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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Development of green-colour-emitting pyrotechnics as a core for 3D temperature imaging sensors inside coal boilers

Efficiency in the control operation of the boilers for coal and coal with biomass can be further improved if the flue gas temperature distribution can be better characterized. This is very difficult in these harsh environmental systems, where spatially resolved measurements are nearly impossible with solid-state sensors. Here, in this work, we evaluate the development of pyrotechnic compounds that would serve as the basis for a novel optical mapping of the temperature inside coal boilers. For this purpose, various green-colour-emitting pyrotechnics using BaCl 2 · 2H 2 O and Ba(NO 3 ) 2 as the green light source were prepared, as this colour offers a distinct signal from the combustion-based background in the boiler. These pyrotechnics were characterized using thermogravimetric analysis (TGA) and X-ray diffraction (XRD) and tested using a flat-flame burner. Furthermore, the composition was varied to evaluate the effect of different metal fuels such as Sn, Co, and Mg, as well as various binders such as ethylcellulose, shellac, parlon, and PVC on green light emission. The emission intensity and the apparent ignition temperature were strongly dependent on the metal type, with Mg showing higher intensities. On the other hand, the effect of the binder showed that the ignition behaviour, emission intensity, and spectral purity were influenced by the nature and exothermicity of the binder. The addition of other potential green light-producing materials, such as boric acid, increased the intensity of emission by 17% for a BaCl 2 · 2H 2 O-based composition. This study identified prospective compositions with intense and bright green-colour emissions that have high spectral purities.

42 ENGINEERING↗
DOE OSTI2023

Sustainble dropwise condensation enabled ultraefficient heat pipes

Heat pipes play a critical role in determining the operations, safety, and energy efficiency of electronics. The main focus to improve the heat pipe performance is on the evaporator design or wicking structures. However, the intrinsic limitation comes from the condenser, which is fundamentally constrained by inefficient filmwise condensation (FWC). In this study, we successfully achieved a peak effective thermal conductivity (k eff ) of ~140 kW/(m·K) on widely used groove heat pipes by implementing sustainable dropwise condensation (DWC) and integrating with enhanced evaporator. To better understand the working mechanisms of the ultraefficient heat pipe, both the evaporator and condenser of the heat pipes have been modified accordingly. Our results show that up to 296% enhancements on the k eff can be achieved under various inclination angles by only inducing DWC in the condenser section. The drawback of temperature fluctuations induced by DWC in smooth heat pipes appears to be effectively solved using the grooves-wicking structure. Furthermore, by integrating the nanostructured evaporator, the k eff of the heat pipe can be boosted up to 517% compared to conventional groove heat pipes. This study, for the first time, demonstrates the huge potential of engineering both the condenser and evaporator simultaneously in developing ultraefficient heat pipes.

42 ENGINEERING↗
DOE OSTI2024

Using GANs to predict milling stability from limited data

Milling is a key manufacturing process that requires the selection of operating parameters that provide efficient performance. However, the presence of chatter, a self-excited vibration causing poor surface finish and potential damage to the machine and cutting tool, makes it challenging to select the appropriate parameters. To predict chatter, stability maps are commonly used, but their generation requires expensive data, making it difficult to employ these maps in industry. Therefore, there is a pressing need for an approach that can accurately predict stability maps using limited experimental data. This study introduces the new Encoder GAN (EGAN) approach based on Generative Adversarial Networks (GANs) that predicts stability maps using limited experimental data. The approach consists of the encoder, generator, and discriminator subnetworks and uses the trained encoder and generator to predict the target stability map. This versatile method can be applied to various tool setups and can accurately predict stability maps with limited experimental data (five to 10 cutting tests) even when there is little information available for unknown parameters. In conclusion, the study evaluates the proposed approach using both numerical data and experiments and demonstrates its superior performance compared to state-of-the-art benchmarks.

42 ENGINEERING↗
DOE OSTI2020

Evaluation of smart charging for electric vehicle-to-building integration: A case study

Higher electric vehicle (EV) adoption will stress the importance of demand flexibility to achieve more economic, efficient, and reliable grid operation. Charging technologies will be paramount in shifting temporally to better fit the variable generation of wind and solar. As such, analysis is warranted on the benefits of EV charge scheduling with respect to installation cost, operation cost, difficulty of implementation, and grid flexibility. We tackle this by analyzing the cost savings of implementing an EV charge scheduling infrastructure to reduce demand charges and installation costs. In this paper, we analyze a case study for operation of 16 level 2 chargers and 1 fast charger for two different building types. We then evaluate various test phases for controlling building and charging loads using an adaptive charging network (ACN) algorithm to characterize the ACN’s potential to reduce overall project cost.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

A comprehensive review of solar only and hybrid solar driven multigeneration systems: Classifications, benefits, design and prospective

Depending on the application and demands, different products can be generated utilizing multigeneration systems. To drive such systems, solar energy can be used as a primary energy source or in hybridization with other renewable or nonrenewable energy sources. Solar driven multigeneration systems are appealing due to the broad availability of solar energy and related technologies. Here, the objective of this study is to review, categorize and discuss different configurations, benefits, potentials, challenges, future research directions and market perspectives of solar energy-driven multigeneration systems, comprehensively. This study also reviews how solar energy systems can be used to hybridize systems for multigeneration purposes. Regardless of using fossil fuel backup sources, these systems are classified as (1) solar only-driven and (2) hybrid solar-driven, in which solar energy is used together with other renewable sources. Reviewing the literature demonstrates numerous ways to build solar energy-driven multigeneration systems by coupling a variety of different cycles and devices. Such systems offer multiple benefits such as enhancing the efficiency, reducing capital and operating costs and carbon dioxide emission. Hybridizing solar with other renewable energies enables continuous operation and dispatchability management. This review shows that for configuration selection and design, different thermodynamics, economic and environmental aspects should be considered. To advance the solar driven multigeneration systems development, further multidisciplinary research on different aspects of such systems is necessary. Particularly, investigations should focus on building different prototypes and on conducting experimental assessments. Also, new incentives and long-term purchase agreements for the products must be established.

14 SOLAR ENERGY↗
DOE OSTI2022

Photochemical micromotor of eccentric core in isotropic hollow shell exhibiting multimodal motion behavior

Adaptive motion behavior in response to different environmental stimuli is ubiquitous in biology and enables creatures to achieve a diversity of complex tasks, but not typically observed in synthetic systems. In this report we propose a design of chemically-powered micromotors actively performing multimodal motion behaviors with the external stimulus changing. They have isotropic outer surfaces but inherent inner mass asymmetry, such as eccentric core-in-hollow shell TiO 2 (E-TiO 2 ) microspheres. Their motion behavior can be spontaneously transformed among random Brownian propulsion (stochastic walk), negative phototaxis (moving against incident light), and negative photogravitaxis (moving against gravity) when the light intensity, illumination direction, or fuel concentration change. At a low light intensity and/or low H 2 O 2 fuel concentration, the E-TiO 2 micromotors perform directional movement away from light based on the dominated diffusiophoresis by the photocatalytic reaction over the isotropic shell. With the increase of light intensity or fuel concentration, there are more and more photons or fuels to reach the eccentric core and the contribution of the photocatalytic reaction over it to the diffusiophoresis gradually becomes dominant. In this case, the E-TiO 2 micromotors perform stochastic walks near the substrate due to their Brownian random rotational reorientations. The micromotors are single component, have low density, and can be synthesized in a large scale and at a low cost. This work will facilitate the development of multifunctional micro/nanomotors with varying behaviors and functions depending on environmental cues, e.g., enabling efficient search and delivery operations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Efficient separation and coprecipitation for simplified cathode recycling

Hydrometallurgical recycling of spent lithium-ion batteries is among the most promising recovery approaches. The current hydrometallurgical method for battery recycling faces challenges such as complex separation and precipitation processes, and environmental concerns from the use of caustic inorganic acid and hazardous hydrogen peroxide. Our proposed modified method, namely polyol-metallurgy, uses citric acid in ethylene glycol as dual-function green solution to overcome these obstacles. This bifunctional solution leaches valuable metal ions from cathode materials (e.g., LiCoO 2 ), and then acts as chelating agents to selectively precipitate cobalt through an esterification reaction, without the need for additional precipitation agents. The leaching efficiency of cobalt and lithium reaches 99.55% and 97.65%, respectively, and more than 96% of cobalt could be directly self-precipitated and recovered. Further, the unique characteristics of the dual-function solution also avoids impurities from Al foils and PVDF/carbon black films, enabling the simple separation process. Therefore, the process can be completed in one-pot system with efficient leaching, separation and coprecipitation, making it more efficient and feasible for operation than existing alternatives.

25 ENERGY STORAGE↗
DOE OSTI2025

Innovative duo-recombination layer design for effective hydrogen crossover mitigation in advanced MEAs for PEM water electrolyzers

Hydrogen crossover in proton exchange membrane water electrolyzers (PEMWEs) poses a safety hazard, reduces the overall efficiency, and limits the operational differential pressure range. Here, in this study, a membrane electrode assembly (MEA) with innovative Pt duo-recombination layer (DRL) design is developed by the unique reactive spray deposition technology (RSDT). The novel design comprises two thin RLs integrated within the volume of the membrane and has a total Pt loading of only 0.04 mg Pt cm −2 . Long-term durability test for over 3000 h is performed with as-fabricated MEA at steady-state conditions typical for an industrial hydrogen production system. The results from the durability test show that the newly developed DRL design effectively suppresses the H2 crossover to below 0.5 vol%. Furthermore, comprehensive post-test characterization of the MEA is performed and potential failure mechanisms in the Pt RLs observed during the durability test are identified and discussed in detail for the first time.

08 HYDROGEN↗
DOE OSTI2021

Multicriterion benefit evaluation methodology for safety enhancements in nuclear power plants and application for FLEX strategies

Here we propose a multicriterion benefit evaluation (MCBE) methodology for evaluating costs and benefits of implementing safety enhancements in nuclear power plants. The MCBE methodology establishes a comprehensive evaluation scope using multiple evaluation criteria (including public risk, occupational risk, plant revenue, and plant cost) and multiple contexts (including plant normal operations, incidents, and accidents). The MCBE methodology formulates a benefit or cost element as the product of a monetary consequence and its occurrence-likelihood change. The MCBE methodology also incorporates a decision maker’ preferences toward occurrence likelihood and monetary consequence into cost and benefit estimations through a modified usage of cumulative prospect theory. This paper applies the MCBE methodology to the implementation of diverse and flexible coping strategy (FLEX) in a generic nuclear power plant as an illustrative example. The FLEX benefits are evaluated through three types of influence paths: plant safety enhancement, risk-informed activities, and potential additional credit of FLEX in supporting plant operation and maintenance-efficiency improvement. The benefit-to-cost ratio (BCR) of FLEX implementation is calculated. Sensitivity analyses are conducted to examine the impacts of modeling assumptions and input parameter values on the BCR.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Debunking common myths in coastal circulation modeling

Despite tremendous progress in algorithm development, computational efficiency and transition into operations over the past two decades, coastal modeling still lacks scientific rigor due to proliferation of many ‘gray’ areas related to various modeling choices made by modelers. Here, in this paper, we propose some guiding principles for the modeling community to improve performance, and we also debunk commonly held myths that make the coastal modeling lack rigor. Using our own experience in developing seamless cross-scale unstructured-grid based models for the past two decades, we describe in unprecedented detail the end-to-end modeling process (i.e., from digital elevation models (DEMs) to mesh generation to post analysis), and demonstrate that defensible modeling is within reach for any end user by following three guiding principles: (1) Bathymetry is a first order forcing in coastal domains and thus should be respected in all aspects of modeling; (2) Oceanographic processes are driven across multiple spatial scales and so models should enable appropriate resolution as needed; and (3) Model assessment should focus on physical processes. Through qualitative and quantitative model assessments, we demonstrate the fundamental role played by bathymetry/topography as embedded in DEMs in making the results defensible, which is unfortunately glossed over in many modeling studies. Focusing on process-based assessment simplifies the calibration process. A major conclusion of this work is that model developers and operators should maximize the scientific rigor for in silico oceanography by avoiding some common pitfalls that rely on error compensation at the expense of representation of physical system processes. We present some best practice procedures for defensive and trustworthy numerical modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Generation-Storage Coordination Dispatch Strategy for Power System Based on Causal Reinforcement Learning

In the backdrop of global energy transformation, power systems integrating high proportions of renewable energy sources are facing unprecedented challenges in operational stability and dispatch efficiency. To address these challenges, this study introduces a generation-storage coordination real-time dispatch strategy based on Causal Power System Dynamic Reinforcement Learning (CPSDRL). Diverging from traditional reinforcement learning approaches, CPSDRL innovatively incorporates causal inference within the state prediction model - the crux of model-based reinforcement learning - thereby establishing the Power Causal Dynamic Model (PCDM). Assisted by the prior knowledge of power systems, the model significantly enhances prediction accuracy and reliability through a two-stage training process. Utilizing PCDM, this study further applies a direct policy search algorithm to optimize the real-time dispatch strategy. Experimental results indicate that the proposed method improves the stability of generation-storage coordination real-time dispatch and exhibits competitive advantages in sample efficiency and computational speed, compared to traditional model-based and model-free reinforcement learning algorithms. This method is expected to enhance the practicality and adaptability of causal reinforcement learning techniques in power system scheduling and control.

causal reinforcement learning↗
DOE OSTI2021

QuantImPy: Minkowski functionals and functions with Python

The Minkowski functionals and functions are a family of morphological measures and can be used to describe both the morphology (shape) and topology (connectedness) of a system. This paper presents the QuantImPy Python package which can compute both the Minkowski functionals and functions. In addition, this package can efficiently perform basic morphological operations and compute their distance maps. QuantImPy is easy to install, well documented, integrated with existing Python packages, and open source.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The heat transfer coefficient associated with a moving packed bed of silica particles flowing through parallel plates

Concentrating Solar Power (CSP) with thermal energy storage has the potential to be a renewable energy technology with long duration, inexpensive energy storage. Higher temperature operation increases the conversion efficiency and reduces the cost of energy storage. Several emerging CSP designs utilize particles as the solar receiver due to their high temperature stability and low cost. In some designs, the particles are also used as the thermal energy storage (TES) media. In either configuration, an energy transfer is required between the hot particles and the working fluid in the power cycle in a Particle-to-Fluid Heat Exchanger (PtFHX). Understanding the heat transfer between a moving packed bed and a stationary surface is critical to the successful design of a PtFHX. In this paper, a test facility is described in which a moving packed bed of silica sand with particle size 100–600 μm is introduced into the channel formed by two parallel plates, one of which is heated. The effective static thermal conductivity of the particles used for the test are separately measured over the entire range of test temperatures. The inlet and outlet bulk temperatures of the particle flow are measured as are the surface temperatures at several axial locations along the centerline of the plate. The result is the measurement of heat transfer coefficient as a function of temperature for several velocities. The uncertainty of the measurements is presented and the results are compared to model results found in the literature.

14 SOLAR ENERGY↗
DOE OSTI2025

srlife : A software tool for estimating the life of high temperature concentrating solar receivers. Part II – Ceramic receivers

As Concentrating Solar Power (CSP) technologies aim for higher operating temperatures to enhance efficiency and meet industrial process heat demands, high-temperature metallic materials, including nickel-based superalloys, face challenges in maintaining structural integrity. Advanced ceramics offer a promising alternative due to their superior high-temperature strength. However, accurately assessing the performance of ceramic components requires a fundamentally different approach from that used for metallic components. This Part II of a two-part paper describes the integration of ceramic statistical failure models within srlife – an open-source tool for predicting the life of high-temperature CSP receivers. These models account for the inherent variability in ceramic strength, as well as the effects of subcritical crack growth (SCG) under high temperature cyclic loads. Here, the paper includes an example problem that demonstrate the process of evaluating ceramic receivers using srlife. Part I details the life estimation process for metallic receivers (i.e. creep-fatigue life) along with input and output data structure, thermohydraulic analysis, and structural analysis. The complete tool is available as open-source software at https://github.com/srlife-project/srlife and can be installed via the PyPi package manager (https://pypi.org). By supporting both ceramic and metallic receiver analyses, srlife facilitates fair comparisons between competing metallic and ceramic designs, enabling accurate evaluations of plant efficiency and the economic benefits of ceramic solar receivers and other components.

High temperature ceramic receivers↗
DOE OSTI2021

A framework for integrated dispatching and charging management of an autonomous electric vehicle ride-hailing fleet

The convergence of electrification and automated driving will introduce opportunities to improve the operation and energy-efficiency of transportation systems. This paper discusses the challenges of dispatching autonomous electric vehicles (AEVs) in a ride-hailing fleet and their interactions with charging infrastructure. An integrated decision-making framework for dispatching and charging has been proposed using system optimization approaches. An agent-based platform has been developed for simulating and testing the proposed methods. A case study using New York City taxi data has been performed with different fleet sizes, dispatching strategies, and charging networks. Advantages of optimization-based approaches for AEV fleet management have been studied and demonstrated, for example, for a fleet of 1,750 AEVs to meet 100,000 daily requests, optimization-based centralized fleet management would result in 14% more ride requests satisfied and 43% fewer zero-occupancy miles traveled than if AEVs make independent decisions based on heuristic strategy. Benefits on reducing fleet size and charging downtime from optimization approaches are also comprehensively illustrated.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Robust, Accurate, and Efficient: Quantum Embedding Using the Huzinaga Level-Shift Projection Operator for Complex Systems

Using wave function (WF) in density functional theory (DFT) embedding methods provides a framework for performing localized, high-accuracy WF calculations on a system, while not incurring the full computational cost of the WF calculation on the full system. To effectively partition a system into localized WF and DFT subsystems, we utilize the Huzinaga level-shift projection operator within an absolutely localized basis. In this work, we study the ability of the absolutely localized Huzinaga level-shift projection operator method to study complex WF and DFT partitions, including partitions between multiple covalent bonds, a double bond, and transition-metal–ligand bonds. We find that our methodology can accurately describe all of these complex partitions. Additionally, we study the robustness of this method with respect to the WF method, specifically where the embedded systems were described using a multiconfigurational WF method. We found that the method is systematically improvable with respect to both the number of atoms in the WF region and the size of the basis set used, with energy errors less than 1 kcal/mol. Additionally, we calculated the adsorption energy of H2 to a model of an iron metal–organic framework (Fe-MOF-74) to within 1 kcal/mol compared to CASPT2 calculations performed on the full model while incurring only a small fraction of the full computational cost. In conclusion, this work demonstrates that the absolutely localized Huzinaga level-shift projection operator method is applicable to very complex systems with difficult electronic structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗