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At least 163 records · Page 9

Lightweight carbon-carbon thermal protection system for STARPROBE

This paper describes the preliminary design, development, and initial testing of prototype carbon-carbon components of the thermal protection system of the NASA STARPROBE spacecraft. The thermal protection system is designed to limit the spacecraft scientific instrument package to a maximum temperature of 55 C during the time of closest approach to the earth's sun when the peak radiative heating rate reaches 393 w/sq cm. The thermal protection system is comprised of a carbon-carbon thin shell primary shield and two carbon-carbon sandwich construction secondary shields which block reradiation from the primary shield to the spacecraft. These shields are joined and stiffened by carbon-carbon structural members and attached to the spacecraft with eight thin-walled carbon-carbon struts. Prototype parts of the principal components have been fabricated and will be tested in a solar radiative flux environment simulating peak mission values in late 1984.

Dirling, R. B., Jr.↗

Heat Transfer Coefficients of Additively Manufactured Tubes with Internal Pin Fins for Supercritical Carbon Dioxide Cycle Recuperators

This paper describes the measurement of convective heat transfer coefficients and friction factors for sCO 2 flowing in additively manufactured tubes with internal pin fins at the US DOE’s National Energy Technology Laboratory in Morgantown, WV. The measurement procedures were validated by conducting benchmark tests with smooth stainless-steel tube and comparing the results with published correlations for Nusselt number (Nu) and friction factor. Over Reynolds numbers (ReD) ranging from 5 × 10 4 to 2.5 × 10 5 , measured Nu was within 5% of the Dittus-Boelter correlation and measured friction factors were within 5% of the McAdams correlation for smooth tube flow. The candidate pin fin patterned pipes were additively manufactured (AM) at the Oak Ridge National Laboratory. The pins were circular or elliptical in cross-section and were printed at a 30⁰ angle relative to the inner wall (to meet AM constraints). The pin arrangement was helical to promote enhanced heat transfer due to swirl flow. Pin length to diameter aspect ratio was 1.33, 2, and 8, while the pin diameter to tube diameter ratio was 0.188, 0.125, and 0.063. Tests were performed for ReD varying from 6.9 × 10 4 to 2.2 × 10 5 and at conditions equivalent to the low pressure (LP) outlet (8.69 MPa, 361 K) and the high pressure (HP) inlet (20.7 MPa, 350 K) of the low temperature recuperator (LTR) in an indirect sCO 2 cycle. The Wilson plot technique was utilized to measure the bulk heat transfer coefficients. For the best performing design (tube A, pin length to tube diameter ratio: 1.33, pin diameter to tube diameter ratio: 0.19), the local heat transfer coefficient increased by 136% relative to the Dittus-Boelter correlation at the LTR low pressure outlet and 194% at the LTR high pressure inlet. These correspond to a 282% and a 271% increase in the product of the heat transfer coefficient and surface area (adjusted for fin efficiency) product, respectively. Large pressure drops across the test articles were observed. For Tube Design A, the average friction factor, across the range of ReD considered, was significantly larger than the McAdams correlation at both the LTR LP outlet and the LTR HP inlet. A thermal performance factor was utilized to express the ratio of material required to build a finned heat exchanger relative to a finless heat exchanger with the same heat duty and pumping power. Tube Design A was estimated to decrease the required heat exchanger material by 13%.

Searle, Matthew↗

Measuring Heat Transfer Coefficients for Supercritical Carbon Dioxide Cycle Recuperators

This paper describes the measurement of convective heat transfer coefficients and friction factors for sCO 2 flowing in pin-fin patterned pipes at the US DoE’s National Energy Technology Laboratory (NETL) in Morgantown, WV. The measurement procedures were validated by conducting benchmark tests with smooth stainless-steel tube and comparing the results with published correlations for Nusselt number (𝑁𝑢) and friction factor. Over Reynolds numbers (Re D ) ranging from 5×104 to 2.5×105 , measured 𝑁𝑢 was within 5% of the Dittus-Boelter correlation and measured friction factors were within 5% of the McAdams correlation for smooth tube flow.

42 ENGINEERING↗

Economics of Carbon Capture and Sequestration

The paper will help state utility regulators understand the economics of CCS and their role in the process. It will introduce the concepts of offsets, tax incentives, and federal and state cooperation as a means of improving the economic benefits of CCS.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Application of carbon-powder-polymer composite as a continuous crack-length sensor

This paper explores the application of carbon-powder-impregnated polymeric composites for measuring crack extensions. The strain sensitivity of the gage material is shown to be very small. In the first series of tests, the gage material is characterized by measuring the change in electrical resistance due to machined slits for various gage lengths. The measured responses is compared with the response predicted from a very simple electrical model. On the basis of good correlation and repeatability, the usefulness of such gages to measure crack extensions is assessed by a second series of tests. Further work to improve the gage response by optimizing the shape of the gage and making the gage and the adhesive layer thinner is proposed. The presented concept, with improvements, can result in a reliable, inexpensive crack gage requiring inexpensive instrumentation.

Prabhakaran, R.↗

Repair of oxidation protection coatings on carbon-carbon using preceramic polymers

The paper describes a field-applicable technique for the repair of damage to SiC protective coatings on carbon/carbon composites, using commercial preceramic polymers, such as perhydropolysilazane developed by the Southwest Research Institute and several commercial polymers (NICALON, PS110, PS116, PS117, NCP-200, and PHPS were tested). After being applied on the damaged panel and oxidized at 1400 C, these polymers form either SiC or Si3N4 (or a mixture of both). It was found that impact damaged carbon/carbon specimens repaired with perhydropolysilazane exhibit substantial oxidation resistance. Many of the other tested preceramic polymer were found to be unsuitable for the purpose of repair due to either low ceramic yield, foaming, or intumescence.

Schwab, Stuart T.↗

Phosphates and Carbon in Martian Meteorites

This paper proposes tests for exobiological examination of samples prior to obtaining martian rocks of known provenance via future sample-return missions. If we assume that all of the secondary minerals in martian meteorite ET79001 were indeed cogenetic and originate from Mars, we list conclusions that can be drawn that are of exobiological interest. This work serves as a preamble for the subsequent work listed below.

Mojzsis, Stephen J.↗

Grain detachment and transport clogging during mineral dissolution in carbonate rocks with permeable grain boundaries

In this paper, we explore the effect of permeable grain boundaries on carbonate rock dissolution in order to improve our understanding of grain detachment and migration during reactive flow. To do so we investigated the effects of grain size and enhanced reactivity along grain boundaries on global dissolution kinetics. Variations of permeability and porosity were calculated, and exponential relationships were observed in fractured rocks. Our model employed a reactive transport framework based on the Darcy-Brinkman equation to simulate calcite dissolution in carbonate rocks composed of microporous grains and, included fluid transport along grain boundaries. The model includes fluid flow, solute transport by advection–diffusion, heterogeneous reaction between fluid and minerals and grain detachment with subsequent grain transport in macropores. The migration of solid particles due to dissolution was based on cluster analysis and local movement, and the results show that grain detachment can lead to significant decreases in permeability due to the clogging of transport pathways. Microporous media with smaller grain sizes (fine grains in this study) showed a higher average reaction rate than those with coarser grains. In addition, as the overall rates of geochemical processes are commonly affected by the presence of texture heterogeneities such as fractures, a single fracture (macropore) introduced into a microporous matrix composed of permeable grains and grain boundaries was modelled as a large channel connecting the inlet and outlet of the simulation domain. It was found that macropore clogging by grain detachment temporary decreased permeability, lowering the long-term global reaction rates. Lastly, we observed that increases in flow rate can reduce detachment and fracture clogging by reducing local dissolution along grain boundaries.

58 GEOSCIENCES↗

Investigation of poly(phenylacetylene) derivatives for carbon precursor with high carbon yield and good solubility

This paper investigates a family of poly(phenylacetylene) derivatives with a p-electrons conjugated polymer backbone and side groups containing only sp 2 and sp carbons. The objective is to identify the suitable carbon precursor that is processible and can be transformed to carbonaceous material with high carbon yield by a simple (one-step) thermal transformation process (without any external reagent). Poly(phenylacetylene) with para-substituted acetylene group poly(PA-A) shows an exceptionally high C-yield (~90%) in one-step heating from ambient temperature to 1000 °C under N 2 atmosphere. Unfortunately, this poly(PA-A) polymer is quite sensitive to heat and light with very limited solubility. On the other hand, poly(phenylacetylene) with para-substituted phenylacetylene group, i.e. poly(PA-PA), offers a relatively high C-yield (~80%) and also good solubility in common organic solvents, such as toluene and tetrahydrofuran (THF). Several uniform dark-red poly(PA-PA) fibers with smooth surface and fiber diameter in the range of 3–6 μm were prepared from 30 wt% poly(PA-PA)/THF solution using electrospinning technique. Furthermore, the resulting precursor fibers were converted to the corresponding carbon structure in a one-step thermal heating process under N 2 atmosphere. Both X-ray and Raman spectra show the polymorphous carbon morphology with the graphene crystalline domains.

36 MATERIALS SCIENCE↗

Indicators of carbon alteration (ICAs) suggest patterns in reservoir methane emissions

Reservoir operations influence emissions via multiple causal pathways. In this paper, we quantify indicators of carbon alteration (ICAs) focused on methane. ICAs were chosen to reflect the potential for methane emission along four causal pathways: 1) water column mixing, 2) wet-dry cycles in sediment, 3) sediment redistribution, and 4) vegetation. We developed algorithms to calculate ICAs for three reservoirs along a longitudinal gradient in the Tennessee River basin of the southeast US. The ICAs revealed interesting longitudinal patterns. Indicators of both methane production and destruction increased downstream. The potential for ebullitive methane emissions driven by sub-daily water level fluctuations and emissions mediated by vegetation were higher in downstream mainstem reservoirs than in the upstream tributary reservoir. Along the remaining two pathways, longitudinal patterns were equivocal (sediment pathway) or suggested decreased emissions downstream (water-column mixing). We also observed seasonal patterns and, by combining ICAs, inferred times when ramping could be achieved with lower risk of emissions. The ICAs demonstrated here are the first step in quantifying mechanistic relationships between reservoir operation and methane emissions. In future, they may lead to improved operations in reservoir cascades and regional-scale estimates of emissions that account for differences among reservoirs.

Greenhouse gases↗

Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects

This is the conference paper accompanying an oral presentation “Unveiling the Potential of MeshGraphNets for Predicting Subsurface Evolution in Carbon Storage Projects” at the 17th International Conference on Greenhouse Gas Control Technologies GHGT-17 held in Calgary, Canada, October 20-24 , 2024. Carbon capture and storage (CCS) technology is critical for mitigating climate change but requires effective subsurface reservoir management to ensure safe containment of injected CO2. Accurate predictions of reservoir pressure and saturation are essential for assessing long-term CCS performance. Traditional numerical simulations, while effective, are computationally intensive, time-consuming, and constrained by data discretization. Previous work has shown the effectiveness of MeshGraphNets (MGN), a graph-based machine learning framework, as an innovative alternative for predicting reservoir behavior. MGN leverages graph neural networks (GNNs) and mesh representations to model complex geological formations, offering superior adaptability across different discretizations and reservoir configurations. Classic MGN implementations utilize an autoregressive technique to predict future behavior based on current predictions, but this technique is hampered by error accumulation over time. To enhance the model accuracy in time-series predictions, this study implemented a multi-step rollout strategy that integrates autoregressive predictions during training to stabilize prediction of saturation over time. Using the Illinois Basin – Decatur Project (IBDP) dataset, comprising 100 simulations of CO2 injection, pressure, and saturation changes, the framework demonstrated its ability to learn spatial dependencies and temporal dynamics. With inputs including permeabilities, porosities, and injection rates, MGN accurately predicted CO2 plume evolution over time, even with limited training data. Moreover, the addition of a multi-step rollout procedure during training improved the ability of MGN to predict stably over time by ~15%. This research positions MGN, enhanced with multi-step rollout capabilities, as a robust and efficient tool for CCS applications. It advances the field by enabling precise, computationally efficient predictions of reservoir behavior, providing a foundation for the broader adoption of machine learning frameworks in CCS and other geoscience domains.

Holcomb, Paul↗

Carbon in the Galaxy: Studies from Earth and Space

Presented here is the text of the invited papers presented during a meeting entitled, Carbon in the Galaxy: Studies from Earth and Space, that was held at NASA Ames Research Center on November 5 and 6, 1987. For completeness, abstracts from all of the poster papers and the text of a paper summarizing what was learned during the course of the meeting are also included. The underlying premise for the meeting was that there is much to be gained by bringing together scientists from very different disciplines, all of whom study carbon in different ways for different reasons. The interchanges took place during the meeting and the contents of the enclosed papers validate that premise.

Tarter, Jill C.↗

Electrical Properties of Unidirectional Carbon Fiber Reinforced Epoxy-Graphene Composites

This paper aims at establishing connections between electrical resistivity and stresses in carbon fiber reinforced epoxy-graphene composites. To avoid the interconnection of multiple parameters, we examined composite specimens consisting of a single strand or tow (12,000 carbon fiber filaments) embedded in an epoxy matrix containing up to 1.0 wt% of graphene (TG679) particles. The specimens show resistance increase with the tensile stress. The characteristic of the dependence varies with the content of graphene particles, tending to be linear as the percentage of graphene content increases. We did not observe any significant changes in the ultimate strength of the composite with an increase of the graphene particles concentration.

Daniel Wentzel↗

Connection between the physicochemical characteristics of amorphous carbon thin films and their electrochemical properties

Connecting a material's surface chemistry with its electrocatalytic performance is one of the major questions in analytical electrochemistry. This is especially important in many sensor applications where analytes from complex media need to be measured. Unfortunately, today this connection is still largely missing except perhaps for the most simple ideal model systems. Here we present an approach that can be used to obtain insights about this missing connection and apply it to the case of carbon nanomaterials. In this paper we show that by combining advanced computational techniques augmented by machine learning methods with x-ray absorption spectroscopy (XAS) and electrochemical measurements, it is possible to obtain a deeper understanding of the correlation between local surface chemistry and electrochemical performance. As a test case we show how by computationally assessing the growth of amorphous carbon (a-C) thin films at the atomic level, we can create computational structural motifs that may in turn be used to deconvolute the XAS data from the real samples resulting in local chemical information. Then, by carrying out electrochemical measurements on the same samples from which x-ray spectra were measured and that were further characterized computationally, it is possible to gain insight into the interplay between the local surface chemistry and electrochemical performance. To demonstrate this methodology, we proceed as follows: after assessing the basic electrochemical properties of a-C films, we investigate the effect of short HNO 3 treatment on the sensitivity of these electrodes towards an inner sphere redox probe dopamine to gain knowledge about the influence of altered surface chemistry to observed electrochemical performance. Overall, these results pave the way towards a more general assessment of electrocatalysis in different systems and provide the first steps towards data driven tailoring of electrode surfaces to gain optimal performance in a given application.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Integrating risk assessment methods for carbon storage: A case study for the quest carbon capture and storage facility

This paper documents how tools developed by the National Risk Assessment Partnership (NRAP) complement the Bowtie risk assessment approach through the demonstration of a risk-based Area of Review (AoR) determination for the Quest Carbon Capture and Storage (CCS) facility near Edmonton, Alberta with the NRAP Open-Source Integrated Assessment Model (NRAP Open-IAM). The Bowtie risk assessment for the Quest CCS site was developed by Shell Canada Ltd., who operates the asset on behalf of the Athabasca Oil Sand Project — a joint venture, owned by Canadian Natural Resources Ltd, Chevron Canada and Shell Canada Ltd. The Quest Bowtie treats site risk comprehensively – considering a large set of technical and project risks (e.g., operational risks, above ground infrastructure, public perception, etc.). NRAP tools, methods, and analyses are focused on quantitative assessment of subsurface technical risks. NRAP-Open-IAM was used to evaluate potential groundwater impacts at the Quest site, i.e., a sufficient change above background groundwater quality levels to be measurable, should CO 2 and/or brine leak from the reservoir via a faulty and/or compromised wellbore. Our results show there is a low potential for groundwater impact and support a further reduction (from ~460 to 100 km 2 ) to the established AoR for the Quest site. Integrating both approaches early in the site characterization period could significantly benefit commercial-scale projects by drastically reducing the region over which leakage risks (e.g., legacy wells) need to be evaluated, i.e., the AoR. This is especially true for brownfield sites, which could contain hundreds to thousands of legacy wells. Further, basing monitoring network design on those regions where impacts are most likely to occur has the potential to facilitate more efficient deployment of monitoring technologies and improve the likelihood of detecting a leak should one occur.

58 GEOSCIENCES↗

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↗

Modeling Oxygen Transport in High Surface Area Carbon Supports for Polymer-Electrolyte Fuel Cells

Here, an analytical model for resistance to oxygen transport in air electrodes containing carbon black supports with high surface area was developed by combining a Thiele modulus—effectiveness factor approach at the agglomerate scale (~150 nm) with nanoscale diffusional resistance in carbon micropores/pits (~5 nm). This paper extends an earlier model for transport resistance to platinum nanoparticles on low surface area carbon. Differences in transport resistances between catalyst layers with high and low surface area carbon blacks predicted by the model with reasonable geometric dimensions and physical properties are consistent with experimental observations.

08 HYDROGEN↗