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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Thermal and electromechanical response of ultra-thin carbon-strip polarimeter targets in relativistic bunched beams

Thin carbon-strip targets provide fast relative hadron beam polarimetry, but their response in intense relativistic bunched beams is not governed by local stopping-power heating alone. We develop a coupled response model that combines beam-target overlap, secondary-electron escape, retained heat, target motion, transient heat transport, RF-induced strip-end heating, beam-induced forces, resistance changes, and slack-strip deformation. RHIC target observations constrain the relevant motion, force, and nonlocal-heating scales and show that target survival depends on both beam-center heating and electromagnetic boundary conditions near the strip ends. Applying the model to Booster, AGS, RHIC, and EIC proton and 3 He cases shows that the RHIC proton lifetime scale is reproduced at the order-of-magnitude level, while the RHIC target-holder fin results require the additional RF/end-heating mechanism. For EIC proton flattop operation, carbon-strip polarimetry may remain viable only with reduced dwell time, sufficient detector acceptance, and suppression of RF-induced end heating. For cooled-emittance 3 He, the calculated sublimation-loss scale is far beyond a straightforward RHIC-like carbon-strip extrapolation. Conventional carbon strips are therefore unlikely to remain viable for the most demanding EIC light-ion cases without major changes in target motion, target technology, or diagnostic concept.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

The Novel Charfuel® Coal Refining Process 18 TPD Pilot Plant Project for Co- Producing an Upgraded Coal Product, and Commercially Valuable Co- Products: Area of Interest #3 – Coal Beneficiation Pilot Plant Testing (Final Report)

Operation of Carbon Fuels, LLC’s (“CF”) existing, permitted 18 TPD pilot plant located in Golden, Colorado using two individually ranked (ASTM D 388) coal types (two campaigns), employing the novel Charfuel® coal refining process to produce an upgraded coal product and a number of high-valued organic and inorganic coproducts (for which there presently exists large commercial markets) in order to produce engineering and product data which will then be utilized toward the design of a commercial scale integrated facility (pre-feed document). Carbon Fuels, LLC has developed the Charfuel® Coal Refining Process which refines domestically abundant, raw coal (in the same manner as crude oil is refined) to produce the identical, high value co-products that are refined from crude oil. Thus, gasoline, jet fuel, “green diesel”, fuel oil, and marine fuels, as well as petrochemicals such as benzene, toluene, xylene, and methanol are refined from raw coal using this process. The Charfuel® Coal Refining Process is not a coal conversion process, like pyrolysis, or indirect liquefaction. Nor is it an alternative energy system. Rather it is a coal refining process that has the ability to economically produce products traditionally associated with the refining of crude oil but using only abundant, raw coal as the refinery feed stock. The Charfuel® Coal Refining Process is more economical than crude oil refining and is environmentally benign. Therefore, this value added process yields a return on investment well above 50% for a commercial facility. Furthermore, the Charfuel® process, unlike alternatives such as ethanol and hydrogen, can utilize the existing transportation, delivery, and other petroleum based systems. Hence, there is no need for new engines, pipelines, tankers, or product acceptance. As a result, the profitability of the process is increased. Objectives: (1) Operation of the integrated 18 tpd pilot plant, using two coal types (ranks); (2) Demonstration of process flexibility in being able to produce different products (gas, liquid, and char), as well as determination of operating parameters for identifying scale up criteria for two coal types (ranks); (3) Generation of engineering and design information (process specifications) for use in designing a commercial scale plant (scale-up); (4) Determination of important environmental issues surrounding the process and the products such as fate of trace elements (mercury and other heavy metals) and distributions of SO2, NOx, and CO 2 by analysis of effluent streams; (5) Production of sufficient product to allow reliable commercial economic evaluation of both the refined coal product and the coproducts; and, (6) Assessment of longer-term reliability of unit operations. Period 1: reconfiguration of the 18 TPD plant to meet specific FOA requirements and to qualify the facility for operation; and, Period 2: operation of the 18 TPD plant for two campaigns using two coals types (ranks) which are widely commercially used and abundant - the first being a subbituminous (Powder River Basin (“PRB”)) coal, and the second a bituminous (Illinois #6) coal.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Emerging investigator series: kinetics of diopside reactivity for carbon mineralization in mafic–ultramafic rocks

The ongoing use of fossil fuels to supply modern energy demands has necessitated research on combating carbon dioxide (CO 2 ) emissions and climate change. Carbon storage via mineral trapping in basalt and related rocks is a promising strategy. However, mineralization rates depend on the variable minerology that makes up these rock formations. Diopside (CaMgSi 2 O 6 ) is a common pyroxene mineral in ultramafic and mafic rocks including basalt, but relatively little work has been done to understand its carbon mineralization kinetics using hydrated supercritical CO 2 , which induces the formation of reactive nanoscale interfacial water films. Here, in situ XRD experiments at 50–110 °C and 90 bar indicate that diopside transforms into a myriad of Mg/Ca carbonates, including huntite [Mg 3 Ca(CO 3 ) 4 ] and very high magnesium calcite (VHMC, i.e., protodolomite). Through ex situ characterization, we were able to constrain reaction pathways for the dissolution–precipitation transformation process including metastable intermediate precipitates. Experiments performed at variable temperatures enabled Avrami-derived rate constants and an apparent activation energy of 97 ± 16 kJ mol –1 , implying the dissolution of diopside is the rate-limiting step. Density functional theory (DFT) calculations, used to gain molecular insight into the surface stability of the diopside during dissolution, suggest that exposed calcium cations are susceptible to dissolution when put in contact with water given their coordination environment. The collective results point to the high CO 2 mineralization potential of diopside in basalts, which could help guide parameterization of reactive transport models needed to design and permit commercial-scale subsurface carbon storage operations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Chapter 6: Recycling Plastic Waste to Produce Chemicals - A Techno-Economic Analysis and Life-Cycle Assessment

This study presents the results of a preliminary assessment on the technology, economics, and sustainability of using waste plastics as a feedstock to produce low molecular weight olefins via pyrolysis and gasification pathways. We also studied the formation of formaldehyde - an important polymer precursor - via the gasification of waste plastics. Process pathways for recovery of ethylene and propylene and production of formaldehyde from a simulated mixed plastic waste were constructed based on literature data. They included direct and indirect pathways based on either gasification or pyrolysis as the primary conversion step. Results of these studies have shown that significant economic challenges exist of producing olefins via pyrolysis and gasification, with the latter pathway especially difficult. Base costs of pyrolysis naphtha from waste plastics are higher when compared to the same material produced from fossil feedstocks. Base olefin costs for one direct route are two times higher than comparable costs from steam cracking of fossil naphtha. These costs are driven primarily by feedstock costs; some pyrolysis scenarios become more economically feasible when very low feedstock costs are used. Similarly, for gasification, the cost of methanol - the central intermediate - was found to be noticeable higher when produced by gasification of waste plastics compared to current selling prices, which negatively impacts all pathways that go through methanol as the central intermediate. Life-cycle assessment indicates that the production of pyrolysis naphtha from plastics is a carbon intensive operation; no major advantages were found in terms of greenhouse gas emissions for any of the pathways producing C2 and C3 olefins. The results of this study can serve as the baseline for future comparison to other plastic waste valorization processes.

BIOMASS FUELS,ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Front End Engineering Design Study on Gasification of Coal and Biomass to Generate Carbon- Free Electric Power and Hydrogen

A 2nd Phase Front End Engineering Design study of a gasification plant concept to co-produce electric power and hydrogen with net-negative CO2 emissions is being completed under the U.S. Department of Energy’s (DOE’s) 21st Century Power Plants initiative, whose goal is to advance innovative power plant concepts that are capable of flexible, net-zero carbon emission operations while producing cost-effective hydrogen to support economy-wide decarbonization goals. The proposed standalone plant would be constructed in Nebraska, USA. The specified design feedstock is a hybrid blend of Powder River Basin (PRB) subbituminous coal from Wyoming and local Nebraska biomass (corn stover), 50% each by weight (dry basis). Other potential feedstocks, including woody biomass (eastern red cedar) and waste plastic (auto shredder residue) were evaluated as alternates. The process block comprises a high-pressure, oxygen-blown fluidized bed gasifier coupled with water-gas shift, Selexol process for acid gas (H2S and CO2) removal, and pressure-swing adsorption (PSA) to yield 8,500 kg/h of high-purity hydrogen. Off-gas from the PSA unit is used in a gas turbine combined cycle plant (the power block) to supply 50 MWe net electric power to the grid. Overall thermal efficiency of the plant is 50% (HHV) with net atmospheric CO2 removal at a rate of 32 t/h. Design activities necessary to provide input to the current front-end engineering design (FEED) study, including, site selection, gasifier technology selection, investment case preparation, and the development of the Environmental Information Volume (EIV) for the host site, have been completed. These, as well as the current FEED activities, are described in this presentation.

gasification, biomass, coal, hydrogen, power gener↗
DOE OSTI2023

A Deep Learning-Based Workflow for Fast Prediction of 3D State Variables in Geological Carbon Storage: A Dimension Reduction Approach

In this study, we used deep learning techniques, which are a form of artificial intelligence, to create fast and effective models for predicting how fluids flow in underground geological formations. This is important for managing geological carbon storage, a method used to fight climate change by storing carbon dioxide underground. The challenge lies in the complex nature of these underground spaces and the large amount of data needed to accurately simulate them. To overcome these issues, we developed a new workflow that reduces the data’s complexity before training the deep learning model and then reconstructs the predicted results in their original form. We also proposed a unique approach to handle the specific complexities found in 3D saturation fields, a crucial aspect of fluid flow prediction. We tested our method using real-world data from the Gulf of Mexico. Our results show that our approach not only accurately predicts fluid behavior but also significantly reduces computation time. This will greatly improve real-time decision-making and risk assessment in large-scale geological carbon storage operations.

Wang, Hongsheng↗
DOE OSTI2024

Overview of SMART Initiative

The objective of the SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to show how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations in three main areas: real-time visualization, virtual learning, and real-time forecasting. This presentation reports the status of SMART initiative for demonstrating: (a) virtual learning during the pre-injection permitting phase, and (b) ML-assisted operational decision making and visualization.

Siriwardane, Hema↗
DOE OSTI2024

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

Presentation material for a paper presented at the GHGT-17 conference, Calgary, Canada, October 20-24, 2024. The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

CO2 geologic storage↗
DOE OSTI2021

Mid-infrared Pulsed Upconversion Imaging in a Rotating Detonation Combustor

To meet the challenges associated with performing mid-InfraRed (IR) imaging in Rotating Detonation Combustors (RDCs), a novel pulsed mid-IR UpConversion Imaging (UCI) diagnostic has been implemented. UCI is an alternative to direct mid-IR detection that uses nonlinear optical frequency mixing to shift mid-IR wavelengths carrying a target image to shorter wavelengths that can be imaged with high-performance silicon-based CCD/CMOS cameras. This approach offers several favorable properties including high spectral selectivity, high temporal resolution, and superior low-light detectivity. A hydrogen-air research RDC was operated with carbon dioxide addition to allow pulsed UCI imaging of mid-IR luminosity within the combustion channel from spontaneous thermal emissions. The resulting measurements demonstrate high spatiotemporal resolution capable of imaging small structures near the supersonically propagating detonation wave front. The results show how this technique can be used to observe sharp gradients and millimeter-scale structures in the high-temperature, high-pressure zones RDC flow fields.

White, Logan W.↗
DOE OSTI2023

Autonomous Inversion of In Situ Deformation Measurement Data for Injection-Induced Stress Change

Geologic carbon storage (GCS) is likely to play a key part of the global effort to dramatically reduce CO2 emissions and perhaps even reduce atmospheric CO2 concentrations through carbon negative operations. A critical part of effort to commercialize and widely deploy this technology is developing the capability to rapidly assimilate real-time monitoring data into a form that will enable site operators to make decisions to manage the safe and efficient operations. Two of the risks associate with GCS are the risk of inducing fractures in the sealing formations that can create leakage pathways and the risk of inducing earthquakes of sufficient magnitude to cause public concern, property damage, or safety risks. To properly manage these risks the site operator needs to know the initial state of stress, the change in stress induced by injection, and the relationship between operational parameters such as injection rate and pressure and the change in stress. Current methods of estimating the change in stress require choosing the type of constitutive model and the model parameters based on core, log, and geophysical data during the characterization phase, with little feedback from operational observations to validate or refine these choices. These characterization methods interrogate the geologic formations using length scales, loading rates or magnitudes that are quite different from those encountered by the actual storage system. It is shown that errors in the assumed constitutive response, even when informed by laboratory tests on core samples, are likely to be common, large, and underestimate the magnitude of stress change caused by injection. Recent advances in borehole-based strain instruments and borehole and surface-based tilt and displacement instruments have now enabled monitoring of the deformation of the storage system throughout its operational lifespan. This data can enable validation and refinement of the knowledge of the geomechanical properties and state of the system, but brings with it a challenge to transform the raw data into actionable knowledge. We demonstrate a method that uses automatic differentiation and a finite-element based geomechanical model perform a gradient-based deterministic inversion of geomechanical monitoring data. This approach allows autonomous integration of the instrument data without the need for time consuming manual interpretation and selection of updated model parameters. Furthermore, only isotropic linear elasticity is considered in this paper, the approach presented is very flexible as to what type of geomechanical constitutive response can be used. The approach is easily adaptable to nonlinear physics-based constitutive models to account for common rock behaviors such as creep and plasticity. The approach also enables training of machine learning-based constitutive models by allowing back propagation of errors through the finite element calculations. This enables strongly enforcing known physics, such as conservation of momentum and continuity, while allowing data-driven models to learn the truly unknown physics such as the constitutive or petrophysical responses.

Burghardt, Jeffrey A.↗
DOE OSTI2022

Quantifying the Value of Grid-Interactive Efficient Buildings through Field Study: Preprint

Quantifying the annual energy impacts of efficient technologies in commercial buildings has been well established by the building science field. As we move toward enabling grid-interactive efficient buildings (GEB) targeting flexible building operation and carbon reduction, quantification methods to evaluate time-sensitive peak load and emissions impact are much less defined. A number of national laboratories are working to field validate four different GEB software solutions that provide the capability to control multiple building end-use systems in multiple load flexibility modes (i.e., energy efficiency, load shed, load shift, and possible load modulation at the second to sub-second level). To guide the laboratory leads in effective measurement and verification (M&V) practices, two of the laboratories collaborated to define metrics to quantify the impacts of flexible load control on building demand, utility costs, carbon emissions, facility management, and occupant comfort. This paper summarizes the proposed metrics to quantify peak load and emission impacts in the field, decision parameters, approaches to accurately conduct M&V, lessons learned, and outstanding needs and next steps.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2022

Quantifying the Value of Grid-Interactive Efficient Buildings through Field Study

Quantifying the annual energy impacts of efficient technologies in commercial buildings has been well established by the building science field. As we move toward enabling grid-interactive efficient buildings (GEB) targeting flexible building operation and carbon reduction, quantification methods to evaluate time-sensitive peak load and emissions impact are much less defined. A number of national laboratories are working to field validate four different GEB software solutions that provide the capability to control multiple building end-use systems in multiple load flexibility modes (i.e., energy efficiency, load shed, load shift, and possible load modulation at the second to sub-second level). To guide the laboratory leads in effective measurement and verification (M&V) practices, two of the laboratories collaborated to define metrics to quantify the impacts of flexible load control on building demand, utility costs, carbon emissions, facility management, and occupant comfort. This paper summarizes the proposed metrics to quantify peak load and emission impacts in the field, decision parameters, approaches to accurately conduct M&V, lessons learned, and outstanding needs and next steps.

Langner, Rois↗
DOE OSTI2023

Flexible Gasification of Coal and Biomass to Generate Carbon Free Electric Power and Hydrogen

This paper describes the development of a coal and biomass-fed plant concept to co-produce electric power and hydrogen with net-negative CO2 emissions under the aegis of the 21st Century Power Plant initiative of the U.S. Department of Energy (DOE), whose goal is to advance innovative power plant concepts that are capable of flexible, net-zero carbon emission operations while producing cost-effective “blue” hydrogen to support economy-wide decarbonization goals. The proposed standalone plant will be in Nebraska, USA. The specified design feedstock is a hybrid blend of Powder River Basin (PRB) subbituminous coal from Wyoming and local Nebraska biomass (corn stover), 50 wt.% each (dry basis). Other potential feedstocks, including woody biomass (eastern red cedar) and waste plastic (auto shredder residue) were evaluated or reviewed as alternates. The proposed process block comprises a high-pressure, oxygen-blown fluidized bed gasifier (GTI Energy U-GAS® process) coupled with water gas shift, the Selexol process for acid gas (H2S and CO2) removal, and pressure-swing adsorption (PSA) to yield 8,500 kg/h of high-purity hydrogen. The off gas from the PSA unit is used in the power block (gas turbine combined cycle) to generate electric power to support the gasification process, hydrogen production, and 50 MWe net electric power to the grid. All major plant equipment including the gasifier, gas cleanup system, and power generation are commercially available and proven in other applications and considered at TRL 8-9. However, gasification of corn stover biomass is considered at TRL 6. Overall thermal efficiency of the plant is 50% (net HHV) with net atmospheric CO2 removal at a rate of 250-300,000 tpa. Design activities necessary to provide input to a FEED study (Phase II of the project), including the development of the Environmental Information Volume (EIV) for the host site, and an investment case, based on a pro-forma pre-FEED level cost estimate, have been completed and are described in detail in this paper.

Gülen, S. Can↗
DOE OSTI2024

SMART – A Comprehensive Research and Development Program to Demonstrate Application of Machine Learning for Supporting CCS Deployment

The objective of the US Department of Energy’s SMART Initiative, i.e., Science-informed Machine Learning (ML) for Accelerating Real-Time Decisions in Subsurface Applications, is to showcase how the utilization of ML can significantly improve efficiency and effectiveness of field-scale commercial carbon storage operations. This paper will present the results from the current phase of SMART (field deployment) for demonstrating the applicability of ML-based tools and workflows for: (a) virtual learning during the pre-injection permitting phase, (b) advanced storage reservoir imaging to better characterize fractures and faults, and (c) dynamic storage reservoir modelling and optimization to inform operational decision making and visualization of system evolution.

Siriwardane, Hema↗
DOE OSTI2024

Analysis of Waste Material Feedstocks Using Laser-Induced Breakdown Spectroscopy and Machine Learning

Predicting properties such as heating value, ash fusion temperature, and mineral ash composition from Laser-Induced Breakdown Spectroscopy (LIBS) data can make gasifiers more flexible to different feedstocks. Understanding these feedstock properties in-situ improves feedstock conversion modelling methods that allow for consistent operation, higher carbon conversion, and reduced fouling and erosion rates. The purpose of this study is to demonstrate methods for model creation that take LIBS data as predictor features and estimate higher order material properties as a function of feedstock material properties. Six samples were chosen to represent a mixture of abundant and carbon rich waste materials. LIBS measurements were performed on these samples for elemental wavelengths and intensity values. Laboratory analytical results were obtained for each sample’s heating value, proximate and ultimate analysis, mineral ash composition, ash fusion temperatures, and viscosity temperatures. Thermal conductivity was measured using a HotDisk TPS 2500S. LIBS measurements were processed and used as predictor features for machine learning (ML) models to predict the sample’s material properties. Predictor feature selection algorithms, particularly minimum redundancy maximum relevance (mRMR), reduced the dimensionality of ML models. Many modelling methods such as Gaussian process regression (GPR), regression tree, neural networks (NN), and support vector machines (SVM) were demonstrated to be effective at predicting higher order properties; however, mRMR with GPR stood out as a clear winning combination.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Enhanced carbon-transfer and -utilization efficiencies achieved using membrane carbonation with gas sources having a range of CO 2 concentrations

The economic viability of microalgal biofuels relies on increasing productivity in a cost-effective manner. As microalgal biomass contains > 50% carbon, a high rate of CO 2 delivery is required for high productivity, and inefficient CO 2 delivery amplifies operating costs. Membrane carbonation using non-porous hollow fiber membranes can ideally deliver CO 2 without bubble formation and high carbon transfer efficiency. Because CO 2 streams from industrial resources are not 100% CO 2 , the buildup of inert gasses can significantly lower the CO 2 delivery rate when the distal end of the membrane is closed. To overcome the buildup of inert gases, we managed the distal end of the membranes with three different approaches: fully open end, restricted bleed valve, and restricted bleed valve with pH-actuated venting. For all approaches, CO 2 was delivered to membranes ondemand based on a pH set point. Evaluating a wide range of CO 2 concentrations (10% to 100%), we found that all approaches eliminated the buildup of inert gases, could maintain target pH values and gave the same biomass productivities and carbon distributions. However, carbon transfer efficiency depended on the operation of the distal end. Fully open-end operation gave a poor carbon transfer efficiency because of excessive loss of CO 2 from the distal end. However, restricting the exit flow rate to ≤4 cm 3 /min mitigated the problems of excessive CO 2 loss, but without incurring a large loss of CO 2 -delivery flux. For the continuous cultivation, combining a restricted bleed valve with pH-actuated venting improved the carbon-transfer efficiency and -utilization efficiencies up to 85% and 67%, respectively, with a sufficient CO 2 delivery flux.

42 ENGINEERING↗