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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 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Optimizing conformance control for gas injection EOR in unconventional reservoirs

Field observations have shown that interference between wells caused by connected fractures commonly exists in unconventional reservoirs. The well interference effect and conformance issues could lead to minimal enhanced oil recovery response (EOR) in actual operations if they are not properly controlled. A series of data analysis, modeling, and experimental activities were performed in this study to investigate the gas EOR strategies in the Bakken Formation. Employing the embedded discrete fracture modeling technology, a multiple-well, multiple-fracture model was developed to capture the well interference and conformance issues in the Bakken. The model made it possible to investigate the complex flow behavior between wells in the EOR (huff ‘n’ puff) processes. Alternative EOR and conformance control strategies using water and surfactant injections were studied to improve oil production performance based on experimental observations. Results showed that water injection could be used for conformance control in the Bakken because of its relatively low mobility compared to gas; however, water could also block oil flow around the conformance control wells because of the high interfacial tension between oil and water. Adding surfactant to the injection water is more effective for improving gas EOR performance since surfactant reduces the oil–water interfacial tension and contact angle effectively. Up to 9.4% more oil could be produced from the huff ‘n’ puff wells in 2 years of EOR operations when rich gas was injected at only 3 MMscf/d with 6000 psi of surfactant injection in the offset wells for conformance control.

42 ENGINEERING↗
NASA NTRS1985

Optimal generalized multistep integration formulae for real-time digital simulation

The problem of discretizing a dynamical system for real-time digital simulation is considered. Treating the system and its simulation as stochastic processes leads to a statistical characterization of simulator fidelity. A plant discretization procedure based on an efficient matrix generalization of explicit linear multistep discrete integration formulae is introduced, which minimizes a weighted sum of the mean squared steady-state and transient error between the system and simulator outputs.

Moerder, D. D.↗
DOE OSTI2025

Ice storage model-predictive control in an office building with PV: scenario, error and sensitivity analysis

Thermal energy storage (TES) can enable more building-sited renewable electricity generation and lower utility bill costs for buildings owners and occupants, especially when there are high demand and variable time-of-use (TOU) charges. A model predictive control (MPC) strategy can offer additional savings over a schedule-based control with added complexity and reliance on forecasts. Here, this study examines savings for medium office buildings with chiller plants in three locations with building-installed solar photovoltaics (PV) to understand the impact of MPC. Control setpoints are fixed by a schedule-based control or optimized by nonlinear MPC. These control setpoints are actuated within EnergyPlus building models to simulate the utility cost of the chiller plant. NLP solutions can be unstable or unrealistic, but our results show that by regularizing the NLP, the solutions can be reasonably followed by the building model. MPC models make simplifications that lead to errors once the controller is participating in and changing the operation of the building. These errors average 9 % across the cases, showing that the most important parts of the system are represented. The no-thermal load costs are computed to show that the optimization can in some cases achieve both the minimum TOU and minimum monthly demand costs by demand management while reducing TOU energy costs by energy arbitrage. The MPC saves 35–66 % in the annual chiller plant operating costs, which is an additional savings above the schedule by 1–33 %. PV and TES are complementary and mostly independent, but a load with PV often results in better performance for the schedule. Our case study and sensitivity analysis show the importance of modeling and optimization for complex rates, but also the circumstances wherein a simpler strategy achieves the same performance with less potential for error.

14 SOLAR ENERGY↗
DOE OSTI2023

Automatic Rural Road Centerline Detection and Extraction from Aerial Images for a Forest Fire Decision Support System

To effectively manage the terrestrial firefighting fleet in a forest fire scenario, namely, to optimize its displacement in the field, it is crucial to have a well-structured and accurate mapping of rural roads. The landscape’s complexity, mainly due to severe shadows cast by the wild vegetation and trees, makes it challenging to extract rural roads based on processing aerial or satellite images, leading to heterogeneous results. This article proposes a method to improve the automatic detection of rural roads and the extraction of their centerlines from aerial images. This method has two main stages: (i) the use of a deep learning model (DeepLabV3+) for predicting rural road segments; (ii) an optimization strategy to improve the connections between predicted rural road segments, followed by a morphological approach to extract the rural road centerlines using thinning algorithms, such as those proposed by Zhang–Suen and Guo–Hall. After completing these two stages, the proposed method automatically detected and extracted rural road centerlines from complex rural environments. This is useful for developing real-time mapping applications.

Lourenço, Miguel (ORCID:0000000157673394)↗
DOE OSTI2025

Design, Optimization, and Control of Floating Offshore Wind Farms for Optimal Energy Production (Final report)

The uncertainty and irregularity of ocean waves and the ocean environment is a major factor in the development of commercial scale floating wind turbines as the operation of floating structures in such an environment can lead to irregular and unpredictable loading, fatigue, and ultimately a reduction in the operational life of the turbine system which affects energy production over the lifetime of the turbine. Control solutions that can limit float motions and mitigate stressful events on the structure become essential for extending lifetime and limiting the operational uncertainty of a floating wind turbine. Digital twins are computational replicas of physical systems that operate in parallel with the operation of the physical system. Given advanced knowledge of a systems input, digital twins have the ability to predict the behavior of a system in advance, which can be valuable in the control of that system. In this project, we developed and assessed potential digital twin models developed in house and openly available (OpenFast) for use in the real time control of the six degree of freedom response motions of a floating wind turbine in ocean waves. Coupling these models with near-field real time irregular sea surface (wve) measurement/sensings and prediction models, we used the digital twin to predict how the floating turbine will respond to the incoming waves. Applying this information to a motion control system of the float, one can limit and control float motions to prevent undesirable loading events/large angular motions, thus increasing system life and ultimately contributing to optimizing energy production. Due to the computational intensity of operating a digital twin in real time, we investigated the use of artificial intelligence techniques to speed-up the processes of the digital twin, as well as the wave reconstruction/prediction models. Model tank testing at the University of Rhode Island and University of Maine both validated and demonstrated the developed techniques on simple float geometries and a scale model of the NREL 15 MW reference turbine.

17 WIND ENERGY↗
DOE OSTI2020

The Need for International Consensus and Acceptance of Free Released Material - 20177

World Nuclear Association (WNA) believes that the waste hierarchy is best implemented when a good compromise exists between disposal and reuse/recycling methods of valuable materials and waste generated by the nuclear industry. The rapid normalization of recycling in both domestic and industrial worlds strengthens WNA's position, as new facilities worldwide emerge providing treatment for clearance. As a foundation for reuse and recycling, the International Atomic Energy Agency (IAEA) provided international guidance on clearance (Safety Guide RSG 1.7) [1], defining associated threshold values approved by all member states. Nevertheless, despite this consensus, a lack of alignment of national regulations has occurred as countries have departed for this international guidance, leading to confusion, even between neighborhood countries. As a consequence, this discrepancy between national rules, despite industrial and technical international consensus based on radiological and environmental considerations appeared as a brake, weakening public acceptance as well as nuclear industry credibility. As a matter of fact, what is allowed in one side of a border may be forbidden on the other side. Conversely, an international consensus on clearance would promote: - Sustainability improvements, including preservation of natural and rare resources resulting from optimized recycling and reuse practices; - A broader acceptance of free released materials; - taking advantage of the available technologies worldwide in materials treatment aiming for clearance; - Increased sharing and use of methods, know-how and operators, leading to better efficiency, innovation, improvement as well as technical and financial mastery. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2010

Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model

In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.

Burken, John J.↗
DOE OSTI2023

Role of Scaffold Architecture and Excess Surface Polymer Layers in a 3D-Interconnected Ceramic/Polymer Composite Electrolyte

3D-interconnected ceramic/polymer composite electrolytes offer promise to combine the benefits of both ceramic and polymer electrolytes. However, an in-depth understanding of the role of the ceramic scaffold's architecture, and the associated polymer/ceramic interfaces on the electrochemical properties of such composite electrolytes is still incomplete. Here, these factors are systematically evaluated using an interconnected composite electrolyte with a tunable and well-defined architecture. The ionic conductivity of the ceramic scaffold is strongly dependent on its porosity and tortuosity, as demonstrated experimentally and via theoretical modeling. The connectivity of the ceramic framework avoids the high interfacial impedance at the polymer/ceramic electrolyte interface within the composite. However, this work discovers that the interfacial impedance between the bulk composite and excess surface polymer layers of the composite membrane dominates the overall impedance, resulting in a 1–2 order drop of ionic conductivity compared to the ceramic scaffold. Despite the high impedance interfaces, an improved Li + transference number is found compared to the neat polymer (0.29 vs 0.05), attributed to the ceramic phase's contributions toward ion transport. Further, this leads to flatter overpotentials in lithium symmetric cell cycling. These results are expected to guide future research directions toward scalable manufacturing of composite electrolytes with optimized architecture and interfaces.

25 ENERGY STORAGE↗
DOE OSTI2022

Pure quark and gluon observables in collinear drop

We construct a class of pure quark and gluon observables by using the collinear drop grooming technique. The construction is based on linear combinations of multiple cumulative distributions of the jet mass in collinear drop, whose specific weights are fully predicted perturbatively. This yields observables which obtain their values purely from quarks (or purely from gluons) in a wide region of phase space. We demonstrate this by showing that these observables are effective in two phase space regions, one dominated by perturbative resummation and one dominated by nonperturbative effects. The nonperturbative effects are included using shape functions which only appear as a common factor in the linear combinations constructed. We test this construction using a numerical analysis with next-to-leading logarithmic resummation and various shape function models, as well as analyzing these observables with PYTHIA and VINCIA. Choices for the collinear drop parameters are optimized for experimental use.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Influence of processing on secondary phase formation and microstructural evolution at U-10Mo alloy and Zr interlayer interfaces

Thermo-mechanical processing of uranium-10 wt. % molybdenum (U-10Mo) fuel plates leads to microstructure changes at the U-10Mo/Zr interfaces. Secondary phases formed at this interface are particularly important to interfacial bond strength, process optimization, and maintaining structural integrity of the U-10Mo fuel plates during irradiation. In this work, we determined the phases and phase transformation products occurring at the interface of the U-10Mo fuel and Zr interlayer when the fuel plate is subjected to short and long hot isostatic pressure times. Interfacial morphology, structure and composition of phases formed, and relative hardness across the U-10Mo/Zr interfaces were studied using a multi-length scale, multi-modal characterization approach involving electron microscopy, atom probe tomography, and atomic force microscopy. Here, results highlight that the extent of phase transformations, secondary phase formation, and hardness variability across interfaces can be controlled by modifying processing parameters. Phase diagram construction and thermodynamic calculations were performed using the Thermocalc software to identify expected phases formed at interfaces during the maximum hold temperature of 560 °C experienced during HIP.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Urban land patterns can moderate population exposures to climate extremes over the 21st century

Abstract Climate change and global urbanization have often been anticipated to increase future population exposure (frequency and intensity) to extreme weather over the coming decades. Here we examine how changes in urban land extent, population, and climate will respectively and collectively affect spatial patterns of future population exposures to climate extremes (including hot days, cold days, heavy rainfalls, and severe thunderstorm environments) across the continental U.S. at the end of the 21st century. Different from common impressions, we find that urban land patterns can sometimes reduce rather than increase population exposures to climate extremes, even heat extremes, and that spatial patterns instead of total quantities of urban land are more influential to population exposures. Our findings lead to preliminary suggestions for embedding long-term climate resilience in urban and regional land-use system designs, and strongly motivate searches for optimal spatial urban land patterns that can robustly moderate population exposures to climate extremes throughout the 21st century.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Stabilization of high-performance rock-salt LiMnSbTe3 thermoelectrics with embedded van der Waals-like gaps

Rock-salt-structured compounds like lead chalcogenides are promising thermoelectrics, as their high symmetry, strong anharmonicity, and favorable phase behavior collectively lead to high performance by enabling large power factors and ultralow thermal conductivity. Here, we report LiMnSbTe 3 , a new rock-salt semiconductor stabilized through targeted chemical design by combining hexagonal MnTe with cubic LiSbTe 2 . Embedded in the highsymmetry matrix, van der Waals-like gaps form due to Sb 2 Te 3 nanoscale segregation, which acts as effective phonon-scattering centers, leading to a low lattice thermal conductivity of 0.37Wm- 1 K -1 at 873 K with alloy scattering from disordered cations. The ordered local structure of Sb2Te 3 -type vdW-like gaps and the cross-gap interaction facilitate the carrier transport. Aided by energyconverged valence bands and a paramagnon drag effect, high Seebeck coefficients and enhanced power factor can be achieved, leading to a high ZT of 1.2 at 873 K. Furthermore, introducing Mn deficiency increases ZT to 1.5, highlighting the potential for higher performance through optimized doping or alloying. A segmented single-leg thermoelectric module achieves an output power density of 0.52 Wcm -2 and an efficiency of 8.7% under ΔT of 478 K, further demonstrating its promising thermoelectric applications.

42 ENGINEERING↗
DOE OSTI2025

Application-specific machine-learned interatomic potentials: exploring the trade-off between DFT convergence, MLIP expressivity, and computational cost

Machine-learned interatomic potentials (MLIPs) are revolutionizing computational materials science and chemistry by offering an efficient alternative to ab initio molecular dynamics (MD) simulations. However, fitting high-quality MLIPs remains a challenging, time-consuming, and computationally intensive task where numerous trade-offs have to be considered, e.g., How much and what kind of atomic configurations should be included in the training set? Which level of ab initio convergence should be used to generate the training set? Which loss function should be used for fitting the MLIP? Which machine learning architecture should be used to train the MLIP? The answers to these questions significantly impact both the computational cost of MLIP training and the accuracy and computational cost of subsequent MLIP MD simulations. In this study, we use a configurationally diverse beryllium dataset and quadratic spectral neighbor analysis potential. We demonstrate that joint optimization of energy versus force weights, training set selection strategies, and convergence settings of the ab initio reference simulations, as well as model complexity can lead to a significant reduction in the overall computational cost associated with training and evaluating MLIPs. This opens the door to computationally efficient generation of high-quality MLIPs for a range of applications which demand different accuracy versus training and evaluation cost trade-offs.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Central Plant Retrofit Assessment Guide for Owners

This document offers support to owners considering optimization upgrades, retrofits, or complete replacement of a central plant, with a particular focus on improving energy efficiency and reliability of the central plant, ultimately leading to reduced energy costs. It outlines recommended steps to prepare for and facilitate a thorough central plant assessment, empowering owners to move forward with the appropriate next steps. While the primary focus is on central plants serving commercial and institutional buildings, the principles and recommendations presented can also be adapted for use in other building types, such as industrial or manufacturing facilities.

42 ENGINEERING↗
DOE OSTI2024

xesn: Echo state networks powered by Xarray and Dask

Xesn is a Python package that allows scientists to easily design Echo State Networks (ESNs) for forecasting problems. ESNs are a Recurrent Neural Network architecture introduced by Jaeger (2001) that are part of a class of techniques termed Reservoir Computing. One defining characteristic of these techniques is that all internal weights are determined by a handful of global, scalar parameters, thereby avoiding problems during backpropagation and reducing training time significantly. Because this architecture is conceptually simple, many scientists implement ESNs from scratch, leading to questions about computational performance. Xesn offers a straightforward, standard implementation of ESNs that operates efficiently on CPU and GPU hardware. The package leverages optimization tools to automate the parameter selection process, so that scientists can reduce the time finding a good architecture and focus on using ESNs for their domain application. Importantly, the package flexibly handles forecasting tasks for out-of-core, multi-dimensional datasets, eliminating the need to write parallel programming code. Xesn was initially developed to handle the problem of forecasting weather dynamics, and so it integrates naturally with Python packages that have become familiar to weather and climate scientists such as Xarray (Hoyer & Hamman, 2017). However, the software is ultimately general enough to be utilized in other domains where ESNs have been useful, such as in signal processing (Jaeger & Haas, 2004).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Theoretical Analysis on the Dynamic Behavior and Electromechanical Response of PZT

Piezoelectric materials are used as a power source in stockpile components for safety and reliability assurances. The objective of this project is to gain insights into the fundamental pressure-induced behavior and electromechanical response of lead zirconate titanate (PZT). Specifically, to establish the basis for an accurate, physics-based material model for robust model-based design to rapidly optimize PZT-based materials and components for performance studies. Established ab-initio methods are used to interrogate and understand the dynamic behavior of PZT as a function of composition (50/50, 65/35, 80/20, 95/5) and dopants (La, Nb) to overcome the costly and time-consuming experimental methodologies. New cold curves for pure and doped single-crystal PZT are obtained as the reference equation-of-state (EOS). A negligible change in the pressure responses was observed for the systems and strains studied. Dielectric and piezoelectric responses of pure and doped single-crystal PZT were also calculated as a function of pressure. For undoped PZT, there is a clear and orderly pressure and composition dependence. For doped PZT, there is a significant increase in the responses, but the behavior is very disordered and inconclusive.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Printed Metal Molds for Mainstream Automotive Production

The main focus of this work was to evaluate additive manufacturing of metal molds, with significantly reduced cost and/or procurement lead time, for production of large composite components for mainstream (> 100k units/yr) automobiles. A two-component large tool with conformal heating channels was designed, optimized, printed, machined, and tested in production. The resulting analysis indicates that large scale AM is suitable for manufacturing complex geometry large scale metal molds.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Strong Local Passivity in Unconventional Scenarios: A New Protocol for Amplified Quantum Energy Teleportation

Quantum energy teleportation (QET) has been proposed to overcome the restrictions of strong local passivity (SLP) and to facilitate energy transfer in quantum systems. Traditionally, QET has only been considered under strict constraints, including the requirements that the initial state be the ground state of an interacting Hamiltonian, that Alice’s measurement commute with the interaction terms, and that entanglement be present. These constraints have significantly limited the broader applicability of QET protocols. In this work, we demonstrate that SLP can arise beyond these conventional constraints, establishing the necessity of QET in a wider range of scenarios for local energy extraction. This leads to a more flexible and generalized framework for QET. Furthermore, we introduce the concept of a “local effective Hamiltonian,” which eliminates the need for optimization techniques in determining Bob’s optimal energy extraction in QET protocols. As an additional advantage, the amount of energy that can be extracted using our new protocol is amplified to be 7.2 times higher than that of the original protocol. These advancements enhance our understanding of QET and extend its broader applications to quantum technologies. To support our findings, we implement the protocol on quantum hardware, confirming its theoretical validity and experimental feasibility.

amplified energy extraction↗