SEARCH · Engineering Papers

Results for “process mining”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 757 records · Page 42

All sources NASA NTRS DOE OSTI

DOE OSTI2024

Simultaneously improving accuracy and computational cost under parametric constraints in materials property prediction tasks

Abstract Modern data mining techniques using machine learning (ML) and deep learning (DL) algorithms have been shown to excel in the regression-based task of materials property prediction using various materials representations. In an attempt to improve the predictive performance of the deep neural network model, researchers have tried to add more layers as well as develop new architectural components to create sophisticated and deep neural network models that can aid in the training process and improve the predictive ability of the final model. However, usually, these modifications require a lot of computational resources, thereby further increasing the already large model training time, which is often not feasible, thereby limiting usage for most researchers. In this paper, we study and propose a deep neural network framework for regression-based problems comprising of fully connected layers that can work with any numerical vector-based materials representations as model input. We present a novel deep regression neural network, iBRNet, with branched skip connections and multiple schedulers, which can reduce the number of parameters used to construct the model, improve the accuracy, and decrease the training time of the predictive model. We perform the model training using composition-based numerical vectors representing the elemental fractions of the respective materials and compare their performance against other traditional ML and several known DL architectures. Using multiple datasets with varying data sizes for training and testing, We show that the proposed iBRNet models outperform the state-of-the-art ML and DL models for all data sizes. We also show that the branched structure and usage of multiple schedulers lead to fewer parameters and faster model training time with better convergence than other neural networks. Scientific contribution: The combination of multiple callback functions in deep neural networks minimizes training time and maximizes accuracy in a controlled computational environment with parametric constraints for the task of materials property prediction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Rare earth metals from secondary sources: Review of potential supply from waste and byproducts

Current concerns about lack of diversity in supply of critical metals have spurred research into utilizing domestic sources, particularly from waste streams. Sustainability strategies like urban mining, industrial symbiosis, and the circular economy suggest avenues to realize new supplies of critical metals. In this work we explore the resource and economic potential for extracting rare earth elements (REEs) from industry byproducts (e.g. coal combustion products, red mud) and secondary sources (e.g. waste electronics and light bulbs). Combining materials flow analysis and characterization data, we find that while REE concentrations in waste and byproduct streams are mostly much lower than current REE ores, some secondary sources are richer than ores in high value REEs such as scandium. The quantities of REEs contained in secondary sources could meet current global demand even with low extraction yield rates. Phosphogypsum, coal ash and red mud from aluminum production stand out as promising candidates for recovery due to high concentrations of valuable REEs and sufficient quantities to potentially meet demand. Processes to extract REEs from secondary sources are under development, it is not clear yet which will be profitable at scale and which can be achieved at least environmental impact. This work provides high level guidance on the potential of secondary sources by characterizing quality (concentrations of different rare earths) and quantity (mass of rare earths in global scale wastes and byproducts). This significant first step helps clarify directions for policy and research and development investments.

42 ENGINEERING↗

DOE OSTI2021

The effect of caustic soda treatment to recover rare earth elements from secondary feedstocks with low concentrations

Caustic soda (NaOH) treatment has enhanced rare earth element (REE) extraction from monazite. Here, this study examined the effectiveness of caustic soda for RE-phosphates with lower concentrations for extraction from coal overburden, an alternative feedstock derived from mining waste. Pourbaix (Eh-pH) diagrams were constructed for La, Ce, Nd, Eu, and Y-PO 4 -H 2 O systems to understand the thermodynamics of NaOH-facilitated acid leaching for low-concentration RE-phosphates and oxides and to elucidate the difference in recoveries among individual REEs. The Eh-pH diagrams indicated that low crystallinity is beneficial for extraction. Nd was thermodynamically most favorable for the extraction process among the five elements examined, and Y was the least promising. Experiments were conducted using three Pennsylvania coal overburden samples to validate the effect of caustic soda on rare earth leaching. The experimental results showed that for NaOH (6 M), a leaching time of 2 h at 125 °C was sufficient to obtain twice the recovery values compared to those without the NaOH treatment. After implementing the caustic soda treatment, a high total REE recovery (>60%), especially for Nd and Pr, could be achieved with diluted HCl and more environmentally friendlier citric acid. The results were similar for both coarse and fine particles. This novel approach is likely to improve the feasibility of REE extraction from coal-associated feedstock in a more environmentally benign manner.

42 ENGINEERING↗

DOE OSTI2023

DECOVALEX-2023: Task F2-Salt Final Report

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

DECOVALEX-2023: Task F2 Salt Final Report

The subject of Task F of DECOVALEX-2023 concerns performance assessment modelling of radioactive waste disposal in deep mined repositories. The primary objectives of Task F are to build confidence in the models, methods, and software used for performance assessment (PA) of deep geologic nuclear waste repositories, and/or to bring to the fore additional research and development needed to improve PA methodologies. In Task F2- (salt), these objectives have been accomplished through staged development and comparison of the models and methods used by participating teams in their PA frameworks. Coupled-process submodels and deterministic simulations of the entire PA model for a reference scenario for waste disposal in domal salt have been conducted. The task specification has been updated continuously since the initiation of the project to reflect the staged development of the conceptual repository model and performance metrics. Thermal, hydrological, mechanical, and chemical properties of individual components of the engineered and natural system were chosen for relevance by participating teams. The salt reference case system was characterized using data and measurements collected at relevant underground research laboratories (URLs), field sites, and simulation results from teams with specialized modelling capability. Participating teams made a wide range of model assumptions from compartmentalized networks to full 3D models of the salt formation. No single contributed model includes full-fidelity representation of all the features, events, and processes (FEPs) detailed in the task specification, but almost all features and processes are represented in at least one model. Despite differences in the modelling strategies developed by participating teams, all models indicate that salt compaction and radionuclide diffusion are key processes in the repository, and for the FEPs and model scenario considered, little of the disposed radionuclides will migrate beyond the repository seal over the 100,000 year simulations. In general, the model output quantities have the largest differences over the short term and near the waste. The models tend to be more similar further from waste and at later time. Disparities between the models are believed to be due to differing simplifications from the task specification, some of which are chosen simplifications to reduce complexity, and some are restrictions imposed by the modelling tools. A second round of this task has been accepted for DECOVALEX-2027 in conjunction with Task F1 on crystalline PA modelling. The future round includes waste package heating, improved modelling of salt creep closure, additional comparisons of coupled-process sub-models, and the impact of repository engineering design on radionuclide migration in the repository. Participants will also propose and finalize a set of uncertain inputs for the reference case simulations, propagate these uncertainties in a set of realizations, and conduct sensitivity analyses on the simulation results.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2021

Using Electrostatic Principles to Separate Out Nutrients from ECLSS Wastewater Brines

This project will study the use electrostatics to perform electrostatic separation and recovery of Environmental Control and Life Support Systems (ECLSS) waste brines. Currently we have no way to perform nutrient recovery on ECLSS waste brines. This process can give us a competing way to separate sodium from potassium to allow tandem production of acids, bases, and plant fertilizers to run upstream operations and hydroponic systems respectively (when combined with electrodialysis). If we can recover valuable chemicals from brine, then this will decrease resupply from earth, which will allow tremendous (multiple kilograms a day up-mass reduction) cost savings. In addition, using electrostatics for regolith enrichment allow much reduced mining costs for metal production on celestial bodies and allow a smaller mining footprint.

Michael D. Hogue↗

DOE OSTI2021

Cognitive analysis of metabolomics data for systems biology

Cognitive computing is revolutionizing the way big data are processed and integrated, with artificial intelligence (AI) natural language processing (NLP) platforms helping researchers to efficiently search and digest the vast scientific literature. Most available platforms have been developed for biomedical researchers, but new NLP tools are emerging for biologists in other fields and an important example is metabolomics. NLP provides literature-based contextualization of metabolic features that decreases the time and expert-level subject knowledge required during the prioritization, identification and interpretation steps in the metabolomics data analysis pipeline. Here, we describe and demonstrate four workflows that combine metabolomics data with NLP-based literature searches of scientific databases to aid in the analysis of metabolomics data and their biological interpretation. Additionally, the four procedures can be used in isolation or consecutively, depending on the research questions. The first, used for initial metabolite annotation and prioritization, creates a list of metabolites that would be interesting for follow-up. The second workflow finds literature evidence of the activity of metabolites and metabolic pathways in governing the biological condition on a systems biology level. The third is used to identify candidate biomarkers, and the fourth looks for metabolic conditions or drug-repurposing targets that the two diseases have in common. The protocol can take 1–4 h or more to complete, depending on the processing time of the various software used.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Mind the gap: Bridging the divide between AI aspirations and the reality of autonomous microscopy

What does materials science look like in the “Age of Artificial Intelligence?” Each material’s domain—synthesis, characterization, and modeling—has a different answer to this question, motivated by unique challenges and constraints. This work focuses on the tremendous potential of autonomous characterization within electron microscopy. We present our recent advancements in developing domain-aware, multimodal models for microscopy analysis capable of describing complex atomic systems. We then address the critical gap between the theoretical promise of autonomous microscopy and its current practical limitations, showcasing recent successes while highlighting the necessary developments to achieve robust, real-world autonomy.

2D materials↗

DOE OSTI2023

Unlocking the magic in mycelium: Using synthetic biology to optimize filamentous fungi for biomanufacturing and sustainability

Filamentous fungi drive carbon and nutrient cycling across our global ecosystems, through its interactions with growing and decaying flora and their constituent microbiomes. The remarkable metabolic diversity, secretion ability, and fiber-like mycelial structure that have evolved in filamentous fungi have been increasingly exploited in commercial operations. The industrial potential of mycelial fermentation ranges from the discovery and bioproduction of enzymes and bioactive compounds, the decarbonization of food and material production, to environmental remediation and enhanced agricultural production. Despite its fundamental impact in ecology and biotechnology, molds and mushrooms have not, to-date, significantly intersected with synthetic biology in ways comparable to other industrial cell factories (e.g. Escherichia coli,Saccharomyces cerevisiae, and Komagataella phaffii). In this review, we summarize a suite of synthetic biology and computational tools for the mining, engineering and optimization of filamentous fungi as a bioproduction chassis. A combination of methods across genetic engineering, mutagenesis, experimental evolution, and computational modeling can be used to address strain development bottlenecks in established and emerging industries. These include slow mycelium growth rate, low production yields, non-optimal growth in alternative feedstocks, and difficulties in downstream purification. In the scope of biomanufacturing, we then detail previous efforts in improving key bottlenecks by targeting protein processing and secretion pathways, hyphae morphogenesis, and transcriptional control. Bringing synthetic biology practices into the hidden world of molds and mushrooms will serve to expand the limited panel of host organisms that allow for commercially-feasible and environmentally-sustainable bioproduction of enzymes, chemicals, therapeutics, foods, and materials of the future.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Utilization of Carbon Supply Chain Wastes and Byproducts to Manufacture Graphite for Energy Storage Applications

This project explored how coal and waste coal can be transformed into high-value graphite used in batteries for electric vehicles and power grids. A manufacturing technique that converts coal into carbon foam and subsequently graphite was developed and refined to improve the thermal and mechanical properties of the resulting materials. Cost-effectiveness and environmental impacts were also evaluated. Coal-derived graphite, especially when processed at high temperatures, was shown to perform comparably to commercial graphite in battery tests. Advanced computer simulations were used to model battery behavior and predict long-term performance, demonstrating that coal-based graphite has the potential to support electric vehicle deployment while reducing reliance on imported materials. This work offers a promising pathway for cleaner energy storage solutions and creates economic opportunities for coal-reliant communities by generating new uses for mining byproducts.

01 COAL, LIGNITE, AND PEAT↗

NASA NTRSDate not supplied

Metallic Powder Core Tubular Wire Development for Additive Manufacturing

powder core tubular wire (PCTW)↗

NASA NTRSDate not supplied

Metallic Powder Core Tubular Wire (PCTW) Development for Additive Manufacturing

NASA Langley Research Center (LaRC) in Hampton, VA, and the Center for Welding, Joining, and Coating Research (CWJCR) in the Department of Metallurgical and Materials Engineering at the Colorado School of Mines (CSM) in Golden, CO, have collaborated for nearly fifteen years to develop metallic powder core tubular wire (PCTW) feedstock for additive manufacturing (AM) using electron beam deposition. The motivation for this development was to offset dealloying observed during deposition of titanium and aluminum alloy solid wire feedstock in the LaRC electron beam freeform fabrication (EBF3) system and to explore novel alloy compositions by tailoring the powder fill. EBF3 is a fusion-based AM process that is performed under vacuum and is consequently prone to vaporization loss of low vapor pressure alloying elements. Research spanning four graduate student research projects succeeded in developing the basic methodology to fabricate PCTW, the mass balance equations used to define the powder fill, microstructure control through particulate inoculation, and the feasibility of producing metal matrix composite materials. Metallic PCTW is comprised of a thin foil sheath wrapped around a powder blend. Fabrication of PCTW at CSM was accomplished using a tubular wire mill system to first bend a flat strip into a u-shaped cross section, deposit a powder fill, create a lap joint to seal the wire, and draw to final diameter. Powder management systems were developed to ensure uniform mixing of powder constituents and identify feed rates for optimum fill ratios. Processing parameters were successfully developed for titanium and aluminum alloy sheaths to account for material work hardening during drawing. Mass balance equations were developed to account for compositional contributions of the sheath and powder fill. PCTW composition can be adjusted through selection of the sheath or powder materials. PCTWs were successfully developed to offset Al loss in deposits of Ti-6-4 and Mg loss in Al 6061, resulting in deposits that were within the composition limits for each material. Ti-6-4 deposits were fabricated using PCTW comprised of commercially pure (CP) titanium sheath and a fill of pre-alloyed Ti-6-4 powder with additions of elemental Al and V powders. Additions of both elements were required to account for the CP Ti from the sheath, and Al was further enhanced to offset documented losses in EBF3 deposits. For Al 6061 deposits, composition was modulated through the choice of sheath material. The PCTW was made using an Al 5052 sheath to supplement Mg content and a fill composition of pre-alloyed 6061 powder with additions of Si and Cu.The slower solidification rate of the EBF3 process compared with laser powder bed fusion processes can lead to coarse-grained microstructures and mechanical property anisotropy. EBF3deposits of Ti-6-4 exhibited large epitaxially grown β grains, which result in degraded mechanical properties in the deposition direction. Microstructure refinement was achieved through a combination of electron beam modulation and the use of a PCTW designed for Ti-6-4 deposits and modified by the addition of powder made from Fe and B. Resulting deposits exhibited reductions in β grain size, α phase colony intercept length and lath width, and an increased volume fraction of β phase. The mechanism of microstructure refinement was related to precipitation of boride particles. Hardness testing confirmed that mechanical property anisotropy was reduced and an overall increase in hardness was achieved.Metal matrix composite (MMC) materials offer strength and stiffness benefits over unreinforced materials. Two methods were investigated using PCTW technology for producing Al 6061 basedMMC materials; the direct addition of SiC reinforcing particles and the in-situ generation of reinforcements through reaction synthesis of precursor powders. Al 6061 based MMCs reinforced with SiC exhibited particle clustering and formation of aluminum carbides during deposition. The application of a Ni coating to the SiC particles prior to incorporation into the powder fill eliminated aluminum carbide formation and aided particle distribution during deposition. Modulation of beam focus and power further reduced aluminum carbide formation and aided particle distribution. In reaction synthesis, precursor additions undergo an exothermic reaction during deposition to form new ceramic products, generally of finer scale than the initial precursor components. The product phases provide reinforcement in the MMC and act as nucleation sites during solidification, resulting in grain refinement, improved mechanical properties, and reduced susceptibility to solidification cracking. Higher tensile strength and stiffness were demonstrated in Al 6061 based MMCs with 2 vol% reinforcement. These combined research efforts demonstrate the potential of PCTW technology for customizing of alloy composition and achieving microstructure control. A manufacturing process for titanium- and aluminum-based PCTWs was developed based on iterative design, theoretical calculations, and empirical data. PCTW technology successfully mitigated Al loss from Ti-6-4 and Mg loss in Al 6061, resulted in grain refinement in Ti-6-4, and demonstrated fabrication of Al based MMCs

Marcia S Domack↗

DOE OSTI2025

Formation trajectories of solution-processed perovskite thin films from mixed solvents

The engineering of mixed-solvent formulations and their evaporation conditions are key to reproducible perovskite coatings for high-performance photovoltaics. Here, we report a lumped-parameter evaporation model to predict the evolution of a perovskite ink liquid film over time (solvent ratio, solute concentration, and film thickness). The drying-rate model is validated via in situ film-thickness measurements, and the predicted transient liquid film state is mapped as a process path. These methods allow for the prediction of process sensitivity to local environmental factors and the understanding and visualization of a broader processing parameter space enabled through the coupling of process and ink engineering. Process maps are applied to create a new framework for scalable perovskite coating development with a goal of improving the reproducibility and transferability of perovskite fabrication. This approach is demonstrated with blade-coated FA 0.83 Cs 0.17 PbI 3 photovoltaic devices, improving the photovoltaic conversion efficiency from 17.5% ± 1.7% to 20.3% ± 0.6%.

14 SOLAR ENERGY↗

NASA NTRS2014

Robust Informatics Infrastructure Required For ICME: Combining Virtual and Experimental Data

With the increased emphasis on reducing the cost and time to market of new materials, the need for robust automated materials information management system(s) enabling sophisticated data mining tools is increasing, as evidenced by the emphasis on Integrated Computational Materials Engineering (ICME) and the recent establishment of the Materials Genome Initiative (MGI). This need is also fueled by the demands for higher efficiency in material testing; consistency, quality and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. Further, the use of increasingly sophisticated nonlinear, anisotropic and or multi-scale models requires both the processing of large volumes of test data and complex materials data necessary to establish processing-microstructure-property-performance relationships. Fortunately, material information management systems have kept pace with the growing user demands and evolved to enable: (i) the capture of both point wise data and full spectra of raw data curves, (ii) data management functions such as access, version, and quality controls;(iii) a wide range of data import, export and analysis capabilities; (iv) data pedigree traceability mechanisms; (v) data searching, reporting and viewing tools; and (vi) access to the information via a wide range of interfaces. This paper discusses key principles for the development of a robust materials information management system to enable the connections at various length scales to be made between experimental data and corresponding multiscale modeling toolsets to enable ICME. In particular, NASA Glenn's efforts towards establishing such a database for capturing constitutive modeling behavior for both monolithic and composites materials

Mutli-scale models↗

NASA NTRS2015

Technology Alignment and Portfolio Prioritization (TAPP): Advanced Methods in Strategic Analysis, Technology Forecasting and Long Term Planning for Human Exploration and Operations, Advanced Exploration Systems and Advanced Concepts

The Advanced Concepts Office (ACO) at NASA, Marshall Space Flight Center is expanding its current technology assessment methodologies. ACO is developing a framework called TAPP that uses a variety of methods, such as association mining and rule learning from data mining, structure development using a Technological Innovation System (TIS), and social network modeling to measure structural relationships. The role of ACO is to 1) produce a broad spectrum of ideas and alternatives for a variety of NASA's missions, 2) determine mission architecture feasibility and appropriateness to NASA's strategic plans, and 3) define a project in enough detail to establish an initial baseline capable of meeting mission objectives ACO's role supports the decision-making process associated with the maturation of concepts for traveling through, living in, and understanding space. ACO performs concept studies and technology assessments to determine the degree of alignment between mission objectives and new technologies. The first step in technology assessment is to identify the current technology maturity in terms of a technology readiness level (TRL). The second step is to determine the difficulty associated with advancing a technology from one state to the next state. NASA has used TRLs since 1970 and ACO formalized them in 1995. The DoD, ESA, Oil & Gas, and DoE have adopted TRLs as a means to assess technology maturity. However, "with the emergence of more complex systems and system of systems, it has been increasingly recognized that TRL assessments have limitations, especially when considering [the] integration of complex systems." When performing the second step in a technology assessment, NASA requires that an Advancement Degree of Difficulty (AD2) method be utilized. NASA has used and developed or used a variety of methods to perform this step: Expert Opinion or Delphi Approach, Value Engineering or Value Stream, Analytical Hierarchy Process (AHP), Technique for the Order of Prioritization by Similarity to Ideal Solution (TOPSIS), and other multi‐criteria decision-making methods. These methods can be labor-intensive, often contain cognitive or parochial bias, and do not consider the competing prioritization between mission architectures. Strategic Decision-Making (SDM) processes cannot be properly understood unless the context of the technology is understood. This makes assessing technological change particularly challenging due to the relationships "between incumbent technology and the incumbent (innovation) system in relation to the emerging technology and the emerging innovation system." The central idea in technology dynamics is to consider all activities that contribute to the development, diffusion, and use of innovations as system functions. Bergek defines system functions within a TIS to address what is actually happening and has a direct influence on the ultimate performance of the system and technology development. ACO uses similar metrics and is expanding these metrics to account for the structure and context of the technology. At NASA technology and strategy is strongly interrelated. NASA's Strategic Space Technology Investment Plan (SSTIP) prioritizes those technologies essential to the pursuit of NASA's missions and national interests. The SSTIP is strongly coupled with NASA's Technology Roadmaps to provide investment guidance during the next four years, within a twenty-year horizon. This paper discusses the methods ACO is currently developing to better perform technology assessments while taking into consideration Strategic Alignment, Technology Forecasting, and Long Term Planning.

Funaro, Gregory V.↗

DOE OSTI2024

Combined Pre-supernova Alert System with KamLAND and Super-Kamiokande

Preceding a core-collapse supernova (CCSN), various processes produce an increasing amount of neutrinos of all flavors characterized by mounting energies from the interior of massive stars. Among them, the electron antineutrinos are potentially detectable by terrestrial neutrino experiments such as KamLAND and Super-Kamiokande (SK) via inverse beta decay interactions. Once these pre-supernova (pre-SN) neutrinos are observed, an early warning of the upcoming CCSN can be provided. In light of this, KamLAND and SK, both located in the Kamioka mine in Japan, have been monitoring pre-SN neutrinos since 2015 and 2021, respectively. Recently, we performed a joint study between KamLAND and SK on pre-SN neutrino detection. A pre-SN alert system combining the KamLAND detector and the SK detector was developed and put into operation, which can provide a supernova alert to the astrophysics community. Fully leveraging the complementary properties of these two detectors, the combined alert is expected to resolve a pre-SN neutrino signal from a 15 M ⊙ star within 510 pc of the Earth at a significance level corresponding to a false alarm rate of no more than 1 per century. For a Betelgeuse-like model with optimistic parameters, it can provide early warnings up to 12 hr in advance.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Synthesis of high-density olivine LiFePO 4 from paleozoic siderite FeCO 3 and its electrochemical performance in lithium batteries

The lithium-ion cathode material olivine LiFePO 4 (LFP) has been synthesized for the first time from natural paleozoic iron carbonate (FeCO 3 ). The ferrous carbonate starting material consists of the mineral siderite at about 92 wt. % purity. Because FeCO 3 has divalent iron, the reaction with lithium dihydrogen phosphate (LiH 2 PO 4 ) provides a unique method to develop iron-(II) containing LFP in an inert atmosphere. Since siderite FeCO 3 is a common mineral that can be directly mined, it may, therefore, provide an inexpensive route for the production of LFP. After carbon-coating, the LFP yields a capacity in the range of 80–110 mAh g -1 LFP (in one chosen specimen sample), which is lower than commercially available LiFePO 4 (150–160 mAh g -1 LFP ). However, the tap density of LFP derived from siderite is noticeably high at 1.65 g cm -3 . The material is likely to be improved with powder purification, nanosized processing, and more complete carbon-coating coverage with increased optimization.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Narrow-Channel, Fluidized Beds for Effective Particle Thermal Energy Transport and Storage

Colorado School of Mines (Mines) led this program in collaboration with Sandia National Laboratories (Sandia) to characterize narrow-channel fluidized beds of aluminosilicate particles – supplied by Carbo Ceramics – as a means for releasing high-temperature thermal energy in particle heat exchangers and for capturing concentrated solar energy in indirect particle receivers. Single-channel, heat transfer experiments at Mines and reduced-order 1-D models and 3-D two-fluid, CFD models explored many aspects of counterflow, bubbling fluidized beds (net downward particle flow and upward gas flow) for enhancing particle-wall heat transfer at elevated temperatures. Results at Mines on single-channel test sections consistently showed that mild bubbling fluidization increases particle-wall heat transfer coefficients (h T,w ) regularly by more than 4.0x over h T,w values without fluidization at similar conditions (mean particle diameter d p , bed depth Δz b , and bed particle temperatures T p ). Insights from lab-scale tests and modeling studies provided Nusselt number correlations for h T,w and informed the design and fabrication (by Vacuum Process Engineering) of a nominal 40-kWth, particle-sCO 2 plate heat exchanger (HX) with 12 parallel narrow-channel, fluidized beds bounded by stainless-steel walls with embedded microchannels for high-pressure sCO 2 flows. Tests of the 40-kW th HX at the particle-sCO 2 HX test stand at Sandia's National Solar Thermal Test Facility (NSTTF) were limited, due to HX design, to particle inlet temperatures T p,in ≤ 520°C with maximum sCO 2 outlet temperatures T sCO2,out ≈ 440°C, which are well below design conditions for a primary HX in a sCO 2 power cycle for a Gen-3 concentrating solar power (CSP) plant. Total heat transfer $\dot{Q}_{HX}$ remains relatively constant with increased fluidization for fixed particle and sCO 2 inlet conditions because higher h T,w due to fluidization is offset by increased axial dispersion, which suppresses temperature differences between the particles and sCO 2 in the counterflow configuration. The axial dispersion reduces the effective overall heat transfer coefficient U based on T p,in to values around 200 W m -2 K -1 .

14 SOLAR ENERGY↗