Integral Experiment Validation of Hafnium with TEX-HEU and TEX-Hf
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Nuclear science and engineering↗
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Results for “Engineering Demonstration Unit”
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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High Velocity Oxygen Fuel Spraying of Erosion and Wear Resistant Coatings on Jet Engine Parts
High velocity oxygen fuel (HVOF) spraying is the most recent development in the field of thermal spraying. The importance of this technique for the repair and new part manufacturing of jet engine parts is rapidly increasing. The HVOF uses a supersonic oxygen-fuel flame to heat and accelerate the powder particles that form the coating. The high particle velocity results in a high density and a low porosity, a high bond strength, and a high macro and micro hardness of the coating. The high quality of the HVOF coatings makes it possible to use these coatings on high loaded, rotating parts in jet engines. This paper will highlight the use of HVOF processes to apply erosion resistant cermet coatings to high pressure compressor blades. These blades are exposed to severe erosion. Next to the D-gun process, HVOF spraying is the only nonproprietary technique that can be used to apply these high performance coatings. Also the use of the HVOF process to apply wear resistant coatings and superalloys to jet engine parts will be discussed. The difference between HVOF coatings and plasma sprayed coatings will be highlighted. During HVOF spraying, the parts are exposed to a high heat flow. Solutions to avoid overheating, especially of titanium parts, will be presented.
A T J Verbeek↗
NASA Engineering Safety Center NASA Aerospace Flight Battery Systems Working Group 2007 Proactive Task Status
In 2007, the NASA Engineering Safety Center (NESC) chartered the NASA Aerospace Flight Battery Systems Working Group to bring forth and address critical battery-related performance/manufacturing issues for NASA and the aerospace community. A suite of tasks identifying and addressing issues related to Ni-H2 and Li-ion battery chemistries was submitted and selected for implementation. The current NESC funded are: (1) Wet Life of Ni-H2 Batteries (2) Binding Procurement (3) NASA Lithium-Ion Battery Guidelines (3a) Li-Ion Performance Assessment (3b) Li-Ion Guidelines Document (3b-i) Assessment of Applicability of Pouch Cells for Aerospace Missions (3b-ii) High Voltage Risk Assessment (3b-iii) Safe Charge Rates for Li-Ion Cells (4) Availability of Source Material for Li-Ion Cells (5) NASA Aerospace Battery Workshop This presentation provides a brief overview of the tasks in the 2007 plan and serves as an introduction to more detailed discussions on each of the specific tasks.
Manzo, Michelle A.↗
Analysis of an irradiated uranium sample for source attribution without chemical separation using microplasma ionization and ultrahigh resolution mass spectrometry
The use of element isotope ratios has great potential in not only determining the reactor type used to produce plutonium (Pu) but also in determining the burnup and the time since irradiation. While a powerful nuclear forensic technique, determining element isotope ratios is complicated by severe isobaric interferences when performed on typical inductively coupled plasma mass spectrometers. Such analyses require extensive chemical separations prior to analysis to alleviate the inter-elemental isobars. Ultrahigh mass resolution spectrometry provides a potential alternative, greatly reducing the complexity of sample preparation and turnaround times for these critical measurements. To demonstrate the power of the approach, a sample of irradiated, depleted uranium was analyzed with the liquid sampling—atmospheric pressure glow discharge ion source coupled to an Orbitrap mass spectrometer. The Orbitrap is augmented with an external data acquisition system, Spectroswiss’s FTMS-Booster X2T, allowing collection of extended ion transients, providing higher mass resolution. In using this approach, the 150 Sm/ 149 Sm and 152 Sm/ 149 Sm isotope ratios were found to be within 20% of predicted values without any chemical separations and without mass bias corrections. In addition, the 240 Pu/ 239 Pu isotope ratio was determined, free from the 238 UH + interferences common to the ICP-MS platforms, while at the same time allowing for the determination of U isotopic signatures. While these demonstrative results are from a single sample, the advantages of the microplasma/ultrahigh mass resolution approach to intra-element isotope ratio determinations are clear.
Fuel burnup↗
Utilization of Battery Electric Buses for the Resiliency of Islanded Microgrids
Not provided.
Energy & Fuels↗
Bridging Fusion Energy and Fission Energy: Synergistic Supply Chains for Fuel and Materials
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Nuclear science and engineering - Nuclear fuel cyc↗
Third Annual Workshop on Space Operations Automation and Robotics (SOAR 1989)
Papers presented at the Third Annual Workshop on Space Operations Automation and Robotics (SOAR '89), hosted by the NASA Lyndon 8. Johnson Space Center at Houston, Texas, on July 25-27, 1989, are documented herein. During the three days, approximately 100 technical papers were presented by experts from NASA, the USAF, universities, and technical companies. Also held were panel discussions on Air Force/NASA AI Overview and Expert System Verification and Validation. Tutorial sessions included Neural Networks; Theory and Application of Back Propagation; Verification and Validation of Expert Systems/ Evaluation of Expert System Tools; and Technical Environment for Modular Architectures for Robotics in Space; and are not documented herein. Technical topics addressed included intelligent systems, robotics, human factors, and environment.
Knowledge representation↗
Technology & Design Innovations to Maximize the Reduction Effect on DCFC Unit Cost Economics (Max‐REDUCE)
With the high cost and reliability issues of DCFC infrastructure the project specifically addressed the needs of innovating on the AC to DC power conversion. We proved the integration of a new power module into existing charger units, and that theoretical educational work on single stage energy conversion is commercially viable, and a reduced cost compared to existing methods. Our A sample shown 3 PH 480VAC 60hz to 350VDC 8.5kW power transfer, and our software and simulation proved efficiency greater than 97% from 20kW to > 60kW, over the DC output voltage range 200 – 1200V. The project was stopped before we could implement B sample and execute full power testing, validation and integration into a demonstration charger (budget period 3).
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Tensor Methods A Unified and Interpretable Approach for Material Design
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Computer science↗
From PINNs to PIKANs: recent advances in physics-informed machine learning
Physics-Informed Neural Networks (PINNs) have emerged as a key tool in Scientific Machine Learning since their introduction in 2017, enabling the efficient solution of ordinary and partial differential equations using sparse measurements. Over the past few years, significant advancements have been made in the training and optimization of PINNs, covering aspects such as network architectures, adaptive refinement, domain decomposition, and the use of adaptive weights and activation functions. A notable recent development is the Physics-Informed Kolmogorov-Arnold Networks (PIKANS), which leverage a representation model originally proposed by Kolmogorov in 1957, offering a promising alternative to traditional PINNs. In this review, we provide a comprehensive overview of the latest advancements in PINNs, focusing on improvements in network design, feature expansion, optimization techniques, uncertainty quantification, and theoretical insights. We also survey key applications across a range of fields, including biomedicine, fluid and solid mechanics, geophysics, dynamical systems, heat transfer, chemical engineering, and beyond. Lastly, we review computational frameworks and software tools developed by both academia and industry to support PINN research and applications.
Kolmogorov-Arnold networks↗
Design and fabrication of ion traps for low RF power dissipation
Large surface-electrode ion traps with multiple trapping regions and junctions are a natural approach to scaling trapped ion quantum computers, supporting the connectivity and ion counts necessary for complex quantum algorithms. However, a major hurdle in this scaling is on-chip power dissipation from the applied RF voltage, which increases at a rate between linear and cubic relative to trap size, depending on whether the losses are dielectric or Ohmic. Here, we present two versions of a trap with features designed to reduce both types of RF power dissipation. The first variant contains a raised RF electrode that increases the electrode–ground distance to reduce capacitance. Different DC voltage sources are demonstrated on this trap to show that technical noise before the filter remains the dominant source of voltage noise and therefore motional heating. The second variant additionally includes a method for removing dielectric from beneath the RF electrode to further reduce dielectric losses. These traps were demonstrated at room temperature with 40 Ca + ions. In conclusion, the similar heating rates and heating rate axial frequency dependencies between 2.4 and 3.0 MHz illustrate that this dielectric modification is not detrimental to trap performance.
Sterk, J. D. [Sandia National Laboratories (SNL-NM↗
Next-Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR) - Predictive Data-Driven Vehicle Dynamics and Powertrain Control: from ECU to the Cloud (Final Scientific/Technical Report)
This project developed and demonstrated a predictive, data-driven vehicle control system designed to improve energy efficiency and driving performance. The team created intelligent self-driving car technology that optimizes fuel and electricity use by proactively planning vehicle actions. By combining Level 4 autonomous driving capabilities with vehicle-to-everything (V2X) connectivity, the system enables vehicles to adjust speed and change lanes in response to traffic signals, surrounding vehicles, and road conditions, reducing unnecessary stops and delays. In testing, the system improved vehicle fuel economy by more than 30% and reduced travel time by approximately 10%, compared to a conventional adaptive cruise control baseline. These results demonstrate the technical effectiveness of using predictive, V2X-enabled strategies, such as traffic light timing and surrounding traffic awareness, to inform real-time vehicle powertrain control and driving behavior. Additionally, a supporting cloud platform was developed to provide dispatch and route recommendations as well as to log vehicle data, demonstrating the economic feasibility of this approach at the fleet level. By optimizing dispatching and routing operations, this technology enables electric fleet operators to use their vehicles more efficiently and reduce reliance on diesel backups, lowering both operating costs and energy consumption. Overall, this project’s technology advances the future of clean, energy-efficient transportation, enabling vehicles and fleets to reduce energy waste, cut costs, and lower emissions through intelligent automation and connectivity.
33 ADVANCED PROPULSION SYSTEMS↗
Development of a sealed lead-acid battery for use in space Final report
Development of sealed lead-acid battery with lead- calcium grid for space application
LEAD ALLOY↗
Machine learning pipeline for denoising low signal-to-noise ratio and out-of-distribution transmission electron microscopy datasets
High-resolution transmission electron microscopy (HRTEM) is crucial for observing material’s structural and morphological evolution at Angstrom scales, but the electron beam can alter these processes. Devices such as CMOS-based direct-electron detectors operating in electron-counting mode can be utilized to substantially reduce the electron dosage. However, the resulting images often lead to a low signal-to-noise ratio, which requires frame integration that sacrifices temporal resolution. Several machine learning (ML) models have been recently developed to successfully denoise HRTEM images. Yet, these models are often computationally expensive, and their inference speeds on GPUs are outpaced by the imaging speed of advanced detectors, precluding in situ analysis. Furthermore, the performance of these denoising models on datasets with imaging conditions that deviate from the training datasets has not been evaluated. To mitigate these gaps, we propose a new self-supervised ML denoising pipeline specifically designed for time-series HRTEM images. This pipeline integrates a blind-spot convolution neural network with pre-processing and post-processing steps, including drift correction and low-pass filtering. Results demonstrate that our model outperforms various other ML and non-ML denoising methods in noise reduction and contrast enhancement, leading to improved visual clarity of atomic features. Additionally, the model is drastically faster than U-Net-based ML models and demonstrates excellent out-of-distribution generalization. The model’s computational inference speed is in the order of milliseconds per image, rendering it suitable for application in in-situ HRTEM experiments.
36 MATERIALS SCIENCE↗
Erosion, Corrosion and Foreign Object Damage Effects in Gas Turbines [Les consequences de l'endommagement des turbines I gaz par erosion, corrosion et objets étrangers]
The Conference Proceedings contains 31 papers presented at the Propulsion and Energetics Panel Symposium on Erosion, Corrosion and Foreign Object Damage Effects in Gas Turbines which was held from 25-28th April 1994, in Rotterdam, The Netherlands. The Technical Evaluation Report and the Keynote Address are included at the beginning and discussions follow most papers. The Symposium was arranged in the following Sessions: Operational Experience and Requirements (7); Deposition and Erosion (7); Foreign Object Damage (5); Coatings, Repairs and Materials Aspects - 1 (4); Coatings, Repairs and Materials Aspects - 2 (7); and Testing and Certification Procedures (1).
Deposition↗
AUTOIGNITION DELAY TIMES FOR REFORMATE GAS MIXTURES FROM METHANE GAS ENGINES
Methane slip is a prominent issue in natural gas reciprocating engines that are used in transportation and marine applications. The incomplete combustion that results in methane slip can be resolved with the introduction of hydrogen within the combustion mixture to improve methane oxidation and further enable combustion within the engine crevices where methane has previously remained unreacted. Steam methane reforming (SMR) is a common method used to produce hydrogen and can be used to design an onboard device to reduce methane slip from reciprocating engines. The development of this reformer device requires the validation of high-fidelity chemical kinetic models at the low temperatures of the crevice volumes of these engines. In this work, auto-ignition data is obtained using a shock tube at lean (φ—0.714 or λ—1.4) and stoichiometric (φ, λ = 1) equivalence ratios spanning a temperature range of 1042–1234 K at the 80-bar operating pressure of the test engine. Blends of methane, hydrogen, and reformate products from the SMR reaction are shock-heated in synthetic air, with the ignition delay time measured using an OH* chemiluminescence detector at 310 nm and a CH* detector at 430 nm. The experimental results are compared to several state-of-the-art chemical kinetic mechanisms from the literature. In general, most of the mechanisms show very good agreement with experiments at higher temperatures, with simulation results showing little deviation from experiments at lower temperatures. A sensitivity analysis was conducted, and the results reveal that the reaction H2 + CH3O2 = H + CH3O2H has a very significant role in determining low-temperature ignition delay times (IDTs) of SMR mixtures. These findings provide valuable insights into the chemical kinetics governing methane reformate combustion and contribute to the optimization of onboard reformer designs aimed at mitigating methane slip in natural gas-fueled engines.
Fraze, Matthew↗