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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 OSTI2024

Machine Learning-Driven Quantification of CO2 Plume Dynamics at Illinois Basin Decatur Project Sites Using Microseismic Data

This study utilizes machine learning to quantify CO2 plume extents by analyzing microseismic data from the Illinois Basin Decatur Project (IBDP). Leveraging a unique dataset of well logs, microseismic records, and CO2 injection metrics, this work aims to predict the temporal evolution of subsurface CO2 saturation plumes. The findings illustrate that machine learning can predict plume dynamics, revealing vertical clustering of microseismic events over distinct time periods within certain proximities to the injection well, consistent with an invasion percolation model. The buoyant CO2 plume partially trapped within sandstone intervals periodically breaches localized barriers or baffles, which act as leaky seals and impede vertical migration until buoyancy overcomes gravity and capillary forces, leading to breakthroughs along vertical zones of weakness. Between different unsupervised clustering techniques, K-Means and DBSCAN were applied and analyzed in detail, where K-means outperformed DBSCAN in this specific study by indicating the combination of the highest Silhouette Score and the lowest Davies–Bouldin Index. The predictive capability of machine learning models in quantifying CO2 saturation plume extension is significant for real-time monitoring and management of CO2 sequestration sites. The models exhibit high accuracy, validated against physical models and injection data from the IBDP, reinforcing the viability of CO2 geological sequestration as a climate change mitigation strategy and enhancing advanced tools for safe management of these operations.

Iyegbekedo, Ikponmwosa↗

DOE OSTI2023

Simulations of Fuel-Air Mixing in a 7 Element Lean Direct Injection (LDI) Aviation Combustor

The increased accessibility of commercial aviation to the general population has in-creased the conventional jet fuel consumption, thereby causing increased CO2 emissions. One of the strategies to reduce the environmental impact is to use sustainable aviation fuels (SAFs). SAFs are jet fuels obtained from renewable resources such as biomass and waste streams such as plastics/municipal solid wastes. Even though the use of SAFs has been gaining importance over the last two decades, only a few numerical studies on their usage have been reported so far. In this study, two SAFs namely, Alcohol to Jet (ATJ) and Hydrotreated Esters and Fatty Acids (HEFA), are chosen and their use in a simple, Lead Direct Injection (LDI) combustor is studied. The focus of this study is limited to the thermo-chemical properties of the fuels and their impact on fuel distribution and evaporation. Hence, only non-reactive simulations are performed. A high accuracy, adaptive mesh refinement based low-Mach solver, PeleLMeX, is used for performing the simulations. The time-averaged flow results indicate faster evaporation of HEFA when compared to ATJ and Jet-A. The difference in fuel evaporation rates is attributed to the differences in fuel viscosity and surface tension properties and the concomitant variations in the fuel droplet size distributions.

adaptive mesh refinement↗

DOE OSTI2023

Simulations of Fuel-Air Mixing in a 7 Element Lean Direct Injection (LDI) Aviation Combustor: Preprint

The increased accessibility of commercial aviation to the general population has in-creased the conventional jet fuel consumption, thereby causing increased CO2emissions. One of the strategies to reduce the environmental impact is to use sustainable aviation fuels (SAFs). SAFs are jet fuels obtained from renewable resources such as biomass and waste streams such as plastics/municipal solid wastes. Even though the use of SAFs has been gaining importance over the last two decades, only a few numerical studies on their usage have been reported so far. In this study, two SAFs namely, alcohol to jet (ATJ) and hydrotreated esters and fatty acids (HEFA), are chosen and their use in a simple, lead direct injection (LDI) combustor is studied. The focus of this study is limited to the thermo-chemical properties of the fuels and their impact on fuel distribution and evaporation. Hence, only non-reactive simulations are performed. A high accuracy, adaptive mesh refinement based low-Mach solver, PeleLMeX, is used for performing the simulations. The time-averaged flow results indicate faster evaporation of HEFA when compared to ATJ and Jet-A. The difference in fuel evaporation rates is attributed to the differences in fuel viscosity and surface tension properties and the concomitant variations in the fuel droplet size distributions.

adaptive mesh refinement↗

DOE OSTI2018

Chromium Plume at LANL - From Conceptual Site Model to Development of Complex Remediation Strategies - 18682

A hexavalent chromium plume is present in deep groundwater beneath Los Alamos National Laboratory (LANL or the Laboratory). The plume originated from releases of potassium dichromate from cooling towers from 1956 - 1972. Estimates are that up to 72,000 kg of chromium was released during that period. Data from surface water-balance studies, core-hole and groundwater characterization, geomorphic investigations and geology and geophysics provide the basis for an evolved conceptual model that chromium initially traveled rapidly via an effluent-supported stream for several kilometers, then infiltrated through a stratigraphically complex 275-300 meters thick vadose zone and eventually into a deep (regional) aquifer that is the water supply for the Laboratory and surrounding municipality. The travel time from the release point to the regional aquifer is estimated at 5-10 years based on modeling and contaminant tracers. Monitoring data from two-screen wells and piezometers within the regional aquifer, and data derived from stratified sampling conducted during sonic coring and from analysis of sonic core indicate that the chromium contamination occurs within the upper 23 meters of the highly stratified regional aquifer. Different geologic units at the water table and structural dip of depositional bedding appear to have little effect on chromium migration and plume shape and thickness which instead appear to be a manifestation of multiple breakthrough locations, interconnectedness of preferential hydraulic strata, and a negligible vertical gradient. Recent monitoring data indicate that the down-gradient plume edge (as defined by the New Mexico groundwater standard of 50 μg/L) may be advancing near the Laboratory's boundary with a neighboring Indian reservation. The Laboratory is addressing the increasing concentrations with a regulatory-driven interim measure that uses hydraulic control to manage plume migration. The interim measure involves limited-duration (2-3 years) pumping, treatment, and injection to rapidly establish and maintain the 50 μg/L plume edge within the Laboratory boundary while a final remediation strategy is developed and approved by the State regulator. A final remediation strategy will depend heavily on the ability to cost-effectively access the deep aquifer. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Polarized fusion and potential in situ tests of fuel polarization survival in a tokamak plasma

Abstract The use of spin-polarized fusion fuels would provide a significant boost towards the ignition of a burning plasma. The cross section for D + T → α + n, would be increased by 1.5 if the fuels were injected with parallel polarization. Furthermore, our simulations demonstrate additional non-linear power gains in large-scale machines such as ITER, due to increased alpha heating. Such benefits require the survival of spin polarizations for periods comparable to the particle confinement time. During the 1980s, calculations predicted that polarizations could survive a plasma environment, although concerns persisted regarding the cumulative impacts of wall recycling. In that era, technical challenges prevented direct tests and left the large scale fueling of a power reactor beyond reach. Over the last decades, this situation has changed dramatically. Detailed simulations of ITER have predicted negligible wall recycling in a high-power reactor, and recent advances in laser-driven sources project the capability of producing large quantities of ∼100% polarized D and T. The remaining crucial step is an in-situ demonstration of polarization survival in a plasma. For this, we outline a measurement strategy using the isospin-mirror reaction, D + 3 He → α + p. Polarized 3 He avoids the complexities of handling tritium, while encompassing the same spin-physics. We evaluate two methods of delivering deuterium, using dynamically polarized Lithium-Deuteride (with vector polarization P V D of 70%) or frozen-spin Hydrogen-Deuteride (with P V D of 40%), together with a method of injecting optically-pumped 3 He (with 65% polarization). Pellets of these materials all have long polarization decay times (∼6 min for LiD at 2 K, ∼2 months for HD at 2 K, and ∼3 d for 3 He at 77 K), all far greater than a plasma shot in a research tokamak such as DIII-D (∼20 s). Both species can be propelled from a single cryogenic injection gun. We review plasma requirements and strategies for detecting polarization survival. Polarization alters both fusion yields and the angular distribution of fusion products, and each of these provides a potential signal. In this paper we simulate a selection of shots with similar characteristics in a future high-T ion H plasma, and find ratios of yields from shots with fuel spins parallel and antiparallel reaching 1.3 (HD + 3 He) to 1.6 (LiD + 3 He) over a wide range of poloidal angles. (A companion paper finds sensitivity to fusion product angular distributions as reflected in the pitch angles of protons and alphas reaching the plasma facing wall.)

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Development of prechamber enabled mixing-controlled combustion strategy for ultra-low methane emissions from lean burn natural gas engines

This numerical study explores the optimization of Prechamber Enabled Mixing-Controlled Combustion (PC-MCC) using natural gas in heavy-duty engines, aiming to enhance combustion efficiency to minimize methane slip and NOx emissions. The approach involves a prechamber ignition system, distinct from conventional spark ignition (SI) systems, to initiate combustion of direct injected natural gas. By leveraging the robust ignition characteristics of the prechamber, the PC-MCC method demonstrates significant potential in achieving efficient combustion akin to diesel engines but with lower greenhouse gas emissions. The research evaluates the effects of various geometric and operational parameters on the combustion process and emissions, including prechamber volume, nozzle diameter, direct injector (DI) geometry, and engine operating strategies. Computational Fluid Dynamics (CFD) simulations are utilized, focusing on a heavy-duty, single-cylinder engine modeled after the Caterpillar C9.3B engine. Key findings indicate that a prechamber volume of 3 cc, coupled with a nozzle diameter of 2.75 mm for two prechamber holes, strikes an optimal balance between combustion efficiency and emissions reduction. This configuration ensures robust combustion across a range of operating conditions while maintaining methane slip within targeted limits. Further investigation into DI geometry shows the significance of the injector umbrella angle and nozzle diameter in shaping the fuel-air mixing and combustion dynamics. An umbrella angle of 130° and a nozzle diameter of 300 microns are identified as optimal, promoting rapid and efficient combustion with minimized methane and NOx emissions. The study also investigates the impact of injection timing and pressure, highlighting their roles in controlling combustion timing and influencing emissions levels. Advanced injection timing is found to be crucial in achieving the desired low methane slip, whereas retarded injection timing assists to reduce NOx emissions while having a slight increase in methane emissions. Operating strategies incorporating various levels of Exhaust Gas Recirculation (EGR) are assessed for their effectiveness in further reducing emissions. The research demonstrates that a judicious combination of internal hot EGR and careful calibration of DI pressure and SOI timing can achieve significant reductions in NOx emissions while keeping methane slip under control. Specifically, an internal EGR level of 15%–25%, combined with DI pressures of 200–300 bar and injection timings at or after top dead center, is recommended. These findings contribute valuable insights into the development of advanced combustion techniques for natural gas engines, offering a viable pathway to reduce methane slip without compromising engine efficiency or performance. The PC-MCC system presents a promising solution for the future of heavy-duty natural gas engine technology to reduce methane emissions.

Nsaif, Osama↗

DOE OSTI2019

Experimental and modeling study of chemical-based strategies for mitigating dust formation in fusion reactors [Plasma Flow Reactor Chemical Kinetics: A Method Toward Optimizing Nano-Manufacturing and Laser Inertial Fusion Energy Strategies]

We studied carbon/hydrogen/oxygen chemical kinetics at time scales and thermal conditions relevant to fusion energy applications using a custom-built plasma flow reactor to investigate chemical-based strategies for eliminating carbon dust formation in fusion reactors. Acetylene and oxygen gases under varying conditions of initial concentrations are injected into an inductively coupled argon plasma where complete molecular dissociation occurs. The evolution of chemical species is investigated along the plasma flow reactor as a function of temperature and residence time. Atomized species of C, H, and O cool from 5000 K to 1000 K within 30 ms at atmospheric pressures. We employed optical emission and infrared absorption spectroscopy to measure the reaction intermediates (e.g. C 2 ) and products (e.g. C 2 H 2 ). Chemical equilibrium models are inadequate to describe the evolution of carbon molecular products, and thus a chemical kinetics model is developed. In both experiments and kinetic modelling, we find that the addition of oxygen in 1:1 proportion to carbon strongly favors the formation of CO, preventing the formation of acetylene (an important soot precursor) in less than 10 milliseconds. The kinetics model is also used to perform a reaction sensitivity and a rate of production analyses to identify the rate determining steps and the major chemical pathways that control the acetylene production/consumption. The results demonstrate the feasibility of chemical-based strategies for eliminating the formation of carbonaceous particles in fusion energy reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Network-Cognizant Time-Coupled Aggregate Flexibility of Distribution Systems Under Uncertainties

Increasing integration of distributed energy resources (DERs) within distribution feeders provides unprecedented flexibility at the distribution-transmission interconnection. To exploit this flexibility and to use the capacity potential of aggregate DERs, feasible substation power injection trajectories need to be efficiently characterized. This paper provides an ellipsoidal inner approximation of the set of feasible power injection trajectories at the substation such that for any point in the set, there exists a feasible disaggregation strategy of DERs for any load uncertainty realization. The problem is formulated as one of finding the robust maximum volume ellipsoid inside the flexibility region under uncertainty. Though the problem is NP-hard even in the deterministic case, this paper derives novel approximations of the resulting adaptive robust optimization problem based on optimal second-stage policies. The proposed approach yields less conservative flexibility characterization than existing flexibility region approximation formulations. The efficacy of the proposed method is demonstrated on a realistic distribution feeder.

adaptive robust optimization↗

DOE OSTI2021

Network-Cognizant Time-Coupled Aggregate Flexibility of Distribution Systems Under Uncertainties

aggregates↗

DOE OSTI2022

Restoration Insights Gained from a Field Deployment of Dithionite and Acetate at a Uranium In Situ Recovery Mine

Mining uranium by in situ recovery (ISR) typically involves injecting an oxidant and a complexing agent to mobilize and extract uranium in a saturated ore zone. This strategy involves less infrastructure and invasive techniques than traditional mining, but ISR often results in persistently elevated concentrations of U and other contaminants of concern in groundwater after mining. These concentrations may remain elevated for an extended period without remediation. Here, we describe a field experiment at an ISR facility in which both a chemical reductant (sodium dithionite) and a biostimulant (sodium acetate) were sequentially introduced into a previously mined ore zone in an attempt to establish reducing geochemical conditions that, in principle, should decrease and stabilize aqueous U concentrations. While several lines of evidence indicated that reducing conditions were established, U concentrations did not decrease, and in fact increased after the amendment deployments. We discuss likely reasons for this behavior, and we also discuss how the results provide insights into improvements that could be made to the restoration process to benefit from the seemingly detrimental behavior.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2018

A strategy of targeting B10 cell by CD19scFv-IL10R for tumor therapy

Highlights: • PcCD19scFv-IL10R had bispecific ability to target IL-10 and CD19 molecules. • Injecting mice with pcCD19scFv-IL-10R plasmid inhibited carcinoma growth. • Mice treated with pcCD19scFv-IL-10R showed a significant reduction in B10 cells and regulatory T (Treg) cells, but an increase in the anti-tumor Th1 immune response and the cytotoxic CD8{sup +} T cell response. IL-10 producing B (B10) cells, a subset of regulatory B (Breg) cells, produce IL-10 and play immunosuppressive roles in antitumor immunity. B10 cells are associated with enhanced tumor-aggressiveness and a poorer prognosis. To specifically inhibit the IL-10 secreted by B cells, we constructed the recombinant plasmid pcCD19scFv-IL10R, which contained the gene of anti-CD19 single-chain variable fragment (CD19scFv) and the extracellular domain of IL-10R1. Soluble CD19scFv-IL10R protein was identified in vitro and in vivo after the cells were transfected with pcCD19scFv-IL10R plasmid or the mice were injected with the plasmid. The fusion protein had the bispecific ability to target both IL-10 and CD19 molecules in vitro. Intramuscularly (i.m.) injecting mice with pcCD19scFv-IL-10R plasmid inhibited hepatocellular carcinoma growth in vivo. Mice treated with pcCD19scFv-IL-10R showed a significant reduction in B10 cells and regulatory T (Treg) cells, but an increase in the anti-tumor Th1 immune response and the cytotoxic CD8{sup +} T cell response. Thus, targeting B10 cells by CD19scFv-IL10R molecule may offer a new avenue for tumor therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Hybrid Data-Driven Based HVdc Ancillary Control for Multiple Frequency Data Attacks

The high voltage direct current (HVdc) intertie has been applied to provide ancillary-services for ac grids, utilizing the real-time feedback from phasor measurement units (PMUs). However, PMU data communication is vulnerable to false data injection attacks (FDIA) due to protocol defects, thus the HVdc ancillary control and system stability will be threatened. To address this issue, this article proposes a novel HVdc control strategy based on a hybrid data-driven (HDD) methodology. In this work, the HDD methodology is first proposed to detect the types and duration time of multiple frequency attacks. Specifically, the Hilbert Huang transform (HHT) is used to decompose the frequency data, using variational mode decomposition instead of the traditional empirical mode decomposition, to extract data features. Second, a multikernel support vector machine is proposed to classify the attacked data based on the designed distinctive features from HHT. Meanwhile, the attacking duration time is decided using an unsupervised technique. Third, an HDD-based HVdc ancillary control strategy is established to eliminate the effect of FDIAs on the HVdc frequency response. Comprehensive experiments of HDD-based HVdc ancillary controls under different FDIAs suggest that the proposed HDD could fast and accurately classify the FDIAs, and the HDD-based HVdc ancillary control strategy could significantly suppress the impact of the FDIAs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Fail-Safe Logic Design Strategies Within Modern FPGA Architectures

Fail-safe computing refers to computing systems that revert to a non-operational safe state when a fault occurs. In this paper, we investigate a circuit level technique as mitigation for single event upsets (SEUs) and fault injection attacks on field programmable gate arrays (FPGAs), and analyze the effectiveness of the technique as a fail-safe monitor for an encryption algorithm. The propagation of fault effects through FPGA primitives including lookup tables (LUTs) and programmable interconnect points (PIPs) is assessed within an FPGA architecture created using an open source tool, and validated using fault injection experiments on an FPGA. The analysis reveals additional vulnerabilities exist within reconfigurable architectures over those in equivalent fail-safe application specific integrated circuit (ASIC), thus requiring a more elaborate network of redundant circuits and checking logic. The configuration memory bits (CMBs), which configure routing and designate logic functions within the LUTs of the FPGA, add complexity to fail-safe design strategies by introducing additional fault conditions and fault propagation paths. A resource-efficient fail-safe circuit design technique called DEsign for Fail-safe in reCONfigurable systems (DEFCON) is proposed. The benefits and limitations associated with DEFCON are described in the context of fault injection experiments carried out as simulations and in FPGA hardware.

Bhakta, Priya A. [Univ. of New Mexico, Albuquerque↗

DOE OSTI2024

Investigation of Scale Deposition and Wellbore Corrosion in Carbonated Brine Injection: A Simulation Study

Carbonated brine injection (CBI), which involves dissolving CO2 in produced water to be injected into deep geologic reservoirs, is a method to manage produced brine, carbon dioxide (CO2) sequestration, and reduce anthropogenic greenhouse gas emissions. This low-risk CO2 storage strategy can leverage the existing saltwater disposal infrastructure and well resources. However, the potential for corrosion and scale deposition are a major challenge for carbonated brine which may result in subsidence, wellbore failure, casing failure, and cement failure. The main objective of this research was to evaluate the wellbore materials compatibility with carbonated brine water during the injection process, for repurposing Class II saltwater disposal wells for CBI.

Belarbi, Zineb↗

DOE OSTI2023

The hidden structure of hydrodynamic transport in random fracture networks

We study the large-scale dynamics and prediction of hydrodynamic transport in random fracture networks. The flow and transport behaviour is characterized by first passage times and displacement statistics, which show heavy tails and anomalous dispersion with a strong dependence on the injection condition. The origin of these behaviours is investigated in terms of Lagrangian velocities sampled equidistantly along particle trajectories, unlike classical sampling strategies at a constant rate. The velocity series are analysed by their copula density, the joint distribution of the velocity unit scores, which reveals a simple, albeit hidden, correlation structure that can be described by a Gaussian copula. Based on this insight, we derive a Langevin equation for the evolution of equidistant particle speeds. In this framework, particle motion is quantified by a stochastic time-domain random walk, the joint density of particle position, and speed satisfies a Klein–Kramers equation. The upscaled theory quantifies particle motion in terms of the characteristic fracture length scale and the distribution of Eulerian flow velocities. That is, it is predictive in the sense that it does not require the a priori knowledge of transport attributes. The upscaled model captures non-Fickian transport features, and their dependence on the injection conditions in terms of the velocity point statistics and average fracture length. It shows that the first passage times and displacement moments are dominated by extremes occurring at the first step. The presented approach integrates the interaction of flow and structure into a predictive model for large-scale transport in random fracture networks.

42 ENGINEERING↗

DOE OSTI2019

Quantifying Hydraulic and Water Quality Uncertainty to Inform Sampling of Drinking Water Distribution Systems

Sampling of drinking water distribution systems is performed to ensure good water quality and protect public health. Sampling also satisfies regulatory requirements and is done to respond to customer complaints or emergency situations. Water distribution system modeling techniques can be used to plan and inform sampling strategies. However, a high degree of accuracy and confidence in the hydraulic and water quality models is required to support real-time response. One source of error in these models is related to uncertainty in model input parameters. Effective characterization of these uncertainties and their effect on contaminant transport during a contamination incident is critical for providing confidence estimates in model-based design and evaluation of different sampling strategies. In this paper, the effects of uncertainty in customer demand, isolation valve status, bulk reaction rate coefficient, contaminant injection location, start time, duration, and rate on the size and location of the contaminant plume are quantified for two example water distribution systems. Results show that the most important parameter was the injection location. The size of the plume was also affected by the reaction rate coefficient, injection rate, and injection duration, whereas the exact location of the plume was additionally affected by the isolation valve status. As a result, uncertainty quantification provides a more complete picture of how contaminants move within a water distribution system and more information when using modeling results to select sampling locations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Model-Free Voltage Control of Active Distribution System with PVs Using Surrogate Model-Based Deep Reinforcement Learning

Accurate knowledge of the distribution system topology and parameters is required to achieve good voltage control performance, but this is difficult to obtain in practice. This paper proposes a physical-model-free voltage control method based on a surrogate-model-enabled deep reinforcement learning approach. Specifically, a surrogate model is trained in a supervised manner using the recorded limited number of historical data to learn the relationship between the power injections and voltage fluctuations of each node. Then, the deep reinforcement learning algorithm is applied to learn an optimal control strategy from the experiences obtained by continuous interactions with the surrogate model. The proposed method can achieve physical-model-free control of unbalanced distribution network and inform real-time decisions to deal with fast voltage fluctuations caused by the rapid variation of PV generation. Simulation results on an unbalance IEEE 123-bus system show that the proposed method can achieve similar performance as that of perfect physical-model-based approaches while being advantageous over other traditional methods.

active distribution network↗