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Results for “Generative Methods”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Impact of Sintering Atmosphere and Temperature on the Phase Evolution of High Surface Area LSCF Prepared by In Situ Carbon Templating

The thermochemical stability of lanthanum strontium cobalt ferrite (LSCF) processed between 1000 °C–1200 °C via the in situ carbon templating method was studied. This method generates high surface area ceramics at traditional solid oxide fuel cell (SOFC) sintering temperatures by generating a carbon template in situ and subsequently removing the template by oxidation at 700 °C. Argon processed samples produced an amorphous carbon template, whereas nitrogen tended to form graphitic carbon. Prior to the oxidation step, nitrogen samples comprised larger La 2 O 3 crystallites (22–40 nm) compared to argon (9–17 nm). Upon oxidation, argon samples resulted in a pure LSCF phase with surface areas in the 21–29 m 2 ·g −1 range, whereas nitrogen samples contained significant impurities. This demonstrates that the size of La 2 O 3 crystallites formed during inert processing limited the ability to produce a pure LSCF phase. Symmetrical cells comprising nano-LSCF electrodes generated by the templating method were compared to cells sintered directly in air. Impedance results suggest that nano-LSCF cells and cells processed in air were dominated by interfacial charge transfer resistance and gas diffusion, respectively. The results map out conditions for preparing and integrating high surface area, nanostructured LSCF into SOFC electrodes at traditional sintering temperatures. Strategies for improving the interfacial resistance of nano-LSCF electrodes are discussed.

Muhoza, Sixbert P. (ORCID:0000000299864241)↗
DOE OSTI2022

Method for Generating Expert Derived Confidence Scores

We executed a pilot demonstration of a methodology for developing a new confidence metric to help operators calibrate their trust in ML event classifiers. This confidence metric was derived from domain expert judgment and was accompanied with a qualitative description describing the reason for each confidence rating. After learning the boundaries of an ML’s performance by studying a subset of events an SME rated his confidence in the ML’s ability to classify similar events and provided an explanation for his ratings. To demonstrate this methodology, we developed our expert driven confidence scores for the ML event classifier within the ESAMS. Next, we assessed the accuracy of the human expert confidence scores relative to the ML’s uncertainty quantification scores. This report includes a description of our methodology, summary of our findings and future directions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Physics-Based Method for Generating Fully Synthetic IV Curve Training Datasets for Machine Learning Classification of PV Failures

Classification machine learning models require high-quality labeled datasets for training. Among the most useful datasets for photovoltaic array fault detection and diagnosis are module or string current-voltage (IV) curves. Unfortunately, such datasets are rarely collected due to the cost of high fidelity monitoring, and the data that is available is generally not ideal, often consisting of unbalanced classes, noisy data due to environmental conditions, and few samples. In this paper, we propose an alternate approach that utilizes physics-based simulations of string-level IV curves as a fully synthetic training corpus that is independent of the test dataset. In our example, the training corpus consists of baseline (no fault), partial soiling, and cell crack system modes. The training corpus is used to train a 1D convolutional neural network (CNN) for failure classification. The approach is validated by comparing the model’s ability to classify failures detected on a real, measured IV curve testing corpus obtained from laboratory and field experiments. Results obtained using a fully synthetic training dataset achieve identical accuracy to those obtained with use of a measured training dataset. When evaluating the measured data’s test split, a 100% accuracy was found both when using simulations or measured data as the training corpus. When evaluating all of the measured data, a 96% accuracy was found when using a fully synthetic training dataset. The use of physics-based modeling results as a training corpus for failure detection and classification has many advantages for implementation as each PV system is configured differently, and it would be nearly impossible to train using labeled measured data.

Hopwood, Michael W. (ORCID:0000000161901767)↗
DOE OSTI2020

System and method for generation of event driven, tuple-space based programs

In a system for automatic generation of event-driven, tuple-space based programs from a sequential specification, a hierarchical mapping solution can target different runtimes relying on event-driven tasks (EDTs). The solution uses loop types to encode short, transitive relations among EDTs that can be evaluated efficiently at runtime. Specifically, permutable loops translate immediately into conservative point-to-point synchronizations of distance one. A runtime-agnostic which can be used to target the transformed code to different runtimes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Apparatuses and methods for generating carbon particles and exhaust gas used by gas turbine systems

Apparatuses for generating carbon particles and exhaust gas used by gas turbine systems are disclosed. One apparatus may include a decarbonization component combusting or reacting a mixture of a fuel and a mixing gas to generate the carbon particles and the exhaust gas and an exhaust conduit to receive the exhaust gas generated by the decarbonization component. The apparatus may also include a mixing duct in fluid communication with the exhaust conduit and the gas turbine system. The mixing duct may receive the exhaust gas and provide the exhaust gas to the gas turbine system to be used to produce a working fluid within the gas turbine system. The apparatus may further include a carbon particle collection component for receiving and storing the generated carbon particles.

Berry, Jonathan Dwight↗
DOE OSTI2022

Apparatus and method for generating medical isotopes

An apparatus for generating medical isotopes provides an annular fissile solution vessel surrounding a neutron generator. The annular fissile solution vessel provides for good capture of the emitted neutrons and a geometry that provides enhanced stability in an aqueous reactor. A neutron multiplier and/or a neutron moderator may be used to improve the efficiency and control the criticality of the reaction in the annular fissile solution vessel.

Piefer, Gregory Richard↗
DOE OSTI2023

Systems and methods for generating phase diagrams for metastable material states

A system can include one or more processors configured to access at least one parameter of a material, generate a plurality of structures of the material using the at least one parameter, determine a state of each structure of the plurality of structures using the at least one parameter, determine a difference between the state of each structure of the plurality of structures and a ground state value, evaluate a convergence condition responsive to determining the difference between the state of each structure of the plurality of structures and the ground state value, and output at least one structure of the plurality of structures responsive to the convergence condition being satisfied.

Sankaranarayanan, Subramanian↗
DOE OSTI2023

System and method for generation of event driven, tuple-space based programs

In a system for automatic generation of event-driven, tuple-space based programs from a sequential specification, a hierarchical mapping solution can target different runtimes relying on event-driven tasks (EDTs). The solution uses loop types to encode short, transitive relations among EDTs that can be evaluated efficiently at runtime. Specifically, permutable loops translate immediately into conservative point-to-point synchronizations of distance one. A runtime-agnostic which can be used to target the transformed code to different runtimes.

Baskaran, Muthu M.↗
DOE OSTI2024

Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)

Ontologies are fundamental components of informatics infrastructure in domains such as biomedical, environmental, and food sciences, representing consensus knowledge in an accurate and computable form. However, their construction and maintenance demand substantial resources and necessitate substantial collaboration between domain experts, curators, and ontology experts. We present Dynamic Retrieval Augmented Generation of Ontologies using AI (DRAGON-AI), an ontology generation method employing Large Language Models (LLMs) and Retrieval Augmented Generation (RAG). DRAGON-AI can generate textual and logical ontology components, drawing from existing knowledge in multiple ontologies and unstructured text sources.We assessed performance of DRAGON-AI on de novo term construction across ten diverse ontologies, making use of extensive manual evaluation of results. Our method has high precision for relationship generation, but has slightly lower precision than from logic-based reasoning. Our method is also able to generate definitions deemed acceptable by expert evaluators, but these scored worse than human-authored definitions. Notably, evaluators with the highest level of confidence in a domain were better able to discern flaws in AI-generated definitions. We also demonstrated the ability of DRAGON-AI to incorporate natural language instructions in the form of GitHub issues.These findings suggest DRAGON-AI's potential to substantially aid the manual ontology construction process. However, our results also underscore the importance of having expert curators and ontology editors drive the ontology generation process.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Cooling systems and methods for thermoelectric power generation

Systems and methods for cooling a power generation working fluid are disclosed that reduce the amount of cooling fluid used. These systems and methods save on water usage in the generation of power by thermoelectric power generation systems.

42 ENGINEERING↗
DOE OSTI2025

Informing Plant Asset Reliability and Availability Through AI-Driven Analysis of Operator Logs

The availability and reliability of nuclear power plant (NPP) structures, systems, and components (SSCs) are critical parameters for NPP safety. Tracking these parameters is necessary but costly and labor-intensive, requiring the collection and evaluation of SSC event data such as shutdowns, startups, and failures. To show how these events are needed for the parameters an example is given: one measure of reliability is based on the number of equipment failure events and the number of run hours (i.e., the time from a startup event to a shutdown event). Here, this work investigates using artificial intelligence (AI) to mine NPP operator log entry texts for SSC event data. Four AI approaches were explored for identifying these events, including natural language processing (NLP) methods, generative AI, generative AI combined with NLP, and topic modeling. A key challenge addressed with all four approaches is the brevity of operator log entries. Among these four a neural network–based NLP method was shown to be the most promising for this application, achieving F1 scores of 86.0% for shutdowns, 92.2% for startups, and 80.4% for failures on a subject-matter-expert-curated dataset from NPP operator logs, compared to a baseline of 66.6% for a random classifier. This shows that NLP methods can perform better than generative AI. Additionally, the NLP methods combined with generative AI were shown to perform better than generative AI alone. Generative AI was most successful at providing the background information for the NLP methods to use. This work demonstrates the potential to use AI to automate parameter collection from NPP operator log entries and other records.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

High performance porous Si anode enabled by an organic-solvent assisted etching process

Silicon (Si) is a promising anode for the next generation of lithium-ion batteries, but its large volume changes (~300 %) during cycling hindered its practical applications. One method to improve its stability is to etch micron sized Si/SiO 2 particles to form porous Si (p-Si) and accommodate volume changes internally. However, the conventional HF etching method generates excess gas/heat and is difficult to scale up. Herein, we developed an organic-solvent-assisted HF etching process (O-HF) using a mixture of benzene and saturated HF aqueous solution. The organic solvent can be preferentially absorbed on the surface of Si/SiO 2 powder so etching rate of SiO 2 can be controlled to avoid rapid gas/heat generation. This method can also prevent over-etching of Si by minimizing direct contact/react between water and newly exposed Si. Si||NMC622 cells using carbon coated p-Si particles prepared by optimized O-HF etching process demonstrate a capacity retention of 82.0 % after 500 cycles, which is much better than those prepared by conventional HF etching (73.7 %). The thickness of Si anode increases only ~10 % during the initial lithiation, which is comparable with those of graphite anode. In conclusion, the O-HF etching strategy developed in this work can also be applied to the etching of a broad range of materials.

HF etching↗
DOE OSTI2023

CrossLink: Advancements in Scalable Unstructured Mesh Generation [Slides]

Traditional mesh generation approaches are labor intensive and have limited robustness when applied to parametric design exploration and optimization of complex geometries. While automatic mesh generation approaches exist, they tend to generate tetrahedral or mixed-hybrid meshes which are generally unsuitable for physics applications with strong shock waves, thin boundary layers, and strong gradients. In addition, simulations sizes in the billions of cells are becoming more common with traditional mesh generation methods quickly reaching scalability limits. CrossLink offers a topology-based mesh generation approach with unstructured block-filling methods and a scalable mesh generation engine. In addition, CrossLink incorporates a python based API for seamless workflow integration and robust repeatability of the geometry handling and mesh generation process. This makes it ideal for parametric design study and optimization of complex geometries. Finally, future versions of CrossLink will offer a parametric mesh capability that optimizes a high-order mesh and enables reconstruction of the final mesh in memory by the physics solver.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

CrossLink: General Overview [Slides]

Problem: Traditional mesh generation approaches are labor intensive and have limited robustness when applied to parametric design exploration and optimization of complex geometries. While automatic mesh generation approaches exist, they tend to generate tetrahedral or mixed-hybrid meshes which are generally unsuitable for physics applications with strong shock waves, thin boundary layers, and strong gradients. In addition, simulations sizes in the billions of cells are becoming more common with traditional mesh generation methods quickly reaching scalability limits. Solution: CrossLink offers a topology-based mesh generation approach with unstructured block-filling methods and a scalable mesh generation engine. In addition, CrossLink incorporates a python-based API for seamless workflow integration and robust repeatability of the geometry handling and mesh generation process. This makes it ideal for parametric design study and optimization of complex geometries. Finally, future versions of CrossLink will offer a parametric mesh capability that optimizes a high-order mesh and enables reconstruction of the final mesh in memory by the physics solver.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Devices and methods for hydrogen generation via ammonia decomposition

Systems and methods for hydrogen generation via ammonia decomposition that utilize a fixed bed reactor configured to receive inflows of NH 3 and oxidant and to produce an outflow of high purity H 2 . The fixed bed reactor contains a fixed bed of a NH 3 decomposition catalyst wherewith the NH 3 decomposes to form N 2 and H 2 ; a plurality of ceramic hollows fibers with a high surface to volume ratio disposed in the fixed bed, the hollow fibers having an H 2 selective membrane disposed thereon for extracting H 2 from N 2 and to form a permeate of the high purity H 2 and a retentate of primarily N 2 ; and a catalytic H 2 burner also disposed in the fixed bed, the catalytic H 2 burner for burning a portion of the H 2 with the oxidant to provide thermal energy for the NH3 decomposition.

Li, Shiguang↗
DOE OSTI2023

High temperature and high beam current compatible targets and methods thereof for generating noble gas/radiohalogen generators for medical isotopes

A method of providing alpha particle emitters and materials suitable for use in generating the alpha particles for medical treatment is disclosed. Metal oxide targets, preferentially Bi 2 O 3 pellets and Bi 2 O 3 coatings on metallic or metal oxide substrates are formed. The targets placed in a heated vacuum chamber subjecting to irradiation using a 6 Li beam at an elevated temperature below the melting point of the target generate a radioactive gas, such as 211 Rn, the radioactive gas is carried by an inert gas which is delivered a carrier for, such as a carbon column or oil for delivery to a treatment facility. The radioactive gas such as 211 Rn generates 211 At, which has a useable half-life of at least about 14 hours, in turn releases alpha particles which are effective for use in medical procedures.

Sampathkumaran, Uma↗
DOE OSTI2020

High power ion beam generator systems and methods

Provided herein are high energy ion beam generator systems and methods that provide low cost, high performance, robust, consistent, uniform, low gas consumption and high current/high-moderate voltage generation of neutrons and protons. Such systems and methods find use for the commercial-scale generation of neutrons and protons for a wide variety of research, medical, security, and industrial processes.

43 PARTICLE ACCELERATORS↗