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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗
DOE OSTI2026

Single-Phase to Split-Phase Inverters with Advanced Grid Support Functions for Grid-Interactive Applications

This work presents a cost-effective single-phase to split-phase inverter with a reduced switch count, achieving grid interactive performance while maintaining operational efficiency. The proposed system integrates an Andronov-Hopf oscillator based secondary controller, which inherently embeds a nonlinear resistive droop architecture, ensuring rapid dynamic response. A Lyapunov energy function-based primary control enhances transient stability and regulation, while an internal model-based point of common coupling voltage estimation enables cost optimization without additional sensors. Equipped with advanced grid support functionalities, the inverter facilitates seamless distribution system operation with enhanced robustness. The effectiveness of the proposed architecture and control strategy is validated through MATLAB/Simulink and PLECS simulations, demonstrating its feasibility for high-performance grid-supportive applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1983

Advanced LOX/H sub 2 engine technologies for future OTVs

The optimization methods and trade studies which were used to define a 1980 state-of-the-art design of orbital transfer vehicles are summarized. The advanced thrust chamber, turbomachinery, and engine power cycle technologies recommended for development and verification during the 1980's are discussed. The state-of-the-art design serves as one of the reference points for evaluation of the advanced technology concepts. A second reference point is provided by the 1960 state-of-the-art RL-10 engine. Advanced heat energy extraction concepts in the combustor and injector are presented that will permit the high chamber pressures expected of the advanced expander cycle engine concept. Advanced turbomachinery concepts are selected that will help utilize efficiently the heat energy extracted in the thrust chamber and aid in uprating chamber pressures to values five times those realized with 1960 to 1980 technologies. The higher chamber pressure benefits are maximized with nozzle concepts that will package within a short retracted length and extend to the very high expansion area ratios required for specific impulse values significantly higher than those now realized by operational systems. Control system component concepts studied will allow utilization of the high turbine drive energy levels in a reliable repeatable manner that will reduce program risk and enhance overall space transportation system mission life cycle cost.

Glass, J.↗
DOE OSTI2025

Scaling Ultrahigh-Resolution E3SM Land Model for Leadership-Class Supercomputers

This paper presents advancements in scaling the ultrahigh-resolution E3SM Land Model (uELM) for deployment on leadership-class supercomputers, addressing the increased demand for km-scale Earth system modeling. By focusing on km-scale ELM simulations, we enhance predictive capabilities for climate interactions, facilitating improved responses to climate change impacts on energy systems, agriculture, and water resources. Our approach leverages innovative software architecture optimizations, sophisticated data handling techniques, and advanced parallel processing, achieving strong scalability on two leadership supercomputers (2400 nodes (105,600 cores) on Summit, and 1200 nodes (76,800 cores) on Frontier). Results from extensive scalability assessments on the Summit and Frontier also demonstrate outstanding I/O performance (close to 400 GB/s write throughput) and the model's ability to efficiently handle increasing computational demands. This study not only establishes uELM's capability for high-resolution simulations over vast geographical domains, but also sets a foundation for future Earth system modeling breakthroughs.

Wang, Dali [ORNL] (ORCID:0000000168065108)↗
DOE OSTI2024

SEAS Communication Engine: An Extensible, Flexible Wrapper for Co-Simulation Agents

When modeling and analyzing the power grid and other large scale systems, researchers often express scenarios as optimization problems and feed them into advanced software solvers. In order to allow multiple solvers to communicate with each other and share data from different domains, the National Renewable Energy Laboratory (NREL) and associated Department of Energy (DOE) labs have developed a software framework called the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS). HELICS allows cosimulation via a collection of client libraries for different languages that can be called from the appropriate optimization software. However, these client libraries do not provide a higher level of abstraction beyond reading and writing data off of the shared HELICS bus. In this paper, we describe a new software library called the SEAS Communication Engine that exposes a higher-level API for running cosimulation problems. The SEAS Engine provides a class-based abstraction on top of the Python HELICS client, in order to allow users to implement their domain-specific cosimulations without needing to interact with core HELICS primitives. This will make adoption of HELICS and cosimulation in general easier, by exposing a simpler API. In the second part of the paper, we validate our library on a collection of different simulation examples, including the canonical IEEE 13 Bus Feeder. Lastly, we demonstrate using the SEAS Engine to directly call domain-specific code written in the Julia programming language. Our hope is that this will serve as a template for easily calling software in different programming languages via the SEAS Engine, thereby avoiding code duplication and complexity.

co-simulation↗
DOE OSTI2024

HERO WEC V1: Design and Experimental Data Collection Efforts

The Hydraulic and Electric Reverse Osmosis Wave Energy Converter (HERO WEC) is a research platform aimed at developing a modular, small-scale wave-powered desalination system for remote and disaster-response applications. Funded by the Department of Energy (DOE)'s Water Power Technologies Office (WPTO), the project aims to advance wave-powered desalination by developing and testing a small-scale, modular wave energy converter (WEC). The insights gained from this project will help guide the design and development of larger-scale wave energy devices as well as the integration of marine energy and reverse osmosis (RO) desalination. The HERO WEC was initially developed to derisk the Waves to Water prize, enabling the staff to practice WEC deployment and recovery, while optimizing installation protocols ologies, aiming to advance the broader fields of marine energy and water treatment.

13 HYDRO ENERGY↗
DOE OSTI2025

Analog Systems for Edge Optimization

Over the past decade, analog computing has the subject of substantial research interest providing a path toward improved computational efficiency in the post-Dennard era. Analog matrix vector multiplication (MVM) accelerators provide a popular approach given the ubiquity of MVM operations in numerous applications. However, historically analog computing systems can struggle with applications requiring high precision due to the inherent susceptibility of these systems to analog non-idealities. Therefore, prior work on analog systems has focused either on applications known to be tolerant of limited precision (e.g., neural network inference), or using expensive techniques to emulate high-precision using many analog MVM operations. In this work, we propose an alternative approach. Motivated by recent advances in inexact nonlinear solvers and optimizers, we explore the potential of co-designing optimization algorithms which can take full advantage of the fundamentally inexact analog MVM operations. To enable these co-designed algorithms we also develop a general mathematical theory of the precision and energy efficiency of analog operations, and a new system architecture for tightly-coupled analog and digital computation. Finally, we examine the applicability of analog computing to a wider class of symmetric positive definite systems and find potential in using analog operations as a sparse approximate inverse preconditioner. With these core innovations, this project provides a path toward effectively implementing optimization algorithms on power-constrained autonomous and semi-autonomous systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

A large scale software system for simulation and design optimization of mechanical systems

The concept of an advanced integrated, networked simulation and design system is outlined. Such an advanced system can be developed utilizing existing codes without compromising the integrity and functionality of the system. An example has been used to demonstrate the applicability of the concept of the integrated system outlined here. The development of an integrated system can be done incrementally. Initial capabilities can be developed and implemented without having a detailed design of the global system. Only a conceptual global system must exist. For a fully integrated, user friendly design system, further research is needed in the areas of engineering data bases, distributed data bases, and advanced user interface design.

Dopker, Bernhard↗
DOE OSTI2025

Understanding the Active Site Structures and Achieving Catalytic Activity Tuning of Atomically Dispersed FeN 4 Sites for Oxygen Reduction Reaction

Atomically dispersed Fe–—N—C catalysts with high oxygen reduction reaction (ORR) activity have attracted great attention since the last decade. Due to comparable ORR activity and low material cost, they are promising platinum group metal (PGM)-free catalysts that can replace the commercialized Pt/C materials; furthermore, it can facilitate the efficiency of the fuel cell technologies and mitigate dependence on fossil fuels. Great advancements have been made to experimentally optimize the synthesis approach of the Fe–—N—C catalysts, enhance the ORR activity, and improve the catalyst stability. Similarly, recent theoretical studies also provide enriched understanding of the active site structures, properties, and reaction mechanisms. In this review, discussions are made upon utilizing combined experimental and computational spectroscopy to reveal the active site structures, employing mechanistic studies to investigate reaction thermodynamics and kinetics, as well as developing scaling relationships to assist the design and development of future PGM-free catalyst materials. Furthermore, recent advances in studying Fe–—N—C catalysts utilizing electrified surface models and explicit solvation models are also discussed. Not only can these aspects improve the accuracy of theoretical simulation and predictions but also deepen the understanding of the catalyst properties and reaction mechanisms under the effect of surface charges and solvent molecules.

Fe single-atom catalysts↗
DOE OSTI2025

Multi-physics Topology OPtimization and Additive Manufacturing for High-temperature Heat Exchangers

This research significantly advances the understanding of high-temperature heat exchanger design through an integrated approach that combines topology optimization (TO), triply periodic minimal surface (TPMS) structures, additive manufacturing (AM) and thermohydraulic testing. Each of these components contributes uniquely to a unified, high-performance design, fabrication and testing workflow. Topology optimization serves as the foundation of the design methodology by providing a systematic way to determine the most effective material layout for separating hot and cold fluids while maximizing thermal performance. The researchers introduced a novel three-material optimization framework using two density fields to represent hot fluid, cold fluid, and solid domains. This approach enables automated discovery of optimal shapes and flow paths that cannot be intuitively designed, especially under constraints imposed by manufacturing technologies. Furthermore, constraints such as minimal wall thickness and overhang angles were embedded into the optimization process, ensuring that resulting designs are not only thermally efficient but also manufacturable using modern additive techniques. In parallel, the study delves into the use of Gyroid-based TPMS geometries for constructing the core of the heat exchanger. TPMS structures are known for their high surface area, excellent fluid mixing capabilities, and minimal pressure drop characteristics. The researchers applied a data-driven modeling framework using Heteroscedastic Sparse Gaussian Process Regression (HSGPR) combined with genetic algorithms. This allowed for the rapid evaluation and optimization of key geometric parameters such as frequency, iso-value, and phase shift. The result was a set of Gyroid structures tailored for high heat transfer and low flow resistance, demonstrating clear improvements over conventional straight-channel designs. After the designing process, additive manufacturing played a critical role by turning these highly complex, optimized geometries into physical components. Utilizing Laser Powder Bed Fusion (LPBF) with Haynes 282, the study demonstrated the feasibility of fabricating these heat exchangers at high precision. Post-processing methods, including dilation-erosion operations, were applied to ensure local features adhered to self-supporting constraints. The fabricated structures were then subjected to thermohydraulic testing under conditions representative of supercritical CO 2 Brayton cycles, validating the predicted performance and confirming the viability of the full design-to-fabrication pipeline. Finally, thermohydraulic testing across the above studies served as a crucial experimental validation of advanced heat exchanger. Under consistent high-temperature and high-pressure conditions using supercritical CO 2 , the testing demonstrated that both TO and Gyroid-based TPMS designs significantly outperformed conventional straight-channel HXs. The TO design achieved a 115% increase in UA and NTU and a 27.6% boost in gravimetric power density, while the data-driven optimized Gyroid design delivered a 166% increase in UA and NTU and improved effectiveness from 68.7% to 86.1%. These results validate the simulation models, confirm the manufacturability of complex geometries under AM constraints, and provide key insights into design-performance trade-offs, thereby advancing the development of high-efficiency, compact heat exchangers for extreme environments.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Research in Structures and Dynamics, 1984

A symposium on advanced and trends in structures and dynamics was held to communicate new insights into physical behavior and to identify trends in the solution procedures for structures and dynamics problems. Pertinent areas of concern were (1) multiprocessors, parallel computation, and database management systems, (2) advances in finite element technology, (3) interactive computing and optimization, (4) mechanics of materials, (5) structural stability, (6) dynamic response of structures, and (7) advanced computer applications.

Robert J Hayduk↗
NASA NTRS1999

The Effects of Gravity on Combustion and Structure Formation During Synthesis of Advanced Materials

Combustion in a variety of heterogeneous systems, leading to the synthesis of advanced materials, is characterized by high temperatures (2000-3500 K) and heating rates (up to 10(exp 6) K/s) at and ahead of the reaction front. These high temperatures generate liquids and gases which are subject to gravity-driven flow. The removal of such gravitational effects is likely to provide increased control of the reaction front, with a consequent improvement in control of the microstructure of the synthesized products. Thus, microgravity experiments can lead to major advances in the understanding of fundamental aspects of combustion and structure formation under the extreme conditions of the combustion synthesis wave. In addition, the specific features of microgravity environment allow one to produce unique materials, which cannot be obtained under terrestrial conditions. The general goals of the current research are: 1) to improve the understanding of fundamental phenomena taking place during combustion of heterogeneous systems, 2) to use low-gravity experiments for insight into the physics and chemistry of materials synthesis processes, and 3) based on the obtained knowledge, to optimize processing conditions for synthesis of advanced materials with desired microstructures and properties. This research follows logically from the results of investigations we have conducted in the framework of our previous grant on gravity influence on combustion synthesis (CS) of gasless systems. Prior work, by others and by us, has clearly demonstrated that gravity plays an important role during combustion synthesis of materials. The immediate tasks for the future are to quantitatively identify the nature of observed effects, and to create accurate local kinetic models of the processes, which can lead to a control of the microstructure and properties of the synthesized materials. In summary, this is the value of the proposed research. Based on our prior work, we focus on the fundamental aspects of combustion and structure formation under the unique condition of microgravity.

Varma, A.↗
NASA NTRS1988

Application of structural tailoring to spar/shell turboprops

The problem of designing a swept advanced turboprop (ATP) blade for minimum noise output is discussed. Optimal sweep distributions are found using the computer code STAT (Structural Tailoring of Advanced Turboprops). The initial designs are unswept. The blade designs have minimum noise output while satisfying other blade design requirements. The STAT program and the modifications required during this work are described. Parameter studies of the effect of sweep on noise output are also presented.

Rubinstein, Robert↗
NASA NTRS2026

Mathematical Model of a Regenerative Fuel Cell for System Optimization

This thesis developed a system-level optimization model of a regenerative fuel cell (RFC) system for long-duration, off-world energy storage applications. Prior RFC design studies have typically been limited to reduced parameter sets and simplified constraints due to computational limitations relative to the number of relevant degrees of freedom. As a result, important nonlinear interactions between subsystems have not been fully captured. This work began to address that gap by developing a higher-fidelity, nonlinear optimization framework that incorporates a broader set of design variables and coupled constraints, enabling a multidimensional model that captures the coupled behavior of RFC subsystems and demonstrates the feasibility of applying optimization to such systems. An expanded system-level optimization approach was established that captures interactions between electrochemical performance, structural requirements, and storage design. This enabled a more comprehensive evaluation of trade-offs than conventional formulations. The model integrates four coupled subsystems: a fuel cell, an electrolyzer, reactant gas, and high-pressure storage tanks, and was formulated to accommodate a wide range of mission parameters, including operational time and required output power. It incorporates constraints on available solar array power, reactant mass balance between production and consumption, and pressure-dependent storage requirements. To enable reliable convergence, the optimization problem was reformulated to reduce dimensionality and improve numerical stability, with subsystem models organized for efficient evaluation. Problem dimensionality was reduced by consolidating lower-level design variables into higher-level representative quantities, and subsystem behavior was evaluated within the optimization loop. A multi-start initialization strategy was employed to mitigate sensitivity to local minima and improve solution quality, while nonlinear relationships were solved using robust numerical methods. The results showed that convergence was achieved across a range of required output power values. Specific energy reached a maximum at a critical mission power level, where the electrolyzer power matched the available solar input and operated near its voltage and current density limits. Beyond this point, further increases in required power resulted in less mass-efficient operation, increasing total system mass and reducing overall performance. The developed model represents an advancement in RFC system-level optimization by enabling analysis of a broader and more tightly coupled design space than previous considerations. While convergence behavior and computational cost remain challenges, the methods introduced improve solvability and allow inclusion of additional design variables with minimal loss of physical fidelity. However, the numerical results should not be interpreted as definitive design recommendations, as the model includes simplifying assumptions and omits several higher-order effects. Future work should extend this framework by incorporating additional subsystems and loss mechanisms, such as thermal management, parasitic power consumption, and reactant losses, to improve fidelity and ensure more representative design conclusions.

Electrochemistry↗
DOE OSTI2025

Optimization of direct air capture processes using reactive transport models of adsorption-desorption cycles

In this study, we develop and implement a reactive transport model in COMSOL Multiphysics® to address the challenges of direct air carbon capture. The model is validated against experimental data and used to simulate the cyclic steady state of the adsorption-desorption process. The optimization of this model is achieved through advanced trust-region methods integrated with Gaussian Processes. Key decision variables, including adsorption and desorption times, desorption temperature and pressure, input velocity, bed porosity, column length, and radius were optimized to minimize the capture cost. After optimization, a sensitivity analysis revealed the complex interplay between the decision variables and their effect on the specific energy and cost of removing the CO 2 . We optimized the capture cost while taking into account the trade-off between energy consumption and productivity. The resulting minimum capture cost was determined to be 265.2 $/t-CO 2 , which aligns with expected values reported in the literature. Numerical results suggest the effectiveness of the optimization strategies applied, and underscore the importance of simultaneous decision variable selection in improving the performance in direct air capture processes. We also extend the modeling approach to a 2D axisymmetric model to better visualize CO₂ uptake and temperature profiles, revealing significant radial gradients during the regeneration step. As a main drawback, this enhanced model comes with a computational cost approximately 40 times higher than that of the 1D model.

Adsorption-desorption process↗
NASA NTRS2011

OLTARIS: An Efficient Web-Based Tool for Analyzing Materials Exposed to Space Radiation

The near-Earth space radiation environment includes energetic galactic cosmic rays (GCR), high intensity proton and electron belts, and the potential for solar particle events (SPE). These sources may penetrate shielding materials and deposit significant energy in sensitive electronic devices on board spacecraft and satellites. Material and design optimization methods may be used to reduce the exposure and extend the operational lifetime of individual components and systems. Since laboratory experiments are expensive and may not cover the range of particles and energies relevant for space applications, such optimization may be done computationally with efficient algorithms that include the various constraints placed on the component, system, or mission. In the present work, the web-based tool OLTARIS (On-Line Tool for the Assessment of Radiation in Space) is presented, and the applicability of the tool for rapidly analyzing exposure levels within either complicated shielding geometries or user-defined material slabs exposed to space radiation is demonstrated. An example approach for material optimization is also presented. Slabs of various advanced multifunctional materials are defined and exposed to several space radiation environments. The materials and thicknesses defining each layer in the slab are then systematically adjusted to arrive at an optimal slab configuration.

Slaba, Tony↗
DOE OSTI2025

Estimating the State of Charge in Lithium Primary Batteries: Recent Advances and Critical Insights

Lithium primary batteries (LPBs) remain essential in critical applications such as military, aerospace, medical and emergency devices, and portable electronics. Their superior energy density over lithium-ion batteries offers a significant advantage for long-duration use. Therefore, accurate estimation of the state of charge (SoC) is essential for ensuring the reliable and safe operation of these batteries. While extensive research has been conducted on SoC estimation techniques for lithium-ion secondary batteries, LPBs present unique challenges that complicate accurate SoC estimation. Moreover, research on nondestructive testing techniques for SoC estimation in LPBs is significantly lacking. In this review article, it is aimed to provide a comprehensive overview of recent advancements in SoC estimation for LPBs and generates new insights and directions for future research. Herein, existing methods are discussed and their effectiveness and mechanisms are identified, and areas for further optimization are outlined. More theoretical/experimental efforts to advance SoC detection in LPBs is recommended due to challenges identified with existing techniques.

25 ENERGY STORAGE↗
DOE OSTI2025

Potential Supply Chain and Cost Reduction Strategies for Advanced Nuclear Reactors

This milestone represents a level of effort to provide recommendations for a supply chain plan and establish relationships between advanced reactor companies and large companies in the oil & gas and chemical industries. It represents a starting point to develop the plan with options, general equipment lists, and rough associated cost estimates of major equipment and the associated systems needed. This effort will provide an opportunity to leverage the experience that oil & gas and chemicals companies possess in large capital equipment procurement, modularization, acquisition and installation. Potential supply chain solutions will be discussed and preliminary options for worldwide manufacturers will be elucidated. The goal of this effort will be to leverage the years of accumulated experience in the oil & gas and chemical industries in the area of capital equipment acquisition to understand the potential supply chain options and to reduce potential acquisition costs by optimizing the supply chain options for advanced nuclear reactor modularization, manufacturing and acquisition.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗