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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Harnessing Machine Learning to Predict MoS 2 Solid Lubricant Performance

Physical vapor deposited (PVD) molybdenum disulfide (MoS 2 ) solid lubricant coatings are an exemplar material system for machine learning methods due to small changes in process variables often causing large variations in microstructure and mechanical/tribological properties. Here, in this work, a gradient boosted regression tree machine learning method is applied to an existing experimental data set containing process, microstructure, and property information to create deeper insights into the process-structure–property relationships for molybdenum disulfide (MoS 2 ) solid lubricant coatings. The optimized and cross-validated models show good predictive capabilities for density, reduced modulus, hardness, wear rate, and initial coefficients of friction. The contribution of individual deposition variables (i.e., argon pressure, deposition power, target conditioning) on coating properties is highlighted through feature importance. The process-property relationships established herein show linear and non-linear relationships and highlight the influence of uncontrolled deposition variables (i.e., target conditioning) on the tribological performance.

MoS2↗
DOE OSTI2022

Microgrid Resilience: A Holistic and Context-Aware Resilience Metric

Microgrids present an effective solution for the coordinated deployment of various distributed energy resources and furthermore provide myriad additional benefits such as resilience, decreased carbon footprint, and reliability to energy consumers and the energy system as a whole. Boosting the resilience of distribution systems is another major benefit of microgrids. This is because they can also serve as a backup power source when the utility grid's operations are interrupted due to either high-probability low-impact events like a component failure or low-probability high-impact events - be it a natural disaster or a planned cyberattack. However, the degree to which any particular system can defend, adapt, and restore normal operation depends on various factors including the type and severity of events to which a microgrid is subjected. These factors, in turn, are dependent on the geographical location of the deployed microgrid as well as the cyber risk profile of the site where the microgrid is operating. Therefore, in this work, we attempt to capture this multi-dimensional interplay of various factors in quantifying the ability of the microgrid to be resilient in these varying aspects. This paper, thus, proposes a customized site-specific quantification of the resilience strength for the individual microgrid's capability to absorb, restore, and adapt to the changing circumstances for sustaining the critical load when a low-probability high-impact event occurs - termed as - context-aware resilience metric. We also present a case study to illustrate the key elements of our integrated analytical approach.

microgrid↗
DOE OSTI2023

Molecular Dynamics Simulation of Hygroscopic Aging Effects in Epoxy Polymer

The automobile industry is incorporating more lightweight content in car designs to boost fuel-economy. New structural adhesives are needed to mitigate the corrosion and thermal expansion issues associated with joining dissimilar lightweight materials, but adhesive developers lack a fundamental understanding of the chemistry that occurs in the adhesive as the joint ages. In this study, we developed structural adhesive molecular models and applied classical molecular dynamics simulations and density functional theory calculations to gain molecular insights into the influence of water molecules on the properties of epoxy-based adhesives (DGEBA + Jeffamine (JD230)). The simulations were complemented by experimental synthesis and characterization. Our work underscores the impact of water molecules on the local structure of the epoxy network as well as resulting mechanical properties. Water molecules were mainly coordinated with hydroxyls, primary amines and secondary amines, but also weakly coordinated with ether linkages, which were found most probable to be labile. Simulated stress–strain data indicates that increasing the water content deteriorates the mechanical properties. The Young’s modulus decreased by ~ 30% when the water content increased to 3 wt%. We conclude, this integration of molecular-level chemical insights with mechanical property simulations of the hydrated epoxy system and experimental validation holds the promise to advance lightweight joint technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Pathway to Decarbonization Through Industrial Energy Efficiency: Micro and Macro Perspectives from Compressed Air Usage

Abstract Energy audits directly provided the industrial sector with reduced energy costs and avoided emissions. Still, they also lead to far-reaching indirect and induced local, regional, and national benefits. This paper aims to present the techno-economic-environmental analysis to achieve decarbonization through implementing industrial energy efficiency at micro and macro levels. An integrated techno-economic-environmental methodology is developed. Case studies of micro-level carbon reduction efforts through industrial energy efficiency technologies are presented. The broader macroeconomic and environmental effects of technology on society are analyzed using data from 206 energy audits of industrial compressed air systems conducted over 13 years. The impacts show that energy-efficient improvements lead to direct cost savings for manufacturers, boost economic activity across sectors, and affect carbon dioxide emissions both short-term and long-term in the region. Given their extensive benefits, energy audits significantly influence policymaking. We devised a methodology to link micro-level energy audit data with macroeconomic and environmental analyses to quantify these cascading benefits. The economic scenario analysis shows that $228 M has been saved from direct industrial energy savings from implementing all compressed air recommendations in the studied periods and the region. In addition, the investment made through manufacturers would create 2,025 jobs and $383 M annually, cascading regional economic impacts. The environmental analysis shows that the regional manufacturers have directly avoided about 2.8 M metric tons of carbon dioxide emissions.

Engineering↗
DOE OSTI2024

Green buffers near industrial plants, examples in Jefferson County TX

Green buffers between industrial plants and residential areas have multiple purposes in mitigating air pollution and protecting the environment. This study focuses on providing information on examples of green space development by industries near residential areas in Jefferson County, Texas. One represents a full buffer where residences were totally removed, another is a partial buffer where some residences were removed in a neighborhood and the third represents vegetation of a formerly industrial facility. Additional estimates on benefits of buffer spaces with respect to a pollutant plume are also considered. The study used geospatial and property data from 1966 to 2020. The transition from a residential area to a full or partial buffers highlights possible mitigation of air pollution impacts while serving additional functions, such as boosting stormwater infiltration and improving the aesthetic attractiveness of the area. The transformation from oil tanks to forested space may display the potential for environmental remediation, but not all spaces are suitable for fully forested buffers, as safety and other limitations should be considered. With the analysis of the classic Plume Equation insights can be provided regarding the possible impact of green buffers on ground-level pollutant concentrations. The calculations for atmospheric stability classes A-F and for various stack heights provide an understanding of how different conditions may affect the pollutant concentrations. The presence of a green buffer can play a crucial role in controlling ground-level pollution concentrations and reduce a community’s perception of risk.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Lax-Oleinik-Type Formulas and Efficient Algorithms for Certain High-Dimensional Optimal Control Problems

Two of the main challenges in optimal control are solving problems with state-dependent running costs and developing efficient numerical solvers that are computationally tractable in high dimension. In this paper, we provide analytical solutions to certain optimal control problems whose running cost depends on the state variable and with constraints on the control. We also provide Lax-Oleinik-type representation formulas for the corresponding Hamilton-Jacobi partial differential equations with state-dependent Hamiltonians. Additionally, we present an efficient, grid-free numerical solver based on our representation formulas, which is shown to scale linearly with the state dimension, and thus, to overcome the curse of dimensionality. Using existing optimization methods and the min-plus technique, we extend our numerical solvers to address more general classes of convex and nonconvex initial costs. We demonstrate the capabilities of our numerical solvers using implementations on a central processing unit (CPU) and a field-programmable gate array (FPGA). In several cases, our FPGA implementation obtains over a 10 times speedup compared to the CPU, which demonstrates the promising performance boosts FPGAs can achieve. Furthermore, our numerical results show that our solvers have the potential to serve as a building block for solving broader classes of high-dimensional optimal control problems in real-time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Chapter 2: Global Value Chain and Manufacturing Analysis on Geothermal Power Plant Turbines

The global geothermal power market has shown significant growth since the last decade and is expected to reach a total installed capacity of 18.4 gigawatts electric (GWe) by the end of 2021 (GEA, 2016). The global geothermal power plant turbine market is dominated by a small number of manufacturers. Between 2005 and 2015, 82% of the geothermal steam turbines were manufactured in Japan, and 74% of the geothermal binary cycle turboexpanders were manufactured in Israel. During this period, the United States played an important role in the global trade flow of fully assembled turbine units and turbine parts, with a high volume of imports and exports. Another significant growth area was in Italian turbine/turboexpander manufacturers, who have increased their market share in the last couple of years. One other important change in the manufacturing market was in Turkey, where the bonus on feed-in-tariff (FIT) for domestic hardware components boosted the national manufacturing sector between 2010 and 2020. When planning geothermal power projects, developers customize their power plant size to fit the available geothermal resource capacity. The turbine is designed and sized to optimize the efficiency and utilization of resource and revenue production. The rest of the power plant components such as heat exchangers (HX), water-cooled cooling towers (WCCT), or air-cooled condensers (ACC) are then chosen to complement the turbine size and design. These one-off manufacturing custom design turbines have relatively higher manufacturing set-up costs, longer lead times, and higher capital costs than the standard design turbines manufactured in larger volumes. However, turbines produced in standard increments and in larger manufacturing volumes could result in lower costs per turbine, but potentially lower efficiency. Based on pipeline projects and resource assessments, there is significant potential value in creating standard turbine sizes that could offer an economic advantage, as is done for modular microturbines.

40 EE - Geothermal Technologies Office (EE-4G)↗
DOE OSTI2020

Carbon nanotube (CNT) metal composites exhibit greatly reduced radiation damage

Radiation damage of structural materials leads to mechanical property degradation, eventually inducing failure. Secondary-phase dispersoids or other radiation defect sinks are often added to materials to boost their radiation resistance. We demonstrate that a metal composite made by adding 1D carbon nanotubes (CNTs) to aluminum (Al) exhibits superior radiation resistance. In situ ion irradiation with transmission electron microscopy (TEM) and atomistic simulations together reveal the mechanisms of rapid defect migration to CNTs, facilitating defect recombination and enhancing radiation tolerance. The origin of this effect is an evolving stress gradient in the Al matrix resulting from CNT transformation under irradiation, and the stability of resulting carbides. Extreme value statistics of large defect behavior in our simulations highlight the role of CNTs in reducing accumulated damage. Furthermore, this approach to controlling defect migration represents a promising opportunity to enhance the radiation resistance of nuclear materials without detrimental effects.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Gap-filling eddy covariance methane fluxes: Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of methane fluxes measured by eddy-covariance require gap-filling to estimate annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for methane, with regards both to the best model algorithms and predictors. In this study, we address the need for standardization by synthesizing results of gap-filling methods applied at 17 wetland sites spanning boreal to tropical regions including all major wetlands classes and two rice paddies. We introduce new procedures for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with robust uncertainty estimates. We tested a conventional method (marginal distribution sampling) and four machine learning algorithms - penalized linear regression, artificial neural networks, random forests, and boosted decision trees - and four predictor sets, including temporal, meteorological, ecosystem carbon and energy flux, and soil predictors. We find that the conventional method can achieve similar median performance to the machine learning models but is worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. Finally, we gap-fill and provide summary evaluation metrics for all 81 sites in the FLUXNET-CH4 community dataset and publicly release the python code for model development, evaluation, and uncertainty estimation.

42 ENGINEERING↗
DOE OSTI2025

Scale-up study of enhancing algal growth through bioaugmentation with the indole-3-acetic acid producing bacteria Azospirillum brasilense

Algae-based wastewater treatment technologies can recover nutrients while generating algal biomass with diverse application potentials. While numerous bacteria have demonstrated the ability to enhance algal growth through symbiotic relationships in laboratory settings, scaling this benefit to larger applications remains challenging due to complex wastewater conditions and microbe-algae dynamics. This study explores the effectiveness of bioaugmentation with Azospirillum brasilense, a plant growth-promoting bacterium known for producing the phytohormone indole-3-acetic acid (IAA), in boosting algal productivity within an Algaewheel wastewater treatment system. Through a series of experiments conducted at lab-, pilot-, and full-scale levels, we evaluated the impact of bioaugmentation on algal growth and developed a bioaugmentation strategy for an Algaewheel system. The results indicate that a biweekly dosing, achieving a final bioaugmenting cell density of 0.2–4 × 10 9 cells/L, effectively doubles the biomass productivity in a residential subdivision wastewater treatment plant in Northern Illinois. The bacterial production of IAA was the primary mechanism driving this enhancement, as demonstrated by the similar growth and yield improvements observed with chemically supplemented IAA and bioaugmentation across all experimental scales. High-throughput sequencing of 18S rRNA genes revealed that the algal community in the bioaugmented tank exhibited more stable biodiversity than the control. Additionally, bioaugmentation improved nutrient removal efficiency during winter, highlighting its potential to enhance the overall performance and sustainability of algae-based wastewater systems. The developed bioaugmentation and chemical treatment methods offer further operational solutions for managing yield, optimizing biochemical profiles, and enhancing biofuel production potential.

Algae-bacterial symbiotic relationship↗
DOE OSTI2022

Design of a supervisory control system for autonomous operation of advanced reactors

Advanced reactors to be deployed in the coming decades will face deregulated energy markets, and may adopt flexible operation to boost profitability. To aid in the transition from baseload to flexible operation paradigm, autonomous operation is sought. This work focuses on the control aspect of autonomous operation. Specifically, a hierarchical control system is designed to support constraint enforcement during routine operational transients. Within the system, data-driven modeling, physics-based state observation, and classical control algorithms are integrated to provide an adaptable and robust solution. A 320 MW Fluoride-cooled High-temperature Pebble-bed Reactor is the design basis for demonstrating the proposed control system. The hierarchical control system consists of a supervisory layer and low-level layer. The supervisory layer receives requests to change the system's operating conditions (e.g., the current reactor power to meet a load -follow), and accepts or rejects them based on constraints that have been assigned. Constraints are issued to keep the plant within an optimal operating region. The low-level layer interfaces with the actuators of the system to fulfill requested changes, while maintaining tracking and regulation duties. Further, to accept requests at the supervisory layer, the Reference Governor algorithm was adopted. To model the dynamics of the reactor, a system identification algorithm, Dynamic Mode Decomposition, was utilized. To estimate the evolution of process variables that cannot be directly measured (e.g., the propagation of delayed neutron precursors), the Unscented Kalman Filter, incorporating a nonlinear model of nuclear dynamics, was adopted. The composition of these algorithms led to a numerical demonstration of constraint enforcement during a 40% power drop transient (at a rate of 5 %/min). Uncontrolled secondary-side temperatures were successfully constrained. Adaptability of the proposed system was demonstrated by modifying the constraint values, and enforcing them during the transient. Robustness was also demonstrated by enforcing constraints under noisy environments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Critical response to M. Worrall et al. Published in Annals of Nuclear Energy 207 (2024) 110731

M. Worrall et al. recently published a manuscript titled “Fast neutron irradiation capability in existing thermal test reactors” (Worrall, 2024) that summarizes an irradiation vehicle design that would boost the fast neutron flux in the Advanced Test Reactor (ATR) for testing of nonfuel materials in a neutron flux energy spectrum that is more representative of fast reactors. Here, the authors compare their design with a separate vehicle design that they conceived of that would be implemented within the High Flux Isotope Reactor (HFIR). They analyzed both designs and drew conclusions on the most realistic near-term options for shielded nonfuel material irradiations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Physics of the Inverted Harmonic Oscillator: From the lowest Landau level to event horizons

In this work, we present the inverted harmonic oscillator (IHO) Hamiltonian as a paradigm to understand the quantum mechanics of scattering and time-decay in a diverse set of physical systems. As one of the generators of area preserving transformations, the IHO Hamiltonian can be studied as a dilatation generator, squeeze generator, a Lorentz boost generator, or a scattering potential. In establishing these different forms, we demonstrate the physics of the IHO that underlies phenomena as disparate as the Hawking–Unruh effect and scattering in the lowest Landau level (LLL) in quantum Hall systems. We derive the emergence of the IHO Hamiltonian in the LLL in a gauge invariant way and show its exact parallels with the Rindler Hamiltonian that describes quantum mechanics near event horizons. This approach of studying distinct physical systems with symmetries described by isomorphic Lie algebras through the emergent IHO Hamiltonian enables us to reinterpret geometric response in the lowest Landau level in terms of relativistic effects such as Wigner rotation. Further, the analytic scattering matrix of the IHO points to the existence of quasinormal modes (QNMs) in the spectrum, which have quantized time-decay rates. We present a way to access these QNMs through wave packet scattering, thus proposing a novel effect in quantum Hall point contact geometries that parallels those found in black holes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Single-phase Ru 1- x-y Mn x Co y O 2 nanoparticles as highly effective oxygen reduction electrocatalysts in alkaline media with enhanced stability and fuel-tolerance

Here, a series of single-phase binary and ternary ruthenium and transition metal oxide nanoparticles supported on Vulcan - Ru 1-x MnxO2/C, Ru1-xCoxO 2 /C, Ru 1-x-y MnxCo y O 2 /C, Ru 1-x Fe x O 2 /C, Ru 1-x Ni x O 2 /C and Ru 1-x V x O 2 /C, as well as RuO 2 /C, MnO 2 /C, Co 3 O 4 /C and Mn 3-x Co x O 4 /C - were synthesized via a facile method and studied for their oxygen reduction reaction (ORR) activity in alkaline media. Single-phase Ru 1-x Mn x O 2 /C, Ru 1-x-y Mn x Co y O 2 /C and Ru 1-x Co x O 2 /C catalysts significantly boosted ORR kinetics in alkaline media. Moreover, they were H 2 and methanol tolerant, and exhibited long term stability due to their single-phase structure. Ru 0.85 Mn 0.15 O 2 /C stood out as the most active catalyst among them. A volcano relationship of the ORR activity of these binary and ternary metal oxide catalysts vs. the O adsorption energy was found, with the maximum activity observed for the Ru 1-x Mn x O 2 /C, Ru 1-x-y Mn x Co y O 2 /C and Ru 1-x Co x O 2 /C catalysts due to their optimal O binding energy. These materials have potential applications as highly active ORR catalysts in alkaline fuel cells and metal-air batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Cactus-like NiCo 2 S 4 @NiFe LDH hollow spheres as an effective oxygen bifunctional electrocatalyst in alkaline solution

The high-performance non-precious electrocatalysts for both oxygen redn. reaction (ORR) and oxygen evolution reaction (OER) are crucial to the practical application of fuel cells and metal-air batteries. Herein, a novel cactus-like NiCo 2 S 4 @NiFe LDH hollow sphere assembled by one-dimensional (1D) NiFe LDH nanowires and two-dimensional (2D) NiFe LDH nanosheets on the NiCo 2 S 4 hollow spheres is prepd. by a facile hydrothermal method. The outer NiFe LDH nanowires and NiFe LDH nanosheets can effectively suppress the collapse and corrosion of inner NiCo 2 S 4 hollow structure during long-term stability tests. The integration of the effective OER electrocatalyst NiFe LDH into NiCo 2 S 4 to form heterostructures, as well as the strong electronic interaction between NiCo 2 S 4 and NiFe LDH, can greatly boost both ORR and OER activities. Due to the above merits, the NiCo 2 S 4 @NiFe LDH achieves remarkably a small potential gap (ΔE = E j =10-E 1/2 ) of only 0.667 V. In this paper, we offer a facile strategy to design efficient catalysts with heterostructures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Toward efficient single-atom catalysts for renewable fuels and chemicals production from biomass and CO 2

Transformation of biomass and CO 2 into renewable value-added chemicals and fuels has been identified as a promising strategy to fulfill high energy demands, lower greenhouse gas emissions, and exploit under-utilized resources. Cost-effective and performance-efficient catalysts are of great importance to lowering the conversion cost of biomass and CO 2 . Significant progress has been made to advance the catalyst design for these processes, with metal catalysts playing a critical role in many involved catalytic reactions. Traditional nanoparticle-based metal catalysts still require improvement in metal utilization rates, stability, and selectivity tunability. Single-atom catalysts, which have maximum atomic efficiency and a uniform and tunable metal center, as well as an adjustable metal-support interaction, provide potential opportunities to boost catalyst efficiency and thermal stability. Their well-defined and uniform structure also provides advantages to fundamental studies for understanding of the intrinsic reaction mechanism and site requirement in biomass and CO 2 conversion. In this article, we summarize and highlight the recent advances in converting biomass and CO 2 to renewable fuels and chemicals using single-atom catalysts. We discuss the design principles of single-atom catalysts and their potential applications to biomass and CO 2 upgrading as well as the origins of catalytic activity. Moreover, we compare the catalytic efficiency of various catalysts reported thus to provide a fair assessment of these catalysts. Finally, perspectives are given on the interesting fields that may guide future studies.

09 BIOMASS FUELS↗
DOE OSTI2020

Multiple injection for improving knock, gaseous and particulate matter emissions in direct injection SI engines

Advances in fuel injector technology have enabled research and development on a large variety of direct injection spark ignition (DISI) engine fueling strategies targeted to improve engine performance and reduce engine-out emissions. This study explores the effect of multiple injections on knock, engine efficiency and stability, and particulate number and gaseous emissions on a single-cylinder DISI research engine. Work to date on multiple injections in the literature is reviewed, and then two aspects of multiple injection strategies are experimentally investigated: the number of injections (up to five times in a cycle); and the timing of the injections (classified relative to the timing of intake valve opening and closing). A boosted, single-cylinder research engine equipped with a state-of-the-art piezoelectric hollow cone spray direct injector and research-grade E10 gasoline was used for the study. The results show multiple injections maintain torque and combustion stability compared with single injection and slightly increase the knock limits and indicated thermal efficiencies (maximum 0.7% absolute, 2.8% relative compared with single-injection baseline) due to improved heat release phasing, especially with an additional late injection during the intake valve closed (compression stroke) period. The gaseous pollutant emissions including nitrogen oxides and unburned hydrocarbons were reduced by 25% with multiple injections, particularly with injection during the compression stroke. In contrast, carbon monoxide emissions increased with multiple injections for all conditions. Increasing the number of injection events significantly reduced particulate number emissions (half with each additional injection), and the decrease in particulate number was not sensitive to the injection timing.

42 ENGINEERING↗