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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Using the FLUKA Monte Carlo Code to Simulate the Interactions of Ionizing Radiation with Matter to Assist and Aid Our Understanding of Ground Based Accelerator Testing, Space Hardware Design, and Secondary Space Radiation Environments

Designing hardware to operate in the space radiation environment is a very difficult and costly activity. Ground based particle accelerators can be used to test for exposure to the radiation environment, one species at a time, however, the actual space environment cannot be duplicated because of the range of energies and isotropic nature of space radiation. The FLUKA Monte Carlo code is an integrated physics package based at CERN that has been under development for the last 40+ years and includes the most up-to-date fundamental physics theory and particle physics data. This work presents an overview of FLUKA and how it has been used in conjunction with ground based radiation testing for NASA and improve our understanding of secondary particle environments resulting from the interaction of space radiation with matter.

Reddell, Brandon↗
NASA NTRS2003

Investigation of Pneumatic Inlet and Diffuser Blowing on a Ducted Fan Propulsor in Static Thrust Operation

Tilting ducted fans present a solution for the lifting and forward flight propulsion requirements of VTOL aircraft. However, the geometry of the duct enshrouding the propeller has great a effect on the efficiency of the fan in various flight modes. Shroud geometry controls the velocity and pressure at the face of the fan, while maintaining a finite loading out at the tips of the fan blades. A duct tailored for most efficient generation of static lifting thrust will generally suffer from performance deficiencies in forward flight. The converse is true as well, leaving the designer with a difficult trade affecting the overall performance and sizing of the aircraft. Ideally, the shroud of a vertical lifting fan features a generous bell mouth inlet promoting acceleration of flow into the face of the fan, and terminating in a converging nozzle at the exit. Flow entering the inlet is accelerated into the fan by the circulation about the shroud, resulting in an overall increase in thrust compared to an open propeller operating under the same conditions . The accelerating shroud design is often employed in lifting ducted fans to benefit from the thrust augmentation; however, such shroud designs produce significant drag penalties in axial flight, thus are unsuitable for efficient forward flight applications. Decelerating, or diffusing, duct designs are employed for higher speed forward flight configurations. The lower circulation on the shroud tends to decelerate the flow into the face of the fan, which is detrimental to static thrust development; however, net thrust is developed on the shroud while the benefits of finite blade loading are retained. With judicious shroud design for intended flight speeds, a net increase in efficiency can be obtained over an open propeller. In this experiment, conducted under contract to NASA LaRC (contract NAG-1-02093) circulation control is being applied to a mildly diffusing shroud design, intended for improved forward flight performance, to generate circulation in the sense of an accelerating duct design. The intent is to improve static thrust performance of a ducted fan tailored for high speed axial flight, while at the same time significantly reduce the pressure signature on the ground plane. Circulation control on the fan shroud is achieved by the Coanda effect.

Kondor, Shayne↗
NASA NTRS1994

Design of Ternary Correlation Filters to Reduce Probability of Error

The problem of designing ternary phase and amplitude filters (TPAF's) that reduce the probability of image misclassification for a two-class image set is studied. The Fisher ratio is used as a measure of the correct classification rate, and an attempt is made to maximize this quantity in the filter designs. Given the nonanalytical nature of the design problem, a simulated annealing optimization technique is employed. Computer simulation results are presented for several cases including single in-class and out-of-class image sets and multiple image sets corresponding to the design of synthetic discriminant function filters. Significant improvements are found in expected rates of correct classification in comparison to binary phase-only filters and other TPAF designs. Approaches to accelerate the filter design process are also discussed.

Downie, John D.↗
DOE OSTI2021

Northstar Accelerator Based Mo99 Production Facility Design Support

Facility design support in FY20 centered on transfer of the target insertion and design details to MBraun and Springs, the companies under contract via Northstar to do the hot cell, target insertion and the local target shielding. A significant number of changes have been introduced by these vendors which have been reviewed and critiqued. In addition, the company contracted to produce the Mo100 disks announced that the tolerance on the thickness of 0.5 mm would be ±25%. An alternative design of the target holder was proposed. Bulk shielding and local target shielding design work has continued also and will be reported. Ongoing design and cooling issues continue to arise as the facility takes shape and moves toward completion. LANL is part of the team identifying, analyzing and designing solutions to these issues. Many of these are covered in this report.

43 PARTICLE ACCELERATORS↗
NASA NTRS1988

Design of a ram accelerator mass launch system

The ram accelerator mass launch system has been proposed to greatly reduce the costs of placing acceleration-insensitive payloads into low earth orbit. The ram accelerator is a chemically propelled, impulsive mass launch system capable of efficiently accelerating relatively large masses from velocities of 0.7 km/sec to 10 km/sec. The principles of propulsion are based on those of a conventional supersonic air-breathing ramjet; however the device operates in a somewhat different manner. The payload carrying vehicle resembles the center-body of the ramjet and accelerates through a stationary tube which acts as the outer cowling. The tube is filled with premixed gaseous fuel and oxidizer mixtures that burn in the vicinity of the vehicle's base, producing a thrust which accelerates the vehicle through the tube. This study examines the requirement for placing a 2000 kg vehicle into a 500 km circular orbit with a minimum amount of on-board rocket propellant for orbital maneuvers. The goal is to achieve a 50 pct payload mass fraction. The proposed design requirements have several self-imposed constraints that define the vehicle and tube configurations. Structural considerations on the vehicle and tube wall dictate an upper acceleration limit of 1000 g's and a tube inside diameter of 1.0 m. In-tube propulsive requirements and vehicle structural constraints result in a vehicle diameter of 0.76 m, a total length of 7.5 m and a nose-cone half angle of 7 degrees. An ablating nose-cone constructed from carbon-carbon composite serves as the thermal protection mechanism for atmospheric transit.

Aarnio, Michael↗
DOE OSTI2025

Accelerating Discovery of Solid‐State Thin‐Film Metal Dealloying for 3D Nanoarchitecture Materials Design through Laser Thermal Gradient Treatment

Thin‐film solid‐state metal dealloying (thin‐film SSMD) is a promising method for fabricating nanostructures with controlled morphology and efficiency, offering advantages over conventional bulk materials processing methods for integration into practical applications. Although machine learning (ML) has facilitated the design of dealloying systems, the selection of key thermal treatment parameters for nanostructure formation remains largely unknown and dependent on experimental trial and error. To overcome this challenge, a workflow enabling high‐throughput characterization of thermal treatment parameters is demonstrated using a laser‐based thermal treatment to create temperature gradients on single thin‐film samples of Nb‐Al/Sc and Nb‐Al/Cu. This continuous thermal space enables observation of dealloying transitions and the resulting nanostructures of interest. Through synchrotron X‐ray multimodal and high‐throughput characterization, critical transitions and nanostructures can be rapidly captured and subsequently verified using electron microscopy. The key temperatures driving chemical reactions and morphological evolutions are clearly identified. While the oxidation may influence nanostructure formation during thin‐film treatment, the dealloying process at the dealloying front involves interactions solely between the dealloying elements, highlighting the availability and viability of the selected systems. Further, this approach enables efficient exploration of the dealloying process and validation of ML predictions, thereby accelerating the discovery of thin‐film SSMD systems with targeted nanostructures.

36 MATERIALS SCIENCE↗
NASA NTRS1988

Design of a Ram Accelerator mass launch system

The Ram Accelerator, a chemically propelled, impulsive mass launch system, is presented as a viable concept for directly launching acceleration-insensitive payloads into low Earth orbit. The principles of propulsion are based on those of an airbreathing supersonic ramjet. The payload vehicle acts as the ramjet centerbody and travels through a fixed launch tube that acts as the ramjet outer cowling. The launch tube is filled with premixed gaseous fuel and oxidizer mixtures that combust at the base of the vehicle and produce thrust. Two modes of in-tube propulsion involving ramjet cycles are used in sequence to accelerate the vehicle from 0.7 km/sec to 9 km/sec. Requirements for placing a 2000 kg vehicle into a 500-km circular orbit, with a minimum amount of onboard rocket propellant for orbital maneuvers, are examined. It is shown that in-tube propulsion requirements dictate a launch tube length of 5.1 km to achieve an exit velocity of 9 km/sec, with peak accelerations not to exceed 1000 g's. Aerodynamic heating due to atmospheric transit requires minimal ablative protection and the vehicle retains a large percentage of its exit velocity. An indirect orbital insertion maneuver with aerobraking and two apogee burns is examined to minimize the required onboard propellant mass. An appropriate onboard propulsion system design to perform the required orbital maneuvers with minimum mass requirements is also determined. The structural designs of both the launch tube and the payload vehicle are examined using simple structural and finite element analysis for various materials.

Source record↗
DOE OSTI2022

Language models for the prediction of SARS-CoV-2 inhibitors

The COVID-19 pandemic highlights the need for computational tools to automate and accelerate drug design for novel protein targets. We leverage deep learning language models to generate and score drug candidates based on predicted protein binding affinity. We pre-trained a deep learning language model (BERT) on ∼9.6 billion molecules and achieved peak performance of 603 petaflops in mixed precision. Our work reduces pre-training time from days to hours, compared to previous efforts with this architecture, while also increasing the dataset size by nearly an order of magnitude. For scoring, we fine-tuned the language model using an assembled set of thousands of protein targets with binding affinity data and searched for inhibitors of specific protein targets, SARS-CoV-2 Mpro and PLpro. We utilized a genetic algorithm approach for finding optimal candidates using the generation and scoring capabilities of the language model. Our generalizable models accelerate the identification of inhibitors for emerging therapeutic targets.

Blanchard, Andrew E.↗
DOE OSTI2025

Unveiling X-ray absorption signatures of boron nitride via first-principles simulation and machine learning

Boron nitride (BN) allotropes hold great promise in many advanced applications ranging from optical and photonic devices to energy storage and battery systems to tribological components. The diverse functionalities of this material stem from BN’s highly tunable structural and electronic properties, which are governed by the versatile boron–nitrogen bonding configurations. Exploring the structural landscape of BN can unveil novel structures possessing unique properties suited for specific applications, therefore accelerating the design of next-generation advanced functional materials. In this work, we leverage boron K-edge X-ray absorption spectroscopy (XAS) as an effective probe for local structural features and chemical environments. A total of 210 BN crystal structures are generated via analogies to the extensive array of carbon allotropes, and XAS is simulated for each unique local motif within the resulting collection of structures. A mapping between structural features and spectral signatures was established by synergizing first-principle simulations with data-driven based post-analysis approaches. Specifically, we developed a neural network model that can satisfactorily predict spectra line shapes from local structural descriptors. Toward automatic spectroscopic interpretation of any new BN structures, supervised machine learning models, trained on this structure–spectrum dataset, can accurately infer local coordination environments from simulated XAS, highlighting the strength of this unique approach of combining high-fidelity first-principles simulation and machine-learning to accelerate target design of novel BN materials via rational understanding of local structure-spectrum correlations.

36 MATERIALS SCIENCE↗
NASA NTRS2011

Electronic Health Management

Accelerated aging methodologies for electrolytic components have been designed and accelerated aging experiments have been carried out. The methodology is based on imposing electrical and/or thermal overstresses via electrical power cycling in order to mimic the real world operation behavior. Data are collected in-situ and offline in order to periodically characterize the devices' electrical performance as it ages. The data generated through these experiments are meant to provide capability for the validation of prognostic algorithms (both model-based and data-driven). Furthermore, the data allow validation of physics-based and empirical based degradation models for this type of capacitor. A first set of models and algorithms has been designed and tested on the data.

Celaya, Jose R.↗
DOE OSTI2021

Machine-Learning Microstructure for Inverse Material Design

Metallurgy and material design have thousands of years’ history and have played a critical role in the civilization process of humankind. The traditional trial-and-error method has been unprecedentedly challenged in the modern era when the number of components and phases in novel alloys keeps increasing, with high-entropy alloys as the representative. New opportunities emerge for alloy design in the artificial intelligence era. Here a successful machine-learning (ML) method is developed to identify the microstructure images with eye-challenging morphology for a number of martensitic and ferritic steels. Assisted by it, a new neural-network method is proposed for the inverse design of alloys with 20 components, which can accelerate the design process based on microstructure. The method is also readily applied to other material systems given sufficient microstructure images. This work lays the foundation for inverse alloy design based on microstructure images with extremely similar features.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Designing and Utilizing Material Acceleration Platforms: Need for Workforce Development

In the quest to accelerate scientific discovery, the materials science field is rapidly moving toward the implementation of robotics and artificial intelligence driven workflows. Our recent summer school “Future Labs: Robotic Synthesis Coupled with Machine Learning for Energy Materials” provided learning opportunities for students, researchers, and educators in the materials science community. We describe this experience and provide our perspective on which new directions could be pursued to enable the future workforce to acquire cross-disciplinary skills.

Educational policy↗
DOE OSTI2025

pnnl/soda-benchmarks

The SODA-Benchmarks repository (currently hosted at: https://gitlab.pnnl.gov/sodalite/soda-benchmarks) provides a comprehensive benchmark suite for evaluating tools within the SODA (Software-Defined Accelerators) toolchain, which focuses on hardware/software co-design and accelerator generation for FPGAs and ASICs

Agostini, Nicolas [Pacific Northwest National Labo↗
DOE OSTI2024

Synthesis of motif and symmetry for accelerated learning, discovery, and design of electronic structures for energy conversion applications (Final Technical Report)

The overall goal of the projects is to develop a framework to incorporate structure motifs and crystal/orbital symmetries into the data-driven materials discovery infrastructure. The PI proposed to develop structure-motif- and symmetry-based graph convolutional networks for effective learning and efficient predictions of electronic structures and related properties. Fundamental understanding of the roles of structure motif and symmetry will establish new hypothesis and design rules, which will be combined with high-throughput computations based on density functional theory to discover novel light absorbers, transparent conductors, as well as 2D light emitting materials and heterojunctions for optoelectronics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Accelerating Additive Manufacturing Process Design for Energy Conversion Materials using In-situ Sensing and Machine Learning

One promising candidate for manufacturing of the bismuth Telluride thermoelectric legs is laser powder bed fusion (LPBF) additive Manufacturing (AM). AM processing parameters highly influence the material properties, however current processing parameter development methods in AM are costly and time consuming. In-situ sensors allow for the capture of physically relevant process information on a layer-by-layer basis and will be used to aide process development. To optimize the AM process for the best thermoelectric performance, process variables, in-situ process sensor data and ex-situ material characterization data are collected. Several different interpretable machine learning (ML) approaches are used, and the performance of each method are assessed. Significant input process variables include laser focus, hatch spacing and laser power. The best performing models are used to determine the manufacturing parameters that maximize the power factor. AM of bismuth telluride material provides the ability to create complex geometries enabling more efficient energy conversion.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Accelerated fission rate irradiation design, pre-irradiation characterization, and adaptation of conventional PIE methods for U-10Mo and U-17Mo

Metallic U alloys have high U density and thermal conductivity and thus have been explored since the beginning of nuclear power research. Alloys of U with modest amounts of Mo, such as U-10 wt % Mo (U-10Mo), are of particular interest because the γ-U crystal structure in this alloying addition shows prolonged stability in reactor service. Historically, radiation data on U-10Mo fuels were collected in Na fast reactors or lower temperature research reactor conditions, but little is known about irradiation behavior, particularly swelling and creep, at irradiation temperatures between 250 and 500°C. This work discusses the methodology and pre-irradiation characterization results from a U-Mo irradiation campaign performed in the High Flux Isotope Reactor at Oak Ridge National Laboratory. U-10Mo and U-17Mo samples irradiations are being completed at temperatures ranging from 250 to 500°C to three targeted fission densities between 2 × 10 20 and 1.5 × 10 21 fissions per cubic centimeter. Swelling measurement of the specimen sizes studied here required development and assessment of new methods for volume determination before and after irradiation. Laser profilometry and X-ray computation tomography (XCT) were used to provide preirradiation characterization of samples to determine the error and applicability of each to determine swelling following irradiation. These outcomes are contextualized through use of BISON simulations performed to assess the predicted expansion of U-Mo fuels subjected to the irradiation conditions of this work. Use of existing BISON fuel performance models predicted a maximum of 7% swelling under the irradiation conditions of this study. Pre-irradiation characterization revealed the as-cast U-Mo fuel samples were uniformly large-grained fully cubic U crystals with small U-C/N bearing precipitates and pores distributed throughout. Samples were found to contain a bulk porosity between .4 and 3% because of the casting process. Local porosity in areas far from large, interconnected pores was found by Slice-and-View to be under .2%. Nanometer-sized precipitates rich in C and N were identified in all samples, likely because of impurities during the fabrication process. Dendritic bands were also observed throughout the samples. These bands were characterized by variable Mo content that deviated from the overall Mo content by 2–3 wt %. No other microstructural features were correlated to these bands. Mechanical properties were found to be slightly strengthened compared to literature reports of bulk U-Mo fuels due to the nano-scale precipitates throughout the sample.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRSDate not supplied

A Nonlinear Schur Complement Solver for CFD-Based Multidisciplinary Models

CFD-based multidisciplinary models are the fundamental building blocks of multidis- ciplinary design optimization frameworks. Linear and nonlinear solutions of these coupled models are difficult, especially when the Jacobian matrices represent a saddle point problem, where a block-diagonal corresponding to a discipline is non-invertible. These scenarios necessitate the use of a coupled solver algorithm such as the Newton’s method instead of the popular block Gauss– Seidel-based methods because of this non-invertible block. To address this challenge, we introduce a nonlinear Schur complement solver suitable for CFD-based multidisciplinary models. The solver leverages the specialized linear and nonlinear solvers of the CFD code, and therefore, does not require the solution of a large coupled linear system as the coupled Newton’s method. Further- more, because the solver primarily uses the specialized linear and nonlinear solvers of the CFD code, it does not suffer from the same robustness limitations as the coupled Newton’s method. In this work, we will implement this solver in NASA’s OpenMDAO framework and demonstrate its effectiveness using a CFD-based aeropropulsive model. The solver will contribute to the develop- ment of aeropropulsive design optimization and CFD-based design optimization methods with the ultimate goal of accelerating the design and integration of advanced propulsion systems.

Nonlinear Solvers↗