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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 19 records

Solid-State Transformer and Hybrid Transformer With Integrated Energy Storage in Active Distribution Grids: Technical and Economic Comparison, Dispatch, and Control

Solid-state transformer (SST) and hybrid transformer (HT) are promising alternatives to the line-frequency transformer (LFT) in smart grids. The SST features medium-frequency isolation, full controllability for voltage regulation, reactive power compensation, and the capability of battery energy storage system (BESS) integration with multiport configuration. The HT has a partially-rated converter for fractional controllability and can integrate a small BESS. Fast grid-edge voltage fluctuations from increased solar photovoltaic (PV) and electric vehicle (EV) penetration are difficult to manage for mechanical load tap changers. Hence, along with the trend towards more BESS in the grid, the controllability and the storage integration capability of the SST and HT are of strong interest. However, a review of literature shows existing SST and HT research is mostly at converter level, while system-level assessments are scarce. Assessing technical and economic impacts is critical to understanding the benefits and role of the SST and HT to guide future research, which is presented for the first time in this article. Experimental results from medium-voltage (MV) SST and MV HT prototypes are shown to confirm equipment-level feasibility, where the voltage controllability waveforms of a MV HT prototype are reported for the first time. Comparative simulations are performed on a modified IEEE 34-bus system. Here, a grid-model-less decentralized grid-edge voltage control method and a day-ahead BESS dispatch method are proposed for the SST and HT. The simulations show that the SST and HT with integrated storage can host more PV, achieve peak shaving, mitigate voltage fluctuation and reverse power flow, and support energy arbitrage for operational cost reduction, as compared to the LFT. Moreover, comprehensive analyses of net present value (NPV) and internal rate of return (IRR) are performed under different installed PV capacities, HT’s partial converter ratings, and BESS capacities. Sensitivities to future cost reductions of the PV and BESS are studied. Although the NPV and IRR are currently negative, 60% capital cost reduction or 150% revenue increase will make the SST and HT economically viable in the use case studied.

14 SOLAR ENERGY↗

An asymmetric hybrid cryptosystem using equal modulus and random decomposition in hybrid transform domain

In this paper, an asymmetric hybrid cryptosystem with coherent superposition, equal modulus and random decomposition in hybrid transform domain is proposed. To further strengthen the security of the cryptosystem, a hyperchaotic system is used as a pixel-swapping procedure. The hybrid transform is generated by utilizing fractional Fourier transform of various orders and Walsh transform. The hyperchaotic framework’s parameters and starting conditions alongside the fractional orders of the fractional Fourier transform extend the key-space and consequently give extra strength to the proposed cryptosystem. The designed cryptosystem has an extended key-space to avoid any brute-force attack and is non-linear in nature. The scheme is validated on gray-scale images. Computer based simulations have been performed to verify the validity and the performance of the proposed cryptosystem against different types of attacks. Results demonstrate that the proposed cryptosystem not only offers higher protection against noise attacks but is also invulnerable to special attack.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A fast computation of complex convolution using a hybrid transform

The cyclic convolution of complex values was obtained by a hybrid transform that is a combination of a Winograd transform and a fast complex integer transform. This new hybrid algorithm requires fewer multiplications than any previously known algorithm.

Reed, I. S.↗

Geothermal well testing pressure prediction by using a hybrid transformer model system: FORGE well use case

Geothermal has huge potential to become an indispensable component in achieving the goal of sustainable energy economy, given its capability to provide consistent baseload power to the electric grid. Injection tests are crucial in geothermal energy system as they naturally help to evaluate reservoir properties, understand fluid flow and even enhance reservoir performance. In this research, we developed a hybrid model system that integrates machine learning (ML) regression, a physics-based mathematical model, and transformer deep learning. Trained and validated using FORGE injection test dataset, this system can forecast the pressure variations both upward and downward over time. The pressure prediction achieved prediction accuracy within 3-6% variance of true pressure values. The system can significantly save time and reduce costs by testing only a few cycles and then using model predictions for further analysis, instead of conducting additional real injection cycle tests. The developed model system also holds promise for designing injection test processes and maintaining well production in geothermal energy. Presented at the IMAGE ‘25 Conference led by Shell.

FORGE↗

A fast complex integer convolution using a hybrid transform

It is shown that the Winograd transform can be combined with a complex integer transform over the Galois field GF(q-squared) to yield a new algorithm for computing the discrete cyclic convolution of complex number points. By this means a fast method for accurately computing the cyclic convolution of a sequence of complex numbers for long convolution lengths can be obtained. This new hybrid algorithm requires fewer multiplications than previous algorithms.

Reed, I. S.↗

Surface-Induced Dissociation of Protein Complexes in a Hybrid Fourier Transform Ion Cyclotron Resonance Mass Spectrometer

Mass spectrometry continues to develop as a valuable tool in the analysis of proteins and protein complexes. In protein complex mass spectrometry studies, surface-induced dissociation (SID) has been successfully applied in quadrupole time-of-flight (Q-TOF) instruments. SID provides structural information on non-covalent protein complexes that is complementary to other techniques. However, the mass resolution of Q-TOF instruments can limit the information that can be obtained for protein complexes by SID. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) provides ultrahigh resolution and ultrahigh mass accuracy measurements. In this study, an SID device was designed and successfully installed in a hybrid FT-ICR instrument in place of the standard gas collision cell. The SID-FT-ICR platform has been tested with several protein complex systems (homooligomers, a heterooligomer, and a protein-ligand complex, ranging from 53 kDa to 85 kDa), and the results are consistent with data previously acquired on Q-TOF platforms, matching predictions from known protein interface information. SID fragments with the same m/z but different charge states are well-resolved based on distinct spacing between adjacent isotope peaks, and the addition of metal cations and ligands can also be isotopically resolved with the ultrahigh mass resolution available in FT-ICR.

Environmental Molecular Sciences Laboratory↗

Two-dimensional lithium diffusion behavior and probable hybrid phase transformation kinetics in olivine lithium iron phosphate

Olivine lithium iron phosphate is a technologically important electrode material for lithium-ion batteries and a model system for studying electrochemically driven phase transformations. Despite extensive studies, many aspects of the phase transformation and lithium transport in this material are still not well understood. Here we combine operando hard X-ray spectroscopic imaging and phase-field modeling to elucidate the delithiation dynamics of single-crystal lithium iron phosphate microrods with long-axis along the [010] direction. Lithium diffusivity is found to be two-dimensional in microsized particles containing ~3%lithium-iron anti-site defects. Our study provides direct evidence for the previously predicted surface reaction-limited phase-boundary migration mechanism and the potential operation of a hybrid mode of phase growth, in which phase-boundary movement is controlled by surface reaction or lithium diffusion in different crystallographic directions. These findings uncover the rich phase-transformation behaviors in lithium iron phosphate and intercalation com-pounds in general and can help guide the design of better electrodes.

25 ENERGY STORAGE↗

Multi-target tracking using a hybrid joint transform correlator

A technique using data association target tracking in a motion sequence via an adaptive joint transform correlator is presented. The massive data in the field of view can be reduced to a few correlation peaks. The average velocity of a target during the tracking cycle is then determined from the location of the correlation peak. A data-association algorithm is used for the analysis of these correlation signals, for which multiple targets can be tracked. A phase-mostly liquid-crystal TV is used in the hybrid joint transform correlation system, and simultaneous tracking of three targets is demonstrated.

Yu, Francis T. S.↗

A Line Impedance Conditioner for Saturation Mitigation of Zigzag Transformer in Hybrid AC/DC Transmission System Considering Line Unbalances

Hybrid ac/dc transmission extends the power transfer capacity of existing long ac lines closer to their thermal limit, by superposing the dc current onto three-phase ac lines through a zigzag transformer. However, this transformer could suffer saturation under unbalanced line impedance conditions. This paper introduces the concept of hybrid line impedance conditioner (HLIC) as a cost-effective approach to compensate for the line unbalance and therefore avoid saturation. The topology and operation principle are presented. The two-level control strategy is described, which enables autonomous adaptive regulation without the need of system-level control. Design and implementation are also analyzed, including dc-link capacitance as one of the key line conditioner components, HLIC installation, and protection under fault conditions. The cost study on this HLIC-based hybrid system is also performed to reveal the benefits of the solution. In conclusion, simulation results and experimental results based on a down-scaled prototype are provided to verify the feasibility of the proposed approach.

30 DIRECT ENERGY CONVERSION↗

Lab-scale Development of a Hybrid Capture System with Advanced Membrane, Solvent system, and Process Integration

The objective of the project is to achieve lab-scale demonstration of a transformational hybrid membrane/solvent system for the capture of CO 2 from flue gas. A novel process integration scheme was proposed to overcome the low partial pressure of CO 2 present in flue gas. This scheme takes advantage of the potential synergies inherent in the membrane and solvent capture systems. The proposed hybrid technology replaces the second-stage membrane with a solvent capture process. The combustion air is used as a sweeping gas in the solvent stripper. This overall configuration has the major advantages of requiring much less air and eliminating the problems associated with oxygen slip in the membrane-based systems. Even more importantly, because of the presence of the air sweep in the stripper, much lower temperatures are required for solvent regeneration, which enables heat integration to the point that no process steam is required. This project was to perform lab-scale demonstration of Liquid Ion Solutions (LIS) transformational hybrid membrane/solvent system for post-combustion CO 2 capture while demonstrating significant progress toward achievement of the overall fossil energy performance goals of 90% CO 2 capture rate with 95% CO 2 purity at a cost of electricity 30% less than baseline capture approaches. This report is written chronologically based on budget periods. Each budget period discusses the work performed and its results. At the end of each budget period the milestone charts are provided to show the progress. This project was not able to meet its stated goals. The performances of the power plant equipped with the hybrid process and Baseline Case B12B were compared. The simulation results showed that the power plant equipped with hybrid CO2 capture process has an improved thermal efficiency of 33.4% compared to the Baseline Case B12B, which is 32.5%. However, the COE for the hybrid process is $146.3/MWh which is higher than the $142.8/MWh for Case B12B. If this process were to be applied as a retrofit, it may make sense to use this configuration as it does not require any change in an existing plant configuration and steam cycle. However, for a new powerplant the capital cost is higher than the Case B12B. On the membrane development side, we successfully showed that interfacially-controlled envelope (ICE) membranes work. The inclusion of surface modified nano-particles results in much higher gas diffusivities. The Gen-1 ICE membrane developed under this project showed exceptional improved permeability for CO 2 . However, we ran into major problems which were associated with the scalability and reproducibility of the poly(phosphozene) polymers. The issues with scale-up are and batch to batch variability is also discussed. At the end of this report we have provided our recommendations on materials development for better membrane materials and alluded to the use of much simpler chemistry while keeping the concept of ICE membrane intact. It is also clear that vacuum and compression equipment is costly. If a process which can eliminate the use of vacuum and compression equipment would significantly decrease the overall cost of capture. Some thoughts regarding such system is also provided in the outlook portion of this report.

20 FOSSIL-FUELED POWER PLANTS↗

Improving the Concrete Crack Detection Process via a Hybrid Visual Transformer Algorithm

Inspections of concrete bridges across the United States represent a significant commitment of resources, given their biannual mandate for many structures. With a notable number of aging bridges, there is an imperative need to enhance the efficiency of these inspections. This study harnessed the power of computer vision to streamline the inspection process. Our experiment examined the efficacy of a state-of-the-art Visual Transformer (ViT) model combined with distinct image enhancement detector algorithms. We benchmarked against a deep learning Convolutional Neural Network (CNN) model. These models were applied to over 20,000 high-quality images from the Concrete Images for Classification dataset. Traditional crack detection methods often fall short due to their heavy reliance on time and resources. This research pioneers bridge inspection by integrating ViT with diverse image enhancement detectors, significantly improving concrete crack detection accuracy. Notably, a custom-built CNN achieves over 99% accuracy with substantially lower training time than ViT, making it an efficient solution for enhancing safety and resource conservation in infrastructure management. These advancements enhance safety by enabling reliable detection and timely maintenance, but they also align with Industry 4.0 objectives, automating manual inspections, reducing costs, and advancing technological integration in public infrastructure management.

42 ENGINEERING↗

New Hybrid Model for Evaluating the Frequency-Dependent Leakage Inductance of a Variable Inductance Transformer (VIT)

Skin and proximity effects can cause a significant drop in the effective leakage inductance of a transformer when the operating frequency is increased. Although the magnetic image method-based double-2-D model can calculate the lowfrequency leakage inductance with sufficient accuracy, it is inherently a frequency-independent model. While Dowell’s 1-D model uses frequency-dependent relations to account for both skin and proximity effects, its accuracy is severely affected by the assumed winding geometry. In this paper, a hybrid model is proposed that uses superposition to combine a modified Dowell’s model with the double-2-D model. The proposed model is investigated on a variable inductance transformer (VIT)—a partially-filled transformer whose leakage inductance can be varied by moving one of the windings mechanically. The frequency-dependent leakage inductances of the VIT evaluated using the hybrid model are in excellent agreement with the corresponding finite element method (FEM) simulated and experimentally measured values, thereby validating the proposed hybrid model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multiple-stage structure transformation of organic-inorganic hybrid perovskite CH 3 NH 3 PbI 3

In this study, by performing spatially resolved Raman and photoluminescence spectroscopy with varying excitation wavelength, density, and data acquisition parameters, we achieve a unified understanding towards the spectroscopy signatures of the organic-inorganic hybrid perovskite, transforming from the pristine state (CH 3 NH 3 PbI 3 ) to the fully degraded state (i.e., PbI 2 ) for samples with varying crystalline domain size from mesoscopic scale (approximately 100 nm) to macroscopic size (centimeters), synthesized by three different techniques. We show that the hybrid perovskite exhibits multiple stages of structure transformation occurring either spontaneously or under light illumination, with exceptionally high sensitivity to the illumination conditions (e.g., power, illumination time, and interruption pattern). We highlight four transformation stages (stages I-IV, with stage I being the pristine state) along either the spontaneous or photoinduced degradation path exhibiting distinctly different Raman spectroscopy features at each stage, and point out that previously reported Raman spectra in the literature reflect highly degraded structures of either stage III or stage IV. Additional characteristic optical features of partially degraded materials under the joint action of spontaneous and photodegradation are also given. This study offers reliable benchmark results for understanding the intrinsic material properties and structure transformation of this unique category of hybrid materials, and the findings are pertinently important to a wide range of potential applications where the hybrid material is expected to function in greatly different environment and light-matter interaction conditions.

14 SOLAR ENERGY↗

Digital transmitter for data bus communications system

An improved digital transmitter for transmitting serial pulse code modulation (pcm) data at high bit rates over a transmission line is disclosed. When not transmitting, the transmitter features a high output impedance which prevents the transmitter from loading the transmission line. The pcm input is supplied to a logic control circuit which produces two discrete logic level signals which are supplied to an amplifier. The amplifier, which is transformer coupled to the output isolation circuitry, converts the discrete logic level signals to two high current level, ground isolated signals in the secondary windings of the coupling transformer. The latter signals are employed as inputs to the isolation circuitry which includes two series transistor pairs operating into a hybrid transformer functioning to isolate the transmitter circuitry from the transmission line.

Proch, G. E.↗

Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics

Models based on vision transformer architectures are considered state-of-the-art when it comes to image classification tasks. However, they require extensive computational resources both for training and deployment. The problem is exacerbated as the amount and complexity of the data increases. Quantum-based vision transformer models could potentially alleviate this issue by reducing the training and operating time while maintaining the same predictive power. Although current quantum computers are not yet able to perform high-dimensional tasks, they do offer one of the most efficient solutions for the future. In this work, we construct several variations of a quantum hybrid vision transformer for a classification problem in high-energy physics (distinguishing photons and electrons in the electromagnetic calorimeter). We test them against classical vision transformer architectures. Our findings indicate that the hybrid models can achieve comparable performance to their classical analogs with a similar number of parameters.

Unlu, Eyup B. (ORCID:0000000266836463)↗