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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Evaporation of Cu, Sn, and S from Fe-C-Cu-Sn-S Liquid Alloys in the Temperature Range from 1513 K to 1873 K (1240 °C to 1600 °C)

Evaporation of Cu or Sn from liquid iron alloys containing C and S was experimentally investigated. The initial C concentration, [pct C] 0 , in the liquid alloy was varied from zero to C saturation, and the evaporation temperature was varied from 1513 K to 1773 K (1240 °C to 1500 °C). Along with the report by one of the present authors, the evaporation mechanism of Cu and Sn from liquid Fe-C-S alloy is proposed, after a modification from the previous mechanism. It was proposed that Cu and Sn evaporate as Cu(g) and Sn(g) and also evaporate as CuS(g) and SnS(g), which are more volatile species. Therefore, availability of S in the alloy affects the overall evaporation rate of Cu and Sn. At the same time, C in the alloy also forms volatile carbosulfides CS(g) and CS 2 (g), thereby competing with Cu and Sn. Moreover, C increases the activity coefficients of Cu, Sn, and S. This increases the thermodynamic driving force for the formation of CuS(g) and SnS(g). Therefore, increasing [pct C] partly accelerates the evaporation rate of Cu and Sn by increasing the activity coefficient but partly decelerates the evaporation rate by lowering the available S content. S partly accelerates the evaporation rate by increasing the available S for the sulfide gas species but partly decelerates the evaporation rate due to the surface poisoning effect. Increasing the reaction temperature increases the overall evaporation rate. All these facts were taken into account in order to develop an evaporation rate model. This model was extended from the present authors’ previous one by taking into account (1) CS(g), S(g), and CS{ 2 (g) (therefore, the following species were considered as dominant evaporating species: Cu(g), CuS(g), Sn(g), SnS(g), S(g), CS(g), and CS 2 (g)); (2) the effect of C and temperature on the activity coefficients of Cu, Sn, and S; (3) the effect of C and temperature on the density of the liquid alloy; and (4) the effect of temperature on the S adsorption coefficient. This revised evaporation model was used in order to explain the experimental data, and it showed good agreement. In particular, it was found that the temperature showed a significant effect on the evaporation rate, and the effect of temperature and C content on the activity coefficients of Cu, Sn, and S also significantly affected the evaporation rate. The chemical reaction rate constant of the individual evaporation reaction (k i } R ) and residual rate constant (k i r ) could be obtained as a function of temperature. The activation energy of each evaporation reaction was derived and discussed. The evaporation rate model can be applied in order to predict the content of Cu and Sn remaining in liquid iron under various conditions of temperature and [pct C].

36 MATERIALS SCIENCE↗
DOE OSTI2017

Optimizing biomass feedstock blends with respect to cost, supply, and quality for catalyzed and uncatalyzed fast pyrolysis applications

Here, biomass cost, quality and quantity are important parameters to consider when choosing feedstocks and locations for biorefineries. Biomass cost is dependent upon type, location, quantities available in a given area and logistics costs as well the quality needed for the biorefinery. Biomass quality depends upon type, growth conditions, weather, harvesting methods, storage conditions as well as any preprocessing methods used to improve quality. Biomass quantity depends heavily on location as well as growth conditions, weather, harvesting methods and storage conditions. This study examines how all three of these parameters affect the biomass mixture that is needed in a biomass depot or biorefinery to achieve the lowest cost with the highest quality and at the quantities needed for biorefinery operation. Four biomass depots were proposed in South Carolina that would each process the predominant type of biomass available in that area and each produce 200,000 tons of feedstock per year. These depots would then feed a centrally located 800,000 ton biorefinery that would convert the feedstocks to pyrolysis oil using either catalyzed or uncatalyzed fast pyrolysis. The four depots each needed to produce different blends of biomass based upon the quantities available to them but still meet the minimum quality requirements for the biorefinery. Costs were minimized by using waste biomass resources such as construction and demolition waste, logging residues and forest residuals. Depending upon the quality specification required by the biorefinery, it was necessary to utilize preprocessing methods such as air classification and acid leaching to upgrade biomass quality. In the case of uncatalyzed fast pyrolysis, all four depots could produce biomass blends that were lower cost than the the preferred pyrolysis feedstock, clean pine, and meet quality and quantity specifications. For catalyzed fast pyrolysis, three of the four depots were able to produce blends that met both quality and quantity specifications at minimum cost. The fourth depot would not be able to produce a blend meeting specifications without increasing the supply radius for the depot.

09 BIOMASS FUELS↗
DOE OSTI2023

Methodology for Thermodynamic Analysis Coupled with Computational Fluid Dynamics Modeling for Casting a Novel Aluminum–Cerium Alloy

In this paper, we present the results of computational fluid dynamics (CFD) analysis to assess castability, porosity, molten metal fluidity and other technological properties of a new Al-Ce alloy. A thermodynamic analysis of a new Al-Ce alloy is done to obtain the physical properties as a function of temperature across both solid and liquid phases. These properties are then used to build the CFD of model the full casting process from initial pouring through to final solidification of the part, here an example of a heavy duty mor mount is used. While several excellent commercial CFD codes exists this process shows that CFD can be used to assess the capability of the alloy to properly fill the mold, as well as give predictions where scattered porosity or large-scale defects may occur in the casting. Further, unlike the commercially available software (e.g., ProCAST, SOLIDCast , MAGMASOFT®) the complex 3D-analysis of the stress / strain fields in cast parts is not performed at this time. However, the availability of free software for assessing the required thermodynamic / thermo-physical properties of new alloys (OpenCALPHAD) and CFD codes such as OpenFOAM® makes the developed option attractive and economical, especially for the analysis of new Al-Ce alloys, for which the available data does not exist.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Physics-informed machine learning for building performance simulation-A review of a nascent field

Building performance simulation (BPS) is critical for understanding building dynamics and behavior, analyzing the performance of the built environment, optimizing energy efficiency, improving demand flexibility, and enhancing building resilience. However, conducting BPS is not trivial. Traditional BPS relies on accurate building energy models, which are primarily physics-based and heavily dependent on detailed building information, expert knowledge, and case-by-case model calibrations, significantly limiting their scalability. With the development of sensing technology and the increased availability of data, there is growing attention and interest in data-driven BPS. However, purely data-driven models often suffer from limited generalization ability and a lack of physical consistency, resulting in poor performance in real-world applications. To address these limitations, recent studies have begun integrating physics priors into data-driven models, a methodology known as physics-informed machine learning (PIML). PIML is an emerging field where its definitions, methodologies, evaluation criteria, application scenarios, and future directions remain open. To bridge those gaps, this study systematically reviews the state-of-the-art PIML for BPS, offering a comprehensive definition of PIML and comparing it to traditional BPS approaches regarding data requirements, modeling effort, performance, and computational cost. We also summarize the commonly used methodologies, validation approaches, application domains, available data sources, open-source packages, and testbeds. In addition, this study provides a general guideline for selecting appropriate PIML models based on BPS applications. Finally, this study identifies key challenges and outlines future research directions, providing a solid foundation and valuable insights to advance R&D of PIML in BPS.

Jiang, Zixin↗
DOE OSTI2017

Competition for light and water in a coupled soil-plant system

Here, it is generally accepted that resource availability shapes the structure and function of many ecosystems. Within the soil-plant-atmosphere (SPA) system, resource availability fluctuates in space and time whereas access to resources by individuals is further impacted by plant-to-plant competition. Likewise, transport and transformation of resources within an individual plant is governed by numerous interacting biotic and abiotic processes. The work here explores the co-limitations on water losses and carbon uptake within the SPA arising from fluctuating resource availability and competition. In particular, the goal is to unfold the interplay between plant access and competition for water and light, as well as the impact of transport/redistribution processes on leaf-level carbon assimilation and water fluxes within forest stands. A framework is proposed that couples a three-dimensional representation of soil-root exchanges with a one-dimensional description of stem water flow and storage, canopy photosynthesis, and transpiration. The model links soil moisture redistribution, root water uptake, xylem water flow and storage, leaf potential and stomatal conductance as driven by supply and demand for water and carbon. The model is then used to investigate plant drought resilience of overstory-understory trees simultaneously competing for water and light. Simulation results reveal that understory-overstory interactions increase ecosystem resilience to drought (i.e. stand-level carbon assimilation rates and water fluxes can be sustained at lower root-zone soil water potentials). This resilience enhancement originates from reduced transpiration (due to shading) and hydraulic redistribution in soil supporting photosynthesis over prolonged periods of drought. In particular, the presence of different rooting systems generates localized hydraulic redistribution fluxes that sustain understory transpiration through overstory-understory interactions. Such complex SPA dynamics cannot be properly summarized by equivalent ecosystem-scale Resistor-Capacitor (RC) rep- resentation. However our results show that, with proper averaging across water flow paths, RC models can provide reasonable estimates of stand-level water and carbon fluxes during inter-storm periods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An uncertainty quantification method relevant to material test reactors

Within material test reactor calculations, energy dependent flux and reaction rate uncertainties are typically not quantified when performing as-run analyses to determine the neutron field experienced by the experiment. When high fidelity Monte-Carlo codes are used in such analyses, straight forward methods to calculate output uncertainties are not available, instead expert opinion is used to postulate computational uncertainties. New methods to propagate uncertainties through these high fidelity simulations are available when sufficient computational power is available. A tool is developed here for sampling any part of an MCNP input from random distributions to determine output uncertainties based on those inputs. Another tool is developed to sample nuclear data cross-section in ACE format using multi-group nuclear data covariances. The Total Monte-Carlo Method and Gesellschaft für Anlagen-und Reaktorsicherheit method (GRS) are implemented and compared to one another as well as MCNP sensitivity and uncertainty calculations. The methods were applied to the Godiva critical sphere k-eigenvalue, the UAM pin-cell benchmark energy dependent flux and reaction rates, and the Advanced Test Reactor energy dependent flux within an experimental location. Furthermore, the two methods agree well, with GRS allowing for an order of magnitude speedup for reaction rate uncertainty calculations and several orders of magnitude for eigenvalue uncertainty calculations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Numerical modeling study of a man-made low-permeability barrier for the compressed air energy storage in high-permeability aquifers

Compressed air energy storage (CAES) is a grid-scale energy storage technology for intermittent energy, as proven by the decades-long successful operation of two existing compressed air energy storage in cavern (CAESC) power plants. Because of the limited availability of salt domes appropriate for CAESC, the more widely available aquifers (compressed air energy storage in aquifers, CAESA) have recently attracted considerable attention as candidates for CAES. An ideal aquifer for CAESA is highly permeable around the well to facilitate easy injection and withdrawal of air, but the high-permeability region is surrounded by low-permeability zones to minimize the loss of injected air and decrease in energy efficiency. However, such ideal geological structures are not always available in nature. Therefore, the potential of creating man-made low-permeability barrier in high-permeability aquifers is very interesting. In this paper, we investigate the feasibility of man-made low-permeability barriers in high-permeability aquifers using the numerical simulator TOUGH2/Gel to calculate the three-component flow (including a miscible gelling liquid). The simulation results show that an expected low-permeability barrier can be created by injecting grout with certain properties, and the altered aquifer performs well for CAESA. Additional sensitivity studies are also performed to reveal the effects of the various factors on the success of the low-permeability barrier creation, including the critical solidification concentration, the scale factor of the time dependence of the grout viscosity, the relative density of the grout, and the volume of the follow-up water injection. The results indicate that, in a horizontal aquifer, low critical solidification concentrations, and small scale factors are generally preferred and the density of grout should be close to that of the in situ water. For the given volume of the injected grout, there is an optimal follow-up water injection that will create the largest storage space without damaging the barrier. Furthermore, these results may help to extend the candidate sites for CAESA and the prospect of large scale energy storage.

25 ENERGY STORAGE↗
DOE OSTI2019

Sensitivity of Western U.S. power system dynamics to droughts compounded with fuel price variability

The energy sector is heavily dependent on surface water availability for reliable electricity generation. Power system operations are usually evaluated through system reliability and economic perspectives, with assumptions based on market prices and normal water availability. As natural gas technologies continue to dominate new thermal capacity, replacing retiring coal and nuclear generators, natural gas price stability becomes increasingly important and the impact of price volatility on grid operations must be understood. Here, we explore the range of Western Electricity Coordinating Council (WECC) regional power operations, which represents the electric interconnection over the western half of the continental United States, using a production cost model driven by different fuel prices and an integrated hydrology model to simulate historical water availability. Our results show system-wide operation costs increasing in drought years or when gas prices increase, as expected. In addition, we found those system-wide increases can be of the same magnitude. Regional analysis of the responses to compounded droughts and price volatility highlight differences in magnitude and direction depending on regional generation technology portfolios. The Pacific Northwest is most sensitive to drought conditions, Southern California is most sensitive to gas prices, and the Desert Southwest is sensitive to both with the same magnitude. This analysis motivates further research in combined hydrology and power system modeling to characterize regional dynamics and associated uncertainties across scales, which is an important underpinning for the development of more resilient energy and water systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Modeling the impact of extreme summer drought on conventional and renewable generation capacity: Methods and a case study on the Eastern U.S. power system

Across recent years, there has been a growing prevalence of extreme weather events throughout the United States, posing significant challenges to the reliable and resilient operation of power systems. Specifically, summer droughts threaten to severely reduce available generation capacity to meet regional electricity demand, potentially leading to power outages. This underscores the importance of accurate resource adequacy (RA) assessment to ensure the reliable operation of the nation’s energy infrastructure. Accurately evaluating the usable capacity of regional generation fleets is a challenging undertaking due to the intricate interactions between power systems and hydro-climatic systems. Here, this paper proposes a systematic and analytical framework to evaluate the impacts of extreme summer drought events on the available capacity of various generating technologies, incorporating both meteorological and hydrologic factors. The framework provides detailed plant-level capacity derating models for hydroelectric, thermoelectric, and renewable power plants, facilitating evaluations with high temporal and spatial resolution. The application of the proposed impact assessment framework to the 2025 generation fleet of the real-world power system within the PJM and SERC regions of the United States yields insightful results. By analyzing the daily usable capacity of 6,055 at-risk generators across the study region, it shows that the summer capacity deration is most significant for hydroelectric and once-through thermal power plants, followed by recirculating thermal power plants and combustion turbines. In the event of the recurrence of the 2007 southeastern summer drought event in the near future, the generation fleet could experience a substantial reduction in available capacity, estimated at approximately 8.5 GW, compared to typical summer conditions. The sensitivity analysis reveals that the usable capacity of the generation fleet would suffer an even more significant decrease under conditions of increasingly severe summer droughts. The proposed approach and the findings of this study provide valuable methodologies and insights, empowering stakeholders to bolster the resilience of power systems against the potentially devastating effects of future extreme drought events.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

A Bayesian Modeling Approach for Estimation of a Shape-Free Groundwater Age Distribution using Multiple Tracers

The mixing of groundwaters with different ages in aquifers, groundwater age is more appropriately represented by a distribution rather than a scalar number. To infer a groundwater age distribution from environmental tracers, a mathematical form is often assumed for the shape of the distribution and the parameters of the mathematical distribution are estimated using deterministic or stochastic inverse methods. We found that the prescription of the mathematical form limits the exploration of the age distribution to the shapes that can be described by the selected distribution. In this paper, the use of freeform histograms as groundwater age distributions is evaluated. A Bayesian Markov Chain Monte Carlo approach is used to estimate the fraction of groundwater in each histogram bin. This method was able to capture the shape of a hypothetical gamma distribution from the concentrations of four age tracers. The number of bins that can be considered in this approach is limited based on the number of tracers available. The histogram method was also tested on tracer data sets from Holten (The Netherlands; 3 H, 3 He, 85 Kr, 39 Ar) and the La Selva Biological Station (Costa-Rica; SF 6 , CFCs, 3 H, 4 He and 14 C), and compared to a number of mathematical forms. According to standard Bayesian measures of model goodness, the best mathematical distribution performs better than the histogram distributions in terms of the ability to capture the observed tracer data relative to their complexity. Among the histogram distributions, the four bin histogram performs better in most of the cases. The Monte Carlo simulations showed strong correlations in the posterior estimates of bin contributions, indicating that these bins cannot be well constrained using the available age tracers. The fact that mathematical forms overall perform better than the freeform histogram does not undermine the benefit of the freeform approach, especially for the cases where a larger amount of observed data is available and when the real groundwater distribution is more complex than can be represented by simple mathematical forms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Characterization of 244 Cm Neutron Sources

There is a need to find a replacement for the 252 Cf sources currently used in Standards-based performance testing of neutron instrumentation. This is a result of its relatively short half-life, concerns about future availability and recent increases in cost. A potential replacement source, 244 Cm is evaluated in this study where two commercially available sources have been acquired and their neutron emission spectra measured using a pair of spectrometers. Both instruments showed the 244 Cm spontaneous neutron spectrum to be fully consistent with a MCNP6®-calculated spectrum using published Watt fission parameters for 244 Cm. In addition, the emission rate of the weaker 244 Cm source was established through a direct count rate comparison against a calibrated and similarly encapsulated 252 Cf source. The 244 Cm source emission rate was found to be in excellent agreement with value stated on the manufacturer's source certificate. It is concluded that 244 Cm would be an ideal replacement for 252 Cf based on its longer half-life (18.1 y) and its essentially identical neutron emission spectrum. In addition, 244 Cm sources are commercially available at reasonable cost.

244Cm↗
DOE OSTI2015

Gear-box fault detection using time-frequency based methods

Gear-box fault monitoring and detection is important for optimization of power generation and availability of wind turbines. The current industrial approach is to use condition monitoring systems, which runs in parallel with the wind turbine control system, using expensive additional sensors. An alternative would be to use the existing measurements which are normally available for the wind turbine control system. The usage of these sensors instead would cut down the cost of the wind turbine by not using additional sensors. One of these available measurements is the generator speed, in which changes in the gear-box resonance frequency can be detected. Two different time-frequency based approaches are presented in this paper. One is a filter based approach and the other is based on a Karhunen-Loeve basis. Both of them detects the gear-box fault with an acceptable detection delay.

Odgaard, Peter Fogh↗

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