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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A Review of Transformer Aging and Control Strategies

Transformer aging is an important challenge in power system. Distribution transformers themselves are minimally controllable, but smart meters provide excellent, new insights into electrical loads, which insights can be used to understand and mitigate transformer aging. The nature of transformer loads is changing with the integration of distributed energy resources (DERs) and electric vehicles (EVs). This paper first reviews factors that influence the aging of distribution transformers, including root causes of transformer failure. Existing and proposed load control methods are then discussed. A distribution model is introduced to help evaluate potential control methods.

Gourisetti, Sri Nikhil Gup↗
DOE OSTI2019

Real-Time Monitoring of Temperature Rises of Energized Transformer Cores With Distributed Optical Fiber Sensors

Real-time temperature mapping that solves local overheating problems is important for obtaining an optimized thermal design for high-efficiency power transformers. Internal temperature monitoring of operating power transformers can also be leveraged for asset monitoring applications targeting at fault detection enabling condition-based maintenance. Transformers present a variety of challenging sensing environments such as high levels of electromagnetic interference and limited space for conventional sensors to operate. Immersion of power transformers in insulation oils for thermal management during operation and the presence of relatively large and time-varying electrical and occasional magnetic fields make sensing technologies requiring electrical wires or active power at sensing locations highly undesirable. In this work, we investigate thermal response of a standard telecom fiber instrumented on compact transformer cores by using an optical frequency-domain reflectometry scheme. As a result, correlation between conventional temperature sensing methods and fiber-optic sensing results as well as tradeoffs between spatial resolution and temperature measurement accuracy is discussed and spatially resolved real-time monitoring of temperatures in energized transformers is experimentally demonstrated.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Understanding the structural origin of crystalline phase transformations in nepheline (NaAlSiO 4 )‐based glass‐ceramics

Abstract Nepheline (Na 6 K 2 Al 8 Si 8 O 32 ) is a rock‐forming tectosilicate mineral which is by far the most abundant of the feldspathoids. The crystallization in nepheline‐based glass‐ceramics proceeds through several polymorphic transformations — mainly orthorhombic, hexagonal, cubic — depending on their thermochemistry. However, the fundamental science governing these transformations is poorly understood. In this article, an attempt has been made to elucidate the structural drivers controlling these polymorphic transformations in nepheline‐based glass‐ceramics. Accordingly, two different sets of glasses (meta‐aluminous and per‐alkaline) have been designed in the system Na 2 O–CaO–Al 2 O 3 –SiO 2 in the crystallization field of nepheline and synthesized by the melt‐quench technique. The detailed structural analysis of glasses has been performed by 29 Si, 27 Al, and 23 Na magic‐angle spinning — nuclear magnetic resonance ( MAS NMR ), and multiple‐quantum MAS NMR spectroscopy, while the crystalline phase transformations in these glasses have been studied under isothermal and non‐isothermal conditions using differential scanning calorimetry ( DSC ), X‐ray diffraction ( XRD ), and MQMAS NMR . Results indicate that the sequence of polymorphic phase transformations in these glass‐ceramics is dictated by the compositional chemistry of the parent glasses and the local environments of different species in the glass structure; for example, the sodium environment in glasses became highly ordered with decreasing Na 2 O/CaO ratio, thus favoring the formation of hexagonal nepheline, while the cubic polymorph was the stable phase in SiO 2 –poor glass‐ceramics with (Na 2 O+CaO)/Al 2 O 3 > 1. The structural origins of these crystalline phase transformations have been discussed in the paper.

Deshkar, Ambar↗
DOE OSTI2024

Reversible phase transformations between Pb nanocrystals and a viscous liquid-like phase

Phase transformations have been a prominent topic of study for both fundamental and applied science. Solid-liquid reaction–induced phase transformations can be hard to characterize, and the transformation mechanisms are often not fully understood. Here, we report reversible phase transformations between a metal (Pb) nanocrystal and a viscous liquid-like phase unveiled by in situ liquid cell transmission electron microscopy. The reversible phase transformations are obtained by modulating the electron current density (between 1000 and 3000 electrons Å –2 s –1 ). The metal-organic viscous liquid-like phase exhibits short-range ordering with a preferred Pb-Pb distance of 0.5 nm. Assisted by density functional theory and molecular dynamics calculations, we show that the viscous liquid-like phase results from the reactions of Pb with the CH 3 O fragments from the triethylene glycol solution under electron beam irradiation. Such reversible phase transformations may find broad implementations.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Optimizing the Four-Index Integral Transform Using Data Movement Lower Bounds Analysis

The four-index integral transform is a fundamental and computationally demanding calculation used in many computational chemistry suites such as NWChem. It transforms a four-dimensional tensor from an atomic basis to a molecular basis. This transformation is most efficiently implemented as a sequence of four tensor contractions that each contract a four-dimensional tensor with a two-dimensional transformation matrix. Differing degrees of permutation symmetry in the intermediate and final tensors in the sequence of contractions cause intermediate tensors to be much larger than the final tensor and limit the number of electronic states in the modeled systems. Loop fusion, in conjunction with tiling, can be very effective in reducing the total space requirement, as well as data movement. However, the large number of possible choices for loop fusion and tiling, and data/computation distribution across a parallel system, make it challenging to develop an optimized parallel implementation for the four-index integral transform. We develop a novel approach to address this problem, using lower bounds modeling of data movement complexity. We establish relationships between available aggregate physical memory in a parallel computer system and ineffective fusion configurations, enabling their pruning and consequent identification of effective choices and a characterization of optimality criteria. This work has resulted in the development of a significantly improved implementation of the four-index transform that enables higher performance and the ability to model larger electronic systems than the current implementation in the NWChem quantum chemistry software suite.

Rajbhandari, Samyam↗
DOE OSTI2025

Knowledge Oriented Graph Unified Transformer (KOGUT) v0.1

KOGUT — Knowledge Oriented Graph Unified Transformer KOGUT implements the Relational Graph Transformer (RelGT) architecture for knowledge graph link prediction in biological domains, with a primary focus on microbial growth media prediction. While the original RelGT (arXiv:2505.10960) targets relational tables, time series, and multi-table databases, KOGUT adapts this architecture for heterogeneous biological knowledge graphs, providing first-in-class AI predictive models for microbial cultivation. Key Adaptations Beyond Original RelGT: - Knowledge Graph Focus: Applied to biological KGs with semantic node types (taxa, chemicals, media, phenotypes, environments) versus generic relational database tables, trained on the KG-Microbe knowledge graph (1.3M entities, 2.9M edges, 24 relation types). - Multimodal Node Encoding: Integrates node labels, categories, descriptions, and synonyms from KG metadata through learned embedding layers—adapting relational column features to graph node attributes with textual semantics. - Extended K-Hop Subgraph Strategy: Optimized neighborhood sampling (3-hop default, configurable up to 200 nodes) tuned for sparse biological networks, building on the original local-global attention framework with biological relation preservation. - Biolink Predicate Preservation: Type-specific transformations for 24 biological edge semantics (occurs_in, consumes, produces, has_phenotype, subclass_of) beyond standard relational foreign keys, enabling multi-relation link prediction. - Inductive Learning Support: Enables zero-shot predictions for novel taxa through feature-based embeddings (temperature, oxygen requirements, gram stain, cell shape), extending the original transductive relational benchmark scope to uncultured microorganisms. CheapSOTA Performance Optimizations (This Distribution): - VQ-EMA Centroid Attention: Vector quantization with exponential moving average for improved global context modeling (+5-10% MRR improvement). - HDF5 Precomputed Data Loading: One-time preprocessing of k-hop subgraphs to eliminate redundant graph traversals (2-5× training speedup). - Distributed Data Parallel Training: Multi-GPU support for scaling to larger knowledge graphs (tested on 4× NVIDIA A100 GPUs at NERSC Perlmutter). - Mixed Precision Training: Automatic mixed precision (AMP) for memory efficiency and faster training. Advantages Over Standard Knowledge Graph Embedding Models: Combines RelGT's proven multi-element tokenization (features, type, hop, structure) with graph-native biological representations, enabling interpretable link prediction across heterogeneous entities that standard embedding models (TransE, RotatE, ComplEx) and table-based transformers cannot directly model. Achieves near-perfect performance on microbial growth media prediction (MRR: 0.9966, Precision@1: 0.9932, Hit@10: 1.0000) while maintaining explainability through attention-based reasoning over biological pathways. Training Data: - KG-Microbe merged knowledge graph: 1,379,337 nodes, 2,960,472 edges - 24 biological relation types including taxonomic hierarchies, metabolic interactions, phenotype associations, and environmental relationships - Primary prediction task: Growth media suitability for microbial taxa (biolink:occurs_in, 50K edges) - Multi-relation capability: Predicts links for any of the 24 relation types, including chemical consumption/production, phenotype associations, and taxonomic classification Citation: Original RelGT Architecture: Dwivedi et al., "Relational Graph Transformer", arXiv:2505.10960, 2025 KOGUT Implementation: Knowledge Oriented Graph Unified Transformer for Microbial Growth Media Prediction Developed at Lawrence Berkeley National Laboratory (LBNL) Trained on NERSC Perlmutter supercomputer

Joachimiak, Marcin [Lawrence Berkeley National Lab↗
DOE OSTI2021

Biogeography of microbial bile acid transformations along the murine gut

Bile acids, which are synthesized from cholesterol by the liver, are chemically transformed along the intestinal tract by the gut microbiota, and the products of these transformations signal through host receptors, affecting overall host health. These transformations include bile acid deconjugation, oxidation, and 7α-dehydroxylation. An understanding of the biogeography of bile acid transformations in the gut is critical because deconjugation is a prerequisite for 7α-dehydroxylation and because most gut microorganisms harbor bile acid transformation capacity. Here, we used a coupled metabolomic and metaproteomic approach to probe in vivo activity of the gut microbial community in a gnotobiotic mouse model. Results revealed the involvement of Clostridium scindens in 7α-dehydroxylation, of the genera Muribaculum and Bacteroides in deconjugation, and of six additional organisms in oxidation (the genera Clostridium, Muribaculum, Bacteroides, Bifidobacterium, Acutalibacter, and Akkermansia). Furthermore, the bile acid profile in mice with a more complex microbiota, a dysbiosed microbiota, or no microbiota was considered. For instance, conventional mice harbor a large diversity of bile acids, but treatment with an antibiotic such as clindamycin results in the complete inhibition of 7α-dehydroxylation, underscoring the strong inhibition of organisms that are capable of carrying out this process by this compound. Finally, a comparison of the hepatic bile acid pool size as a function of microbiota revealed that a reduced microbiota affects host signaling but not necessarily bile acid synthesis. In this study, bile acid transformations were mapped to the associated active microorganisms, offering a systematic characterization of the relationship between microbiota and bile acid composition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Dose-Rate Effects of Protons and Light Ions for DNA Damage Induction, Survival and Transformation in Apparently Normal Primary Human Fibroblasts

In this work, we report on effects of low-dose exposures of accelerated protons delivered at high-dose rate (HDR) or a simulated solar-particle event (SPE) like low-dose rate (LDR) on immediate DNA damage induction and processing, survival and in vitro transformation of low passage NFF28 apparently normal primary human fibroblasts. Cultures were exposed to 50, 100 and 1,000 MeV monoenergetic protons in the Bragg entrance/plateau region and cesium-137 γ rays at 20 Gy/h (HDR) or 1 Gy/h (LDR). DNA double-strand breaks (DSB) and clustered DNA damages (containing oxypurines and abasic sites) were measured using transverse alternating gel electrophoresis (TAFE) and immunocytochemical detection/scoring of colocalized γ-H2AX pS139/53BP1 foci, with their induction being linear energy transfer (LET) dependent and dose-rate sparing observed for the different damage classes. Relative biological effectiveness (RBE) values for cell survival after proton irradiation at both dose-rates ranged from 0.61–0.73. Transformation RBE values were dose-rate dependent, ranging from ~1.8–3.1 and ~0.6–1.0 at low doses (≤30 cGy) for HDR and LDR irradiations, respectively. However peak transformation frequencies were significantly higher (1.3–7.3-fold) for higher doses of 0.5–1 Gy delivered at SPE-like LDR. Cell survival and transformation frequencies measured after low-dose 500 MeV/n He-4, 290 MeV/n C-12 and 600 MeV/n Si-28 ion irradiations also showed an inverse dose-rate effect for transformation at SPE-like LDR. This work demonstrates the existence of inverse dose-rate effects for proton and light-ion-induced postirradiation cell survival and in vitro transformation for space mission-relevant doses and dose rates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

International Review of Standards and Labeling Programs for Distribution Transformers

Transmission and distribution (T&D) losses in electricity networks represent 8.5% of final energy consumption in the world. In Latin America, T&D losses range between 6% and 20% of final energy consumption, and represent 7% in Chile. Because approximately one-third of T&D losses take place in distribution transformers alone, there is significant potential to save energy and reduce costs and carbon emissions through policy intervention to increase distribution transformer efficiency. A large number of economies around the world have recognized the significant impact of addressing distribution losses and have implemented policies to support market transformation towards more efficient distribution transformers. As a result, there is considerable international experience to be shared and leveraged to inform countries interested in reducing distribution losses through policy intervention. The report builds upon past international studies of standards and labeling (S&L) programs for distribution transformers to present the current energy efficiency programs for distribution transformers around the world.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Design, Test and Demonstration of Fault Current Limiting HTS Transformer

The project developed new technology that enables the creation of a high temperature superconductor-based FCL power transformer. SuperPower’s research and development created new methods to bond HTS conductor to a supporting substrate, test, and insulate the resulting bonded conductor, reduce winding ac losses, ensure FCL functionality during a transformer fault and build firm superconducting joints in the transformer harnesses and cabling. The bonded conductor in this program was shown to meet the critical operating parameters of providing the superconducting transformer operation while being able to meet the target normal state resistance required for FCL operation. The bonded conductor was also shown to be able to handle the fabrication stresses associated with the manufacture of the FCL transformer while also being able to handle the high hoop stresses and axial forces during a fault transient. Much of the technology developed here is applicable to the broader applied superconductivity community. The ability to tailor the clad conductors performance characteristics gives the designer of devices utilizing HTS a broader capability to address the particular needs of an given application. SuperPower worked with its sub-recipients Waukesha Electric Systems, ORNL, Southern California Edison and University of Houston to develop the design, fabrication, installation and operational aspects of a fault current limiting transformer on the electrical grid.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Basic Research Needs for Catalysis Science to Transform Energy Technologies: Report from the U.S. Department of Energy, Office of Basic Energy Sciences Workshop May 8–10, 2017, in Gaithersburg, Maryland

Energy technologies affect virtually every aspect of life in modern societies—including transportation, utilities, agriculture, medicine, and the availability of a myriad of consumer products—and depend on human ability to accelerate and to guide chemical transformations. Controlling these transformations, which occur in the microscopic world of atoms and molecules, forms the basis of countless technologies such as production of fuels, fertilizers, plastics, pharmaceuticals and much more. At the very core of these chemical transformations are catalysts—specialized and often highly complex types of matter that allow chemical reactions to occur rapidly and produce specific products. Catalysts also have the remarkable ability to perform their tasks millions of times without themselves being consumed. The discovery of inexpensive and widely-deployable energy and chemical technologies, and their underpinning catalysis science, is critical to ensure the economic viability of U.S. energy and chemical industries. Over the past decade, remarkable new tools have been discovered that allow the observation of catalytic transformations in exquisite detail, and assembly of novel and elaborate catalytic architectures with atomic precision. Furthermore, increasingly sophisticated theoretical and computational tools allow understanding of the essential details of the catalytic processes, and this overall progress has led to the discovery of catalysts with superior performance and the associated economic benefit. In the next decade and beyond, science promises to revolutionize how catalysts and catalytic processes are designed, to enable the introduction of new energy resources, to provide routes to sustainable synthesis of chemicals and other valuable materials, and to create novel approaches to chemical energy storage. This report is the result of the Basic Energy Sciences Workshop on Basic Research Needs for Catalysis Science to Transform Energy Technologies that was held in May 2017, and was attended by more than 100 leading national and international scientific experts. The attendees were organized into four panels: 1. Diversified Energy Feedstocks and Carriers, 2. Novel Approaches to Energy Transformations, 3. Advanced Chemical Conversion Approaches, and 4. Crosscutting Capabilities and Challenges: Synthesis, Theory, and Characterization. The workshop identified five priority research directions (PRDs) that are aimed at harnessing complexity in catalysis to create next-generation energy technologies and realizing efficient catalytic processes to increase the diversity of resources for production of chemicals and energy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Solid State Transformer Architecture and Control Compensation for Common Mode Currents

A high-altitude electromagnetic pulse (HEMP) or similar geomagnetic disturbance (GMD) has the potential to impact the operation of large-scale electric power grids. By introducing low-frequency common-mode (CM) currents, these events can degrade the performance of critical system components, such as large power transformers by introducing CM currents which can lead to magnetic saturation of the transformer core. In this work, a solid-state transformer (SST) is developed to replace susceptible equipment and improve grid resiliency by safely absorbing these CM disturbances. This device will be referred to as a common-mode solid-state transformer (CM-SST). An SST architecture based on a four-legged AC/DC converter is developed. This architecture enables active control of CM signals without disturbing the AC voltages or the real and reactive power delivery capabilities. A system-level model of this architecture is created, and time-domain simulations are performed to evaluate the SST’s performance in response to simulated CM disturbances. A control strategy for mitigating CM current is also investigated. Hamiltonian surface shaping and power flow control (HSSPFC) is used to design a nonlinear controller for the SST’s output inverter. The objectives of the controller are to suppress CM-induced AC current offsets and regulate AC currents to desired setpoints. Nonlinear system analysis is applied to design and validate the controller. Two cases are tested: (a) the proposed four-leg inverter and (b) a standard three-leg inverter. The results show that the proposed controller rapidly mitigates CM disturbances while maintaining high-quality AC current waveforms in the four-leg configuration. Finally, the hardware performance of an SST prototype is evaluated. In particular, the ability of the SST to safely redirect and absorb CM currents is demonstrated, showing how it can protect neighboring conventional transformers in the system. The study confirms that appropriate control laws allow the SST to protect both itself and adjacent transformers during a HEMP or GMD event.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

The Effects of Ram-pressure Stripping and Supernova Winds on the Tidal Stirring of Disky Dwarfs: Enhanced Transformation into Dwarf Spheroidals

A conclusive model for the formation of dwarf spheroidal (dSph) galaxies still remains elusive. Owing to their proximity to the massive spirals Milky Way (MW) and M31, various environmental processes have been invoked to explain their origin. In this context, the tidal stirring model postulates that interactions with MW-sized hosts can transform rotationally supported dwarfs, resembling present-day dwarf irregular (dIrr) galaxies, into systems with the kinematic and structural properties of dSphs. Using N -body+SPH simulations, we investigate the dependence of this transformation mechanism on the gas fraction, f {sub gas}, in the disk of the progenitor dwarf. Our numerical experiments incorporate for the first time the combined effects of radiative cooling, ram-pressure stripping, star formation, supernova (SN) winds, and a cosmic UV background. For a given orbit inside the primary galaxy, rotationally supported dwarfs with gas fractions akin to those of observed dIrrs ( f {sub gas} ≳ 0.5), demonstrate a substantially enhanced likelihood and efficiency of transformation into dSphs relative to their collisionless ( f {sub gas} = 0) counterparts. We argue that the combination of ram-pressure stripping and SN winds causes the gas-rich dwarfs to respond more impulsively to tides, augmenting their transformation. When f {sub gas} ≳ 0.5, disky dwarfs on previously unfavorable low-eccentricity or large-pericenter orbits are still able to transform. On the widest orbits, the transformation is incomplete; the dwarfs retain significant rotational support, a relatively flat shape, and some gas, naturally resembling transition-type systems. We conclude that tidal stirring constitutes a prevalent evolutionary mechanism for shaping the structure of dwarf galaxies within the currently favored CDM cosmological paradigm.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Low-temperature solid-state phase transformations in 2H silicon carbide

Single crystals of 2H SiC were observed to undergo phase transformations at temperatures as low as 400 C. Some 2H crystals transformed to a structure with one-dimensional disorder along the crystal c axis. Others transformed to a faulted cubic/6H structure. The transformation is time and temperature dependent and is greatly enhanced by dislocations. Observations indicate that the transformation takes place by means of a slip process perpendicular to the c axis. Cubic SiC crystals were observed to undergo a solid state transformation above 1400 C.

Will, H. A.↗
NASA NTRS1972

Low-temperature solid-state phase transformations in 2H silicon carbide.

Study of the phase transformations taking place in 2H SiC single crystals at temperatures as low as 400 C. Some crystals transformed to a structure with one-dimensional disorder along the crystal c axis. Others transformed to a faulted cubic/6H structure. The transformation is time and temperature dependent, and is greatly enhanced by dislocations. The transformation takes place by means of a slip process perpendicular to the c axis. Cubic SiC crystals were observed to undergo a solid-state transformation above 1400 C.

Powell, J. A.↗
NASA NTRS1975

On the Laplace transform for distributions

A new characterization of the Laplace transform for Schwartz distributions is developed, using sequences of linear transformations on the space of distributions. The standard theorems on analyticity, uniqueness and invertibility of the transform are proved, using the new characterization as the definition of the Laplace transform. It is shown that this sequential definition is equivalent to Schwartz's extension of the ordinary Laplace transform to distributions which he obtained from the Fourier transform.

Price, D. B.↗
NASA NTRS1975

The transformation of aerodynamic stability derivatives by symbolic mathematical computation

The formulation of mathematical models of aeronautical systems for simulation or other purposes, involves the transformation of aerodynamic stability derivatives. It is shown that these derivatives transform like the components of a second order tensor having one index of covariance and one index of contravariance. Moreover, due to the equivalence of covariant and contravariant transformations in orthogonal Cartesian systems of coordinates, the transformations can be treated as doubly covariant or doubly contravariant, if this simplifies the formulation. It is shown that the tensor properties of these derivatives can be used to facilitate their transformation by symbolic mathematical computation, and the use of digital computers equipped with formula manipulation compilers. When the tensor transformations are mechanised in the manner described, man-hours are saved and the errors to which human operators are prone can be avoided.

Howard, J. C.↗
NASA NTRS1982

Discrete Fourier transforms of nonuniformly spaced data

Time series or spatial series of measurements taken with nonuniform spacings have failed to yield fully to analysis using the Discrete Fourier Transform (DFT). This is due to the fact that the formal DFT is the convolution of the transform of the signal with the transform of the nonuniform spacings. Two original methods are presented for deconvolving such transforms for signals containing significant noise. The first method solves a set of linear equations relating the observed data to values defined at uniform grid points, and then obtains the desired transform as the DFT of the uniform interpolates. The second method solves a set of linear equations relating the real and imaginary components of the formal DFT directly to those of the desired transform. The results of numerical experiments with noisy data are presented in order to demonstrate the capabilities and limitations of the methods.

Swan, P. R.↗