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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Selective penetration behavior of microgels in superpermeable channels and reservoir matrices

Gel treatment is an effective way to attack excessive water production in many mature oilfields around the world. Selective penetration is desired for successful gel treatments. That is, gel materials should easily penetrate the target zones (i.e., channeling features such as superpermeable channels) without entering/damaging the nontarget zones (i.e., reservoir matrices or oil zones). This study revealed that presence of threshold penetration pressure (ΔP th ) was responsible for selective penetration behavior of tested microgels. The concept of ΔP th was utilized to figure out favorable working conditions for effective gel treatments. Microgel dispersions were injected into superpermeable (super-k) sandpacks (mimicking super-k channels in reservoirs, 60–221 darcies), heterogeneous models with super-k channels (79–230 darcies), and sandstone cores (mimicking reservoir matrices, 50–5000 md). The results demonstrated that a minimum differential driving pressure (i.e., threshold penetration pressure, ΔP th ) was required to push microgel particles to penetrate channels or matrices. The critical penetration behavior was closely related to the particle/pore size ratio. Low ΔP th at smaller particle/pore ratios was beneficial to allow easy penetration of gel materials into the channeling zones. On the contrary, high ΔPth at larger particle/pore ratios was desirable to prevent gel materials from massively invading and damaging the matrices. Instead, the gel particles accumulated at the inlet surface, and a gel cake was gradually formed. The cake further prevented the invasion of the gels. The cake could be removed by chemical breakers to resume the injectivity/productivity of the matrices. Correlations were developed to describe the relationship between ΔP th and particle/pore ratio. A distinct transition was identified at the particle/pore ratio of about 3. This research could help identify the favorable conditions to achieve successful gel treatments. In an effective conformance treatment, the particle/pore ratio in the channel should be sufficiently low to allow easy penetration of gel materials into the channel (e.g., particle/pore ratio<2 in this study). Meanwhile, the particle/pore ratio in the matrix should be large enough to support a high ΔP th and thus prevent massive gel invasion into the matrix. This study advances the current pore scale studies (a single particle passing through a single channel) to Darcy-scale characterization.

02 PETROLEUM↗
DOE OSTI2023

K-RET: knowledgeable biomedical relation extraction system

Abstract Motivation Relation extraction (RE) is a crucial process to deal with the amount of text published daily, e.g. to find missing associations in a database. RE is a text mining task for which the state-of-the-art approaches use bidirectional encoders, namely, BERT. However, state-of-the-art performance may be limited by the lack of efficient external knowledge injection approaches, with a larger impact in the biomedical area given the widespread usage and high quality of biomedical ontologies. This knowledge can propel these systems forward by aiding them in predicting more explainable biomedical associations. With this in mind, we developed K-RET, a novel, knowledgeable biomedical RE system that, for the first time, injects knowledge by handling different types of associations, multiple sources and where to apply it, and multi-token entities. Results We tested K-RET on three independent and open-access corpora (DDI, BC5CDR, and PGR) using four biomedical ontologies handling different entities. K-RET improved state-of-the-art results by 2.68% on average, with the DDI Corpus yielding the most significant boost in performance, from 79.30% to 87.19% in F-measure, representing a P-value of 2.91×10−12. Availability and implementation https://github.com/lasigeBioTM/K-RET.

Sousa, Diana F. (ORCID:0000000305979273)↗
DOE OSTI2018

MICP in the Field: Enhancement of Wellbore Cement Integrity and Permeability Modification

Microbially-induced calcite precipitation (MICP) is being widely researched as an emerging technology for subsurface engineering applications including sealing defects in wellbore cement and modifying the permeability of rock formations [1]. Our study team, including Montana State University’s Energy Research Institute and Center for Biofilm Engineering, The University of Stuttgart, Montana Emergent Technologies, and Schlumberger Carbon Services, has conducted two successful MICP-based field trials. The first field test successfully used MICP to seal a horizontal “pancake fracture” in tight sandstone [2]. The following test resulted in MICP sealing of compromised wellbore cement. Both tests were carried out in the Gorgas well in Alabama and used the ureolytic bacteria, Sporosarcina pasteurii, to promote calcium carbonate precipitation. A third field test is now underway targeting an existing oil well, Rexing #4, in Indiana. The Rexing #4 well was previously used as an injection well to sweep residual oil to production wells. Several years ago, injection pressure was lost, and the well was removed from service. Subsequent well logging measurements suggested that, rather than entering the target injection formation, injectate was traveling up the wellbore through defects in the well cement to a sandstone thief zone approximately 50 feet above the target formation. The goal of the field demonstration project at the Rexing #4 well is to use MICP to reduce permeability in the thief zone and cement defect until the injection pressure reaches the pre-breakthrough condition necessary to return Rexing #4 to service as an injection well. The field demonstration in Indiana, funded by the US Department of Energy, will be conducted the first week of December 2017 using a custom mobile laboratory designed for field applications of MICP. Results presented at the conference will include a rationale for the injection strategy employed, as well as its success at sealing the leakage pathway.

Kirkland, Catherine↗
DOE OSTI2019

Wabash CarbonSAFE Subtask 7.1 – Pre-drilling Site Assessment Topical Report: DOE-FE0031626-1

The Wabash CarbonSAFE project will drill a stratigraphic test well at the Wabash Valley Resources facility near Terre Haute, Indiana. Lithologic, geomechanical, and geophysical data collected from samples testing and an extensive geophysical logging suite will be used to determine the feasibility for the geologic sequestration of 50 million metric tons or more of injected carbon dioxide. The primary target reservoir and caprock to be investigated for the Wabash CarbonSAFE project are the Mt. Simon Sandstone and Eau Claire Shale, respectively. The project team has assessed the planned Wabash #1 drilling site using subsurface geologic data and analyses from both Illinois and Indiana. These data were used to generate geologic structure and isopach thickness maps for target reservoir and caprock layers which were incorporated into a detailed discussion of the nature of the Illinois Basin’s Cambro-Ordovician carbon dioxide storage complex at the drilling site. Formation tops were prognosed for 19 lithologic units to aid drilling and coring procedures. Additional GIS analysis indicates that no known structural features will negatively impact the target storage reservoir or caprock, nor will protected and sensitive areas, groundwater resources, or existing resource development be negatively affected by Wabash #1 drilling activities. The Wabash #1 Geologic/Structure Test well drilling permit was awarded by Indiana Department of Natural Resources (IN-DNR) – Division of Oil and Gas on November 12th, 2019, and the well is expected to be drilled to a total depth of approximately 8,350 feet. Potential impacts on drilling progress include abandoned underground coal mines which mined the Springfield and Survant coals until 1964 and 1954, respectively, and a lost circulation zone in the Potosi Dolomite, which has been demonstrated to have intermittent cavernous porosity from karstification. This document also details the coring and sampling program, proposed logging suite, and well testing program, all of which will be dynamically reviewed as drilling progresses.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Optimization of a Lethal, Combat-Relevant Model of Sterile Inflammation in Mice for Drug Candidate Screening

ABSTRACT Introduction Extensive trauma, commonly seen in wounded military Service Members, often leads to a severe sterile inflammation termed systemic inflammatory response syndrome (SIRS), which can progress to multiple organ dysfunction syndrome (MODS) and death. MODS is a serious threat to wounded Service Members, historically causing 10% of all deaths in trauma admissions at a forward deployed combat hospital. The importance of this problem will be exacerbated in large-scale combat operations, in which evacuation will be delayed and care of complex injuries at lower echelons of care may be prolonged. The main goal of this study was to optimize an existing mouse model of lethal SIRS/MODS as a therapeutic screening platform for the evaluation of immunomodulatory drugs. Materials and Methods Male C57BL/6 mice were euthanized, and the bones and muscles were collected and blended into a paste termed tissue–bone matrix (TBX). The TBX at 12.5%–20% relative to body weight of each recipient mouse was implanted into subcutaneous pouches created on the dorsum of anesthetized animals. Mice were observed for clinical scores for up to 48 hours postimplantation and euthanized at the preset point of moribundity. To test effects of anesthetics on TBX-induced mortality, animals received isoflurane or ketamine/xylazine (K/X). In a separate set of studies, mice received TBX followed by intraperitoneal injection with 20 mg/kg or 40 mg/kg Eritoran or a placebo carrier. All Eritoran studies were performed in a blinded fashion. Results We observed that K/X anesthesia significantly increased the lethality of the implanted TBX in comparison to inhaled anesthetics. Although all the mice anesthetized with isoflurane and implanted with 12.5% TBX survived for 24 hours, 60% of mice anesthetized with K/X were moribund by 24 hours postimplantation. To mimic more closely the timing of lethal SIRS/MODS following polytrauma in human patients, we extended observation to 48 hours. We performed TBX dose–response studies and found that as low as 15%, 17.5%, and 20% TBX caused moribundity/mortality in 50%, 80%, and 100% mice, respectively, over a 48-hour time period. With 17.5% TBX, we tested if moribundity/mortality could be rescued by anti-inflammatory drug Eritoran, a toll-like receptor 4 antagonist. Neither 20 mg/kg nor 40 mg/kg doses of Eritoran were found to be effective in this model. Conclusions We optimized a TBX mouse model of SIRS/MODS for the purpose of evaluating novel therapeutic interventions to prevent trauma-related pathophysiologies in wounded Service Members. Negative effects of K/X on lethality of TBX should be further evaluated, particularly in the light of widespread use of ketamine in treatment of pain. By mimicking muscle crush, bone fracture, and necrosis, the TBX model has pleiotropic effects on physiology and immunology that make it uniquely valuable as a screening tool for the evaluation of novel therapeutics against trauma-induced SIRS/MODS.

General & Internal Medicine↗
DOE OSTI2020

Comparing Cetane Number Measurement Methods

Cetane number is one of the most important fuel performance metrics for mixing controlled compression-ignition “diesel” engines, quantifying a fuel’s propensity for autoignition when injected into end-of-compression-type temperature and pressure conditions. The historical default and referee method on a Cooperative Fuel Research (CFR) engine configured with indirect fuel injection and variable compression ratio is cetane number (CN) rating. A subject fuel is evaluated against primary reference fuel blends, with heptamethylnonane defining a low-reactivity endpoint of CN = 15 and hexadecane defining a high-reactivity endpoint of CN = 100. While the CN scale covers the range from zero (0) to 100, typical testing is in the range of 30 to 65 CN. Alternatively, several constant-volume combustion chamber (CVCC)-based cetane rating devices have been developed to rate fuels with an equivalent derived cetane number (DCN) or indicated cetane number (ICN). These devices measure ignition delay for fuel injected into a fixed volume of high-temperature and high-pressure air to simulate end-of-compression-type conditions. In this study, a range of novel fuel compounds are evaluated across three CVCC methods: the Ignition Quality Tester (IQT), Fuel Ignition Tester (FIT), and Advanced Fuel Ignition Delay Analyzer (AFIDA). Resulting DCNs and ICNs are compared for fuels within the normal diesel fuel range of reactivity, as well as very high (~100) and very low DCNs/ICNs (~5). Distinct differences between results from various devices are discussed. This is important to consider because some new, high-efficiency advanced compression-ignition (CI) engine combustion strategies operate with more kinetically controlled distributed combustion as opposed to mixing controlled diffusion flames. These advanced combustion strategies may benefit from new fuel chemistries, but current rating methods of CN, DCN, and ICN may not fully describe their performance. In addition, recent evidence suggests ignition delay in modern on-road diesel engines with high-pressure common rail fuel injection systems may no longer directly correlate to traditional CN fuel ratings. Simulated end-of-compression conditions are compared for CN, DCN, and ICN and discussed in the context of modern diesel engines to provide additional insight. Results highlight the potential need for revised and/or multiple fuel test conditions to measure fuel performance for advanced CI strategies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Robust Carbon Dioxide Plume Imaging Using Joint Tomographic Inversion of Seismic Onset Time and Distributed Pressure and Temperature Measurements (Final Report)

We develop and demonstrate rapid and cost-effective methodologies for spatiotemporal tracking of CO2 plumes during geologic sequestration using joint inversion of seismic data and distributed pressure and temperature measurements. Key elements of our methodology are: (a) a computationally efficient approach to pressure and temperature propagation, (b) analysis of time lapse seismic data using a novel ‘seismic onset time’ approach to detect fluid front propagation, and (c) data assimilation and uncertainty assessment via joint inversion of pressure, temperature and time lapse seismic data, and (d) validating the numerical tomographic inversion using a CO2 injection demonstration projects, specifically data collected from the from the Petra Nova Parish Holdings CCUS project in the West Ranch Field, Texas and the Chester-16 reef CO2 injection site in Northern Michigan which is part of the DOE Midwestern Carbon Sequestration Project. The research team is led by Texas A&M University and includes Battelle as a subcontractor with support from Shell, Anadarko, Chevron and JX Nippon. A carbon dioxide (CO2) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO2 flood in the West Ranch Field as part of the Petra Nova project, the world’s largest post-combustion CO2 capture and utilization initiative. With a fluvial formation geology and large contrasts in permeability, this is a challenging and novel application of CO2 enhanced oil recovery (EOR). We build a predictive dynamic model of the subsurface that incorporates the multiphase and compositional data acquired during the pilot operation. The calibrated model is used for the carbon dioxide plume imaging. The study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. In the second step, local permeability field is fine-tuned using a streamline-based method to match CO2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO2 recovery as a fraction of the injected CO2. The use of seismic onset times has shown great promise for integrating near-continuous seismic surveys for updating geologic models. In this study, we analyze the impact of seismic survey frequency on the onset time approach aiming to extend the application of onset time to infrequent seismic surveys. In addition, we quantitatively examine the nonlinearity of the onset time method and compare it to the commonly used amplitude inversion method. We carry out a sensitivity analysis of seismic survey frequency based on the complete seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. Our results show that an adequate onset time map can be obtained from the infrequent seismic surveys by interpolation between seismic surveys as long as there is no change in the dominant underlying physics between the successive surveys. The study also shows that nonlinearity of the onset time method can be -smaller than that of the amplitude inversion method by several orders of magnitude. Application to the Brugge benchmark case shows that the onset time method obtains comparable permeability update as the traditional seismic amplitude inversion method with faster computation and improved convergence characteristics. We extend the streamline-based data integration approach to incorporate distributed temperature sensor (DTS) data using the concept of thermal tracer travel time. Then, a hierarchical workflow composed of evolutionary and streamline methods is employed to jointly history match the DTS and pressure data. Finally, CO2 saturation and streamline maps are used to visualize the CO2 plume movement during the sequestration process. The hierarchical workflow is applied to a carbon sequestration project in a carbonate reef reservoir within the Northern Niagaran Pinnacle Reef Trend in Michigan, USA. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at the injection well and a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. The history matching results indicate that the CO2 movement is mostly restricted to the intended zones of injection which is consistent with an independent warm-back analysis of the temperature data. In addition to employing simulation models and inverse methods for CO2 plume imaging, we also initialized a data-driven technology for detecting inter-well connectivity based on production and pressure data. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO2 EOR projects utilizing the water-alternating-gas (WAG) process. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. Texas A&M University, the lead organization in the project, was primarily responsible for the development of tomographic approaches for CO2 plume mapping in conjunction with distributed pressure, temperature and seismic onset time data. Battelle, as a subcontractor, was primarily responsible for the development of analytical and empirical methods for analyzing transient injection rate and pressure data from point/line sources such as injection and monitoring wells. An additional area of emphasis for Battelle was the use of machine learning for such tasks as inferring reservoir connectivity information from injection-production data, and identifying variable importance for machine learning-based proxy models developed from full-physics simulations. The two organizations also collaborated on the application of the tomographic inversion methodology for a field data set.

02 PETROLEUM↗
DOE OSTI2022

Hybrid Data-Driven Physics-Based Model Framework Implementation: Towards a Secure Cyber-Physical Operation of the Smart Grid

False data injection cyber-attack detection models on smart grid operation have been much explored recently, considering analytical physics-based and data-driven solutions. Recently, a hybrid data-driven physics-based model framework for monitoring the smart grid is developed. However, the framework has not been implemented in real-time environment yet. In this paper, the framework of the hybrid model is developed within a real-time simulation environment. OPAL-RT real-time simulator is used to enable Hardware-in-the-Loop testing of the framework. IEEE 9-bus system is considered as a testing grid for gaining insight. The process of building the framework and the challenges faced during development are presented. The performance of the framework is investigated under various false data injection attacks.

false data injection attack, machine learning, sta↗
DOE OSTI2018

Calculating Trajectories Associated With Solute Transport in a Heterogeneous Medium

Here, we present a trajectory-based technique for calculating solute transport in a porous medium that has several advantages over existing methods. Unlike streamlines, the extended trajectories are influenced by each of the important parameters governing transport, including molecular diffusion and transverse dispersion. The approach is complete and does not require any additional techniques, such as operator splitting or particle tracking, in order to account for the full dispersion tensor. The semianalytic expressions make it clear how the flow field, the concentration distribution, and the dispersion tensor contribute to the velocity field of an injected solute. The equations are valid for an arbitrary porous medium, including those with rapid spatial variations in properties, overcoming limitations faced by previous approaches based upon asymptotic techniques. A test on a layered model with sharp boundaries indicates that the extended trajectories are compatible with the results of a numerical simulator and differ from streamlines. We also describe a new form of the dispersion tensor that incorporates a known asymmetry. The trajectories indicate that the modifications of the dispersion tensor lead to more focused transport within regions of high conductivity. The trajectories are used to define a semianalytic relationship between solute travel times and variations in solute velocities along a path that may be used for tomographic imaging. In an application to the injection of a radioactive tracer into a Berea sandstone core, monitored using micropositron emission tomographic (micro-PET) observations, the sensitivities are used to map the spatial variations of permeability within the core.

42 ENGINEERING↗
DOE OSTI2020

Reducing Cost of Chlorinated Volatile Organic Compound Remediation by Transitioning from Active to Passive Soil Vapor Extraction - 20157

Areas of high chlorinated volatile organic compound (cVOC) contamination at the Savannah River Site (SRS) have been undergoing remediation via soil vapor extraction, sometimes coupled with thermal treatments to enhance extraction rates. These active systems are effective in removing large amounts of contaminant mass from the subsurface and mitigating the impacts to groundwater. However, as extraction rates decline, costs must be evaluated with respect to the benefit of continued active operation. A decision framework for identifying conditions when a transition to a more passive remediation is appropriate has been developed with state and federal regulatory agencies. Two remediation areas have recently been transitioned from active soil vapor extraction (ASVE) to passive soil vapor extraction (PSVE) at the SRS. Performance evaluation goals including plume stabilization, overall mass removal trends, environmental sustainability and costs were considered in transitioning from active remediation to passive technologies at both sites. At the Dynamic Underground Stripping (DUS) project at the M-Area Settling Basin, ASVE was combined with steam injection to extract cVOCs during active operations. Steam injection occurred from September 2005 to September 2009. DUS utilized 63 steam injection wells, 34 active vapor extraction wells, and 3 active soil vapor extraction units (SVEUs). Two active SVEUs had 60 horsepower blowers; the third had a 25-horsepower blower. Mass removal was closely tracked during DUS operations; over 181,437 kilograms (400,000 pounds) of cVOCs were removed while active steam injection occurred. After steaming was stopped, ASVE continued. The 34 active wells were evaluated in 2012. The ASVE wells were grouped into categories of high, medium, and low extraction rates. High producing wells remained connected to a single active SVEU. Low producing wells were abandoned, and the medium producing wells were transitioned to PSVE (Microblowers{sup TM}). Microblowers{sup TM} utilize a dedicated blower per well and are solar powered. This passive technology provides energy, maintenance, and operation costs savings while still providing an efficient reduction in cVOC migration to groundwater. In 2018, the remaining ASVE wells were evaluated again. The purpose of this testing was to identify which wells removed the most mass. An optimal well configuration was determined. The criteria to discontinue ASVE was removal of less than 18 kilograms (40 pounds) per week of cVOCs. After 3 months of shutdown (rebound conditions), 2.7 kilograms (5.9 pounds) of cVOCs per week were being removed. Data from the rebound test justified ending ASVE and transitioning wells with higher extraction rates to PSVE. Wells that had depleted the cVOC mass within their zone of influence were abandoned. Performance data from existing PSVE wells justified ending PSVE at wells with depleted extraction rates. Currently the system has 16 PSVE wells operating. Another ASVE system was being used to treat cVOC contaminated soil at the A-Area Miscellaneous Rubble Pile (AMRP) at SRS. System operation began in 2004, with 7 ASVE wells connected to a 60- horsepower blower. Mass removal rates and contaminant concentrations remained consistently low over the ASVE lifespan at AMRP. This indicated that mass removal was diffusion limited. With this data, the 7 ASVE wells were transitioned to PSVE in 2017. Twelve pressure monitoring points were also transitioned to PSVE wells. AMRP currently has 19 PSVE wells operating. Both transitions from active to passive remediation had concurrence from the United States Environmental Protection Agency and the South Carolina Department of Health and Environmental Control. These transitions ensure that only the necessary amount of energy is being exerted to remediate the environment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Bench-Scale Apparatus for Rapid, Simultaneous, Comprehensive Vapor–Liquid Equilibrium and Kinetic Property Measurements to Advance CO 2 Capture Solvent Technology

We present here, the design, fabrication, and testing of a new "pressure, volume, temperature (PVT)" apparatus that enables rapid standardized testing for viscosity, vapor–liquid equilibria, and kinetics for water-lean carbon capture solvents. This unit is the first of its kind where equilibrium data are collected during operation as a PTx (pressure–temperature–composition) cell while kinetic data are collected simultaneously with an internal mini wetted-wall contactor (WWC) using controlled adjustments of CO 2 injections to allow for measurements of gas flux (in and out of the liquid). Additionally, in situ measurements of viscosity data are also continuously collected while a solvent is in circulation during gas absorption. This cell empowers comprehensive testing of critical CO 2 capture solvent properties in a single measurement, ensuring all data are collected at the same temperature, pressure, and CO 2 loading. This apparatus also expedites screening of materials since less than 50 mL of sample is needed as compared to 2–3 L needed to get similar data from a conventional WWC. In conclusion, we describe here the methodology of data collected on this new PVT cell, nicknamed “Gary” in honor of Professor Gary Rochelle, for multiple water-lean amine solvents, which we compare to data collected from conventional instrumentation for amine testing.

Zheng, Richard [STARS Technology Corporation, Rich↗
DOE OSTI2018

Von Hippel-Lindau (VHL) protein antagonist, VH298, promotes functional activities of tendon-derived stem cells and accelerates healing of entheses in rats by inhibiting ubiquitination of hydroxy-HIF-1α

Enthesis is the region where a tendon attaches to a bone. It is a relatively vulnerable position, and in most cases surgical treatment is required upon rupture. The reconstructed enthesis is usually weaker compared to the original, and is prone to rupture again. Hypoxia-inducible factor-1 α (HIF-1α) is known to be involved in extensive activities in cells. It is inhibited under normoxic conditions, and undergoes two essential processes, hydroxylation and ubiquitination, the latter of which has been largely unexplored. Herein, we measured the levels of HIF-1α and hydroxy-HIF-1α in VH298-treated rat tendon-derived stem cells (TDSCs) by immunoblotting. We also detected the proliferation of TDSCs using CCK-8 assay and the mRNA levels of related genes by quantitative RT-PCR. The TDSCs were observed to be induced and the chondrogenic differentiation related genes were found to be enhanced. We also simulated in-vitro wounding in a scratch test and reconstructed the enthesis in a rat model of Achilles tendon by classical surgery followed by administration of phosphate buffer saline (PBS) injection or VH298 injection. We observed that HIF-1α and hydroxy-HIF-1α levels were increased in VH298-treated TDSCs in a dose- and time-dependent manner. Thirty micromolar VH298 could significantly increase cell proliferation, migration, and expression of collagen-1α, collagen-3α, decorin, tenomodulin, tenascin C genes, and chondrogenic differentiation-related genes, collagen-2α, SRY-box9, aggrecan. VH298-treated enthesis could tolerate more load-to-failure, had a better healing pattern, and activation of HIF signaling pathway. VH298 can thus enhance the functional activities of TDSCs, enhance their chondrogenic differentiation potential, and accelerate enthesis healing by inhibiting the ubiquitination of hydroxy-HIF-1α.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Machine learning based rate optimization under geologic uncertainty

We propose a novel approach for rate optimization during a waterflood under geologic uncertainty in reservoir properties such as permeability and porosity. The traditional approach typically involves several runs of the forward simulator. This may not scale well when the optimization is to be performed at the full field-level and over multiple geologic realizations. A machine-learning (ML) based approach which is quick and scalable for rate optimization over multiple geologic realizations is proposed instead. The training data for the model is generated by running the forward simulator with randomly assigned well rates using multiple geologic realizations. A reduced order representation of the permeability heterogeneity in each of the realizations is derived using a grid connectivity transformation (GCT). This step involves finding basis functions corresponding to the different modal frequencies of the grid connectivity represented by the grid Laplacian. The projection of the heterogeneous property field along these basis functions gives the basis coefficients that form the reduced order representation. Subsequently, for each training datapoint, streamlines are traced and the minimum time of flight (TOF) representing the tracer breakthrough time at each producer is recorded. The basis coefficients and well rates are fed to a machine learning model as input and the minimum TOF at the producers forms the output of the model. This trained model can then be used along with an optimizer for computing the optimal injection rates to maximize the injection sweep efficiency. This corresponds to minimizing the variance in the minimum TOF within each well group. Different architectures of neural network are tested using 5-fold cross validation to decide the best ML model to compute the streamline time of flight. The trained model is used to perform well rate optimization over multiple realizations of geology by using a risk tolerance penalty. The optimal well rates thus obtained are compared with two cases: a) equal well rates assigned to all injectors and producers and b) well rates obtained by optimizing over a single realization without considering the uncertainty in geology. The optimal well rates are seen to offer better oil recovery and sweep efficiency than both cases.

02 PETROLEUM↗
DOE OSTI2022

Physics makes the difference: Bayesian optimization and active learning via augmented Gaussian process

Abstract Both experimental and computational methods for the exploration of structure, functionality, and properties of materials often necessitate the search across broad parameter spaces to discover optimal experimental conditions and regions of interest in the image space or parameter space of computational models. The direct grid search of the parameter space tends to be extremely time-consuming, leading to the development of strategies balancing exploration of unknown parameter spaces and exploitation towards required performance metrics. However, classical Bayesian optimization (BO) strategies based on the Gaussian process (GP) do not readily allow for the incorporation of the known physical behaviors or past knowledge. Here we explore a hybrid optimization/exploration algorithm created by augmenting the standard GP with a structured probabilistic model of the expected system’s behavior. This approach balances the flexibility of the non-parametric GP approach with a rigid structure of physical knowledge encoded into the parametric model. The fully Bayesian treatment of the latter allows additional control over the optimization via the selection of priors for the model parameters. The method is demonstrated for a noisy version of a standard univariate test function used to evaluate optimization algorithms and further extended to physical lattice models. This methodology is expected to be universally suitable for injecting prior knowledge in the form of physical models and past data in the BO framework.

42 ENGINEERING↗
DOE OSTI2023

IN SITU PLASMA PROCESSING OF SUPERCONDUCTING CAVITIES AT JLAB, 2023 UPDATE

Jefferson Lab has an ongoing R&D program in plasma processing which just completed a round of production processing in the CEBAF accelerator. Plasma processing is a common technique for removing hydrocarbons from surfaces, which increases the work function and reduces the secondary emission coefficient. The initial focus of the effort was processing C100 cavities by injecting RF power into the higher order mode (HOM) coupler ports. Results from processing cryomodules in the CEBAF accelerator as well as vertical test results will be present-ed. The goal of in-situ processing is to improve the operational gradients and the energy margin of the linacs. This work will describe the systems and methods used at JLAB for processing cavities using an argon-oxygen gas mixture as well as a helium-oxygen gas mixture. Before and after plasma processing results will also be presented.

Powers, Thomas↗
DOE OSTI2020

Time-Lapse Vertical Seismic Profiling (VSP) for CO 2 Storage in a Depleted Oil Field in Northern Michigan

The goal of the Dover 33 VSP study was to test the effectiveness of time-lapse VSP for detecting and delineating a plume of more than 271,000 tonnes of CO 2 injected into the Brown Niagaran and A-1 Carbonate formations within the Dover 33 reef between March 2013 and September 2016. Five 2D walkaway VSP (WVSP) source lines were acquired by SIGMA3 in September 2016 to investigate the possible time-lapse response in both P-wave and PS-wave seismic data. The data was compared to the same survey geometry acquired in March 2013 by SR2020.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Assessing Edge Localized Mode (ELM) Mitigation by Pellet Triggering in Smallest-Possible Affordable Robust Compact (SPARC) Low-Collisionality Discharges

Simulations of pellet edge-localized mode (ELM) triggering with the M3D-C1 code confirmed experimentally observed pellet mass thresholds in low-collisionality DIII-D discharges and predicted extremely large thresholds in ITER [A. Wingen et al, Nucl. Fusion 64, 066015(2024)]. The linear (static) and nonlinear (dynamic) workflows developed in this previous work are now applied to the SPARC tokamak. Multiple synthetic equilibria for the high-performance H-mode scenario are tested for MHD stability without pellets using the linear workflow and ELITE simulations; a stable one is identified. Pellets of various mass are injected along an inboard, near-midplane trajectory in the M3D-C1 simulation. No pellet mass threshold for ELM triggering can be found for realistic pellet masses, concluding that fueling from this injection location would not trigger ELMs. A poloidal scan of possible injection locations shows very high thresholds on the high-field side and reasonable thresholds on the low-field-side (LFS). Based on results of this work the location for a LFS injection was finalized in the SPARC design. For this LFS injection the pellet mass threshold is determined using the linear workflow, aligning well with the poloidal scan.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗