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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 145 records · Page 8
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DOE OSTI2024

Summer Bat Monitoring Report for Calendar Year 2023

Bats are mammals belonging to the order Chiroptera, which means “hand-wing.” They use a thin membrane of skin stretched between their fingers to fly. All bat species known in the state of Washington are insectivorous and each bat can consume 600-1,000 insects per hour while feeding. Bats typically give birth once per year to a single pup, making bat populations vulnerable to impacts and slow to recover. Several species of bats have been documented on the Hanford Site, with nine species identified during The Nature Conservancy surveys in 1997 and 1998, and an additional seven species listed as potentially present as documented in Biodiversity Inventory and Analysis of the Hanford Site. Final Report 1994-1999 (Soll et al., 1999). Ongoing U.S. Department of Energy (DOE), Richland Operations Office (RL) acoustic surveys, including HNF-53759, Summer Bat Monitoring Report for Calendar Year 2012, have also confirmed the presence of the same nine species documented by Soll et al. (1999). An additional species, the spotted bat (Euderma maculatum), was observed roosting on the exterior of a facility by Hanford Site personnel in 2021; the species was confirmed by Hanford Site biologists via photograph (Table 1-1).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Employing MACS/ViBRANT as a Surrogate MARVEL Reactor for Startup Reactivity Tuning and Supervisory Control Processes

Advanced nuclear reactors are a key part of the future of nuclear energy both in the United States and globally. They offer unique benefits for various energy-demanding applications, including use in remote locations, compact size, modular manufacturing, remote monitoring, low and/or variable power rating operation, and reliance on novel technologies to enhance operational safety. To achieve economic feasibility, advanced reactors must significantly reduce their workforces in comparison with the current fleet. Achieving this reduction will occur through reducing staff workloads using technology to achieve autonomous or semi-autonomous operations, demonstrated by comprehensive testing and validation activities. These operations will require both software and hardware platforms during the design and testing phases. While simulations are useful during the design phase, their performance can significantly deviate during actual deployment on hardware. This report presents the outcomes of a collaborative technical initiative between the U.S. Department of Energy (DOE) Microreactor Program (MRP) and Advanced Sensors and Instrumentation (ASI) Program. The collaboration utilized the Microreactor Automated Control System (MACS) hardware platform to bridge the gap between theoretical reactor design and actual startup and control operations. Two key use cases were investigated: facilitating the startup testing period and demonstrating supervisory control. The first use case details the key Microreactor Applications Research Validation and Evaluation (MARVEL) reactor startup physics testing activities conducted using the MACS platform. These activities included drum worth measurements, shutdown margin assessment, temperature feedback analysis, and scram time evaluation, as well as unique testing that would apply to the MARVEL reactor to demonstrate the testing methodologies in a low-risk environment. The MACS platform, serving as a surrogate representation of the MARVEL reactor, proved instrumental in performing these tests. The exercise revealed aspects that led to optimized processes, refined hardware design, and enhanced base software capabilities. By maturing methods and technologies in this manner, the initiative promises to reduce wasted time in the actual on-site reactor deployment effort, thereby saving significant time and resources. The second use case focuses on the development and implementation of supervisory control methods aimed at managing core tilt, which can result from asymmetrical operations or manufacturing imperfections in fuel rods or reactivity control devices. A key objective was to assess and compare the use of artificial intelligence (AI) for supervisory control. The effort aimed to define the role of supervisory control to enhance performance without risking control instability. This effort explored three distinct approaches: rules-based (RB) methods, optimization techniques, and reinforcement learning (RL) algorithms. Each approach was evaluated for its ease of implementation, its usability, and its effectiveness in responding to asymmetries in neutron flux. Comparative analysis of these approaches provided valuable insights into their applicability and effectiveness, offering a robust framework for advanced reactor operations. Together, these two use cases highlight the potential of hardware test beds to help streamline the design, operation, and control of advanced nuclear reactors. This collaborative effort underscores the importance of continued innovation and experimentation in achieving the next generation of safe, reliable, and economically viable nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Planetary Boundary-Layer Height (PBLHT) Value-Added Product: Remote-Sensing Retrievals

The planetary boundary layer (PBL) is fundamental to numerous atmospheric processes, including aerosol mixing and transport, cloud evolution, and precipitation formation. A critical parameter in these studies is the PBL height (PBLHT). This vertical depth is essential for characterizing PBL structures in numerical simulations and serves as a primary metric for estimating flux exchanges between the Earth’s surface and the atmosphere. Radiosonde (SONDE) observations provide high-vertical-resolution measurements of temperature and moisture profiles and are widely used to estimate PBLHT (Liu and Liang 2010, Seidel et al. 2010). The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s PBLHT value-added product (VAP) for radiosonde measurements, known as PBLHTSONDE, applies three commonly used methods—the Heffter (1980) method, the Liu and Liang (2010) method, and the bulk Richardson number approach (Seibert et al. 2000)—to derive PBLHT. The PBLHTSONDE VAP operates routinely at ARM observatories and mobile facilities, with data available from the ARM Data Center shortly after sounding observations are collected (Sivaraman et al. 2013). However, radiosonde observations are limited by their low temporal resolution. Most stations launch soundings only twice daily, which constrains the ability to investigate and characterize the temporal evolution of the PBL using radiosonde data alone. The use of continuous remote-sensing observations provides high temporal resolution of PBLHT estimates. These observations include aerosol lidars (Dang et al. 2019, Su et al. 2020), Doppler lidar (DL; Tucker et al. 2009, Krishnamurthy et al. 2021), and water vapor and/or temperature lidars and radiometers (Turner et al. 2014). These observations provide valuable data on the PBL’s thermodynamic properties (e.g., water vapor and/or temperature lidars and radiometers), dynamic properties (e.g., DL), and distribution of tracer substances (e.g., aerosol lidars), all of which can be used to estimate PBLHT. ARM developed PBLHT estimates from the micropulse lidar (MPL; PBLHTMPL), Doppler lidar (PBLHTDL), and combined Raman lidar (RL)/atmospheric emitted radiance interferometer (AERI) thermodynamic profiles (PBLHTTHERMO). Each estimate captures different physical characteristics of the boundary layer—aerosol tracers, vertical velocity turbulence, and thermodynamic structure—and exhibits distinct strengths and limitations depending on the PBL regime and time of day. In addition, the ARM ceilometer (CEIL) provides three potential PBLHT candidates derived from the vendor's built-in algorithm. Building on these individual retrievals, ARM developed the PBLHTBEML VAP, which combines the four remote-sensing-based estimates with ancillary meteorological variables using the machine learning approach of Zhang et al. (2025) to produce a best-estimate PBLHT at 10-minute resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Reinforcement Learning Control for Enhancing Marine Hydrokinetic Turbine Energy Generation

This paper proposes a reinforcement learning-based method to maximize power generation for a direct-drive marine hydrokinetic turbine. A high levelized cost of energy (LCOE) is preventative in the widespread adoption of many marine energy conversion technologies. A straightforward way to reduce LCOE is to increase conversion efficiency and ensure maximum energy generation. The proposed method utilizes a damping control methodology, varying applied generator torque via a linear relationship between the applied damping coefficient and rotor speed. A state-action-reward-state-action (SARSA) algorithm has been used to learn the optimal control action for a given flow velocity. The proposed SARSA methodology uses Gaussian radial basis functions to create a three-dimensional surface to estimate the relationship between damping coefficient, incoming flow velocity, and coefficient of power (C p ). Here, the SARSA algorithm was compared against a baseline optimal tip speed ratio controller over a year-long flow velocity case profile while considering the effects of biofouling on the turbine system, where the proposed RL method generated 0.92% more energy than the baseline.

Damp↗
DOE OSTI2025

Unconventional compute methods and future challenges for superconducting digital computing

Superconducting digital computing (SDC) based on Josephson junctions (JJs) offers significant potential for enhancing compute throughput and reducing energy consumption compared to conventional room-temperature CMOS-based approaches. Current superconducting logic families exhibit diverse characteristics in clocking strategies, power management, and information encoding techniques. This paper reviews recent advancements in unconventional computing methods specifically designed for superconducting digital circuits, emphasizing temporal computing and pulse-train representations. Notable techniques include race logic (RL), temporal pulse train computing (U-SFQ), and temporal multipliers, each offering unique performance and area advantages suited to superconducting implementations. Additionally, this paper reviews innovations in superconducting coarse-grain reconfigurable architectures (CGRA), superconducting-specific on-chip communication architectures, cryogenic sensor interfaces, and quantum computing control electronics. Finally, we highlight research challenges that should be addressed to facilitate the widespread adoption of superconducting digital computing.

EDA tools↗
DOE OSTI2025

ARM-IRL: Adaptive Resilience Metric Quantification Using Inverse Reinforcement Learning

The resilience of safety-critical systems is gaining importance due to the rise in cyber and physical threats, especially within critical infrastructure. Traditional static resilience metrics may not capture dynamic system states, leading to inaccurate assessments and ineffective responses to cyber threats. This work aims to develop a data-driven, adaptive method for resilience metric learning. We propose a data-driven approach using inverse reinforcement learning (IRL) to learn a single, adaptive resilience metric. The method infers a reward function from expert control actions. Unlike previous approaches using static weights or fuzzy logic, this work applies adversarial inverse reinforcement learning (AIRL), training a generator and discriminator in parallel to learn the reward structure and derive an optimal policy. The proposed approach is evaluated on multiple scenarios: optimal communication network rerouting, power distribution network reconfiguration, and cyber–physical restoration of critical loads using the IEEE 123-bus system. The adaptive, learned resilience metric enables faster critical load restoration in comparison to conventional RL approaches.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

Large language models (LLMs) are increasingly adapted to downstream tasks via reinforcement learning (RL) methods like Group Relative Policy Optimization (GRPO), which often require thousands of rollouts to learn new tasks. We argue that the interpretable nature of language often provides a much richer learning medium for LLMs, compared to policy gradients derived from sparse, scalar rewards. To test this, we introduce GEPA (Genetic-Pareto), a prompt optimizer that thoroughly incorporates natural language reflection to learn high-level rules from trial and error. Given any AI system containing one or more LLM prompts, GEPA samples trajectories (e.g., reasoning, tool calls, and tool outputs) and reflects on them in natural language to diagnose problems, propose and test prompt updates, and combine complementary lessons from the Pareto frontier of its own attempts. As a result of GEPA's design, it can often turn even just a few rollouts into a large quality gain. Across six tasks, GEPA outperforms GRPO by 6% on average and by up to 20%, while using up to 35x fewer rollouts. GEPA also outperforms the leading prompt optimizer, MIPROv2, by over 10% (e.g., +12% accuracy on AIME-2025), and demonstrates promising results as an inference-time search strategy for code optimization. We release our code at https://github.com/gepa-ai/gepa.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Best estimate of the planetary boundary layer height from multiple remote sensing measurements

Remote sensing measurements have been widely used to estimate the planetary boundary layer height (PBLHT). Each remote sensing approach offers unique strengths and faces different limitations. In this study, we use machine learning (ML) methods to produce a best-estimate PBLHT (PBLHT-BE-ML) by integrating four PBLHT estimates derived from remote sensing measurements at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) observatory. Three ML models – random forest (RF) classifier, RF regressor, and light gradient-boosting machine (LightGBM) – were trained on a dataset from 2017 to 2023 that included radiosonde, various remote sensing PBLHT estimates, and atmospheric meteorological conditions. Evaluations indicated that PBLHT-BE-ML from all three models improved alignment with the PBLHT derived from radiosonde data (PBLHT-SONDE), with LightGBM demonstrating the highest accuracy under both stable and unstable boundary layer conditions. Feature analysis revealed that the most influential input features at the SGP site were the PBLHT estimates derived from (a) potential temperature profiles retrieved using Raman lidar (RL) and atmospheric emitted radiance interferometer (AERI) measurements (PBLHT-THERMO), (b) vertical velocity variance profiles from Doppler lidar (PBLHT-DL), and (c) aerosol backscatter profiles from micropulse lidar (PBLHT-MPL). The trained models were then used to predict PBLHT-BE-ML at a temporal resolution of 10 min, effectively capturing the diurnal evolution of PBLHT and its significant seasonal variations, with the largest diurnal variation observed over summer at the SGP site. We applied these trained models to data from the ARM Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) field campaign (EPC), where the PBLHT-BE-ML, particularly with the LightGBM model, demonstrated improved accuracy against PBLHT-SONDE. Analyses of model performance at both the SGP and EPC sites suggest that expanding the training dataset to include various surface types, such as ocean and ice-covered areas, could further enhance ML model performance for PBLHT estimation across varied geographic regions.

Zhang, Damao [Pacific Northwest National Laborator↗
NASA NTRS1973

Low speed inducers for cryogenic upper stages

Briefing charts are presented, which were used in an oral presentation of the results and recommendations for the design and analysis of low speed hydrogen and oxygen inducers and their drive systems applicable to the space tug. A discussion of the design of the 15K and RL-10 inducers is included.

King, J. A.↗
NASA NTRS1974

Propulsion system tests on a full scale Centaur vehicle to investigate 3-burn mission capability of the D-lT configuration

Propulsion system tests were conducted on a full scale Centaur vehicle to investigate system capability of the proposed D-lT configuration for a three-burn mission. This particular mission profile requires that the engines be capable of restarting and firing for a final maneuver after a 5-1/2-hour coast to synchronous orbit. The thermal conditioning requirements of the engine and propellant feed system components for engine start under these conditions were investigated. Performance data were also obtained on the D-lT type computer controlled propellant tank pressurization system. The test results demonstrated that the RL-10 engines on the Centaur vehicle could be started and run reliably after being thermally conditioned to predicted engine start conditions for a one, two and three burn mission. Investigation of the thermal margins also indicated that engine starts could be accomplished at the maximum predicted component temperature conditions with prestart durations less than planned for flight.

Groesbeck, W. A.↗
NASA NTRS1974

Centaur feedline dynamics study using power spectral methods

Tests were conducted to determine the dynamic characteristics of the Centaur/RL-10 oxygen and hydrogen feedlines. The fundamental-mode resonant frequencies were determined by applying power spectral methods to noise-generated data from hot firings of the RL-10 engine. The effect of net positive suction pressure of the main feed pumps on resonant frequency characteristics was determined to be a straight-line relation. Power spectral methods were also used to determine the dynamic characteristics of the boost pumps.

Lorenzo, C. F.↗
NASA NTRS1974

The spectrum of cosmic electron with energies between 6 and 100 GeV

This experiment was carried out during three balloon flights which provided a total exposure of 3500 + or - 60 sq m sec sterad at an average depth of 4.8 g/sq cm The detector, in which the development of cascade showers in a 33.7 rl absorber was sampled by 10 scintillation counters and 216 Geiger-Muller tubes, was calibrated at the Cornell Electron Synchrotron, the separation of cosmic electrons from the nuclear background was confirmed by extensive analysis of data from the flights, from the calibration and from ground level exposure. The spectral intensity of primary cosmic ray electrons were found in particles/sq m sec sterad GeV. Similarly, the ground level spectrum of secondary cosmic ray electrons was also found. The steepness of the spectrum of cosmic electrons relative to that of nuclei implies one of the following conclusions: either the injection spectrum of electrons is steeper than that of nuclei, or the electron spectrum has been steepened by Compton/synchrotron losses in the energy range covered by the experiment.

Meegan, C. A.↗
NASA NTRS1978

Space transportation systems, 1980-2000

An overview of projected space transportation systems for the 1980-2000 period is presented. Methods for meeting the requirements in that area are documented through a description of the Space Shuttle and its current upper stages, reusable transfer vehicles, Shuttle uprating, fully reusable and single-stage transports, heavy lift vehicles, and advanced vehicles for orbital transfer and lunar landing. The structure of the liquid oxygen/liquid hydrogen boosters, cryogenic propellants, whose main propulsion system is a derivative of the RL-10 engine used in the Centaur launch, and mixed mode propulsion engine is also described, as is the flyback booster concept and such related issues as propellants and rocket engines, staging velocity, configuration shape, and whether it should be manned or unmanned. Especially noted are proposed propulsion systems going beyond the present Shuttle such as the nuclear and electric propulsion concepts, the resistojet, using liquid hydrogen, ion thruster, using argon, magnetoplasmadynamic thrusters, solar thermal rocket, and solar sail concept where the basic idea is to use a 'sail' of thin reflective material to generate a net force by reflection of solar radiation.

Cohan, C. J.↗
NASA NTRS1980

Orbit transfer vehicle engine study. Volume 1: Executive summary

The orbit transfer vehicle (OTV) engine study provided parametric performance, engine programmatic, and cost data on the complete propulative spectrum that is available for a variety of high energy, space maneuvering missions. Candidate OTV engines from the near term RL 10 engine to advanced high performance expander engines were examined.

Source record↗
NASA NTRS1980

Transient solution for megajoule energy release in a lumped-parameter series RLC circuit

A method is developed for optimizing the energy release from a megajoule capacitive discharge in a series RLC circuit with an RL load. Both the resistance and inductance of the load are represented by effective values that characterize their behavior during the discharge. Using Kirchhoff's laws, equations utilizing the load impedance and the external circuit impedance are derived for determining the instantaneous load voltage and energy characteristics. A program (ERES) computes and displays the load characteristics and the circuit current. Use of the ERES program allows a designer to perturbate values of the circuit elements in order to produce the desired time distribution for the load energy input.

Barnes, G.↗