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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Modulating Ce 3+ Sites in Ce-Zr Oxide Nanocatalysts through Protamine Biomineralization for Organophosphate Dephosphorylation

Catalytic is a crucial reaction for environmental detoxication of pesticides and neutralization of various molecules classified as chemical warfare agents. Herein, we report on a series of tunable Ce-Zr-based metal oxides, (Zr a Ce 1–a O x ) prepared using a facile biomineralization technique, as catalysts for organophosphates dephosphorylation. Synchrotron scattering and spectroscopy methods showcase that Zr a Ce 1–a O x catalysts are highly defective and exhibit an abundance of Ce 3+ sites that promote oxygen vacancies needed for enhanced dephosphorylation reactions. The catalytic performance was assessed using a model para-nitrophenyl phosphate reaction and showcases a strong dependence on Zr dopant concentration and subsequent tuning of the Ce 3+ /Ce 4+ ratio. Analysis of synchrotron datasets allowed structure-performance correlations between the Ce 3+ concentration and associated oxygen vacancies, the dephosphorylation rate constant, and Zr concentration to be established, confirming that Ce 3+ as active sites is positively correlated with the rate constant. We envision that similar biomineralization approaches can be used to fabricate Ce 3+ -rich Ce-Zr oxide for environmental application in dephosphorylation and other hydrolysis reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Workflow for evaluating enzyme immobilization and performance for continuous flow manufacturing

Enzymes have shown promise in various industries due to their functional specificity, catalytic efficiency, and environmental sustainability. These biological catalysts can be a pivotal component of manufacturing pipelines like continuous flow chemistry. For this, there exists a need to robustly immobilize enzymes on solid supports and assess the effects of the solid supports on catalytic performance and stability. Here, we use an industrially relevant model enzyme, C. ensiformis (Jack bean) urease, to demonstrate immobilization and assess performance in the context of continuous flow manufacturing. Various immobilization strategies were screened focusing on immobilization efficiency, protocol simplicity, and urease biocatalyst kinetics. Based on this, CDI-agarose and NHS-agarose resins were identified as the best-performing immobilization strategies for urease. CDI-agarose-urease and NHS-agarose-urease were then scaled up and applied to a large-scale continuous flow reactor to evaluate product yields, operational stability, and long-term stability. These experiments identified differences in stability and performance depending on the immobilization method tested. This highlights the importance of screening immobilization methods and subsequent enzyme performance for each candidate biocatalyst used in manufacturing to promote optimal performance and stability. As such, this work provides a framework for evaluating enzyme biocatalyst immobilization approaches to improve performance and enable transition into industrial processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Parameter dependencies of the experimental nitrogen concentration required for detachment on ASDEX Upgrade and JET

While current tokamak experiments are beginning to use real-time feedback control systems to manage the plasma exhaust, future tokamaks still require validation of theoretical models used to predict the threshold impurity concentration required to sufficiently reduce the power and particle fluxes to the divertor. This work exploits new spectroscopic measurements of the divertor nitrogen concentration, c n , in partially detached N 2 -seeded H-mode plasmas on ASDEX Upgrade (AUG) and JET with the ITER-Like Wall (JET-ILW) to test the parameter dependencies of the power flowing to the outer divertor, P div,outer , and the separatrix electron density, n e.sep . A least-squares regression of the AUG measurements demonstrates that the threshold c n required for detachment scales as $c_n∝P^{1.19±0.32}_{div,outer}n^{-2.77±0.36}_{e,sep}$. This scaling of n e,sep is also consistent with the measurements from JET which, at constant P div,outer , show $c_n∝n^{-2.43±0.27}_{e,sep}$. The dependencies of P div,outer and n e.sep is demonstrated over at least a factor of two change in both parameters and indicates a stronger dependence on n e.sep in comparison to the Lengyel model, which could be due to the assumption in this model that the heat flux channel width is independent of density. This first assessment of detachment scaling with impurity seeding highlights the need for further analysis of the systematic uncertainties of the measurement and more consistent scenarios from more tokamaks to investigate the machine size scaling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

An iterative learning and inference approach to managing dynamic cyber-vulnerabilities of complex systems

As modern systems become increasingly reliant on cyber-technologies and continue to be integrated with physical systems, managing risks from deliberate and non-deliberate sources is a significant research challenge. Unlike strictly physical systems, cyber-enabled physical systems are influenced by dynamic and evolving technologies, environments, and attack mechanisms. As a result, vulnerabilities are rapidly changing and difficult to detect and manage. While there is recent interest in the dynamic properties of performance through resilience analysis, limited research addresses the dynamic nature of cyber-system vulnerability. This paper presents a dynamic iterative learning approach to evaluate the state of health for systems as related to cyber-vulnerabilities. These time-varying system health characteristics may not be visible, but can be inferred using observable characteristics. The approach recognizes that multiple types of vulnerabilities need to be included in a holistic system health assessment. The methods are applied to the Common Vulnerability Scoring System database containing over 100,000 documented cybersecurity vulnerabilities. This work is the first to acknowledge the dynamic properties of cyber-vulnerability, while also inferring system health using observable data and hidden states of system health. This work will be of interest to managers of large-scale cyber-enabled physical systems who are seeking to prioritize system health investments.

Chatterjee, Samrat↗
DOE OSTI2021

Reconciling the Driving Force and the Barrier to Charge Separation in Donor–Nonfullerene Acceptor Films

We investigate the dependence of charge yields on the driving force for photoinduced electron transfer in a series of all-small-molecule, semiconducting films made from indacenodithiophene nonfullerene acceptors (IDT NFAs). In contrast to reports of efficient, barrierless charge separation at near zero driving force for NFA-containing organic photovoltaics, we find that barrierless charge separation occurs only if the driving force is sufficient to overcome the Coulomb potential, =300 meV, based on time-resolved microwave conductivity and PL quenching measurements of 5 mmolal sensitized and 700 mmolal blended films comprising IDT NFAs paired with three different donors. This discrepancy with recent literature is caused by a difference in the way that we calculate driving force. Far from being semantic, the driving force calculation is crucial because its value controls the mechanisms needed to explain experimental observations. We provide a candid assessment of the uncertainties for our methods and popular ones used in the literature and emphasize the importance of standardizing methods across this field.

14 SOLAR ENERGY↗
DOE OSTI2025

Modeling the Air Quality Impacts of Future Energy Scenarios

Many greenhouse gas (GHG) emission reduction measures achieve simultaneous reductions in air pollutants. Human-Earth system models can estimate such emission changes in the energy system but using them in chemistry-transport models (CTMs) to study their air quality impacts involves resource-intensive emissions processing. This is greatly simplified by an emissions scaling approach linking state-level emissions estimated by a human-Earth system model to a CTM. A scenario continuing pre-2022 energy policy in the U.S. to 2050 shows widespread air quality improvements over the 2015 baseline from SO 2 and NO x emission reductions of 50–80% from electricity generation and light-duty vehicles. Scenarios of GHG mitigation and vehicle electrification at the state and national level add further benefits. However, PM 2.5 increases from increased use of wood heating and bioenergy suggest that additional PM 2.5 management may be needed when using biofuels. In conclusion, this approach helps assess multiple future energy scenarios efficiently without sacrificing chemical detail in the air quality simulations.

air quality↗
DOE OSTI2026

Dominant Controls on Preferential Flow and Their Implications for Future Soil Water Fluxes

Abstract Soil water flow, particularly preferential flow (PF), is a critical control on hydrological and biogeochemical processes, including groundwater recharge, contaminant transport, and carbon cycling. However, it remains challenging to predict PF occurrence across large environmental gradients. Here, we developed a deep learning (DL) model to estimate event‐scale soil water flow velocity and the probability of PF occurrence using high‐frequency soil moisture and precipitation data from 33 sites across the National Ecological Observatory Network. The model demonstrated high skill in predicting the binary occurrence of PF (91% F1‐score; 85% accuracy) but the performance was limited in predicting soil water velocity ( R 2 = 0.31). We found that precipitation characteristics (duration, volume, and intensity) were the most important predictors for soil water velocity. Among the non‐precipitation event variables, sand content showed relatively high predictive skill, though differences among non‐event climate variables were generally modest. Lower sand content was associated with increased predicted soil water velocity, a finding that highlights the role of soil structure in producing more non‐uniform flow, which contrasts with traditional uniform flow models. Projecting a reduced DL model under both moderate and high‐emissions future climate scenarios (2060–2099 Representative Concentration Pathways 4.5 and 8.5), we found ∼7.3% increase under RCP4.5 and ∼15% under RCP8.5 of soil water velocities compared to the historical simulation, while modeled likelihood of PF changed little. These findings suggest climate change is not making PF more frequent, but it is making existing PF pathways more efficient with important consequences for associated nutrient and contaminant transport under climate change. Plain Language Summary Water movement in soil is critical for water quality. While often modeled as a uniform flow process, in reality water moves rapidly through cracks and burrows in what is called “preferential flow” (PF), which limits natural filtration and can transport pollutants. We developed a deep learning model, trained on data from 33 U.S. sites, to predict when and how fast this PF occurs based on precipitation, soil, and climate data. The model showed that precipitation characteristics (duration, intensity, volume) were the most important predictors of PF. Lower soil sand content/higher clay content was associated with faster water flow, likely due to clay soils forming aggregates and cracks that water moves through rather than infiltrating uniformly. Further analyses based on climate projections suggest that the speed at which PF occurs will become more rapid under future climate scenarios compared to historical simulation. This highlights the need to represent PF in soil water models when assessing future water quality. Key Points The effect of precipitation peak intensity on soil water velocities declined with increasing precipitation intensity Antecedent soil moisture failed to predict preferential flow (PF), contrasting the high predictive power of sand content Climate predictions suggest that soil water velocities through PF paths will increase ∼15% by 2099

Li, Bonan↗
DOE OSTI2021

Quantifying uncertainty in aggregated climate change risk assessments

High-level assessments of climate change impacts aggregate multiple perils into a common framework. This requires incorporating multiple dimensions of uncertainty. Here we propose a methodology to transparently assess these uncertainties within the ‘Reasons for Concern’ framework, using extreme heat as a case study. We quantitatively discriminate multiple dimensions of uncertainty, including future vulnerability and exposure to changing climate hazards. High risks from extreme heat materialise after 1.5–2 °C and very high risks between 2–3.5 °C of warming. Risks emerge earlier if global assessments were based on national risk thresholds, underscoring the need for stringent mitigation to limit future extreme heat risks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Water Resource Opportunities at Lake Gazivode/Ujmani

The U.S. Department of Energy’s (DOE’s) Pacific Northwest National Laboratory (PNNL) has been tasked by DOE’s Office of International Affairs to assess the use of water resources for power generation needs on Lake Gazivode/Ujmani in Kosovo, and provide recommendations for improved coordination and efficiency. Lake Gazivode/Ujmani is a 15-mile long man-made reservoir that straddles the Serbian-Kosovo border. Lake Gazivode/Ujmani is currently managed without a transboundary cooperation agreement. Kosovo is profoundly dependent on the lake’s waters, which provide one-third of Kosovo’s drinking water and cool two coal plants that provide 95 percent of Kosovo’s energy production. After conducting a scoping visit to Pristina, Kosovo, Lake Gazivode/Ujmani, and Belgrade, Serbia, in October 2020, PNNL staff compiled hydrometeorological, water management operations, and power grid operations data. They analyzed the data and existing literature to provide third-party observations about and recommendations for the use of the lake. Their recommendations aim to promote regional water and energy security.

13 HYDRO ENERGY↗
DOE OSTI2022

Solar Radiometer Instrumentation Evaluation: Cooperative Research and Development (Final Report, CRADA Number CRD-16-00619)

The purpose and intent of this agreement is to evaluate newly manufactured thermopile pyranometers and spectroradiometers. The purpose also extends to provide a framework for Participant to conduct research to improve and develop new radiometric devices and application in the future. The overall objective is to provide more accurate, site-specific, long-term, continuous measurements of the solar resources needed by industry to increase the deployment and improve the operations of photovoltaic and concentrating solar power plants. This CRADA addresses the needs for proven solar irradiance measurement to validate resource assessment models and generate high quality data used for site selection, energy system design, deployment, maintenance, and operation. This work will be conducted at NREL and Participant facilities. This project will place instrumentation at the NREL Solar Radiation Research Laboratory (SRRL) in cooperation with EKO Instruments, USA. Participant instruments will be deployed for the purpose of evaluation under controlled conditions. The scope of the project will be a 3 years-long segmented comparison of the instruments vs. other NREL baseline instruments with a well-characterized history. These evaluations will include planned improvements to instruments as well as extensions of future instrument applications. The final evaluation will be a written report similar to the work done by Wilcox and Myers (see http://www.nrel.gov/docs/fy09osti/44627.pdf).

14 SOLAR ENERGY↗
DOE OSTI2025

Advancing INFCIRC/908 Insider Threat Mitigation International Working Group: Activity Roadmap, 2025-2027

This 2-year work plan provides a roadmap for activities the IWG and other stakeholders will undertake between 2025 and 2027. Members of the IWG Steering Committee (SC) are responsible to (1) engage the broader insider threat mitigation community of practice to inform and promote work plan activities, (2) track progress towards goals, and (3) provide updates to the IWG at regular intervals. This work plan is a living document and will be updated periodically to assess progress towards goals and will be revised as needed to address emergent and exigent areas of concern identified by the IWG.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

The Role of the U.S. Electric Distribution System in Serving Data Center and Other Large Loads

The rapid expansion of data centers in the United States is reshaping how the electric distribution system must plan for and accommodate large load interconnections. This report evaluates the role of the distribution grid in serving these loads, from small edge facilities to hyperscale campuses. Using national datasets, utility filings, and industry studies, we assess demand growth, reliability requirements, interconnection thresholds, and infrastructure needs at substations and feeders. The analysis highlights the mismatch between fast data center development timelines and slower utility planning and construction cycles, as well as strategies such as phased energization, on-site generation, hosting capacity maps, and structured interconnection frameworks. While focused on data centers, the insights also apply to other high-density loads such as advanced manufacturing, hydrogen production, and electrified transportation. The report concludes with approaches to align planning processes, transparency tools, and regulatory frameworks so utilities can manage new large loads in ways that support a reliable and resilient grid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Rice Bran Stabilisation and Oil Extraction Using the Microwave-Assisted Method and Its Effects on GABA and Gamma-Oryzanol Compounds

Rice bran oil (RBO) is a valuable ingredient extracted from rice bran (RB), a side stream of polishing rice grain in the milling process. RBO is rich in bioactive ingredients with potential health benefits, such as gamma-oryzanol (GO) and gamma-aminobutyric acid (GABA). Despite its benefits, the quality of RBO depends on the degree of stabilisation of the RB, which is easily affected by lipase enzymes, and thus needs an effective treatment prior to RBO production. To assess the potential of the microwave-assisted method for RB stabilisation and RBO extraction, three Carolino rice varieties (Ariete, Teti, Luna) were tested. The effect of RB stabilisation was evaluated via acid value, water absorption, and GO and GABA levels. The RBO yield was optimised by solvent, temperature, and solvent-to-sample ratio, and the GO and fatty acid levels were determined. The RB stabilisation for the Luna variety did not affect the GO and GABA; for the Ariete and Teti varieties, the GO decreased by 34.4% and 24.2%, and the GABA increased by 26.5% and 47.0%, respectively. The GO levels in RBO samples were not affected by RB stabilisation. The RBO nutritional value was confirmed by the suitable ratio (>2) between polyunsaturated (PUFA) and saturated fatty acids (SFA), with the Teti variety presenting the highest ratio.

Reis, Núria (ORCID:0000000194339109)↗
DOE OSTI2024

Modeling PAH Mixture Interactions in a Human In Vitro Organotypic Respiratory Model

One of the most significant challenges in human health risk assessment is to evaluate hazards from exposure to environmental chemical mixtures. Polycyclic aromatic hydrocarbons (PAHs) are a class of ubiquitous contaminants typically found as mixtures in gaseous and particulate phases in ambient air pollution associated with petrochemicals from Superfund sites and the burning of fossil fuels. However, little is understood about how PAHs in mixtures contribute to toxicity in lung cells. To investigate mixture interactions and component additivity from environmentally relevant PAHs, two synthetic mixtures were created from PAHs identified in passive air samplers at a legacy creosote site impacted by wildfires. The primary human bronchial epithelial cells differentiated at the air–liquid interface were treated with PAH mixtures at environmentally relevant proportions and evaluated for the differential expression of transcriptional biomarkers related to xenobiotic metabolism, oxidative stress response, barrier integrity, and DNA damage response. Component additivity was evaluated across all endpoints using two independent action (IA) models with and without the scaling of components by toxic equivalence factors. Both IA models exhibited trends that were unlike the observed mixture response and generally underestimated the toxicity across dose suggesting the potential for non-additive interactions of components. Overall, this study provides an example of the usefulness of mixture toxicity assessment with the currently available methods while demonstrating the need for more complex yet interpretable mixture response evaluation methods for environmental samples.

3D in vitro models↗
DOE OSTI2020

Smart Adhesive Joint with High-Definition Fiber-Optic Sensing for Automotive Applications

Structural health monitoring of fiber-reinforced composite-based joints for automotive applications during their manufacturing and on-demand assessment for its durability in working environments is critically needed. High-definition fiber-optic sensing is an effective method to measure internal strain/stress development using minimally invasive continuous sensors. The sensing fiber diameters are in the same order of magnitude when compared to reinforcement (glass, basalt, or carbon fibers) used in polymer composites. They also offer a unique ability to monitor the evolution of residual stresses after repeated thermal exposure with varying temperatures for automotive components/joints during painting using an electrophoretic painting process. In this paper, a high-definition fiber-optic sensor utilizing Rayleigh scattering is embedded within an adhesive joint between a carbon fiber-reinforced thermoset composite panel and an aluminum panel to measure spatially resolved strain development, residual strain, and thermal expansion properties during the electrophoretic paint process-simulated conditions. The strain measured by the continuous fiber-optic sensor was compared with an alternate technique using thermal digital image correlation. The fiber-optic sensor was able to identify the spatial variation of residual strains for a discontinuous carbon fiber-reinforced composite with varying local fiber orientations and resin content.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The Beam Dump eXperiment

Hadronic matter makes about 14% of the known universe. The remaining 86% is Dark Matter (DM). Since it does not interact with the ordinary matter via electromagnetic force, DM is not visible and, to date, it escaped detection. The search for Dark Matter (DM) is one of the hottest topic in modern physics. Despite the increasing number of astrophysical and cosmological observations proving the existence, so far no particle physics experiment has detected DM yet. Up to now, most of the experimental efforts have been focused on the so called WIMP (Weakly Interacting Massive Particle) paradigm, which predicts heavy DM (10 GeV-10 TeV mass range) interacting with Standard Model (SM) particles via the weak force mediators (W or Z bosons). More recently, due to the lack of clear evidence of WIMPs, other models of DM gained the interest of the physics community. These models consider Light DM particles (LDM), in MeV-GeV mass range. Among LDM theories, the Dark Photon theory predicts the existence of a Dark Sector interacting with SM particles via a new massive vector boson (Dark Photon, Heavy Photon or A0), mediator of a new force. This scenario, despite being theoretically well motivated, is remarkably experimentally unexplored. The Beam Dump eXperiment (BDX), is an approved experiment at Jefferson Lab (JLab), aiming to discover the DM predicted witihn the Dark Photon theory. The experiment uses the CEBAF (Continuous Electron Beam Accelerator Facility) 11 GeV electron beam, impinging on the JLab Hall-A beam-dump, to produce a beam of DM particles, detected by a ~ 1 m3 detector made of thallium doped cesium iodide (CsI(Tl)) crystals located ~ 20 m downstream. In order to achieve excellent background rejection, the experimental setup includes active vetos and passive shielding surrounding CsI(Tl) crystals. Given the weakness of the DM-SM interaction, the scattering of a DM particle in the BDX detector is a rare event. Therefore, the characterization of the expected background is a critical aspect of the experiment. Both cosmogenic and penetrating SM particles produced by the beam interaction in the dump contribute to the background of the experiment. While the cosmogenic contribution can be measured during the experiment when the beam is off, beam-related background can only be estimated via Monte Carlo (MC) simulations. Therefore, a careful assessment of possible systematics introduced by the MC is needed. The beam-correlated background characterization was made by measuring the muon flux produced by the interaction of the CEBAF beam with Hall-A dump in a dedicated experimental campaign in spring 2018 [1]. The comparison to the ?ux predicted by MC allowed us to validate the BDX simulation framework. The reach of BDX, i.e. the region that the experiment can probe in the LDM theory parameter space, depends critically on the background rejection capability and signal detection effciency. For this reason, the detector setup was fine-tuned through a dedicated study. The response to LDM and background events was evaluated for different setups and selection cuts. As a result of this procedure, the configuration resulting in the best sensitivity was selected [2]. The reach calculation was performed taking into account the different LDM production mechanisms, including the contribution of secondary particles produced in the beam-dump. In particular, the effect of the secondary positrons annihilation was found to be extremely significant. In the majority of the sensitivity studies, this contribution is neglected, but recent results [3] [4] demonstrated that this process significantly enhances the sensitivity of lepton beam-dump experiments. Currently, the BDX collaboration is focused on the deployment and operation of a small detector, called BDX-MINI, built to perform a preliminary physics measurement searching for LDM at JLab. This test will pave the way to the realization of the full BDX experiment. The measurement is currently ongoing but results are expected by the end of this year. During my PhD I was involved in all aspects of the BDX experiment: design, simulation, prototyping and data analysis. The main results of my work are reported in this thesis. This manuscript is organized as follows: the first Chapter provides an introduction to the theory of LDM, with particular attention to the Dark Photon paradigm; the second Chapter illustrates the BDX experimental setup, the LDM production and detection mechanisms and the expected backgrounds; Chapter 3 and 4 describe, respectively, the BDX-HODO measurement, with a detailed description of the simulations, and the BDX experimental setup and analysis cuts optimization. Chapter 5 reports about BDXMINI detector characterization, calibration and sensitivity estimate. Finally, Chapter 6 describes in detail the calculation of the secondary positron annihilation contribution to the sensitivity of BDX and other electron-beam thick-target experiment.

Marsicano, Luca↗
DOE OSTI2020

CBRN Situational Awareness Tools for the Modern Age

CBRN Situational awareness (SA) should be a key operational requirement in the CNI area of discussion, not only for the “boots-on-the-ground” warfighter, but at a strategic level. For example, maneuver plans will need to be developed for contamination avoidance and battlefield survivability. Large datasets from instruments dispersed across the battlefield will thus need to be collected and processed into a holistic assessment of the radiological hazard. From there, hazard maps then must be distributed at the tactical level, all while continuing to effectively engage a peer adversary. This vision represents a network of sensors, software tools, data processing algorithms, communications suites, and common operational picture (COP) platforms working in concert to inform warfighters and command echelons alike of evolving nuclear and radiological hazards. This complex system-of-systems and the ultimate goal of effective engagement in a nuclear or radiological-hazard battlefield can be achieved through pursuit of improvement in collaborative SA tools.

Becker, Eric M.↗
DOE OSTI2020

Parametric Study to Assess Technical Prospect Feasibility for Offshore CO 2 Storage

This report is a white paper on the parametric study to assess technical prospect feasibility for CO 2 storage with and without CO 2 -EOR. The SECARB Offshore GOM team reviewed key parameters that previous modeling experience suggests have the largest impact on CO 2 plume size and CO 2 -EOR performance (SSEB, 2019) These parameters include tectonic impacts (reservoir dip and fault block size), reservoir properties (permeability) and development strategies (well field payout, waterflood, and CO 2 flooding strategies). These parameters are further evaluated in this study in order to identify upper and lower boundary conditions for the parametric values. The boundary conditions are needed to set constraints for key parameters when performing modeling assessments. Understanding the key parametric values for the GOM will facilitate locating successful offshore carbon capture utilization and storage (CCUS) projects in terms of plume size, CO 2 stored and, in the case of EOR, oil recovery. Importantly, this white paper focuses on both technical factors (geologic and engineering), but does not address economic, commercial, or stakeholder considerations. The report is organized into four sections and includes a review of the datasets used to define the parameter ranges, the results of a full-physics reservoir simulation, a summary of a reduced order modeling approach to evaluate the impact of the study parameters, and, finally, a discussion of the work that will occur during the next phase of the project.

02 PETROLEUM↗