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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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Future long duration exploration missions will require astronauts to work and behave more autonomously. Over the last several years, we have been investigating how integrating sensors into an astronaut’s environment enables crew autonomy. This paper describes the prototypes we have deployed in Earth analogs investigating the concept of the Internet of “Space” Things.
In the advanced reactor domain, a flexible and scalable software/hardware infrastructure is crucial for integrating and validating various control technologies. This study used the Microreactor Automated Control System (MACS) hardware platform as a testbed. MACS was originally designed to mirror Idaho National Laboratory (INL)'s Microreactor Applications Research Validation and Evaluation (MARVEL), a 85-kW thermal fission microreactor. It features control drums for simulated reactivity control; lights that function as a surrogate reactor core, with the brightness being proportional to the reactor power; and light sensors that emulate neutron detectors. To transform MACS into a physical twin of MARVEL for evaluating control methods, the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software was employed. This software integrated the hardware with two models of the MARVEL core, based on Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The study aimed to demonstrate the gap between control theory and actual practice—a gap that often necessitates empirical adjustments such as control gain retuning, filters, time discretization, and integrator anti-windup measures. Controllers were developed based on increasingly complex simulations without hardware, starting from the base MARVEL model and then introducing actuator saturation constraints and sensor noise. The final control strategy was then tested using MACS, and a comparative performance analysis was conducted.
Interface stabilization is critical to the development of working all‐solid‐state batteries. Rigid cathode/solid electrolyte interfaces often disintegrate due to anisotropic volume change of cathode‐active materials, resulting in irreversible capacity loss. Herein, we demonstrate that Li 1.211 Mo 0.467 Cr 0.3 O 2 (LMCO), a pioneering cation‐disordered rocksalt oxide (DRX) cathode that has intrinsically small volume change upon lithium intercalation, can be integrated with a thiophosphate‐based solid electrolyte for all‐solid‐state batteries. Interface stability of the all‐solid LMCO cell was investigated by electrochemical impedance spectroscopy, X‐ray micro‐computed tomography, and electron microscopy. Since LMCO was initially synthesized as a layered phase exhibiting a large volume change, interface disintegration can be observable in the early cycles. As layered LMCO phase‐transformed into DRX LMCO in subsequent cycles, reintegration of the interfaces occurs within a pressurized cell as a result of its zero‐stain behavior. Consequently, the DRX LMCO cathode maintains interface integrity, and thus electrical wiring, over an extended number of cycles, leading to improved capacity retention with small internal cell resistance.
Accurate outage location is essential for expediting post-outage power restoration, minimizing outage duration, and enhancing the resilience of distribution networks. With the advent of advanced metering infrastructure, data-driven outage location methods have significantly advanced beyond traditional approaches that rely on manual inspections. However, existing methods still face critical challenges, like reliance on single-source data, limited ability to handle partially observable systems or difficulties with loop networks. To the best of our knowledge, no single approach has comprehensively addressed all of these challenges at once. To this end, this paper proposes a comprehensive multisource data fusion framework for outage locations via probabilistic graph networks. The framework consists of three key phases. First, a novel method for reconstituting distribution networks with loops is developed, transforming looped networks into multiple radial subnetworks that retain all outage causalities of the original network. Second, Bayesian network (BN) models are established for each subnetwork, integrating multiple data sources and network structures. Finally, a joint Gibbs sampling mechanism, featuring forward and backward information flow, is designed to merge data from separate BN models and maximize the utilization of limited evidence, ensuring accurate outage location identification. In conclusion, the framework was validated on two modified public test systems, and comparative studies confirmed its effectiveness.
Over the years, the solid rocket motor community has made increasing use of composite materials for thermal and structural applications. This is particularly true of solid rocket nozzles, which have used carbon phenolic and, increasingly, carbon-carbon materials to provide structural integrity and thermal protection at the high temperatures encountered during motor burn. To evaluate the degree of structural performance of nozzles and their materials and to verify analysis models, many subscale and full-scale tests are run. These provide engineers with valuable data needed to optimize design and to analyze nozzle hardware. Included among these data are strains, pressures, thrust, temperatures, and displacements. Recent nozzle test hardware has made increasing use of strain gauges embedded in the carbon composite material to measure internal strains. In order to evaluate strength, these data must be transformed into strains along the fiber directions. The fiber-direction stresses can then be calculated. A computer program written to help engineers correctly manipulate the strain data into a form that can be used to evaluate structural integrity of the nozzle is examined.
A search for the violation of the charge-parity (CP) symmetry in the production of top quarks in association with Z bosons is presented, using events with at least three charged leptons and additional jets. The search is performed in a sample of proton-proton collision data collected by the CMS experiment at the CERN LHC in 2016–2018 at a center-of-mass energy of 13 TeV and in 2022 at 13.6 TeV, corresponding to a total integrated luminosity of 173 fb –1 . For the first time in this final state, observables that are odd under the CP transformation are employed. Also for the first time, physics-informed machine-learning techniques are used to construct these observables. While for standard model (SM) processes the distributions of these observables are predicted to be symmetric around zero, CP-violating modifications of the SM would introduce asymmetries. Two CP-odd operators $\mathcal{O}$$^{I}_{tW}$ and $\mathcal{O}$$^{I}_{tZ}$ in the SM effective field theory are considered that may modify the interactions between top quarks and electroweak bosons. The obtained results are consistent with the SM prediction within two standard deviations, and exclusion limits on the associated Wilson coefficients of –2.7 < $c$$^{I}_{tW}$ < 2.5 and –0.2 < $c$$^{I}_{tZ}$ < 2.0 and are set at 95 % confidence level. The largest discrepancy is observed in $c$$^{I}_{tZ}$ where data is consistent with positive values, with an observed local significance with respect to the SM hypothesis of 2.5 standard deviations, when only linear terms are considered.
The inherent complexity of boundary plasma, characterized by multi-scale and multi-physics challenges, has historically restricted high-fidelity simulations to scientific research due to their intensive computational demands. Consequently, routine applications such as discharge control and scenario development have relied on faster but less accurate empirical methods. This work introduces DivControlNN, a novel machine-learning-based surrogate model designed to address these limitations by enabling quasi-real-time predictions (i.e., ~ 0.2 ms) of boundary and divertor plasma behavior. Trained on over 70,000 2D UEDGE simulations from KSTAR tokamak equilibria, DivControlNN employs latent space mapping to efficiently represent complex divertor plasma states, achieving a computational speed-up of over 10 8 compared to traditional simulations while maintaining a relative error below 20% for key plasma property predictions. During the 2024 KSTAR experimental campaign, a prototype detachment control system powered by DivControlNN successfully demonstrated detachment control on its first attempt, even for a new tungsten divertor configuration and without any fine-tuning. These results highlight the transformative potential of DivControlNN in overcoming diagnostic challenges in future fusion reactors by providing fast, robust, and reliable predictions for advanced integrated control systems.
In this paper, we introduce Surf-Deformer, a code deformation framework that seamlessly integrates adaptive defect mitigation functionality into the current surface code workflow. It crafts several basic deformation instructions based on fundamental gauge transformations, which can be combined to explore a larger design space than previous methods. This enables more optimized deformation processes tailored to specific defect situations, restoring the QEC capability of deformed codes more efficiently with minimal qubit resources. Additionally, we design an adaptive code layout that accommodates our defect mitigation strategy while ensuring efficient execution of logical operations. Our evaluation shows that Surf-Deformer outperforms previous methods by significantly reducing the end-to-end failure rate of various quantum programs by 35× to 70×, while requiring only about 50% of the qubit resources compared to the previous method to achieve the same level of failure rate. Ablation studies show that Surf-Deformer surpasses previous defect removal methods in preserving QEC capability and facilitates surface code communication by achieving nearly optimal throughput.
SF-26-025 WFSuite is a graphical and command-line toolkit for coded-mask-based X-ray wavefront sensing and phase reconstruction at synchrotron beamlines. It integrates analysis tools for both relative and absolute speckle-based measurements. In the relative metrology module, WFSuite implements Wavelet-transform-based X-ray Speckle Tracking (WXST) and Wavelet-transform-based Speckle Vector Tracking (WSVT) methods to retrieve differential phase and wavefront distortions by comparing speckle patterns recorded with and without the test sample. In the absolute phase module, WFSuite uses coded-mask speckle patterns and replaces the measured reference with a numerically simulated one, enablingsingle-shot wavefront reconstruction using either WXST or a neural-network-based method (SPINNet).
In this study, we reassess the dynamics within a simple accelerator lattice featuring a single degree of freedom and incorporating a sextupole magnet. In the initial segment, we revisit the H\'enon quadratic map, a representation of a general transformation with quadratic nonlinearity. In the subsequent section, we unveil that a conventional sextupole is essentially a composite structure, comprising an integrable McMillan sextupole and octupole, along with non-integrable corrections of higher orders. This fresh perspective sheds light on the fundamental nature of the sextupole magnet, providing a more nuanced understanding of its far-from-trivial chaotic dynamics. Importantly, it enables the description of driving terms of the second and third orders and introduces associated nonlinear Courant-Snyder invariant.
This report is part of a broader program focused on supporting Indian states with long-term power system planning. More information about this program can be found at the National Renewable Energy Laboratory's "Supporting India's States With Renewable Energy Integration" web page at https://www.nrel.gov/international/india-renewable-energy-integration.html. The power sector in Uttar Pradesh, India's most populous state, is poised to transform over the next few decades due to a combination of national and state-level policies impacting both the supply and demand of electricity. The Government of Uttar Pradesh has policies and plans to develop in-state solar PV, pumped storage hydropower, and green hydrogen. Power system policymakers and utilities in Uttar Pradesh are faced with the challenges of planning a system that incorporates increasing amounts of renewable energy and storage resources, meets rising electricity demand due to economic development and green hydrogen production, and satisfies operational and reliability requirements. To support these various objectives, the National Renewable Energy Laboratory (NREL), RMI, and the Uttar Pradesh New and Renewable Energy Development Agency (UPNEDA) evaluated the least-cost pathways for the state's power sector through 2050. NREL developed a capacity expansion model that identifies investment and operational decisions for every year (2024-2050) for all of India, with detailed representation for the state of Uttar Pradesh, which can provide a framework for recurring planning studies. The main insights from this study can also help inform policy development and investment decisions.
In this study, we reassess the dynamics within a simple accelerator lattice featuring a single degree of freedom and incorporating a sextupole magnet. In the initial segment, we revisit the H\'enon quadratic map, a representation of a general transformation with quadratic nonlinearity. In the subsequent section, we unveil that a conventional sextupole is essentially a composite structure, comprising an integrable McMillan sextupole and octupole, along with non-integrable corrections of higher orders. This fresh perspective sheds light on the fundamental nature of the sextupole magnet, providing a more nuanced understanding of its far-from-trivial chaotic dynamics. Importantly, it enables the description of driving terms of the second and third orders and introduces associated nonlinear Courant-Snyder invariant.
This slide deck is part of a broader program focused on supporting Indian states with long-term power system planning. More information about this program can be found at the National Renewable Energy Laboratory's "Supporting India's States With Renewable Energy Integration" web page at https://www.nrel.gov/international/india-renewable-energy-integration.html. The power sector in Uttar Pradesh, India's most populous state, is poised to transform over the next few decades due to a combination of national and state-level policies impacting both the supply and demand of electricity. The Government of Uttar Pradesh has policies and plans to develop in-state solar PV, pumped storage hydropower, and green hydrogen. Power system policymakers and utilities in Uttar Pradesh are faced with the challenges of planning a system that incorporates increasing amounts of renewable energy and storage resources, meets rising electricity demand due to economic development and green hydrogen production, and satisfies operational and reliability requirements. To support these various objectives, the National Renewable Energy Laboratory (NREL), RMI, and the Uttar Pradesh New and Renewable Energy Development Agency (UPNEDA) evaluated the least-cost pathways for the state's power sector through 2050. NREL developed a capacity expansion model that identifies investment and operational decisions for every year (2024-2050) for all of India, with detailed representation for the state of Uttar Pradesh, which can provide a framework for recurring planning studies. The purpose of this slide deck is to supplement the main study (published in May 2024) with additional modeling scenarios to explore hydrogen flexibility.
Photoenzymatic catalysis enables new-to-nature transformations, but its scalability is limited by high enzyme loading, costly cofactors, and radical-induced instability. Here we report the integration of light-driven photoenzymatic reactions into the cellular metabolism of Escherichia coli, bridging flavin-based photobiocatalysis with biosynthesis. Using synthetic biology strategies, we engineered microbial cells to continuously produce olefin substrates and ene-reductase photoenzyme while regenerating cofactors directly from glucose. By externally supplying radical precursors or by introducing synthetic pathways for their in situ production, we enabled fermentation-based microbial photobiosynthesis, achieving high titers and demonstrating its feasibility for scale-up in bioreactor. This approach extends photobiocatalysis from in vitro applications to in vivo semi-biosynthesis and complete biosynthesis, revealing its full potential for integrating light-driven reactions into cellular metabolism.
Effects of noise through analog integrator which integrates with respect to arbitrary variable
An inertial navigation system utilizing a servo-controlled two degree of freedom pendulum to obtain specific force components in the locally level coordinate system is described. The pendulum includes a leveling gyroscope and an azimuth gyroscope supported on a two gimbal system. The specific force components in the locally level coordinate system are converted to components in the geographical coordinate system by means of a single Euler transformation. The standard navigation equations are solved to determine longitudinal and lateral velocities. Finally, vehicle position is determined by a further integration.
Fault tolerance in future processing and switching communication satellites is addressed by showing new methods for detecting hardware failures in the first major subsystem, the multichannel demultiplexer. An efficient method for demultiplexing frequency slotted channels uses multirate filter banks which contain fast Fourier transform processing. All numerical processing is performed at a lower rate commensurate with the small bandwidth of each bandbase channel. The integrity of the demultiplexing operations is protected by using real number convolutional codes to compute comparable parity values which detect errors at the data sample level. High rate, systematic convolutional codes produce parity values at a much reduced rate, and protection is achieved by generating parity values in two ways and comparing them. Parity values corresponding to each output channel are generated in parallel by a subsystem, operating even slower and in parallel with the demultiplexer that is virtually identical to the original structure. These parity calculations may be time shared with the same processing resources because they are so similar.
The continuous-time regularization scheme for defining phase-space path integrals is briefly reviewed as a method to define a quantization procedure that is completely covariant under all smooth canonical coordinate transformations. As an illustration of this method, a limited set of transformations is discussed that have an image in the set of the usual squeezed states. It is noteworthy that even this limited set of transformations offers new possibilities for stationary phase approximations to quantum mechanical propagators.