Search NASA⌕ Search

SEARCH · Search NASA

Results for “TRANSFORMATIONS”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

An efficient and broadly applicable method for transient transformation of plants using vertically aligned carbon nanofiber arrays

Transient transformation in plants is a useful process for evaluating gene function. However, there is a scarcity of minimally perturbing methods for gene delivery that can be used on multiple organs, plant species, and non-excised tissues. We pioneered and demonstrated the use of vertically aligned carbon nanofiber (VACNF) arrays to efficiently perform transient transformation of different tissues with DNA constructs in multiple plant species. The VACNFs permeabilize plant tissue transiently to allow molecules into cells without causing a detectable stress response. We successfully delivered DNA into leaves, roots and fruit of five plant species (Arabidopsis, poplar, lettuce, Nicotiana benthamiana , and tomato) and confirmed accumulation of the encoded fluorescent proteins by confocal microscopy. Using this system, it is possible to transiently transform plant cells with both small and large plasmids. The method is successful for species recalcitrant to Agrobacterium -mediated transformation. VACNFs provide simple, reliable means of DNA delivery into a variety of plant organs and species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Determining the biogeochemical transformations of organic matter composition in rivers using molecular signatures

Inland waters are hotspots for biogeochemical activity, but the environmental and biological factors that govern the transformation of organic matter (OM) flowing through them are still poorly constrained. Here we evaluate data from a crowdsourced sampling campaign led by the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium to investigate broad continental-scale trends in OM composition compared to localized events that influence biogeochemical transformations. Samples from two different OM compartments, sediments and surface water, were collected from 97 streams throughout the Northern Hemisphere and analyzed to identify differences in biogeochemical processes involved in OM transformations. By using dimensional reduction techniques, we identified that putative biogeochemical transformations and microbial respiration rates vary across sediment and surface water along river continua independent of latitude (18°N–68°N). In contrast, we reveal small- and large-scale patterns in OM composition related to local (sediment vs. water column) and reach (stream order, latitude) characteristics. These patterns lay the foundation to modeling the linkage between ecological processes and biogeochemical signals. We further showed how spatial, physical, and biogeochemical factors influence the reactivity of the two OM pools in local reaches yet find emergent broad-scale patterns between OM concentrations and stream order. OM processing will likely change as hydrologic flow regimes shift and vertical mixing occurs on different spatial and temporal scales. As our planet continues to warm and the timing and magnitude of surface and subsurface flows shift, understanding changes in OM cycling across hydrologic systems is critical, given the unknown broad-scale responses and consequences for riverine OM.

rivers↗
DOE OSTI2023

Cross-cutting concepts to transform agricultural research

Agriculture is an important link to many issues that challenge society today, including adaptation to and mitigation of climate change, food security, and communicable and non-communicable diseases in animals and humans. Transformation of agriculture and food systems has become a priority for a range of federal agencies and global organizations. It is imperative that food and agricultural researchers effectively harness the global convergence of priorities to overcome research “silos” through deep and sustained systemic change. Herein, we identify intersections in federal and global initiatives encompassing climate adaptation and mitigation; human health and nutrition; animal health and welfare; food safety and security; and equity and inclusion. Many agencies and organizations share these priorities, but efforts to address them remain uncoordinated and opportunities for collaboration untapped. Based on the interconnectedness of the identified priority areas, we present a research framework to catalyze agricultural transformation, beginning with the research enterprise. We propose that transformation in agricultural research should incorporate (1) innovation, (2) integration, (3) implementation, and (4) evaluation. This framework provides approaches for food and agricultural research to contribute to sustainable, flexible, and coordinated transformation in the agricultural sector.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Transformers and Long Short-Term Memory Transfer Learning for GenIV Reactor Temperature Time Series Forecasting

Automated monitoring of the coolant temperature can enable autonomous operation of generation IV reactors (GenIV), thus reducing their operating and maintenance costs. Automation can be accomplished with machine learning (ML) models trained on historical sensor data. However, the performance of ML usually depends on the availability of large amount of training data, which is difficult to obtain for GenIV, as this technology is still under development. We propose the use of transfer learning (TL), which involves utilizing knowledge across different domains, to compensate for this lack of training data. TL can be used to create pre-trained ML models with data from small-scale research facilities, which can then be fine-tuned to monitor GenIV reactors. In this work, we develop pre-trained Transformer and long short-term memory (LSTM) networks by training them on temperature measurements from thermal hydraulic flow loops operating with water and Galinstan fluids at room temperature at Argonne National Laboratory. The pre-trained models are then fine-tuned and re-trained with minimal additional data to perform predictions of the time series of high temperature measurements obtained from the Engineering Test Unit (ETU) at Kairos Power. The performance of the LSTM and Transformer networks is investigated by varying the size of the lookback window and forecast horizon. The results of this study show that LSTM networks have lower prediction errors than Transformers, but LSTM errors increase more rapidly with increasing lookback window size and forecast horizon compared to the Transformer errors.

LSTM↗
DOE OSTI2022

Transformer Health Monitoring Using Dissolved Gas Analysis

As integral components of any power plant, transformers supply the generated electricity to the grid. However, a transformer’s cellulose-based paper insulation and the mineral oil in which it is immersed break down over time under standard operating conditions—or more rapidly due to potential faults within the system. As the transformer’s mineral oil breaks down, gases are released that can be measured and monitored. This technical brief exhibits a collection of diagnostic and prognostic techniques that utilities can adopt in lieu of labor-intensive periodic preventive maintenance routines. Furthermore, prognostic models have been incorporated using the latest version of the Institute of Electrical and Electronics Engineers (IEEE) standard (IEEE, 2019) for dissolved gas analysis (DGA), thus expanding it to include estimation of the time to maintenance. Overall, four different methodologies are explained, each of which aids in determining a transformer’s state of health. These methodologies include the Chendong model, the IEEE thermal life consumption model (IEEE, 2012), a diagnostic model for DGA, and a prognostic model for DGA that uses an autoregressive integrated moving average (ARIMA) model. An additional improvement for estimating missing system parameters by using monitoring data (i.e., a tool for parameter estimation utilizing Powell’s method) is presented, enabling the IEEE thermal life consumption model to benefit not only the collaborating power plant, but also the power industry at large.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

A Canonical Transformation to Eliminate Resonant Perturbations. I

We study dynamical systems that admit action-angle variables at leading order, which are subject to nearly resonant perturbations. If the frequencies characterizing the unperturbed system are not in resonance, the long-term dynamical evolution may be integrated by orbit-averaging over the high-frequency angles, thereby evolving the orbit-averaged effect of the perturbations. It is well known that such integrators may be constructed via a canonical transformation, which eliminates the high-frequency variables from the orbit-averaged quantities. An example of this algorithm in celestial mechanics is the von Zeipel transformation. However, if the perturbations are inside or close to a resonance, i.e., the frequencies of the unperturbed system are commensurate; these canonical transformations are subject to divergences. We introduce a canonical transformation that eliminates the high-frequency phase variables in the Hamiltonian without encountering divergences. This leads to a well-behaved symplectic integrator. We demonstrate the algorithm through two examples: a resonantly perturbed harmonic oscillator and the gravitational three-body problem in mean motion resonance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

U.S. Distribution Transformer Demand Phase III - Key Drivers and Managing Demand [Slides]

This presentation demonstrates a significant analysis, on forecasting the demand for distribution transformers. The analysis is conducted for the United States, estimating the initial in-service capacity of these assets, and forecasting demand for these assets through 2050 with several sensitivities conducted. It examines not only demand for these assets, but importantly, how utility planning practices can impact the demand for theses assets in time. Under load growth scenarios, whether utilities practice like-for-like replacement strategies as failures occur, or whether they practice proactive up-sizing, anticipating electric load growth, can have major impacts on future demand. It also examines several other growth factors, such as the increasing demand for step-up transformers, which share many of the same characteristics as distribution transformers, and the demand for specific transformers for large project growth from data centers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

On the Use of Smart Meter Data to Estimate the Voltage Magnitude on the Primary Side of Distribution Service Transformers: Preprint

This paper develops a novel method to estimate the voltage magnitude on the primary side of distribution service transformers. The proposed method relies exclusively on smart meters, and therefore it is fully data-driven. This is an important feature because electric utilities have detailed models of only the primary network--that is, the network between the distribution substation and the primary side of service transformers that are installed closer to end-customer sites. The network that connects the secondary side of service transformers to end-customer sites, referred to as the secondary network, is simply represented by a lumped load. For each secondary network, the proposed method uses data acquired from only 2 smart meters: the closest and the farthest--in the sense of electrical distance--from the service transformer. As a reference to this feature, the proposed method is named SM2Vp. To our knowledge, this is the first time a method is shown to provide actionable information for real-time operation and control of power distribution grids using only two smart meters per secondary network. This is important because utilities have experienced barriers in managing and using large data sets for real-time operation and control. SM2Vp is primarily intended to provide pseudo-measurements for distribution system state estimation, but it can also be used directly for voltage control schemes. The performance of SM2Vp is demonstrated by numerical simulations carried out on three secondary network synthetic models and by using field data provided by a utility partner serving customers in southwestern California. A maximum relative error of approximately 3.9% or less is observed for the primary voltage magnitude estimates in all numerical experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

FLEXIBLE POWER TRANSFORMERS TO IMPROVE RESILIENCY OF TRANSMISSION NETWORKS

For decades, transformer flexibility of operation has been limited to adjustable voltage ratio and, in some cases, several ratings with staged cooling. Transformers reconnectable to multiple voltage ratings have been primarily applied as emergency replacements. Other versions of “flexible transformers” were developed for continuous, long-term operation at specific sites, with application limited to large utilities. A new technology that supports today’s power systems adaptability requirements has been developed to provide not only voltage and power rating flexibility, but also an adjustable short-circuit impedance. This last, unique feature allows for a closer match to actual system operational requirements and could be used in the future to enhance resiliency and improve dynamic control of electrical grids. While the solution’s fundamentals have already been introduced in several technical forums, the intention of this article is to focus on the potential benefits of this new type of transformer and share the deployment experience of a full-scale prototype that has been in operation in a major U.S. utility since 2021

flexible transformer, resilient grid, variable lea↗
DOE OSTI2022

Design, Deployment, and Characterization of the World’s First Flexible Large Power Transformer

As we know, power transformers are the most critical asset of the transmission network. Although highly reliable, they still can fail prematurely or ultimately retire at the end of their service life. In today’s design practices, transformers are tailored to their specific application and therefore cannot replace each other unless identical. Additionally, they provide minimal support to the grid operation and therefore limit the grid flexibility and resiliency when facing severe conditions. In this presentation, we will introduce the concept of flexible power transformer and demonstrate how one single unit can serve as a spare to multiple units in a given fleet, allow to control the power flow between transformers or lines operating in parallel and ultimately be used to limit subsequent faults in transmission lines. We will also introduce the world’s first prototype in operation, a 60MVA, 165kV flexible autotransformer.

flexible power transformer, autotransformer, varia↗
DOE OSTI2024

Distribution Transformer Demand: Understanding Demand Segmentation, Drivers, and Management Through 2050

The National Renewable Energy Laboratory (NREL) has been working closely with the U.S. Department of Energy's Office of Electricity (OE) to understand the critical drivers and potential means of managing distribution transformer demand through 2050. This effort has consulted with utility representative organizations and transformer manufacturers to understand the problem, characterized the in-service assets, and modeled future demand. Distribution transformers, or service transformers, range from 10 to 5,000 kilovolt-amperes (kVA), have a high-side voltage of less than 34.5 kilovolts, and have step-down power delivery for customer end use. This research will help the manufacturing sector understand production requirements and better inform utility strategies for managing their demand.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Soft-Switching Solid-State Transformer With Reduced Conduction Loss

Solid-state transformers (SSTs) are a promising solution photovoltaic (PV), wind, traction, data center, battery energy storage system (BESS), and fast charging electric vehicle (EV) applications. The traditional SSTs are typically three-stage, i.e., hard-switching cascaded multilevel rectifiers and inverters with dual active bridge (DAB) converters, which leads to bulky passives, low efficiency, and high electromagnetic interference (EMI). This article proposes a new soft-switching solid-state transformer (S4T). The S4T has full-range zero-voltage switching (ZVS), electrolytic capacitor-less dc link, and controlled dv/dt, which reduces EMI. The S4T comprises two reverse-blocking current-source inverter (CSI) bridges, auxiliary branches for ZVS, and transformer magnetizing inductor as a reduced dc link with 60% ripple. Compared with the prior S4T, an effective change on the leakage inductance diode is made to reduce the number of the devices on the main power path by 20% for significant conduction loss saving and retain the same functionality of damping the resonance between the leakage and resonant capacitors and recycling trapped leakage energy. The conduction loss saving is crucial, being the dominating loss mechanism in SSTs. Importantly, the proposed single-stage SST not only holds the potential for high power density and high efficiency but also has full functionality, e.g., multiport dc loads integration, voltage regulation, and reactive power compensation, unlike the traditional single-stage matrix SST. The S4T can achieve single-stage isolated bidirectional dc–dc, ac–dc, dc–ac, or ac–ac conversion. It can also be configured input-series output-parallel (ISOP) in a modular way for medium-voltage (MV) grids. Hence, the S4T is a promising candidate for the SST. The full functionality, e.g., voltage buck–boost, multiport, etc., and the universality of the S4T for the dc–dc, dc–ac, and ac–ac conversion are verified through the simulations and experiments of two-port and three-port MV prototypes based on 3.3 kV SiC MOSFETs in dc–dc, dc–ac, and ac–ac modes at 2 kV.

14 SOLAR ENERGY↗
DOE OSTI2021

Current-Source Solid-State DC Transformer Integrating LVDC Microgrid, Energy Storage, and Renewable Energy Into MVDC Grid

Solid-state DC transformer to integrate low-voltage DC (LVDC) microgrid, wind turbine (WT) generator, photovoltaic (PV), and energy storage (ES) into medium-voltage (MV) direct-current (MVDC) distribution grids is attractive. This paper proposes current-source DC solid-state transformer (SST) for MVDC collection system in WT, PV, and ES farms or as an interface between the MVDC grid and the LVDC microgrid. Compared to conventional current-source converter (CSC) based SSTs, a switch reduction scheme on reverse-blocking device bridges is proposed to reduce device count and the number of devices on the DC-link current path. Importantly, the proposed switch reduction scheme is generic and can be applied to the DC ports of DC-AC, AC-DC, or DC-DC hard-switching or soft-switching CSC-based SSTs. Based on this scheme, the proposed current-source DC SSTs are derived, which have reduced electrolytic-capacitor-less DC-link. The proposed DC SSTs also achieve single-stage isolated DC-DC or DC-AC conversion, full-range zero-voltage switching (ZVS) for main switches, zero-current switching (ZCS) for resonant switches, and controlled dv/dt. The proposed DC SSTs, operating principles, predictive control method, the ZVS, and the controlled dv/dt under voltage buck-boost ranges are verified with MV simulations and an experimental prototype based on SiC MOSFETs, diodes, and a nanocrystalline transformer.

14 SOLAR ENERGY↗
DOE OSTI2022

Device Voltage Stress from Ground Leakage Current in Medium-Voltage Solid-State Transformer

Grounding related issues are critical for safe and reliable operation of solid-state transformer (SST) in medium-voltage (MV) applications, e.g., solar photovoltaic and energy storage integration, date center, electric vehicle fast charging, etc. This article presents for the first time the issue of additional device voltage stress due to grounding-loop current in current-source SST, using the soft-switching solid-state transformer (S4T) as an example. The S4T features single-stage isolated AC-AC, AC-DC, or DC-DC conversion with full-range ZVS, derived from flyback converter or current-source converter (CSC). However, the flyback operation for CSC-based SST means that magnetizing current flows through the reverse-blocking devices on only one side of the medium-frequency transformer (MFT) at a time. Then, the voltages across the devices, especially those on the other side of the MFT, can be influenced by parasitic current. A parasitic model of a modular S4T (M-S4T) prototype is developed from direct measurements and datasheets. Using the developed parasitic model and equivalent circuits, the causes of the voltage stress are analyzed. A voltage-stress mitigation scheme of connecting additional grounding capacitors is proposed. Damping resistors are also installed to damp out the grounding-loop resonance. A robust parameter design of the proposed scheme is given. The existence of the voltage stress issue and the effectiveness of the proposed scheme are verified experimentally on an MV SiC M-S4T prototype with inherent parameter variations among the five modules in the prototype. Here, both single-module and stacked-module operation are demonstrated during steady state and dynamic conditions up to 4 kV peak.

42 ENGINEERING↗
DOE OSTI2021

External-Field-Induced Phase Transformation and Associated Properties in a Ni 50 Mn 34 Fe 3 In 13 Metamagnetic Shape Memory Wire

Metamagnetic shape memory alloys exhibit a series of intriguing multifunctional properties and have great potential for applications in magnetic actuation, sensing and magnetic refrigeration. However, the poor mechanical properties of these alloys with hardly any tensile deformability seriously limit their practical application. In the present work, we developed a Ni-Fe-Mn-In microwire that exhibits both a giant, tensile superelasticity and a magnetic-field-induced first-order phase transformation. The recoverable strain of superelasticity is more than 20% in the temperature range of 233–283 K, which is the highest recoverable strain reported heretofore in Ni-Mn-based shape memory alloys (SMAs). Moreover, the present microwire exhibits a large shape memory effect with a recoverable strain of up to 13.9% under the constant tensile stress of 225 MPa. As a result of the magnetic-field-induced first-order phase transformation, a large reversible magnetocaloric effect with an isothermal entropy change ΔS m of 15.1 J kg –1 K –1 for a field change from 0.2 T to 5 T was achieved in this microwire. The realization of both magnetic-field and tensile-stress-induced transformations confers on this microwire great potential for application in miniature multi-functional devices and provides an opportunity for multi-functional property optimization under coupled multiple fields.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Phase Transformations Driving Biaxial Stress Reduction During Wake-Up of Ferroelectric Hafnium Zirconium Oxide Thin Films

Biaxial stress is identified to play an important role in the polar orthorhombic phase stability in hafnium oxide-based ferroelectric thin films. However, the stress state during various stages of wake-up has not yet been quantified. In this work, the stress evolution with field cycling in hafnium zirconium oxide capacitors is evaluated. The remanent polarization of a 20 nm thick hafnium zirconium oxide thin film increases from 9.80 to 15.0 µC cm –2 following 10 6 field cycles. This increase in remanent polarization is accompanied by a decrease in relative permittivity that indicates that a phase transformation has occurred. The presence of a phase transformation is supported by nano-Fourier transform infrared spectroscopy measurements and scanning transmission electron microscopy that show an increase in ferroelectric phase content following wake-up. The stress of individual devices field cycled between pristine and 10 6 cycles is quantified using the sin 2 (ψ) technique, and the biaxial stress is observed to decrease from 4.3 ± 0.2 to 3.2 ± 0.3 GPa. The decrease in stress is attributed, in part, to a phase transformation from the antipolar Pbca phase to the ferroelectric Pca2 1 phase. This work provides new insight into the mechanisms controlling and/or accompanying polarization wake-up in hafnium oxide-based ferroelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Quantum Fourier transform revisited

Summary The fast Fourier transform (FFT) is one of the most successful numerical algorithms of the 20th century and has found numerous applications in many branches of computational science and engineering. The FFT algorithm can be derived from a particular matrix decomposition of the discrete Fourier transform (DFT) matrix. In this paper, we show that the quantum Fourier transform (QFT) can be derived by further decomposing the diagonal factors of the FFT matrix decomposition into products of matrices with Kronecker product structure. We analyze the implication of this Kronecker product structure on the discrete Fourier transform of rank‐1 tensors on a classical computer. We also explain why such a structure can take advantage of an important quantum computer feature that enables the QFT algorithm to attain an exponential speedup on a quantum computer over the FFT algorithm on a classical computer. Further, the connection between the matrix decomposition of the DFT matrix and a quantum circuit is made. We also discuss a natural extension of a radix‐2 QFT decomposition to a radix‐ d QFT decomposition. No prior knowledge of quantum computing is required to understand what is presented in this paper. Yet, we believe this paper may help readers to gain some rudimentary understanding of the nature of quantum computing from a matrix computation point of view.

Camps, Daan↗
DOE OSTI2023

In Situ X-ray Diffraction Investigation of Hydrogen Effects on Deformation-Induced Phase Transformation in Forged and Additively Manufactured 304L Stainless Steels

Here, this study utilized high energy synchrotron x-ray diffraction to probe microstructural evolution during uniaxial deformation of conventionally manufactured and additively manufactured (AM) 304L stainless steel with and without internal hydrogen. The objective of this effort is to highlight the effect of hydrogen on deformation-induced martensite phase transformations in austenitic stainless steels. Solute hydrogen depresses the required applied strain to initiate austenite transformation to ε-martensite and α'-martensite in both forged and AM stainless steel. Similarly, the total fraction of transformation product is larger when the microstructure is saturated with hydrogen. Deformation induced phase transformations also lead to a variation in strain partitioning behavior, which is linked to the chemical composition and stacking fault energy of the starting and hydrogen-charged materials.

36 MATERIALS SCIENCE↗