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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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Saratoga Energy has developed a system for making graphite from carbon dioxide. LBNL has experience in benchmarking graphites for Li-ion battery applications. In half cells, we tested graphites for their reversible capacity and their rate capability. They used this data to support a phase II proposal that was funded by DOE to scale up their best material and test in larger cells.
The United States Department of Energy (DOE) established the Concentrating Solar Power Generation 3 (CSP Gen3) program to promote the development of advanced CSP systems capable of producing electricity at a levelized cost of energy (LCOE) less than $60/MWh, based on criteria published in the CSP Gen3 Roadmap and a subsequent funding opportunity announcement (Gen3 FOA). This report documents the progress and potential of the “Liquid Pathway” to meet these objectives. The Liquid Pathway proposes the use of low-cost molten chloride salts for energy storage, mated with an operationally flexible solar receiver that employs liquid-metal sodium for heat capture and transfer to the storage salt. This approach leverages molten-salt technology from the current state-of-the-art CSP power towers embodied by plants such as Gemasolar, Crescent Dunes, Noor III, and the DEWA 700 CSP project. Furthermore, the design builds on the knowledge gained over decades of use of liquid-metal sodium as a high-temperature heat transfer fluid (HTF) in solar tests and nuclear-power applications. The commercial representation of the proposed Gen3 design incorporates a high-efficiency sodium receiver operating at ~740°C, with a liquid-liquid heat exchanger feeding a two-tank, molten-chloride salt storage system. Chloride salt is dispatched to a supercritical CO 2 (sCO 2 ) power cycle to provide electric power to the grid. The design integration is a conceptual match for the current sodium receiver → solar salt storage → steam-Rankine power cycle promoted by developer Vast Solar, which may facilitate commercial acceptance and development.
The Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility at Los Alamos National Laboratory (LANL) is the world’s first flash x-ray facility able to take multiple high-resolution radiographs of the interior features of fast-moving dense objects during a single experiment. DARHT’s radiography and complimentary diagnostics makes it an important diagnostic tool in support of the US Department of Energy’s (DOE)/National Nuclear Security Administration (NNSA)’s stewardship of the US nuclear deterrent. The project to construct DARHT ran from 1988 through 2003. Initial Operating Capability along a single axis began in 1999. A technical issue delayed Critical Decision 4 for the full dual-axis capability until 2008. DARHT was characterized by several directed changes resulting from an environmental impact study, changes to the global security context resulting from the end of underground nuclear testing, and rapid evolution of applicable technology. Conventional building and lab-space construction were part of the project, but the project was dominated by Special Facility Equipment that, together with the mission to support the nuclear weapons program, required the project to be completed by national laboratories. Although the project pre-dated implementation of DOE Order 413.3, several important lessons for national laboratory projects remain applicable today and will be discussed here, including projects appropriate for the national laboratory environment, scope stability, risk acceptance and mitigation, communication, and collaboration. Finally, considerations for DOE contractor project managers are offered based upon the DARHT experience.
Radiographic imaging and tomography (RadIT) come in many flavors such as X-ray imaging and tomography (IT), proton IT, neutron IT, muon IT, neutrino IT, etc. We identify five RadIT themes: Physics, Sources, Detectors, Methods, and Data Science, which are integral parts of image interpretation and three-dimensional (3D) tomographic reconstruction. Traditionally, RadIT have been driven by medicine, non-destructive testing, material sciences, and security applications. The latest thrusts of growth come from automation, machine vision, additive manufacturing and virtual reality (‘metaverse’). The five RadIT themes parallel their counterparts in optical IT. Synergies among different forms of RadIT and with optical IT motivate further advances towards multi-modal IT and quantum IT.
The focus of the project is on building an innovative accelerated materials design platform for molten salt technologies using novel high-throughput methods coupled to data analytics. The main objectives is to predict a FeCrMnNi alloy compositional space with better corrosion resistance than stainless steel 316 and identify new molten salt corrosion mechanisms. The project demonstrates the feasibility to use high-throughput methods coupled to data analytics to accelerate alloy design for extreme environments applications. Using a trained and tested machine learning (ML) model, 2000 FeCrMnNi alloy corrosion rate in molten chloride salts were predicted and a compositional field with corrosion rate lower than 316 stainless steel was identified. The ML model interpretability unveiled multiple features of importance in the model prediction. Some features were expected to be of relative significance, such as work function, surface energy and alloy electronegativity, and the ML model interpretability analysis confirmed those. On the other hand, the most important feature is the diffusion coefficient of Ni in the bulk alloy which indicates that a surface diffusion mechanism plays an important role in the overall corrosion mechanism in molten salts.
A formulation for a dimensionless coefficient c b is derived that represents a scale of microstructural softening for alloys which follow Kocks-Mecking (K-M) work hardening behavior. The variation of the true plastic strain ε p between the proportional limit σ y and the strength σ u at the instability is determined using the Considère criterion. Parameterization of the model is limited to variables expressly measured within tensile experiments. Further development is now made for the softening factor c bi through the individual and sequential stages 3 and 4 of plastic deformation during K-M work hardening Q behavior. Application is shown for tensile test results of Ti-6Al-4V made by different additively manufactured (AM) processes. It is found that the variation in plastic strain as a function of c bi produces a continuous curve representative of the alloy system. The results of data analysis indicate that Θ o3 and c b3 increase, while Θ o4 and c b4 decrease, as the total plastic strain ε p increases. Furthermore, formulations derived for K-M stages 3 and 4 enable the evaluation of other material parameters such as the activation volume ν* for the onset of plastic deformation. This activation volume is found to be near constant, at a ν*-value of 0.353±0.036 nm 3 as computed using a strain-rate sensitivity of strength exponent m of 0.014, irrespective of the AM method used to produce the Ti-6Al-4V alloy.
In this work, we have tested individual and combination of applications of ozonolysis and liquid hot water (LHW) to pretreat sugarcane bagasse (SCB) for the removal of enzyme and/or microbial inhibitors and generation of potential value-added chemicals. A solid content with 80% cellulose and a liquid phase (liquor) rich in phenolic derived compounds (3 g . L −1 ) from lignin, sugars (>20 g . L −1 ), and other compounds, such as furfural and hydroxymethylfurfural (HMF), were generated. Maximal (59%) glucan conversion occurred in the presence of double-pretreated bagasse, which had 32–50% more glucan available than the samples that were individually LHW or ozone-pretreated, resulting in maximal ethanol production (92% after 42 h) from double-pretreated SCB enzyme hydrolyzate. In summary, this work showed that ozone reacts effectively with lignin without the use of any other chemical reagent, and LHW pretreatment, followed by a washing step, was effective in solubilizing and cleaning up the fiber enzyme and microbial inhibitory compounds with ozone being effective against phenolics. Moreover, the generated cellulose-rich substrate is readily fermentable. The acidic liquor fraction removed by sequential washings and containing mainly sugars and phenolic compounds may be evaluated for use in green chemistry bioconversions processes.
This paper summarizes the literature on detection of islanding resulting from distributed generating capabilities in a power distribution system, with emphasis on the rural distribution systems. It is important to understand the legacy technology and equipment in the rural distribution electrical environment due to the growth of power electronics and the potential for adding the new generations of intelligent sensors. The survey identified four areas needing further research: 1. Robustness in the presence of distribution grid disturbances; 2. the future role of artificial intelligence in the islanding application; 3. more realistic standard tests for the emerging electrical environment; 4. smarter sensors. In addition, this paper presents a synchro-phasor-based islanding detection approach based on a wireless sensor network developed by the University of Texas at Austin. Initial test results in a control hardware-in-the-loop (CHIL) simulation environment suggest the effectiveness of the developed method.
Simulated galaxy distributions are suitable for developing filament detection algorithms. However, samples of observed galaxies, being of limited size, cause difficulties that lead to a discontinuous distribution of filaments. We created a new galaxy filament catalog composed of a continuous cosmic web with no lone filaments. The core of our approach is a ridge filter used within the framework of image analysis. We considered galaxies from the HyperLeda database with redshifts 0.02 ≤ z ≤ 0.1, and in the solid angle 120° ≤ R.A. ≤ 240°, 0° ≤ decl. ≤ 60°. We divided the sample into 16 two-dimensional celestial projections with redshift bin Δ z = 0.005, and compared our continuous filament network with a similar recent catalog covering the same region of the sky. We tested our catalog on two application scenarios. First, we compared the distributions of the distances to the nearest filament of various astrophysical sources (Seyfert galaxies and other active galactic nuclei, radio galaxies, low-surface-brightness galaxies, and dwarf galaxies), and found that all source types trace the filaments well, with no systematic differences. Next, among the HyperLeda galaxies, we investigated the dependence of the g - r color distribution on the distance to the nearest filament, and confirmed that early-type galaxies are located on average further from the filaments than late-type ones.
Building energy modeling (BEM) has been widely used by researchers, regulators, and engineers to quantify building energy performance. Quality assurance (QA) and quality control (QC) of the model's performance are essential parts of such analysis. Currently, QA/QC is done in a manual and ad-hoc manner, which is tedious, error-prone, and time-consuming when QA/QC a large number of models. To solve these challenges, we propose a a dAta-driveN buIlding perforMance verificATion framEwork (ANIMATE), which conducts automated output-based verification of building operations requirements (especially for time-series output-based verification of control requirements). While this framework was developed for verifying energy model performance, it can be extended for other applications such as BEM software testing and performance verification of real buildings in the field.
This paper aims to forecast high-resolution (hourly) aggregated load for a certain region in the medium term (a few days to over a year). One region is defined as some places with similar climate characteristics because the climate influences people's daily lifestyles and hence the electric usage. We decompose the electric usage records into two parts: base load and seasonal load. Considering both temperature and time factors, different deep-learning methods are adopted to characterize them. The first goal of our approach is to predict the peak load which is critical for power system planning. Furthermore, our proposed forecast method can provide the depiction of the hourly load profile to provide customized load curves for high-level real-time applications. The proposed method is tested on real-world historical data collected by CAISO, BPA, and PACW. The experimental results show that trained by three years of data, our method could reduce the prediction error for a one-year lead hourly load below $5\%$ MAPE, and predict the occurrence of the peak load for next year in CAISO with an error within three days. Furthermore, as a byproduct, an interesting observation on the impact of COVID-19 on human life was made and discussed based on these case studies.
This paper aims to forecast high-resolution (hourly) aggregated load for a certain region in the medium term (a few days to over a year). One region is defined as some places with similar climate characteristics because the climate influences people's daily lifestyles and hence the electric usage. We decompose the electric usage records into two parts: base load and seasonal load. Considering both temperature and time factors, different deep-learning methods are adopted to characterize them. The first goal of our approach is to predict the peak load which is critical for power system planning. Furthermore, our proposed forecast method can provide the depiction of the hourly load profile to provide customized load curves for high-level real-time applications. The proposed method is tested on real-world historical data collected by CAISO, BPA, and PACW. The experimental results show that trained by three years of data, our method could reduce the prediction error for a one-year lead hourly load below 5% MAPE, and predict the occurrence of the peak load for next year in CAISO with an error within three days. Furthermore, as a byproduct, an interesting observation on the impact of COVID-19 on human life was made and discussed based on these case studies.
Rapid solidification (RS) is a field of study that has increased in importance due to the rise of additive manufacturing (AM) techniques. The breakdown of equilibrium at the solid-liquid interface results in an inability to use traditional solidification models that have been applied to great success in casting. As such, there is a current need for a high-throughput testing method to screen alloys at rapid solidification conditions without the significant cost for powder atomization. In this work, twin hammer splat quenching (SQ) is utilized and theoretically developed as a technique uniquely placed to test alloy systems for AM applications. Using analytical thermal spray models and numerical heat transfer simulations, the cooling rate and solidification conditions of splat quenching are compared across several parameters to evaluate the key parameters for generating cooling rates relevant to AM process. Once a framework for the cooling rates and relevancy of SQ are developed, SQ was used to process alloy compositions in the Ti5553 alloy space (AMS 7026) to study the formation of detrimental secondary phases occurring upon rapid quenching from the melt. A martensitic phase is found to occur at the lower end of the standard, but the composition listed in the standard were found to be safe. Finally, the rapid solidification behavior of Ti-5553 is evaluated by comparing splat quenching, laser welding, and plasma atomization that offer a wide window of solidification conditions. The segregation and solidification structure are analyzed and compared to models to provide a deeper understanding of the solidification behavior of beta stabilized titanium alloys.
A method and corresponding apparatus are provided for measuring neutron spin precession in an electric field with high sensitivity suitable for practical applications in non-destructive testing, imaging, and the like. Production of a neutron beam with a polarization vector P is followed by transmitting the spin-polarized neutron beam through a sample region in which there is a target generating an electric field, polarization-analyzing the transmitted neutron beam with an analyzing direction orthogonal to P, detecting an intensity of the polarization-analyzed neutron beam; and mapping the detected neutron-beam intensity to a field-strength value for the target electric field.
This paper presents an overview of the DOE Marine Biofuel Feasibility Study to evaluate the potential of biofuels for ocean-going vessels. These vessels operate on low-cost residual fuel oils (also known as heavy fuel oils or HFO), which require significant heating and purification onboard vessels. The industry is looking at economical alternative fuels that can enhance performance from combustion/emissions, rheology, and other perspectives. Four U.S. national laboratories are collaborating to evaluate a variety of biofuels, including bio-intermediates (pyrolysis and hydrothermal liquefaction oils), biodiesel (fatty acid methyl esters or FAME), bio-residuals (FAME byproducts) for their suitability as fuels for marine diesel engines. Bio-intermediates in particular are of interest because large marine engines that operate on HFO can tolerate lowerquality, more viscous fuels and may be able to utilize these fuels with less upgrading than other applications, presenting economic advantages. The test fuels of interest are examined to determine the minimum level of upgrading required for blend compatibility with market HFOs containing high levels of asphaltenes as well as their impact on the viscosity, polymerization tendency, and combustion properties (particularly cetane number) of the fuel blends in preparation for future evaluation in engine studies.
Engineering problems are generally solved by analytical models or computer codes. These models, in addition to conservation equations, also include many empirical relationships and approximate numerical methods. Each of these components contributes to the uncertainty in the prediction. A systematic approach to judge the applicability of the code to the intended application is needed. It starts from verification of implementation of formulation in the code, identification of important phenomena, finding relevant tests with quantified uncertainty for these phenomena, and validation of the code by comparing predictions with the relevant test data. The relevant tests must address phenomena as expected in the intended application. In case of small size or limited condition tests, the scaling analyses are needed to assess the relevancy of the tests. Finally, a statement of uncertainty in the prediction is needed. Systematic approaches are described to aggregate uncertainties from different components of the code for intended application. Here, verification, validation, and uncertainty quantifications (VVUQs) are briefly described.
Clay-polymer nanocomposites (CPNs) have been studied for two decades as sorbents for water pollutants, but their applicability remains limited. Our aim in this review is to present the latest progress in CPN research using a meta-analysis approach and identify key steps necessary to bridge the gap between basic research and CPN application. Based on results extracted from 99 research articles on CPNs and 8 review articles on other widely studies sorbents, CPNs had higher adsorption capacities for several inorganic and organic pollutant classes (including heavy metals, oxyanions, and dyes, n = 308 observations). We applied principal component analysis, analysis of variance, and multiple linear regressions to test how CPN and pollutant properties correlated with Langmuir adsorption model coefficients. While adsorption was, surprisingly, not influenced by mineral properties, it was influenced by CPN fabrication method, polymer functional groups, and pollutant properties. For example, among the pollutant classes, heavy metals had the highest adsorption capacity but the lowest adsorption affinity. Conversely, dyes had high adsorption affinities, as reflected by the linear correlation between adsorption affinity and pollutant molecular weight. Scaling from ‘basic research’ to ‘technological application’ requires testing CPN performance in real water, application in columns, comparison to commercial sorbents, regeneration, and cost evaluation. However, our survey indicates that of the 158 observations, only 20 compared the CPN's performance to that of a commercial sorbent. We anticipate that this review will promote the design of smart and functional CPNs, which can then evolve into an effective water treatment technology.
Heat exchangers with excellent corrosion and oxidation resistances are essential for the next-generation concentrating solar power (CSP) plants using a molten salt heat transfer fluid and a supercritical CO 2 Brayton power cycle that can operate at temperatures > 700 °C for higher efficiencies. Techniques were developed for additively manufacturing ceramic materials for applications involving high temperature, high pressure, and high corrosion resistance as needed for the CSP application. Based on a previous ceramic heat exchanger design with its cross-section geometry of the flow channels optimized for heat transfer and mechanical strength, lab-scale prototype heat exchangers, with integrated headers and incorporated flow channel dimensional compensations, were fabricated by using the binder jetting process. The printed prototype heat exchangers were successfully densified through the processes of liquid polymer infiltration and pyrolysis. In addition, thermophysical properties of the densified silicon carbide parts were measured to provide necessary design information. Experimental heat transfer testing of the lab-scale prototype heat exchanger was conducted, and the experimental data agreed reasonably well with the simulated results. Furthermore, this agreement provides validation of the simulation models for their applicability to the development of a full-scale ceramic heat exchanger.