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DOE OSTI2019

Effect of Bath Depth and Nozzle Geometry on Spout Height in Submerged Gas Injection at Bottom

Spout height is a widely used parameter to quantitatively analyze the performance of the submerged gas injection in industrial applications. However, the effect of bath depth and nozzle geometry on spout height in submerged gas injection is still unclear. In this work, the effect of bath depth and nozzle geometry on spout height in submerged gas injection at bottom was experimentally investigated. Circular-shaped, three-leaf-shaped, four-leaf-shaped, and four-flower-shaped nozzles were used for this study. Spout height was extracted from the images captured by high-speed camera and analyzed by digital image processing. The results indicate that the effect of nozzle geometry on spout height is as important as gas flow rate and bath depth. Through dimensional analysis, predictive correlations of spout height from circular shape and four-leaf shape were developed with dimensionless bath depth and a modified Froude number using orifice perimeter and opening area as characteristic parameters. Experimental data were compared with the correlations from literature and good agreement was found.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Data trustworthiness signatures for nuclear reactor dynamics simulation

With the increased reliance on digitization in industrial control systems, the need for effective monitoring techniques has risen dramatically. Specifically, there is now a growing concern about the so-called false data injection (FDI) attacks. These attacks aim to alter the raw sensors’ data to cause malicious outcomes. Any serious FDI algorithm is based on an intimate knowledge of the system and its associated physics models, which renders conventional outlier/anomaly detection techniques almost obsolete in the face of such attacks. Thus, a critical need has emerged to develop a new class of defense methods that are capable of detecting FDI attacks under the assumption that the attacker has a strong familiarity with the system and its physics modeling. This class of defense methods are denoted by model-based defenses which are premised on the assumption that the attacker, while having a good understanding of the system, does not have full privileged access to all proprietary data and historical records of operation. However, (s)he is assumed to be capable of learning system behavior using self-learning techniques during an initial lie-in-wait period. To defend against this scenario, we propose a new model-based randomized window algorithm that searches time-series data for signatures that can serve as classifiers between normal and FDI scenarios. The classifiers are based on the correlations between the dominant degrees of freedom (DOFs) and the less-dominant DOFs (expected to be very sensitive to the system details that are unknown to the attacker). For demonstration, RELAP5 models are employed to calculate representative nuclear reactor behavior during a number of transient scenarios. Finally, falsified data are injected into the RELAP5-simulated behavior, and the proposed signature-identification algorithm is employed to detect the injected data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Quantifying electron cyclotron power deposition broadening in DIII-D and the potential consequences for the ITER EC system

Abstract The injection of electron cyclotron (EC) waves fulfills a number of important tasks in nuclear fusion devices for which detailed knowledge of the spatial power deposition profile is critical. This deposition profile is commonly determined using forward models such as beam or ray tracing. Recent numerical and experimental studies have shown that small-angle scattering of the EC beam as it passes through the turbulent plasma edge can cause significant broadening of the effective deposition profile, leading to considerable underestimation of the deposition width by forward methods. However, traditional inverse methods to determine the deposition profile from measurements overestimate the deposition profile width due to transport broadening. In this work, we implement three novel methods to resolve the EC power deposition profile from measurements that counteract transport broadening by simultaneously resolving transport and power deposition. We validate their assumptions and compare the results from these methods to the traditional break-in-slope method as well as to the TORAY ray-tracing code in a set of DIII-D discharges spanning five different confinement modes. We show that the four different inverse methods, novel and established, paint a consistent picture of deposition broadening. Specifically, we show that the measured power deposition profile is between 1.6 and 3.6 times wider than the TORAY profiles. Moreover, we show the considerable consequences that this level of broadening can have for ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Numerical Optimization of Spray-Guided Spark Assistance for Cold Idle Operation in a Heavy-Duty Gasoline Compression Ignition Engine

This article describes the results of a response surface model (RSM)-based numerical optimization campaign for spray-guided spark assistance at cold operations in a heavy-duty gasoline compression ignition (GCI) engine. On the basis of an earlier work on spark-assisted GCI cold combustion, a space-filling design of experiments (DoE) method was first undertaken to investigate a multitude of hardware design variables and engine operating parameters. The main design variables included the number of injector nozzles, fuel split quantities and injection timings, and spark timing. The objective variables were engine combustion efficiency (ŋ c ), maximum pressure rise rate (MPRR), and engine-out nitrogen oxide (NO x ) emissions. A total of 150 design candidates were automatically generated using the Sobol sequence method provided by the commercial software package, CAESES. Then, closed-cycle computational fluid dynamic (CFD) spark-assisted GCI simulations under cold idling operations were performed. The outcomes from the CFD-DoE design campaign were utilized to construct high-fidelity RSMs that allowed for further design optimization of the spark plug- and fuel injector-related design variables, along with fuel injection strategy parameters. A merit function with respect to objective variables was formulated with an appropriate weight assignment on each objective variable. Finally, the best design candidate was identified from the RSM-based optimization process and further validated in the CFD analysis. The best design candidate showed the potential to significantly improve combustion efficiency (ŋ c > 90%) over the baseline at cold idle while satisfying MPRR and NOx emissions constraints (MPRR < 5 bar/CAD and NO x < 4.5 g/kWh).

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

Large eddy simulation of a pressurized reactive fluid–particle system: single-particle dynamics analysis

Pressurized oxy-combustion (POC) is a promising candidate to reduce carbon emissions in power generation. Designing an effective burner plays a vital role in developing new combustion technologies. Because of the high pressure, the volume fraction of particles in a pressurized oxy-combustor could be higher than that in the conventional combustor, therefore, the particle dynamics in the pressurized vessel need to be evaluated accordingly. The present computational work is to predict the influence of the particle size and particle injection location on the particle trajectory. The Stokes number based on turbulence fluctuation, St, is adopted to evaluate the impact of the gas phase on the particulate phase. A large eddy simulation (LES) with the environment pressure of 15 bar and the thermal input of the fuel particle of 100 kWth has been performed by means of the commercial CFD package. It is shown that that in this pressurized environment St << 1 for the 25 µm particles, St ~ 1 for the 100 µm particles, while for the particles exceeding 200 µm St >> 1. The trajectories of the sampling particles from the LES results support this conclusion: the particles less than 100 µm tend to be uniformly distributed in the space while the particles exceeding 200 µm tend to concentrate in the combustor.

Li, Lei↗

DOE OSTI2020

Molybdenum Contacts to MoS 2 Field‐Effect Transistors: Schottky Barrier Extraction, Electrical Transport, and Low‐Frequency Noise

MoS 2 has great interest for nanoscale electronic devices, including transistors and sensors. Defect‐free structure, clean interface with the gate dielectric, and metals with suitable metal–semiconductor junctions are key for reliable devices. Molybdenum is shown as an excellent electrode for MoS 2 field‐effect transistors (FETs), but the correlation among device current, field‐effect mobility, and the low‐frequency noise (LFN) with number of atomic layers is not studied. Furthermore, the impact of Mo/MoS 2 Schottky barrier on electronic injection and scattering in the device needs to be understood. Herein, by studying the FETs with channels of different numbers of atomic‐layer thicknesses, it is shown that a molybdenum metal contact to MoS 2 provides reliable current injection with low Schottky barrier height, low contact resistance, low electron–phonon scattering, and negligible impurity scattering. The mobility and LFN are optimal at a channel thickness of ≈12 atomic layers, which is consistent with the “mobility maximum window” in MoS 2 transistors with prior studies using other contact metals.

Kwon, Jiseok↗

DOE OSTI2021

Fuel Property Effects on Knock Propensity and Thermal Efficiency in a Direct-Injection Spark-Ignition Engine

Engine knock remains one of the major barriers to further improvement in thermal efficiency of Direct-Injection Spark-Ignition (DISI) engines. While Research Octane Number and Motor Octane Number are often used as standard rating methods for knock resistance of fuels, the impacts of other fuel properties on knock propensity in modern engines such as heat of vaporization (HoV) and laminar flame speed (LFS) require better understanding in order to co-optimize fuels and engine designs to achieve higher thermal efficiency and lower CO2 emission. In the present study, computational fluid dynamics (CFD) is used to model a boosted DISI engine with a focus on knock prediction and fuel property effects. A level-set G-equation model is employed to capture turbulent premixed combustion, and is coupled with a transported Livengood-Wu (L-W) integral approach to predict autoignition in the unburnt region. A criterion associated with the L-W integral is developed to accurately predict knock onset and knock-limited spark-advance. This model is then applied to a sensitivity analysis of HoV and LFS on knock tendency and thermal efficiency. The pressure-temperature trajectory framework is applied and extended to study the fuel effects on auto-ignition process in the engine. An existing efficiency-based merit function, which is derived from experiments for boosted SI engines, is evaluated and improved based on the current CFD results.

DISI↗

DOE OSTI2021

Stress Controls Rupture Extent and Maximum Magnitude of Induced Earthquakes

Abstract Seismic hazard forecasts of induced seismicity often require estimates of the maximum possible magnitude ( M max ). Empirical models suggest that maximum magnitudes, or expected number of earthquakes, are related to the volume of injected fluid. We perform a suite of 3D physics‐based earthquake simulations with rate‐ and state‐dependent friction, systematically varying the area of the pressurized region and the amplitude of the initial homogeneous or heterogeneous shear stress. Using the resulting catalog we explore the conditions that result in pressure‐controlled versus runaway ruptures that extend outside the pressurized zone. We find that proposed empirical scaling laws correctly predict M max when shear stresses are further from failure (≤90% of maximum shear stress) and for high amplitude stress fields. Runaway ruptures are observed for higher initial shear stresses and smoother stress fields. In these cases, runaway ruptures occur early after the onset of injection and rarely preceded by foreshock activity.

58 GEOSCIENCES↗

DOE OSTI2026

FLASH-therapy suitable single-pulse proton generation using TiH 2 under nanosecond laser irradiation

We investigated proton emission from titanium hydride (TiH 2 ) targets irradiated in vacuum by a 6-ns, 1064-nm Nd:YAG laser. Time-of-flight measurements with a Faraday cup and an electrostatic ion analyzer resolved distinct proton peaks at high pulse energies, with yields on the order of 10 9 protons per shot. Systematic scans over pulse energy and up to 1000 repeated shots showed that, while the peak amplitude gradually decreased, the integrated proton number remained nearly constant. This behavior is consistent with surface-induced broadening of the plasma expansion while bulk hydrogen is replenished by diffusion and repeated ablation of fresh TiH 2 layers. Using the measured proton numbers and pulse widths, a simple direct-plasma-injection-style scaling indicates peak currents of ∼100 mA and sub-microsecond pulse durations. The pulse structure and yield satisfy key ultra-high-dose-rate criteria and, together with sustained output over 1000 shots, support TiH 2 -based laser ion sources as practical candidates for FLASH-therapy (ultra-high-dose-rate)-oriented studies and injector development using direct plasma injection.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

The Single Event Error (SEE) test and analysis of the CMS Endcap Timing Layer readout chip

The ETROC2, the first full size and full functionality prototype chip for the CMS Endcap Timing Layer readout, is strategically designed to meet the SEE immunity requirements of detector operation with the low power constraint. The triplicated periphery and pixel I2C configuration registers are designed with self-correction feature. The pixel readout control is centralized in the global readout and fully triplicated. The pixel readout is not triplicated, instead protected with power-efficient one-bit correction Hamming code. The TMR protection of the on-pixel threshold calibration can be turned off allowing the detection of the beam spot during the beam test by checking the bit-flips of the internal memory cells. In the initial proton beam test in January 2024, the chip readout process did not hang throughout the tests. The Hamming code correction strategy works because the error corrected TDC data were observed in the data frames. The error-injection simulation is performed to analy ze the small number of bit-flips in the configuration registers. We also performed SEE testing with a heavy ion beam in April and the data analysis is ongoing. The detailed design on the SEE immunity and the testing as well as simulation results will be presented, including follow-up SEE testing results in May and June 2024.

Gong, Datao↗

DOE OSTI2020

Ion Number Density Quantification Utilizing Pulsing Frequency in Negative Differential Resistance (NDR) Regime of Microplasma Operation

A mathematical model is presented for quantifying the ion number density over a range of discharge current in microplasma discharges. The ion number density is determined from measured discharge voltage, current, pulsing frequency, and trace impurity that is injected into the system deliberately. Experiments are conducted in pure helium with nitrogen being introduced as the trace species. The ion number density is estimated over a range of discharge current and is compared with multidimensional simulation results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Optimization of Water-Alternating-CO2 Injection Field Operations Using a Machine-Learning-Assisted Workflow

Summary This paper will present a robust workflow to address multiobjective optimization (MOO) of carbon dioxide (CO2)-enhanced oil recovery (EOR)-sequestration projects with a large number of operational control parameters. Farnsworth unit (FWU) field, a mature oil reservoir undergoing CO2 alternating water injection (CO2-WAG) EOR, will be used as a field case to validate the proposed optimization protocol. The expected outcome of this work would be a repository of Pareto-optimal solutions of multiple objective functions, including oil recovery, carbon storage volume, and project economics. FWU’s numerical model is used to demonstrate the proposed optimization workflow. Because using MOO requires computationally intensive procedures, machine-learning-based proxies are introduced to substitute for the high-fidelity model, thus reducing the total computation overhead. The vector machine regression combined with the Gaussian kernel (Gaussian-SVR) is used to construct proxies. An iterative self-adjusting process prepares the training knowledge base to develop robust proxies and minimizes computational time. The proxies’ hyperparameters will be optimally designed using Bayesian optimization to achieve better generalization performance. Trained proxies will be coupled with multiobjective particle swarm Optimization (MOPSO) protocol to construct the Pareto-front solution repository. The outcomes of this workflow will be a repository containing Pareto-optimal solutions of multiple objectives considered in the CO2-WAG project. The proposed optimization workflow will be compared with another established methodology using a multilayer neural network (MLNN) to validate its feasibility in handling MOO with a large number of parameters to control. Optimization parameters used include operational variables that might be used to control the CO2-WAG process, such as the duration of the water/gas injection period, producer bottomhole pressure (BHP) control, and water injection rate of each well included in the numerical model. It is proved that the workflow coupling Gaussian-SVR proxies and the iterative self-adjusting protocol is more computationally efficient. The MOO process is made more rapid by squeezing the size of the required training knowledge base while maintaining the high accuracy of the optimized results. The outcomes of the optimization study show promising results in successfully establishing the solution repository considering multiple objective functions. Results are also verified by validating the Pareto fronts with simulation results using obtained optimized control parameters. The outcome from this work could provide field operators an opportunity to design a CO2-WAG project using as many inputs as possible from the reservoir models. The proposed work introduces a novel concept that couples Gaussian-SVR proxies with a self-adjusting protocol to increase the computational efficiency of the proposed workflow and to guarantee the high accuracy of the obtained optimized results. More importantly, the workflow can optimize a large number of control parameters used in a complex CO2-WAG process, which greatly extends its utility in solving large-scale MOO problems in various projects with similar desired outcomes.

Energy & Fuels↗

DOE OSTI2021

Method for optimization of huff-n-puff gas injections in hydrocarbon reservoirs

Methods for optimization of liquid oil production by huff-n-puff in shale reservoirs to achieve an improved (and optimal) oil recovery factor. The process determines and utilizes the optimum huff and puff times, number of cycles and soaking time under practical operation and reservoir conditions. The huff time in the process is a period so long that the pressure near the wellbore reaches the set maximum injection pressure during the huff period. The puff time in the process is the time required for the pressure near the wellbore to reach the set minimum production pressure during the puff period. Soaking is typically not necessary during the huff-n-puff gas injection in shale oil reservoirs. The number of huff-n-puff cycles is determinable by the time in which the economic rate cut-off is reached.

Sheng, James J.↗

DOE OSTI2023

Method for optimization of huff-n-puff gas injection in hydrocarbon reservoirs

Sheng, James J.↗

DOE OSTI2021

Mitigating Injection‐Induced Seismicity Along Basement Faults by Extraction: Application to 2016–2018 Pohang Earthquakes

Abstract The risk of induced earthquake is considered as the major obstacle for sustainable subsurface energy activities. As a mitigation approach, mechanistic risk assessment can be essential to minimize the potential of seismic hazard. Coupled hydro‐mechanical modeling approach is integrated with geomechanical analysis to better assess the occurrence of seismicity induced by injection and/or extraction, which will provide a basis to update operational conditions (e.g., number and location of mitigating wells, rate and duration of operations) for mitigating earthquake nucleation. The Coulomb stability analysis and seismicity rate estimates from this generic study indicate that simultaneous extraction can relieve injection‐induced pore‐pressure buildup, but also transfer and accumulate elastic energy along the faults. Field‐scale simulation with variation in well design for the Pohang EGS site, South Korea, show that multiple wells aligned across a preexisting fault form gradients of pressure and stress fields normal to the fault, which can enhance the direct impact of diffusion process and poroelastic stressing on the fault stability perturbation. Our mechanistic study suggests multiphysics‐oriented mitigation strategies that consider (1) possible mechanical deformation, caused by hydro‐mechanical coupling effects, and (2) proper configuration of well operations based on site‐specific geological characteristics.

Chang, K. W.↗

DOE OSTI2020

The EGS Collab Project: Learnings from Experiment 1

The primary objective of the EGS Collab Project sponsored by DOE is to increase the understanding needed to efficiently implement enhanced geothermal systems (EGS). One goal of the EGS Collab project is to create a collaborative research environment in which to study stimulation of crystalline rock at the 10 meter scale. Key to this effort is the collection of high quality data to allow comparison to numerical coupled process models in an effort to build confidence in the codes and modeling techniques used. In response to this, the EGS Collab team has created an underground test bed at the Sanford Underground Research Facility (SURF) in Lead SD at a depth of approximately 1.5 km to examine hydraulic fracturing (Experiment 1). We are currently designing a second test bed aimed at investigating shear stimulation (Experiment 2). At the Experiment 1 location, we have characterized our host rock using laboratory testing and numerous field-based geophysical and geological techniques, and created a well-instrumented test bed to allow us to carefully monitor stimulation events and flow tests. In addition to the installed geophysical sensors, we have used tracer tests, differences in the ambient microbial communities at flow collection locations, and cold water injection to inform us about dynamic flow pathways. In Experiment 1, we have hydraulically stimulated the host rock in a number times at several locations in one well, creating new fractures that connect to existing fractures between the injection and production boreholes. We have performed long-term ambient and chilled water injection tests as an analog to EGS, and have monitored system changes resulting from these water injections through geophysical monitoring, flow and pressure measurements, tracer tests, and microbiology. Here, we summarize the tests performed, issues identified including poroelastic and thermoelastic effects, Joule-Thomson effects, restarting effects, indications of flow channeling, and the primary learnings from Experiment 1.

Enhanced Geothermal Systems, EGS Collab, stimulati↗

DOE OSTI2020

Microbial and Geochemical Dynamics of an Aquifer Stimulated for Microbial Induced Calcite Precipitation (MICP)

Microbially induced calcite precipitation (MICP) is an alternative to existing soil stabilization techniques for construction and erosion. As with any biologically induced process in soils or aquifers, it is important to track changes in the microbial communities that occur as a result of the treatment. Our research assessed how native microbial communities developed in response to injections of reactants (dilute molasses as a carbon source; urea as a source of nitrogen and alkalinity) that promoted MICP in a shallow aquifer. Microbial community composition (16S rRNA gene) and ureolytic potential (ureC gene copy numbers) were also measured in groundwater and artificial sediment. Aquifer geochemistry showed evidence of sulfate reduction, nitrification, denitrification, ureolysis, and iron reduction during the treatment. The observed changes in geochemistry corresponded to microbial community succession in the groundwater and this matched parallel geophysical and mineralogical evidence of calcite precipitation in the aquifer. We detected an increase in the number of ureC genes in the microbial communities at the end of the injection period, suggesting an increase in the abundance of microbes possessing this gene as needed to hydrolyze urea and stimulate MICP. We identify geochemical and biological markers that highlight the microbial community response that can be used along with geophysical and geotechnical evidence to assess progress of MICP.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Experimental and simulated heating in nanocrystalline diamond charge exchange injection films using an electron beam to mimic SNS conditions

Nanocrystalline diamond (NCD) foils have been in use at the Spallation Neutron Source as primary stripper foils for charge exchange injection since the machine’s inception. NCD’s low atomic number leads to reduced beam scattering while still being easy to handle, as opposed to even lighter elements. NCD foils also have the benefit of being free-standing, and rigid when grown under the right conditions to minimize residual stresses. This study overviews a method to mimic the Spallation Neutron Source (SNS) beam and characterize thermally driven failure of NCD foils. To do this, a foil test stand was developed with in situ diagnostics that tracks signs of foil sublimation and thinning. The foil test stand’s electron beam is equated to the SNS beamline by comparing peak deposited energy densities for both beams. Post-mortem testing is also conducted to help elucidate changes the NCD foils undergo during exposure to the beam. Further, a COMSOL simulation was also developed as a method to assess potential future changes to the NCD film and predict how changes to beam conditions will effect foil temperatures. This method allows for examination of the NCD foil’s thermal limits and can be used to assess future changes to SNS stripper foils.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗