011

Symmetric-Galerkin boundary element transient analysis of the DSIFs for the interaction of a crack with a circular inclusion

A dynamic analysis of crack-inclusion interaction is described in this paper. The analysis employs a two-dimensional symmetric-Galerkin boundary integral formulation for multi-domain elastodynamic fracture analysis in the frequency domain. The multi-domain technique is based on the assumption of perfectly bonded inclusions. The numerical implementation of this boundary integral formulation is carried out with standard quadratic elements, allowing the use of an improved quarter-point element for accurately determining frequency responses of the dynamic stress intensity factors (DSIFs). To deal with singular and hypersingular integrals, the formulation is decomposed into two parts: the rst part is identical to that for elastostatics while the second part contains at most logarithmic singularities. The treatment of the elastostatic singular and hypersingular singular integrals employs an exterior limit to the boundary, while the weakly singular integrals in the second part are handled by Gauss quadrature. Time histories (transient responses) of the DSIFs are obtained in a post-processing step by applying the fast Fourier transform (FFT) and inverse FFT to the frequency responses of these DSIFs. Two numerical examples are presented for the computation of the DSIFs due to crack-inclusion interaction under two types of impact loading: Heaviside step loading and blast loading. The numerical results are consistent and con rm the well known crack tip shielding mechanism observed during the interaction between a crack and a much stiffer inclusion.

36 MATERIALS SCIENCE↗
DOE OSTI2010

H5hut: A High-Performance I/O Library for Particle-based Simulations

Particle-based simulations running on large high-performance computing systems over many time steps can generate an enormous amount of particle- and field-based data for post-processing and analysis. Achieving high-performance I/O for this data, effectively managing it on disk, and interfacing it with analysis and visualization tools can be challenging, especially for domain scientists who do not have I/O and data management expertise. We present the H5hut library, an implementation of several data models for particle-based simulations that encapsulates the complexity of HDF5 and is simple to use, yet does not compromise performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

BFSVBF (BatFinder Smart Video BioFilter) [SWR-22-87] and Multi-class BatFinder Smart Video BioFilter Keras

Bats are notoriously difficult to study, therefore, identifying specific behavioral trends and the precise environmental conditions at the time of collision requires a monitoring solution that can reliably collect relevant data. To date, thermal infrared video surveillance has been extensively applied to study bats and has proven to be a powerful yet cumbersome tool. Current analytical approaches are time consuming because data processing data has not been fully automated. In the past, steps have been taken to record avian and bat activity in conjunction with complicated image processing techniques that separate species from other moving objects within the field of view (i.e. clouds and portions of the wind turbine). Once the videos are collected, the post-processing does not allow real time monitoring and identification, leading to a delay in both studying the behavior of these species and determining the effectiveness of any impact reduction strategy being studied. Moreover, object identification capability is lacking, thus limiting the usefulness of video data. To resolve these issues, we are using open source computer vision and machine learning techniques allowing for automatic detection of objects in real-time with the ability to correlate these objects with environmental variables and recording the flight paths of each object. The code has gone through five rounds of development with images used to train the models. This advancement allows for automated real-time data collection, identification, and tracking, thereby eliminating the need for long and tedious post-analysis processing of the videos. We will discuss the two open source and publicly available machine learning models developed within this scope of this work: 1) a binary model with a 97.5% accuracy in identifying the difference between an object and an empty scene, including wind turbine and clouds; and 2) a multiple classification model with the capability of identifying the type of object detected: bats (90% accuracy), birds (83% accuracy), insects (69% accuracy) and non-biological (99% accuracy).

Yarbrough, John↗
DOE OSTI2016

Feasibility of in situ controlled heat treatment (ISHT) of Inconel 718 during electron beam melting additive manufacturing

A novel technique was developed to control the microstructure evolution in Alloy 718 processed using Electron Beam Melting (EBM). In situ solution treatment and aging of Alloy 718 was performed by heating the top surface of the build after build completion scanning an electron beam to act as a planar heat source during the cool down process. Results demonstrate that the measured hardness (478 ± 7 HV) of the material processed using in situ heat treatment similar to that of peak-aged Inconel 718. Large solidification grains and cracks formed, which are identified as the likely mechanism leading to failure of tensile tests of the in situ heat treatment material under loading. Despite poor tensile performance, the technique proposed was shown to successively age Alloy 718 (increase precipitate size and hardness) without removing the sample from the process chamber, which can reduce the number of process steps in producing a part. Lastly, tighter controls on processing temperature during layer melting to lower process temperature and selective heating during in situ heat treatment to reduce over-sintering are proposed as methods for improving the process.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Removing Fluoride from Double Four-Membered Rings Yielding Defect-Free Zeolites under Mild Conditions Using Ozone

We have investigated ozone treatment of as-made LTA zeolites under mild temperature conditions (175 °C) using experiments and periodic DFT as a method of energy savings and engineering defects such as silanol nests in comparison with conventional calcination at 550 °C. We have studied ozone treatment on LTA samples synthesized with 1,2-dimethyl-3-(4-methylbenzyl) imidazolium (denoted as “BULKY”) as the primary organic structure-directing agent (OSDA) and with various amounts of tetramethylammonium (TMA) as a secondary OSDA. Ozone treatment of LTA-BULKY at 175 °C was found to give defect-free, pristine LTA materials as determined by 29 Si NMR, 13 C NMR, Raman spectra, and DFT to assign the spectra. This represents a significant and unexpected finding: that fluoride ions can be completely removed from double four-membered rings (D4Rs) under such mild conditions. Furthermore, ozone treatment of LTA-BULKY-TMA samples removed BULKY but left behind TMA/F, giving a new and more diverse structural landscape of Si environments in LTA. Ab initio MetaDynamics calculations provide pathways with relatively low barriers, explaining how fluoride ions can be removed from D4Rs, leaving behind defect-free LTA materials under mild conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Sulfidation kinetics of titanium and Ti-6Al-4V with elemental sulfur

The sulfidation kinetics of titanium and Ti-6Al-4V (Ti64) using elemental sulfur were studied by measuring the amount of metal consumed instead of the change in mass or scale thickness. Here this metal consumption approach combines the parabolic oxidation law, Arrhenius equation, and Pilling-Bedworth ratio to determine the apparent activation energy and the pre-exponential factor of consumption of Ti64 during sulfidation. The estimations of apparent activation energy and pre-exponential factor were 110.4 kJ·mol -1 and 1.3×10 -9 m 2 s -1 for the titanium-sulfur, and 116.2 kJ·mol -1 and 1.2×10 -9 m2s -1 for the Ti64-sulfur system. Finally, a material removal predictor was developed to predict the amount of Ti64 consumed for a given sulfidation temperature and time.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Additive manufacturing of high‐density silicon carbide ceramics through post‐processing spark plasma sintering

This research advances the field of additive manufacturing (AM) of silicon carbide (SiC) ceramics by integrating spark plasma sintering (SPS) to enhance material density, mechanical strength, and thermal properties. Traditional AM techniques struggle to achieve the high‐density SiC required for demanding applications, such as aerospace engineering, where high thermal conductivity and mechanical strength are paramount. Here, our study addresses these challenges by incorporating SPS as a post‐processing step, achieving near‐theoretical maximum densities and significantly reducing porosity, thereby resulting in outstanding thermal conductivity in SiC ceramics. We developed a specialized SiC ink optimized for 3D printing, ensuring structural integrity after deposition through tailored rheological properties. The application of SPS facilitates rapid, uniform sintering, essential for attaining superior density, mechanical properties, and thermal performance. Our experimental results, confirmed through scanning electron microscopy analysis, demonstrate significant microstructural properties, mechanical strength, and thermal conductivity, showcasing the effectiveness of integrating SPS in AM processes. This innovative approach not only expands the capabilities of AM in producing complex, high‐density ceramic structures but also broadens the potential applications of SiC in demanding environments.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Scalable Analysis Methods and In Situ Infrastructure for Extreme Scale Knowledge Discovery

High performance computers have for many years been on a trajectory that gives them extraordinary compute power with the addition of more and more compute cores. At the same time, other system parameters such as the amount of memory per core and bandwidth to storage have remained constant or have barely increased. This creates an imbalance in the computer, giving it the ability to compute a lot of data that it cannot reasonably save out due to time and storage constraints. While technologies have been invented to mitigate this problem (burst buffers, etc.), software has been adapting to employ in situ libraries which perform data analysis and visualization on simulation data while it is still resident in memory. This avoids the need to ever have to pay the costs of writing many terabytes of data files. Instead, in situ enables the creation of more concentrated data products such as statistics, plots, and data extracts, which are all far smaller than the full-sized volume data. With the increasing popularity of in situ, multiple in situ infrastructures have been created, each with its own mechanism for integrating with a simulation. To make it easier to instrument a simulation with multiple in situ infrastructures and include custom analysis algorithms, this project created the SENSEI framework.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Comparison of the Gaussian Wind Farm Model with Historical Data of Three Offshore Wind Farms

A recent expert elicitation showed that model validation remains one of the largest barriers for commercial wind farm control deployment. The Gaussian-shaped wake deficit model has grown in popularity in wind farm field experiments, yet its validation for larger farms and throughout annual operation remains limited. This article addresses this scientific gap, providing a model comparison of the Gaussian wind farm model with historical data of three offshore wind farms. The energy ratio is used to quantify the model’s accuracy. We assume a fixed turbulence intensity of $I_∞$ = 6% and a standard deviation on the inflow wind direction of $σ_{wd}$ = 3° in our Gaussian model. First, we demonstrate the non-uniqueness issue of $I_∞$ and $σ_{wd}$, which display a waterbed effect when considering the energy ratios. Second, we show excellent agreement between the Gaussian model and historical data for most wind directions in the Offshore Windpark Egmond aan Zee (OWEZ) and Westermost Rough wind farms (36 and 35 wind turbines, respectively) and wind turbines on the outer edges of the Anholt wind farm (110 turbines). Turbines centrally positioned in the Anholt wind farm show larger model discrepancies, likely due to deep-array effects that are not captured in the model. A second source of discrepancy is hypothesized to be inflow heterogeneity. In future work, the Gaussian wind farm model will be adapted to address those weaknesses.

17 WIND ENERGY↗
DOE OSTI2024

Surface Finishing and Coating Parameters Impact on Additively Manufactured Binder-Jetted Steel–Bronze Composites

In this paper, electroless nickel plating is explored for the protection of binder-jetting-based additively manufactured (AM) composite materials. Electroless nickel plating was attempted on binder-jetted composites composed of stainless steel and bronze, resulting in differences in the physicochemical properties. We investigated the impact of surface finishing, plating solution chemistry, and plating parameters to attain a wide range of surface morphologies and roughness levels. We employed the Keyence microscope to quantitatively evaluate dramatically different surface properties before and after the coating of AM composites. Scanning electron microscopy revealed a wide range of microstructural properties in relation to each combination of surface finishing and coating parameters. We studied chempolishing, plasma cleaning, and organic cleaning as the surface preparation methods prior to coating. We found that surface preparation dictated the surface roughness. Taguchi statistical analysis was performed to investigate the relative strength of experimental factors and interconnectedness among process parameters to attain optimum coating qualities. The quantitative impacts of phosphorous level, temperature, surface preparation, and time factor on the roughness of the nickel-plated surface were 17.95%, 8.2%, 50.02%, and 13.21%, respectively. On the other hand, the quantitative impacts of phosphorous level, temperature, surface preparation, and time factor on the thickness of nickel plating were 35.12%, 41.40%, 3.87%, and 18.24%, respectively. The optimum combination of the factors’ level projected the lowest roughness of Ra at 7.76 µm. The optimum combination of the factors’ level projected the maximum achievable thickness of ~149 µm. This paper provides insights into coating process for overcoming the sensitivity of AM composites in hazardous application spaces via robust coating.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Quantum Key Distribution for Critical Infrastructures: Towards Cyber-Physical Security for Hydropower and Dams

Hydropower facilities are often remotely monitored or controlled from a centralized remote control room. Additionally, major component manufacturers monitor the performance of installed components, increasingly via public communication infrastructures. While these communications enable efficiencies and increased reliability, they also expand the cyber-attack surface. Communications may use the internet to remote control a facility’s control systems, or it may involve sending control commands over a network from a control room to a machine. The content could be encrypted and decrypted using a public key to protect the communicated information. These cryptographic encoding and decoding schemes become vulnerable as more advances are made in computer technologies, such as quantum computing. In contrast, quantum key distribution (QKD) and other quantum cryptographic protocols are not based upon a computational problem, and offer an alternative to symmetric cryptography in some scenarios. Although the underlying mechanism of quantum cryptogrpahic protocols such as QKD ensure that any attempt by an adversary to observe the quantum part of the protocol will result in a detectable signature as an increased error rate, potentially even preventing key generation, it serves as a warning for further investigation. In QKD, when the error rate is low enough and enough photons have been detected, a shared private key can be generated known only to the sender and receiver. We describe how this novel technology and its several modalities could benefit the critical infrastructures of dams or hydropower facilities. The presented discussions may be viewed as a precursor to a quantum cybersecurity roadmap for the identification of relevant threats and mitigation.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

Small-Grid Dithers for the JWST Coronagraphs

We discuss new results of coronagraphic simulations demonstrating a novel mode for JWST that utilizes sub-pixel dithered reference images, called Small-Grid Dithers, to optimize coronagraphic PSF subtraction. These sub-pixel dithers are executed with the Fine Steering Mirror under fine guidance, are accurate to approx.2-3 milliarcseconds (1-σ/axis), and provide ample speckle diversity to reconstruct an optimized synthetic reference PSF using LOCI or KLIP. We also discuss the performance gains of Small-Grid Dithers compared to the standard undithered scenario, and show potential contrast gain factors for the NIRCam and MIRI coronagraphs ranging from 2 to more than 10, respectively.

coronagraphy↗
NASA NTRS2026

Fatigue Behavior of Laser Powder Bed Fused HAYNES 214: Effects of Different Surface Treatments

In this study, under NASA’s Rapid and Analysis Manufacturing Propulsion Technology (RAMPT) project, effects of different surface post-treatments on surface texture and fatigue behavior of L-PBF Alloy 214 were investigated. Various subtractive SPTs including abrasive flow machining (AFM), machining (M), shot peening (SP), vapormatt (VM), dry electropolishing (DE), chemical milling (CM), chemical-mechanical polishing (CMP), electro chemical (ECP) were applied to study the variations of the surface texture, microstructure and uniaxial fatigue behavior under fully reversed strain-controlled condition at four different strain amplitudes of 0.005, 0.004, 0.003, and 0.0025 mm/mm. The insights gained regarding the relationship between structural and mechanical properties for different SPTs can help establish guidelines for selecting the most effective process to enhance the performance of Laser Powder Bed Fusion (L-PBF) Alloy 214, especially for critical aerospace applications.

Post-Processing↗
DOE OSTI2010

Visualization at Supercomputing Centers: The Tale of Little Big Iron and the Three Skinny Guys

Supercomputing Centers (SC's) are unique resources that aim to enable scientific knowledge discovery through the use of large computational resources, the Big Iron. Design, acquisition, installation, and management of the Big Iron are activities that are carefully planned and monitored. Since these Big Iron systems produce a tsunami of data, it is natural to co-locate visualization and analysis infrastructure as part of the same facility. This infrastructure consists of hardware (Little Iron) and staff (Skinny Guys). Our collective experience suggests that design, acquisition, installation, and management of the Little Iron and Skinny Guys does not receive the same level of treatment as that of the Big Iron. The main focus of this article is to explore different aspects of planning, designing, fielding, and maintaining the visualization and analysis infrastructure at supercomputing centers. Some of the questions we explore in this article include:"How should the Little Iron be sized to adequately support visualization and analysis of data coming off the Big Iron?" What sort of capabilities does it need to have?" Related questions concern the size of visualization support staff:"How big should a visualization program be (number of persons) and what should the staff do?" and"How much of the visualization should be provided as a support service, and how much should applications scientists be expected to do on their own?"

97 MATHEMATICS AND COMPUTING↗