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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 235 records · Page 13

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on Banshee Distribution Network

This study investigates the hosting capacity of the Banshee Distribution Network by optimizing the real power injection at carefully selected Distributed Energy Resource (DER) locations. The analysis is conducted within the framework of power system operational constraints, including bus voltage ranges, thermal line ratings, and transformer loading limits. A Python-based Genetic Algorithm (GA), implemented using the PyGAD library, is employed to iteratively identify the optimal power injection configuration that maximizes network utilization while preserving system reliability. The methodology integrates a real-time simulation environment using the Real-Time Digital Simulator (RTDS), allowing high-fidelity evaluation of power flow and voltage behavior under each proposed injection scenario. By coupling the optimization algorithm with real-time simulation feedback, this approach ensures that both static and dynamic constraints are enforced during the evaluation process. The GA leverages evolutionary operators such as selection, crossover, and mutation to navigate the nonlinear search space efficiently. The results of the study delineate the feasible hosting capacity at three targeted buses, reflecting maximum real power levels that can be injected without causing voltage violations, transformer overloading, or line congestion. These findings provide a decision- support tool for distribution planners and utilities aiming to integrate higher penetrations of DERs in existing infrastructure. Additionally, the work lays the foundation for extending such optimization techniques to multi-objective formulations, including economic dispatch and reactive power coordination, in future studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Structural Verification of the Space Shuttle's External Tank Super LightWeight Design: A Lesson in Innovation

The Super LightWeight Tank (SLWT) team was tasked with a daunting challenge from the outset: boost the payload capability of the Shuttle System by safely removing 7500 lbs. from the existing 65,400 lb. External Tank (ET). Tools they had to work with included a promising new Aluminum Lithium alloy, the concept of a more efficient structural configuration for the Liquid Hydrogen (LH2) tank, and a highly successful, mature Light Weight Tank (LWT) program. The 44 month schedule which the SLWT team was given for the task was ambitious by any measure. During this time the team had to not only design, build, and verify the new tank, but they also had to move a material from the early stages of development to maturity. The aluminum lithium alloy showed great promise, with an approximately 29% increase in yield strength, 15% increase in ultimate strength, 5 deg/O increase in modulus and 5 deg/O decrease in density when compared to the current 2219 alloy. But processes had to be developed and brought under control, manufacturing techniques perfected, properties characterized, and design allowable generated. Because of the schedule constraint, this material development activity had to occur in parallel with design and manufacturing. Initial design was performed using design allowable believed to be achievable with the Aluminum Lithium alloy system, but based on limited test data. Preliminary structural development tests were performed with material still in the process of iteration. This parallel path approach posed obvious challenges and risks, but also allowed a unique opportunity for interaction between the structures and materials disciplines in the formulation of the material.

Otte, Neil↗

Science Overview

This report presents an overview of the latest scientific consensus understanding of the effect of aviation emissions on the atmosphere for both local air quality and climate change in order to provide a contextual framework for raising future questions to help assess the environmental benefits of technology goals. The questions may take the form of what are the environmental benefits that would result if goals are achieved, what are the consequences for other aviation pollutants, and whether tools exist to evaluate the trade-off. In addition to this documents, presentations will be made at the meeting to illustrate current developing views on these subjects. To facilitate studies on trade-offs among environmental impacts from aviation, one must start with scientific investigations that quantify the impacts. A second step is to select representative metrics with policy relevance so that diverse impacts can be put on the same common scale. The IPCC Special Report on Aviation (IPCC, 1999) serves as an excellent example of the first step. The report was produced by IPCC's Working Group 1, whose mandate is to provide the assessment of the scientific aspects of the climate system and climate change. An example of the second step is Witt et al. (2005), a study commissioned by the Environment DG of the European Commission. Within the context of CAEP, step 1 is aligned with the responsibilities of the Research Focal Points, while step 2 is more related to activities of FESG. These steps are likely to be iterative as proposed policy options will raise new science questions, and new science will expand or limit policy options. Past experiences show that clearly defined policy-related scientific needs will help focus the scientific community to marshal their intellects to provide the needed answers.

Bruning, Claus↗

Space Biotech: Hindsight, Insight, Foresight

Over the past forty years, microgravity has inspired and enabled applications in a wide range of sectors including medicine, materials, computers, communications, and national defense. Trends show that demand for high-tech solutions is increasing in these sectors, solutions that require higher resolution, greater precision, novel materials, innovative processes, and more sophisticated tools. These are areas where microgravity can offer unique capabilities for innovation. The Emerging Space Office (ESO) has engaged in multiple studies over the past year that have found that microgravity RD is one of the most promising technology areas for contributing to economic growth and to NASAs mission. The focus of these studies was on terrestrial markets rather than NASA applications, applied research rather than basic research, and commercial rather than academic investigators. There have been more success stories than are generally appreciated and there are significant areas of promising future potential. Many of the problems that have limited commercial microgravity development in the past are being solved. Microgravity research and development (RD) requires iteration and learning, as rapidly as possible. New technologies enable high throughput and rapid data collection in increasingly small payloads. The International Space Station is in orbit and provides a laboratory that is available 247 at least until 2024. Frequent flights by commercial space providers to and from the ISS now enable the fast learning cycles needed by high-tech industries. Launch costs are decreasing and the ability to return payloads to Earth is increasing. New commercial space laboratories, such as those being developed by SpaceX and Bigelow Aerospace, are in the final stages of development and testing. This ecosystem for microgravity RD has never been available before. These are game-changer conditions for attracting high-tech industries to space for terrestrial, as well as NASA, applications. However, few know that these capabilities are available or how to use them. In aggregate, the potential value for new applications from microgravity RD over the next ten years could add billions of dollars per year in terrestrial applications to the future economy, create new jobs, and generate a wide range of public benefits in medical advances, while broadening the customer base for the emerging space industry.

biotech↗

Development of a Maxwell X-57 High Lift Motor Reference Design

NASA's all-electric X-57 airplane will utilize 14 electric motors, of which 12 are exclusively for lift augmentation during takeoff and landing. This report covers the design and development process taken to create an open reference model representative of the 12 lift augmenting motors. A combined worst case scenario was used as the design point, which represents the simultaneously occurring worst case aspects of thermal, static stress, electromagnetic, and rotor dynamic conditions. This work also highlights the tightly coupled nature of aerospace electric motor design, requiring constant iteration between all disciplines involved. Further adding to the uniqueness is the cooling method, which is limited to nacelle skin forced convection cooling only, no internal air flow is permitted. The stator outer diameter limit of 156.45 mm greatly impacts the degree of coupling between the electromagnetic design with the thermal analysis. The permanent magnet synchronous motor developed here operates between 385 V and 538 V, at a peak current of 50 A. Detailed electromagnetic, thermal, static load, and rotordynamic analysis was completed for this electric motor; all of which are required for a full design. The rotordynamic analysis took into consideration the motor housing which is designed specifically for this motor. The final electric motor has a mass of 2.34 kg, produces 24.1 Nm of torque with a specific power of 5.56 kW/kg, and has an efficiency of 96.61% at the combined worst case design point.

Electric Aircraft↗

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on the Banshee Distribution Network: Preprint

This study investigates the hosting capacity of the Banshee Distribution Network by optimizing the real power injection at carefully selected Distributed Energy Resource (DER) locations. The analysis is conducted within the framework of power system operational constraints, including bus voltage ranges, thermal line ratings, and transformer loading limits. A Python-based Genetic Algorithm (GA), implemented using the PyGAD library, is employed to iteratively identify the optimal power injection configuration that maximizes network utilization while preserving system reliability. The methodology integrates a real-time simulation environment using the Real-Time Digital Simulator (RTDS), allowing high-fidelity evaluation of power flow and voltage behavior under each proposed injection scenario. By coupling the optimization algorithm with real-time simulation feedback, this approach ensures that both static and dynamic constraints are enforced during the evaluation process. The GA leverages evolutionary operators such as selection, crossover, and mutation to navigate the nonlinear search space efficiently. The results of the study delineate the feasible hosting capacity at three targeted buses, reflecting maximum real power levels that can be injected without causing voltage violations, transformer overloading, or line congestion. These findings provide a decision- support tool for distribution planners and utilities aiming to integrate higher penetrations of DERs in existing infrastructure. Additionally, the work lays the foundation for extending such optimization techniques to multi-objective formulations, including economic dispatch and reactive power coordination, in future studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Simultaneous ELM suppression and divertor detachment via synergistic boron powder and neon injection in EAST

A novel approach for simultaneous power exhaust and edge-localized mode (ELM) control is presented in the Experimental Advanced Superconducting Tokamak discharges, which utilize an ITER-like tungsten divertor. Real-time injection of boron (B) powder and neon (Ne) gas overcomes their limitations encountered when used separately. Pure Ne seeding leads to a narrow operational window constrained by core impurity accumulation and H-mode to L-mode back transitions, while pure solid B injection (SBI) is insufficient for effective divertor cooling. In comparison, their combined use achieves a stable, stationary, ELM-suppressed H-mode with adequate power exhaust. This synergistic scenario features partial energy detachment at the outer divertor while maintaining good plasma confinement (H 98 ∼ 1) with minimal degradation. Two key features of this scenario are: (1) the SBI triggers a persistent Edge Harmonic Mode (EHM), which provides a crucial continuous particle transport channel, preventing Ne and tungsten/molybdenum accumulation without flushing out by ELM, and (2) the B + Ne mixture allows for active optimization of the radiated power profile. Core radiation can be reduced by substituting a portion of the Ne with B, leveraging their complementary non-coronal equilibrium radiation efficiencies. This combined B + Ne injection scheme presents a promising pathway toward integrated core-edge scenarios, offering the potential to minimize total impurity throughput while leveraging an actuator (powder injection) already being considered for ITER.

Boron↗

Macromolecular Crystallization in Microfluidics for the International Space Station

At NASA's Marshall Space Flight Center, the Iterative Biological Crystallization (IBC) project has begun development on scientific hardware for macromolecular crystallization on the International Space Station (ISS). Currently ISS crystallization research is limited to solution recipes that were prepared on the ground prior to launch. The proposed hardware will conduct solution mixing and dispensing on board the ISS, be fully automated, and have imaging functions via remote commanding from the ground. Utilizing microfluidic technology, IBC will allow for on orbit iterations. The microfluidics LabChip(R) devices that have been developed, along with Caliper Technologies, will greatly benefit researchers by allowing for precise fluid handling of nano/pico liter sized volumes. IBC will maximize the amount of science return by utilizing the microfluidic approach and be a valuable tool to structural biologists investigating medically relevant projects.

Monaco, Lisa A.↗

Recent progress in shattered pellet injection technology in support of the ITER disruption mitigation system*

Shattered pellet injection (SPI) has been selected as the baseline technology for the disruption mitigation (DM) system for ITER. Typical SPI utilizes cryogenic cooling to desublimate low pressure (<100 mbar) gases onto a cold zone within a pipe gun barrel, forming a cylindrical pellet. Pellets are dislodged from the barrel and accelerated using either a gas driven mechanical punch or high-pressure light-gas delivered by a fast-opening valve. SPI technology developed at Oak Ridge National Laboratory is currently deployed and operational on DIII-D, JET, and KSTAR. These SPI systems are used in experiments for physics scaling to ITER thermal mitigation and runaway electron dissipation/avoidance. The pellet sizes used for these machines are in the range of 4 to 12.5 mm in diameter with length to diameter ratios (L/D) of ~1.5. The current plan for ITER SPI is to utilize pellets that are 28.5 mm in diameter with an L/D of ~2. Furthermore, the large pellet sizes, high steady-state magnetic fields, and limitations of operating in a radiation environment render much of the current technology unusable. In addition to technology improvements, a deeper understanding of pellet material properties, formation, and release is being developed for implementation in future SPI designs, specifically ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Efficient QAOA Optimization using Directed Restarts and Graph Lookup

Variational Quantum Algorithms (VQA) aim to enhance the capabilities of Noisy Intermediate-Scale Quantum (NISQ) devices. These algorithms utilize parameterized circuits and classical optimizers to iteratively execute circuits with varying parameters. However, VQA faces computational overheads due to repeated iterations and random restarts. Prior work suggests using basic sub-graphs to transfer parameters for the input graph, reducing optimizer overheads but limiting applicability to structured regular graphs. In real-world applications, random irregular graphs are common, and existing methods are not scalable or practical for such graphs. This paper presents a framework that aims to improve random irregular graphs in VQA. The framework uses graph similarity and important features like total edge counts, average edge counts, and variance. It follows an iterative process to choose basis sub-graphs from a small database and adjust parameters accordingly. Classical optimizers then utilize these parameters to determine when to restart and perform gradient descent. This approach increases the chances of reaching global maximum points.

Wang, Meng↗

Iterative Nonlinear Tikhonov Algorithm with Constraints for Electromagnetic Tomography

Low frequency electromagnetic tomography such as the capacitance tomography (ECT) has been proposed for monitoring and mass-gauging of gas-liquid two-phase system under microgravity condition in NASA's future long-term space missions. Due to the ill-posed inverse problem of ECT, images reconstructed using conventional linear algorithms often suffer from limitations such as low resolution and blurred edges. Hence, new efficient high resolution nonlinear imaging algorithms are needed for accurate two-phase imaging. The proposed Iterative Nonlinear Tikhonov Regularized Algorithm with Constraints (INTAC) is based on an efficient finite element method (FEM) forward model of quasi-static electromagnetic problem. It iteratively minimizes the discrepancy between FEM simulated and actual measured capacitances by adjusting the reconstructed image using the Tikhonov regularized method. More importantly, it enforces the known permittivity of two phases to the unknown pixels which exceed the reasonable range of permittivity in each iteration. This strategy does not only stabilize the converging process, but also produces sharper images. Simulations show that resolution improvement of over 2 times can be achieved by INTAC with respect to conventional approaches. Strategies to further improve spatial imaging resolution are suggested, as well as techniques to accelerate nonlinear forward model and thus increase the temporal resolution.

Xu, Feng↗

LoTToR: An Algorithm for Missing-Wedge Correction of the Low-Tilt Tomographic 3D Reconstruction of a Single-Molecule Structure

A single-molecule three-dimensional (3D) structure is essential for understanding the thermal vibrations and dynamics as well as the conformational changes during the chemical reaction of macromolecules. Individual-particle electron tomography (IPET) is an approach for obtaining a snap-shot 3D structure of an individual macromolecule particle by aligning the tilt series of electron tomographic (ET) images of a targeted particle through a focused iterative 3D reconstruction method. The method can reduce the influence on the 3D reconstruction from large-scale image distortion and deformation. Due to the mechanical tilt limitation, 3D reconstruction often contains missing-wedge artifacts, presented as elongation and an anisotropic resolution. Here, we report a post-processing method to correct the missing-wedge artifact. This low-tilt tomographic reconstruction (LoTToR) method contains a model-free iteration process under a set of constraints in real and reciprocal spaces. A proof of concept is conducted by using the LoTToR on a phantom, i.e., a simulated 3D reconstruction from a low-tilt series of images, including that within a tilt range of ±15°. The method is validated by using both negative-staining (NS) and cryo-electron tomography (cryo-ET) experimental data. A significantly reduced missing-wedge artifact verifies the capability of LoTToR, suggesting a new tool to support the future study of macromolecular dynamics, fluctuation and chemical activity from the viewpoint of single-molecule 3D structure determination.

97 MATHEMATICS AND COMPUTING↗

Diagnostics for Burning Plasmas

Here, recent progress in the design and manufacturing development of in-vessel diagnostic components by the U.S. ITER team is reported. Design and manufacturing choices are driven by engineering challenges stemming from ITER’s burning plasma mission, which entails levels of plasma neutron emission, pulse lengths, and size scales well beyond the existing database. Challenges include port access limitations, neutron irradiation and activation risks, nuclear heating of components, complex interfaces, remote handling compatibility, and constraints on component and processing materials. Responses to these challenges are presented using examples from the low field side reflectometer, toroidal interferometer polarimeter, and electron cyclotron emission diagnostics. Relevance of the experience from ITER diagnostics engineering to the design of future integrated fusion facilities based on burning plasmas is addressed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Exploiting the Local Parabolic Landscapes of Adversarial Losses to Accelerate Black-Box Adversarial Attack

Existing black-box adversarial attacks on image classifiers update the perturbation at each iteration from only a small number of queries of the loss function. Since the queries contain very limited information about the loss, black-box methods usually require much more queries than white-box methods. We propose to improve the query efficiency of black-box methods by exploiting the smoothness of the local loss landscape. However, many adversarial losses are not locally smooth with respect to pixel perturbations. To resolve this issue, our first contribution is to theoretically and experimentally justify that the adversarial losses of many standard and robust image classifiers behave like parabolas with respect to perturbations in the Fourier domain. Our second contribution is to exploit the parabolic landscape to build a quadratic approximation of the loss around the current state, and use this approximation to interpolate the loss value as well as update the perturbation without additional queries. Since the local region is already informed by the quadratic fitting, we use large perturbation steps to explore far areas. We demonstrate the efficiency of our method on MNIST, CIFAR-10 and ImageNet datasets for various standard and robust models, as well as on Google Cloud Vision. The experimental results show that exploiting the loss landscape can help significantly reduce the number of queries and increase the success rate. Our codes are available at https://github.com/HoangATran/BABIES.

Tran, Hoang↗

A Quantum-Classical Collaborative Training Architecture Based on Quantum State Fidelity

Recent advancements have highlighted the limitations of current quantum systems, particularly the restricted number of qubits available on near-term quantum devices. This constraint greatly inhibits the range of applications that can leverage quantum computers. Moreover, as the available qubits increase, the computational complexity grows exponentially, posing additional challenges. Consequently, there is an urgent need to use qubits efficiently and mitigate both present limitations and future complexities. To address this, existing quantum applications attempt to integrate classical and quantum systems in a hybrid framework. In this study, we concentrate on quantum deep learning and introduce a collaborative classical-quantum architecture called co-TenQu. The classical component employs a tensor network for compression and feature extraction, enabling higher-dimensional data to be encoded onto logical quantum circuits with limited qubits. On the quantum side, we propose a quantum-state-fidelity-based evaluation function to iteratively train the network through a feedback loop between the two sides. co-TenQu has been implemented and evaluated with both simulators and the IBM-Q platform. Compared to state-of-the-art approaches, co-TenQu enhances a classical deep neural network by up to 41.72% in a fair setting. Additionally, it outperforms other quantum-based methods by up to 1.9 times and achieves similar accuracy while utilizing 70.59% fewer qubits.

42 ENGINEERING↗

Coherent potential theory of a random binary alloy Effects of scattering from two-sites clusters and off-diagonal randomness

Extension of the single-site coherent potential approximation for random binary alloys to include the effect of off-diagonal randomness and pair scattering. This extension is achieved by analyzing a one-band model of a random binary alloy in terms of a two-sites coherent potential approximation. Numerical results are presented for a number of different alloys. In the overlapping-band case, the presence of off-diagonal randomness is shown to modify the bandwidths to values larger than those obtained from the virtual-crystal approximation. A simple iterative procedure is described for overcoming the convergence difficulties in the split-band case. In this limit, the inclusion of pair scattering and off-diagonal randomness is found to lead to the appearance of structure in the density of states of the minority component band.

Moorjani, K.↗

Program for analysis of nonlinear equilibrium and stability (PANES)

PANES utilizes improved techniques for analysis of structures with material and geometric nonlinearities, including limit point and bifurcations behavior which occurs in buckling and collapse problems. Incremental loading, Newton-Raphson iteration, and higher order methods are used in program.

Vos, R. G.↗