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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Production, fuel properties and combustion testing of an iso-olefins blendstock for modern vehicles

With the increasing pressure to decarbonize the transportation sector, exploring strategies that can reduce emissions from light-duty vehicles (LDV) has become critical. Bioblendstocks that allow for higher engine efficiency and fuel economy could complement vehicle electrification and help reach carbon neutrality by 2050. In this context, the potential of a mixture of iso-olefins as a bioblendstock was investigated for multimode boosted spark-ignition (SI)/advanced compression ignition (ACI) engine operation designed to achieve higher overall vehicle fuel economy. By establishing the relationship between the molecular structure of iso-olefins and research octane number (RON), octane sensitivity (S) (i.e., the difference between RON and motor octane number [MON]), and phi-sensitivity a dimethyl-hexenes rich olefins mixture (DMHROM) was identified as a preferred blendstock for SI/ACI combustion engines. Here, a pathway for DMHROM production from biomass-derived ethanol was developed and scaled up. More than 1 gallon of DMHROM blendstock was produced for fuel properties assessment including engine testing. Measurements in a Cooperative Fuel Research Engine showed that the DMHROM blendstock possesses a RON of 94 and S of 13.5, and blends synergistically. Rapid compression machine tests coupled with single-cylinder gasoline direct injection engine measurements demonstrated the 20 vol.% DMHROM blend has higher phi-sensitivity than an olefin-free gasoline base fuel and a typical California Reformulated Gasoline Blendstock for Oxygenate Blending (CARBOB) gasoline fuel. These results demonstrate the potential of DMHROM for improving gasoline fuel performance and quality for operation under ACI conditions. The effectiveness of the aftertreatment system in mitigating emissions was verified and showed that the pure DMHROM blendstock and 20 vol.% blend would not increase non-methane organic gases, NO x , and carbon monoxide (CO) emissions. The DMHROM blendstock was found to slightly decrease sooting tendency when added to a gasoline-base fuel (i.e., ~6% reduction at 20 vol.% blending level). Oxidation stability and lubricant compatibility were both confirmed for the 20 vol.% blend. Overall, these results demonstrate that dimethyl-hexenes have potential for improving engine efficiency and fuel economy while meeting emissions regulations and ASTM specifications for gasoline fuel.

09 BIOMASS FUELS↗
DOE OSTI2026

Microwave-Assisted Hydrogen Generation from Hydrocarbon-Bearing Reservoir Rocks: Stage-Dependent Thermal Runaway and In-Situ Carbonate Engineering

Microwave-assisted hydrogen generation from hydrocarbon-bearing reservoir rocks is strongly influenced by mineralogy, methane activation, carbonate reactions, and thermal runaway behavior. This study investigates a new approach in which carbonate phases are generated in-situ through the reaction of internally produced CO2 with Ca(OH)2 under microwave heating conditions. The objective is to evaluate how rock mineralogy, methane injection, and Ca(OH)2 addition influence hydrogen generation, carbon redistribution, and stage-dependent reaction pathways during microwave exposure. Microwave heating experiments were conducted using Permian Basin reservoir rocks under three experimental conditions: rock-only experiments under Ar atmosphere, CH4–Ar experiments without additive, and CH4–Ar experiments containing 5 wt% Ca(OH)2. Methane-assisted experiments were performed under continuous injection of 30 standard cubic centimeters per minute (sccm) CH4 and 30 sccm Ar. Based on thermal runaway behavior, each experiment was divided into three operational stages: Before Thermal Runaway (BR), After Thermal Runaway–Decrease in Microwave Power (ARD), and After Thermal Runaway– Increase in Microwave Power (ARI). Temperature and gas composition were continuously monitored throughout the experiments. The rock-only experiments demonstrated that hydrogen generation can occur intrinsically from hydrocarbon-bearing rocks under microwave heating, even without externally injected methane. However, hydrogen production did not correlate solely with kerogen content, indicating that mineralogy strongly influences hydrogen-generation pathways. Correlation analyses suggested that kerogen decomposition initially generated CH4, CO, and CO2, followed by secondary hydrocarbon reactions associated with H2 and C2 hydrocarbon formation. Methane-assisted experiments substantially increased hydrogen production; however, identical methane injection rates produced significantly different hydrogen yields among the rock samples, confirming that mineralogical composition controls methaneconversion behavior under microwave heating conditions. The addition of Ca(OH)2 significantly altered carbon evolution behavior in a stage-dependent manner. During the BR stage, Ca(OH)2 reduced gas-phase CO2 production, particularly in carbonate-rich rocks, indicating favorable conditions for in-situ carbonation and carbonate deposition prior to extensive thermal decomposition. The suppression of CO2 during BR became more pronounced with increasing carbonate content of the rock system. After thermal runaway, carbonate-containing systems exhibited enhanced hydrogen generation behavior, suggesting that carbonatederived mineral transformations and carbonate-mediated reactions contribute to high-temperature hydrogen-generation pathways. In carbonate-poor rocks, Ca(OH)2 addition enabled simultaneous URTeC 4493775 2 enhancement of hydrogen production and partial suppression of CO2 release during the post-runaway stages. Overall, the results demonstrate that microwave-assisted hydrogen generation is governed by dynamically evolving interactions among kerogen decomposition, methane activation, mineral transformations, carbonate formation/decomposition, and thermal runaway behavior. This work introduces in-situ carbonate engineering with Ca(OH)2 as a strategy for coupling hydrogen generation with partial insitu carbon management under microwave heating conditions.

03 NATURAL GAS↗
NASA NTRS2013

Mars Sample Return Using Commercial Capabilities: ERV Trajectory and Capture Requirements

Mars Sample Return was presented as the highest priority planetary science mission of the next decade [1]. Lemke et al. [2] present a Mars Sample Return mission concept in which the sample is returned directly from the surface of Mars to an Earth orbit. The sample is recovered in Earth Orbit instead of being transferred between spacecraft in Mars Orbit. This paper provides the details of this sample recovery in Earth orbit and presents as such a sub-element of the overall Mars sample return concept given in [2]. We start from the assumption that a Mars Ascent Vehicle (MAV), initially landed on Mars using a modified SpaceX Dragon capsule, has successfully delivered the sample, already contained within an Earth Return Vehicle (ERV), to a parking orbit around Mars. From the parking orbit, the ERV imparts sufficient Delta-V to inject itself into an earthbound trajectory and to be captured into an Earth orbit eventually. We take into account launch window and Delta-V considerations as well as the additional constraint of increased safety margins imposed by planetary protection regulations. We focus on how to overcome two distinct challenges of the sample return that are driven by the issues of planetary protection: (1) the design of an ERV trajectory meeting all the requirements including the need to avoid contamination of Earth's atmosphere; (2) the concept of operations for retrieving the Martian samples in Earth orbit in a safe way. We present an approach to retrieve the samples through a rendezvous between the ERV and a second SpaceX Dragon capsule. The ERV executes a trajectory that brings it from low Mars orbit (LMO) to a Moon-trailing Earth orbit at high inclination with respect to the Earth-Moon plane. After a first burn at Trans-Earth Injection (TEI), the trajectory uses a second burn at perigee during an Earth flyby maneuver to capture the ERV in Earth orbit. The ERV then uses a non-propulsive Moon flyby to come to a near-circular Moon-trailing orbit. To perform the Earth Orbit Rendezvous (EOR), a second Dragon capsule is then launched from Earth and a similar lunar flyby is performed to rendezvous with the ERV. The requirements for rendezvous, close proximity operations and capture of the sample canister are described. A concept of operations for sample retrieval is presented along with design specifications of the ERV, the required modifications to the Dragon capsule, as well as the hardware, software, sensors, actuators, and capture mechanisms used. In our concept, a container is mounted to the front hatch of Dragon, capable of accommodating the sample canister and sealing it from the rest of the capsule. The sample canister is captured using a robotic arm with a magnetic grappling mechanism. Dragon then performs a propulsive maneuver to return to Earth for a controlled re-entry while the ERV (sans sample container) is left in the Moon trailing orbit. Contingency cases and related mitigation strategies are also discussed, including the advantages and disadvantages of performing the ERV rendezvous with a crew.

Faber, Nicolas F.↗
DOE OSTI2020

Time-resolved 3D imaging of two-phase fluid flow inside a steel fuel injector using synchrotron X-ray tomography

The multiphase flow inside a diesel injection nozzle is imaged using synchrotron X-rays from the Advanced Photon Source at Argonne National Laboratory. Through acquisitions performed at several viewing angles and subsequent tomographic reconstruction, in-situ 3D visualization is achieved for the first time inside a steel injector at engine-like operating conditions. The morphology of the internal flow reveals strong flow separation and vapor-filled cavities (cavitation), the degree of which correlates with the nozzle's asymmetric inlet corner profile. Micron-scale surface features, which are artifacts of manufacturing, are shown to influence the morphology of the resulting liquid-gas interface. The data obtained at 0.1 ms time resolution exposes transient flow features and the flow development timescales are shown to be correlated with in-situ imaging of the fuel injector's hydraulically-actuated valve (needle). As more than 98.5% of the X-ray photon flux is attenuated within the steel injector body itself, we are posed with a unique challenge for imaging the flow within. Time-resolved imaging under these low-light conditions is achieved by exploiting both the refractive and absorptive properties of X-ray photons. The data-processing strategy converted these images with a signal-to-noise ratio of similar to 10 into a meaningful dataset for understanding internal flow and cavitation in a nozzle of diameter 200 mu m enclosed within 1-2 millimeters of steel.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Stacked Greenfield and Brownfield ROZ Fairways in the Illinois Basin Geo-Laboratory: Co-Optimization of EOR and Associated CO 2 Storage

Residual oil zones (ROZs) are economically viable targets for carbon dioxide enhanced oil recovery (CO 2 -EOR); thick, carbonate ROZs in the San Andres Formation in the Wasson Field of the Permian Basin are an example. Incremental oil produced from CO 2 -EOR can be carbon negative via associated storage of injected CO 2 . Given the regional extent of ROZ fairways and generally higher net utilization of CO 2 (compared to conventional CO 2 -EOR), ROZs provide the opportunity for significant carbon neutral to carbon negative oil production with associated CO 2 storage, and therefore should be a priority target for exploration. However, ROZs have not been widely recognized or identified due to poor or no conventional oil production. Hence, in places like the Illinois Basin (ILB), exploratory analyses are required to recognize the existence of an ROZ. As part of this study, four formations were selected for detailed regional characterization and analysis: Carper Sandstone (part of the Borden Siltstone), Tar Springs Sandstone, Cypress Sandstone, and Middle Devonian (Geneva Dolomite and associated Dutch Creek Sandstone). The four formations underwent regional geological characterization to develop a regional geologic framework for the ROZs and their overlying seals. Findings of this study are supported by data from two field laboratory sites, one with stacked greenfield ROZs and the other with a stacked complex that includes a brownfield ROZ and depleted conventional reservoirs. The field laboratory sites were used to collect data and conduct tests to validate ROZ detection methodologies and identify economic field-deployable strategies to co-optimize CO 2 -EOR and associated storage in stacked ROZs. Findings from these field sites were extrapolated to characterize the basin-wide stacked ROZ fairway resource.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2019

Mid-Atlantic U.S. Offshore Carbon Storage Resource Assessment Project (Final Technical Report)

The greatest potential for carbon storage in the northeastern United States lies in the offshore geologic formations comprising the outer continental shelf (Monteverde et al., 2011). Offshore storage can be linked to large point-sources of carbon dioxide (CO 2 ) while avoiding many of the logistical difficulties and potential risks encountered when siting onshore projects, especially in densely populated areas of the East Coast. Offshore CO 2 storage assessment and research in the United States is underway to address uncertainty in potential storage resources, particularly in the mid- and north-Atlantic offshore area. Given the current knowledge base and access to publicly available data, the objectives of the Mid-Atlantic U.S. Offshore Carbon Storage Resource Assessment Project (MAOCSRAP) were fourfold: (1) complete a systematic carbon storage resource assessment of the mid-Atlantic offshore coastal region from the Georges Bank Basin (GBB) through the Long Island Platform (LIP) to the southern Baltimore Canyon Trough (BCT); (2) define key input parameters to reduce uncertainty for offshore storage resource and efficiency estimates; (3) perform a preliminary assessment of risk factors, uncertainties, and data gaps; and (4) engage industry and regulatory stakeholders through development of a Road Map to assist future project planning and implementation. The MAOCSRAP project has compiled, inventoried, and assimilated various publicly available data sets to provide a strong technical basis on which future carbon storage studies and applications can be built. The knowledge infrastructure necessary to support the development of full-scale offshore carbon storage include: Defining the geologic characteristics of candidate storage sites (Chapter 2). Using existing seismic data to better define the continuity of the storage zones and seals (Chapter 3). Cataloguing the hydrogeologic properties of mid-Atlantic offshore storage sites (Chapter 4). Calculating prospective CO 2 storage resources using net effective pore volumes and fluid displacement properties specific to offshore lithologies (Chapter 5). Examining risk factors related to offshore storage (Chapter 6). Communicating with industry and other stakeholders about the future prospects for offshore storage (Chapter 7). Ensuring technology transfer to industry and other stakeholders (Chapter 8). Led by Battelle, this project was conducted by public and private entities with expertise in offshore geology and resources for the study region, including state geological surveys of Delaware, Maryland, and Pennsylvania; United States Geological Survey-Woods Hole Coastal and Marine Science Center and Haifa University; Rutgers University; Harvard University; and Lamont-Doherty Earth Observatory (LDEO) at Columbia University. The storage resource assessment was completed for a broad region offshore of the U.S. East Coast, from Massachusetts to Virginia. The results include high-level storage resource estimates for areas not previously characterized and improved storage resource estimates for geographically expansive portions of offshore geologic units. Results of the project provide a foundation for developing CO 2 storage along offshore areas of the mid-Atlantic United States. A combination of information was used to provide confidence in project results. Key findings of the major project tasks are summarized as follows. Subsurface Data Analysis: Legacy seismic, well-log, core, and biostratigraphic data were digitized, reprocessed, and analyzed using modern techniques, augmenting previous characterization efforts. The sequence stratigraphic framework for the Cretaceous and Jurassic strata was developed by correlating well-log depositional sequences to seismic reflectors identified in the BCT, LIP, and GBB. The integration of well-log stratigraphy with seismic stratigraphy and petrophysical analysis helped to identify and map potential storage zones within sequences of the Logan Canyon (LC), Missisauga, and Mohawk formations, as well as the regionally extensive caprock comprised of the Dawson Canyon shale. Approximately 4,000 kilometers (km) of seismic data was reprocessed to create a structural framework that was used to tie together all available well data, constrain sequence stratigraphic interpretations, and make regional assessments of offshore carbon storage resources. Prospective storage resource estimates were 150 to 1136 megatons (Mt) for the combined storage zones. This suggests mid-Atlantic U.S. offshore formations can store decades of CO 2 from industrial sources in the region. Preliminary local reservoir simulations suggest that injection rates of 1 Mt CO 2 /year may be sustained for 30 years in single injection wells in the BCT. Advanced geologic modeling and new data acquisition are needed to address data gaps and advance carbon capture and storage (CCS) in key offshore areas selected for further investigation. Offshore Risk Factors: Offshore geologic risk factors include soft sediment deformation, unit continuity, sedimentological and structural features, seismicity and hydrates. CO 2 storage risks include inadequate seals, migration/leakage, and chemical interactions leading to decreased storage. Sensitive habitats, environmental impacts, disturbance to seafloor, and other risks need to be identified in advance of project activities and integrated into detailed mitigation plans for all project phases. Stakeholder Engagement: Input and participation from government, industry, and environmental groups provided input into the Road Map and address next steps needed for project deployment. Early engagement and ongoing communication, as well as policy framework development, is key to large-scale deployment of CCS. Next Steps: This project represents an important first step by completing a high-level CO 2 storage resource assessment and building the knowledge infrastructure necessary to improve quantitative storage resource estimates. The data sets that have been curated under this project provide an opportunity to conduct research and development (R&D) needed to address data gaps and reduce risk and uncertainty. Offshore characterization and validation strategies that are systematically designed to provide data and infrastructure that can be upscaled to meet commercial requirements could be developed off of this foundation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Towards time-resolved MicroED grid preparation using mix-and-inject gas dynamic virtual nozzles

Recent progress in gas dynamic virtual nozzle (GDVN) technologies in combination with high-brilliance synchrotron and X-ray free-electron lasers (XFELs) has allowed the visualization of protein dynamics in crystallo by mixing macromolecular protein crystals with a substrate using tunable mixing times on the order of milliseconds to seconds prior to serial X-ray diffraction data collection. This has become the method of choice for high-resolution structure determination of intermediate states. However, such experiments require large counts of crystals of proper sizes for high-resolution data collection, and premium beam times for screening efforts. Cryogenic microcrystal electron diffraction (MicroED) represents a complementary technique that may be a more accessible avenue for time-resolved nanocrystallography compared with serial X-ray diffraction experiments. MicroED can produce full diffraction datasets from just a few submicrometre-thick crystals, and the approach is more readily accessible, requiring standard cryogenic transmission electron microscopy (TEM) equipment available at many universities and institutes. Cryogenic MicroED, like other forms of cryo-EM, begins with rapidly freezing biological material on electron microscopy grids. In the case of MicroED, micro- to nano-crystals (<500 nm thick) are deposited onto electron microscopy grids and plunge-frozen for subsequent electron diffraction data collection. Here, we have incorporated GDVN technology developed originally for XFEL experiments into the freezing process as a first step towards time-resolved studies. We describe the limited deposition efficiency of the model MicroED protein proteinase K on TEM grids using GDVNs, preceding sample vitrification and successful MicroED data collection. We discuss both the initial results from such experiments and the methodological challenges in developing this approach into a reliable workflow for millisecond-to-second time-resolved structural studies of macromolecules. Our results promise a strategy to deposit crystals on grids using GDVNs and determine high-resolution structures by MicroED, constituting a first step towards development of time-resolved MicroED experiments.

MicroED↗
DOE OSTI2026

Flexible Natural Gas/Hydrogen CHP System

This project included design, development, and demonstration of a cost-effective and scalable, unique-to-the-industry 2.0 MWe fuel-flexible Caterpillar G3516 CHP genset that can run on 100% hydrogen, 100% natural gas, and up to 25% blends of hydrogen in natural gas (volume basis). This was accomplished based on over two years of extensive R&D work done on a single-cylinder engine for developing innovative hydrogen fueling, combustion, air, and electronic control systems design and strategies. Findings from the single-cylinder engine work were scaled up and applied for modifications of and lab testing and development of a 2.0 MWe 16-cylinder G3516 fuel-flexible engine-genset and electronic controls systems. During this testing and development in the engine lab, the genset was run on 100% hydrogen, 100% natural gas, and up to 25% blends of hydrogen in natural gas (volume basis) and its steady-state and transient performance and emission were documented.

03 NATURAL GAS↗
DOE OSTI2021

Preheating and premixing effects on NO x emissions in a high-pressure axially staged combustor

NO x emissions remain a primary concern for modern and future gas turbines, particularly as we progress towards a net-zero carbon future. It is critical to identify novel strategies to mitigate environmental pollutants for both modern turbines operated on natural gas and future turbines projected to use carbon-free fuels (such as hydrogen). In the current study, NO x emissions of a reacting methane-air jet in a vitiated crossflow are experimentally investigated in a model axially staged combustor at 5 atm. The combustion products from the main stage combustor flow into the axial stage at temperatures ranging from 1580 to 1650 °C. The axial stage contains a reacting jet in crossflow, which provides an overall temperature rise ranging from 50 to 220 °C to generate exit temperatures similar to gas turbine engines. The focus of this paper is to explore the effects of flame liftoff and ignition timescales on the NO x contribution of this secondary jet. This is done by varying the premixed level and preheat temperature of the axial jet. The effects are explored at different momentum flux ratios (J), jet equivalence ratios (φ jet ), exit temperatures (T exit ), and main stage (headend) temperatures (T HE ). High-speed CH* chemiluminescence imaging is employed for each test case to determine the flame stabilization point. For a given temperature rise and combustor exit temperature, an increase in ignition delay was observed with a decrease in jet temperature. This provided a NO x benefit, particularly for jets that are injected at or close to an ignitable mixture fraction. Similarly, the coaxial injector caused a significant ignition delay compared to the fully premixed injector; this also led to a NO x benefit. Overall, the results show that a thermally driven delay in the axial stage provides a greater NO x reduction than a mixing delay.

03 NATURAL GAS↗
DOE OSTI2021

Depletion of Fractalkine ameliorates renal injury and Treg cell apoptosis via the p38MAPK pathway in lupus-prone mice

Highlights: • FKN and p-p38 were increased in the renal of lupus mice. • Anti-FKN antibody and SB203580 ameliorated renal injury in lupus mice. • FKN KD and SB203580 reduced cell apoptosis, and suppressed p38MAPK signal in Treg cells derived from lupus mice spleen. • The p38MAPK activator U-46619 had the opposite effect in these cells. • Depletion of FKN ameliorates renal injury and Treg cell apoptosis via p38MAPK signal in lupus nephritis. Fractalkine (FKN) is a chemokine with several roles, including chemotaxis; adhesion; and immune damage, which also participates in cell inflammation and apoptosis and responds to the pathogenesis of autoimmune diseases. Given the involvement of regulatory T cells (Treg) cells in autoimmune diseases, this study investigated the regulatory mechanism of FKN in renal injury and Treg apoptosis via the p38 mitogen-activated protein kinase (p38MAPK) signaling pathway in lupus-prone mice. Lupus was induced in BALB/c female mice by injection of pristane, followed by isolation of CD4{sup +}CD25{sup +} Treg cells from the spleen of lupus model mice. To deplete FKN, mice received injection of an anti-FKN antibody, and Treg cells were transfected with FKN small-interfering RNA. Lupus mice and Treg cells were treated with the p38MAPK inhibitor SB203580 and activator U-46619, respectively, and urine protein and serum urea nitrogen, creatinine, and autoantibodies were measured and renal histopathological changes analyzed. We determined levels of FKN, phosphorylated p38 (p-p38), and forkhead box P3 (FOXP3) in renal tissue and Treg cells, and analyzed apoptosis rates and levels of key apoptotic factors in Treg cells. The renal FKN and p-p38 levels increased, whereas renal FOXP3 level decreased in lupus-prone mice. Treatment with the anti-FKN antibody and the p38MAPK inhibitor ameliorated proteinuria and renal function, significantly reducing serum autoantibody, renal FKN, and p-p38 levels while increasing renal FOXP3 level in lupus-prone mice. Moreover, FKN knockdown and administration of the p38MAPK inhibitor reduced apoptosis and levels of pro-apoptotic factors, increased levels of anti-apoptotic factors, and suppressed activation of p38MAPK signaling in Treg cells derived from lupus model mice. Furthermore, treatment with the p38MAPK activator U-46619 had the opposite effect on these cells. These data indicated that depletion of FKN ameliorated renal injury and Treg cell apoptosis via inhibition of p38MAPK signaling in lupus nephritis, suggesting that targeting FKN represents a potential therapeutic strategy for treating Lupus nephritis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

A cloud computing approach to massively-parallel distributed stochastic optimization with application to geomechanical reservoir characterization

Many search strategies used to optimize parameters during hydrologic model calibration are inherently limited in that simulations must be performed sequentially in order for the algorithm to converge. As a result, the overall time required to reach a solution increases linearly with the number of steps necessary. In contrast, sampling strategies that attempt to approximate the posterior distribution of the parameters do not require the model simulations to be run in sequence and therefore invite the use of a massively parallel approach across heterogeneous computing environments. We apply a cloud computing methodology to this problem where a head node running on Amazon Web Services continuously produces candidate models that are distributed to arbitrary compute environments to run the simulation, in our case Clemson’s Palmetto cluster computer. Thus the time required to obtain a sufficient number of samples to produce an adequate approximation of the posterior distribution of the parameters is limited by the number of available compute sites. Monte Carlo sampling of the posterior space would be duplicative and inefficient, thus we combine Latin hypercube methods with genetic algorithms to ensure that no large regions of the parameter space are left unexplored, and that high probability regions are investigated thoroughly. We independently assess the fit to different types of data sets without the need to construct a single objective function. Sets of Pareto optimal models are particularly valuable when the quality and information content of data is poorly known or conceptual model errors exist in our simulation. We illustrate our approach for a problem where in situ strain data are used to calibrate the parameters of an oil reservoir in the Avant oil field in Oklahoma. We use well injection and shut-in to stress a deep (500m) confined formation, and observe the geomechanical response using borehole strainmeters installed in the shallow subsurface (30m). These data were then used to calibrate the poroelastic properties of the reservoir and caprock along with the geometry of an elliptic channel associated with the formation. Using our approach we are able to identify issues with model error as well as substantial tradeoffs that occur within the parameters.

inversion, stochastic, geomechanics, poroelastic, ↗
DOE OSTI2020

Pump-and-Treat Impacts on Aquifer Conditions and the Development of System-Wide Performance Strategies - 20377

The pump-and-treat (P and T) system on the Hanford Site's Central Plateau currently treats multiple contaminants within the 200-ZP-1 operable unit, including nitrate through its biological treatment processes. Although it was initially designed to support the 200-ZP-1 Remedial Action Objectives, the P and T system has evolved in use to address contaminants from other regions of the aquifer as well. The P and T influents are biogeochemically distinct, treating groundwaters with elevated concentrations of cyanide, uranium, technetium-99, and nitrate. Given the varying geochemical signatures from current and potential future sources, operational conditions, and amendments considered for treatment processes, there is a need to identify the impacts that the P and T effluent has on the aquifer, and how the aquifer affects P and T performance. To this end, laboratory efforts have focused on characterizing P and T effluent and its biogeochemical effects on the sediments through a series repacked column experiments. The P and T effluent is rich in particulate matter. A systematic inspection of this particulate matter in the P and T effluent showed significant levels of manganese/iron oxides, calcite crystals, relatively large organic matter molecules, and biomass. Therefore, the column experiments were designed and conducted for four different treatment systems: artificial groundwater, filtered P and T effluent, non-filtered P and T effluent, and chlorinated P and T effluent. Different levels of microbiologically- and geochemically-induced changes in the columns occurred and modified the flow systems. For example, physical filtration occurred in the sediments where the particulate material had accumulated in the top portion of the column. Reactive transport modeling of the laboratory experiments is being carried out so that the reaction network can be extrapolated to the field scale. These simulations will provide predictive evaluations of system performance based on P and T operational changes and aquifer mass loading and capacity estimates. This information can be used to address combined subsurface and operational challenges, such as the need for frequent well redevelopment to maintain injection capacity. This information also provides the technical basis for decisions related to the P and T system operations that support remedy optimization efforts and short- and long-term remedy decisions related to multiple operable units on the Hanford Site Central Plateau. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Optics Studies for Multipass Energy Recovery at CEBAF: ER@CEBAF

Energy recovery linacs (ERLs), focus on recycling the kinetic energy of electron beam for the purpose of accelerating a newly injected beam within the same accelerating structure. The rising developments in the super conducting radio frequency technology, ERL technology has achieved several noteworthy milestones over the past few decades. In year 2003, Jefferson Lab has successfully demonstrated a single pass energy recovery at the CEBAF accelerator. Furthermore, they conducted successful experiments with IR-FEL demo and upgrades, as well as the UV FEL driver. This multi-pass, multi-GeV range energy recovery demonstration proposed to be carried out at CEBAF accelerator at Jefferson Lab focuses on demonstrating highest energy recovery in super conducting linac in the low-current range. Continuous electron beam accelerate up to 7.5 GeV within 5-passes and decelerate in the next 5-passes recovering RF energy and dumps at a low energy dump. The beamline optics design for recirculating linacs require special attention to avoid beam instabilities due to RF wakefields. Usually, multi-pass linac beam lines require stronger focusing at lower energies as that is necessary to avoid beam breakup (BBU) instabilities, even with this small beam current. The CEBAF linac optics optimization is focused on balancing over-focusing at higher energies and beta excursions at lower energies. The race-track-shaped geometry of CEBAF accelerator allows its linacs to accommodate multiple energy beams simultaneously, while individual recirculating arcs transporting one beam energy, are shared between accelerating/decelerating beams. For the linac optics optimization process, an extended strategy is used that is originally used in 6-pass Recirculating Linac design of the LHeC, to represent the ten passes through a single linac. Using proper mathematical expressions, linac optics optimization can be achieved with evolutionary genetic algorithms, with Multi-Objective optimization. This thesis introduces a CEBAF optics redesign tailored to accommodates the ER@CEBAF multi-pass ER scheme. The isochronous arcs were retuned to match into optics solutions for optimized 10-pass linacs. Within this work, a single bunch particle tracking analysis presented here focuses on the further improvements of the beamline and beam transportation.

Neththikumara, Isurumali↗
DOE OSTI2023

Deep Learning for Modeling Enhanced Geothermal Systems

Enhanced Geothermal Systems (EGS) offer a vast potential to expand the use of geothermal energy. Heat is extracted from this engineered system by injecting cold water into a subsurface fractures, which are in contact with the hot dry rock, and pulled through the production wells. Creating EGS requires improving the natural permeability of hot crystalline rocks. To develop economically viable EGS reservoirs, significant technical barriers (e.g., better stimulation technologies without adequate water and/or permeability) and non-technical barriers (e.g., land access and permitting) must be overcome. In this short conference paper, we present a workflow to address a part of this challenge – “How to develop economically viable EGS using existing technologies?”. Our workflow called the GeoThermalCloud (GTC) for EGS, leverages recent advances in machine learning, deep learning, and cloud computing. This GTC framework is open-source and available at https://github.com/SmartTensors/GeoThermalCloud.jl. The GTC framework provides trained deep learning (DL) models to estimate the net present value of a given EGS design scenario. The Geothermal Design Tool (https://github.com/GeoDesignTool/GeoDT.git), a fast and simplified multi-physics solver, is used to develop a database for training DL models. The database consists of EGS design parameters (inputs to DL model) and their net present value (output of DL model) in uncertain geologic systems. The EGS design parameters for constructing this training database are based on Utah FORGE but include the options of more wells and deeper depths. The DL models are trained by ingesting the EGS design parameters and estimating the corresponding net present value. Such an emulation allows us to screen various EGS designs quickly and identify good development strategies by coupling them with optimization techniques. Our preliminary results show promise in DL emulation of net present value. However, a lot more work is needed to improve the predictive capability of DL models (i.e., extensive hyperparameter tuning is necessary). This will be the primary focus of our future work.

artificial neural networks, geothermal↗
DOE OSTI2021

Protective effects of intravitreal administration of mesenchymal stem cell-derived exosomes in an experimental model of optic nerve injury

Traumatic optic neuropathy results in the loss of retinal ganglion cells (RGCs), leading to unavoidable visual impairment. However, there is no effective therapy by far. Accumulated studies support the perception that mesenchymal stem cells (MSCs) secrete exosomes that serve as a protective paracrine factor. The study aimed to explore and evaluate the potential therapeutic effects of intravitreal transplantation of MSC-derived exosomes (MSC-exos) in an experimental model of optic nerve crush (ONC). Exosomes were isolated from rat MSCs and characterized by transmission electron microscope and western blotting. At the onset of ONC, a single intravitreal injection of exosomes or PBS was administered to the rats. At day 30, hematoxylin and eosin staining, immunohistochemistry, and βIII-tubulin staining were performed to evaluate the survival of RGCs. Moreover, TUNEL assay was used to examine the apoptosis of RGCs. Inflammation-relevant factors were identified via quantitative polymerase chain reaction. The expression levels of cell apoptosis-related molecules and key members of the PI3K/AKT signaling pathway were determined via western blot analysis. We found that MSC-exos exhibited typical characteristic morphologies (cup-shaped) and sizes (peak size of 93 nm). Furthermore, they exhibited substantial expression of the exosome markers CD63 and TSG101, but lacked the expression of the cellular marker GM130. Treatment with intravitreal MSC-exos notably promoted the survival of RGCs in ONC rats. The level of pro-inflammatory cytokines, including TNF-α, IL-1β, IL-6, IL-8, and MCP-1, were reduced, whereas those of the anti-inflammatory factor IL-10 were increased. Moreover, the apoptosis induced by ONC was decreased by the administration of MSC-exos via upregulation of the Bcl-2/Bax ratio and downregulation of caspase-3 activity. Furthermore, MSC-exos significantly stimulated AKT phosphorylation, whereas LY294002 restored the apoptosis-preventing effects of MSC-exos. The results of our results demonstrated that intravitreal administration of MSC-exos ameliorates ONC-induced injury in a rat model. These findings might aid in the development of effective exosome-based therapeutic strategies for the treatment of optic nerve degeneration.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells - increasing or decreasing the fluid flow rates across the wells - and drilling new wells at appropriate locations. The latter is expensive, time-consuming, and subject to many engineering constraints, but the former is a viable mechanism for periodic adjustment of the available fluid allocations. Data and supporting literature from a study describing a new approach combining reservoir modeling and machine learning to produce models that enable strategies for the mitigation of decreased heat and power production rates over time for geothermal power plants. The computational approach used enables translation of sets of potential flow rates for the active wells into reservoir-wide estimates of produced energy and discovery of optimal flow allocations among the studied sets. In our computational experiments, we utilize collections of simulations for a specific reservoir (which capture subsurface characterization and realize history matching) along with machine learning models that predict temperature and pressure timeseries for production wells. We evaluate this approach using an "open-source" reservoir we have constructed that captures many of the characteristics of Brady Hot Springs, a commercially operational geothermal field in Nevada, USA. Selected results from a reservoir model of Brady Hot Springs itself are presented to show successful application to an existing system. In both cases, energy predictions prove to be highly accurate: all observed prediction errors do not exceed 3.68% for temperatures and 4.75% for pressures. In a cumulative energy estimation, we observe prediction errors that are less than 4.04%. A typical reservoir simulation for Brady Hot Springs completes in approximately 4 hours, whereas our machine learning models yield accurate 20-year predictions for temperatures, pressures, and produced energy in 0.9 seconds. This paper aims to demonstrate how the models and techniques from our study can be applied to achieve rapid exploration of controlled parameters and optimization of other geothermal reservoirs. Includes a synthetic, yet realistic, model of a geothermal reservoir, referred to as open-source reservoir (OSR). OSR is a 10-well (4 injection wells and 6 production wells) system that resembles Brady Hot Springs (a commercially operational geothermal field in Nevada, USA) at a high level but has a number of sufficiently modified characteristics (which renders any possible similarity between specific characteristics like temperatures and pressures as purely random). We study OSR through CMG simulations with a wide range of flow allocation scenarios. Includes a dataset with 101 simulated scenarios that cover the period of time between 2020 and 2040 and a link to the published paper about this project, where we focus on the Machine Learning work for predicting OSR's energy production based on the simulation data, as well as a link to the GitHub repository where we have published the code we have developed (please refer to the repository's readme file to see instructions on how to run the code). Additional links are included to associated work led by the USGS to identify geologic factors associated with well productivity in geothermal fields. Below are the high-level steps for applying the same modeling + ML process to other geothermal reservoirs: 1. Develop a geologic model of the geothermal field. The location of faults, upflow zones, aquifers, etc. need to be accounted for as accurately as possible 2. The geologic model needs to be converted to a reservoir model that can be used in a reservoir simulator, such as, for instance, CMG STARS, TETRAD, or FALCON 3. Using native state modeling, the initial temperature and pressure distributions are evaluated, and they become the initial conditions for dynamic reservoir simulations 4....

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Preshaping clear glass at low temperatures

Advances in available glass chemistries and glass processing methods have accompanied and enabled some of the biggest technology revolutions, from the development and mass production of light bulbs to low-loss fiber optics and durable smartphone touchscreens. An emerging generation of low-temperature processing technologies aims to continue this important trend and make a broader array of glass components mass producible. In the issue, Mader et al. (1) describe one such innovation in glass processing—the use of low-temperature injection molding to preshape silica particle–filled composites that can later be transformed into transparent fused silica glass objects. Traditionally, transparent glass objects are manufactured in high volume from molten or softened glass, which is floated, drawn, blown, cast, or blow-molded to a desired shape (see the figure, top). The glass composition and processing technique dictate the working temperature, which is usually quite high (near 1000°C) and often restricts the choice of compatible equipment or limits the choice of glass composition. Because geometry-specific capital investment is required for production, drastic or frequent component design changes or small batches may be cost prohibitive. Alternatively, transparent glass components can also be shaped at ambient temperature from solid glass by a series of subtractive processes, including cutting or multiple stages of grinding, followed by slower processing steps, such as polishing or etching. This approach is somewhat less amenable to mass production, and certain geometries containing tool-inaccessible regions cannot be fabricated in this way. Several emerging glass-shaping technologies aim to reduce the required manufacturing temperatures and still provide access to a broader range of glass compositions and component geometries (see the figure). These approaches use a three-step process. First, a desired shape is preformed at low temperature from a glass-forming, organic-inorganic composite. Next, the preform is dried, and organic materials used to bind particles are removed. Finally, the preform is heated (sintered) well below the glass-melting temperature to densify to transparent glass. Although the second and third steps do occur at increased temperatures, only standard, geometry-agnostic driers and furnaces are required. This strategy builds on the well-studied sol-gel approach to forming monolithic glass, where silica network–forming chemical solutions are poured into molds, slowly dried, and condensed into dense glass without melting (2). In a departure from the sol-gel process, these new technologies use solvents, cross-linkers, and polymers to formulate organic-inorganic composites tuned for compatibility with a particular shaping process, with formats ranging from photocurable liquids to shear-thickening pastes to solids. The composite inorganic loadings are also typically higher than those in the pure sol-gel approach, which drastically reduces shrinkage in comparison.

36 MATERIALS SCIENCE↗