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At least 1,153 records · Page 64

Fermilab PIP II Machine Protection System Digitized Data Noise Elimination Scheme and Its FPGA Implementation

In Fermilab's PIP-II machine protection system, beam loss signals from various detectors are digitized at 125 MS/s. Noise from both high-frequency sources and low-frequency 60 Hz AC power equipment can con-taminate the data. To suppress noise across these ranges especially 60 Hz and its harmonics, which overlap with beam loss signal frequencies advanced digital processing beyond standard filtering is re-quired. Several real-time functional blocks were simu-lated and tested on an FPGA: (1) a dual time-constant discharging integrator filter, (2) a de-ripple baseline extraction and storage block, and (3) a fast-recovery discharging integrator. The nonlinear IIR integrator filter removes high-frequency noise and feeds into the baseline extractor. Upon detecting abrupt beam loss, it switches to a longer time constant to prevent baseline distortion. The de-ripple block calculates a valid base-line by averaging over multiple 60 Hz periods, storing results in a 4096-word FPGA RAM. This baseline is subtracted from raw data before integration by the fast-recovery block, which resets quickly after use. All blocks achieved expected performance.

Wu, Jinyuan [Fermilab] (ORCID:0000000344329521)↗

Probing the Effectiveness in Stabilizing Lithium Metal Anodes through Functional Additives

A variety of electrolyte additives were comprehensively evaluated to understand their relative capability in stabilizing lithium metal anode. Although the Li||Cu test is an effective test to rule out ineffective additives, a reliable assessment of individual additives cannot be obtained just by a single evaluation method. Therefore, various methods must be combined to truly assess the stabilization of a lithium anode. Moreover, it was also discovered that a significant depletion of electrolytes occurred during the end-of-life of the lithium batteries, which partially contributed to the sudden failure of the lithium batteries during cycling. However, the main culprit of the sudden failure was identified as the significant increase in the resistance of the lithium metal anode. Further, when used as an additive, cyclic fluorinated carbonates are the most effective in stabilizing the lithium anode and improving the cycling performance of lithium batteries among all the common additives. Despite its cost-effectiveness, the additive in the conventional electrolyte approach provides insufficient protection for lithium metal due to the complete consumption of the additive materials, which is necessary to repair the solid-electrolyte interphase (SEI). Therefore, it is suggested that a larger ratio (>15 wt %) of the SEI former should be employed to achieve effective lithium stabilization.

25 ENERGY STORAGE↗

Dual-mycorrhizal colonization is determined by plant age and host identity in two species of Populus

Plants have evolved symbioses with mycorrhizal and endophytic fungi that are essential for their growth and survival. While most plants associate with a single guild of mycorrhizal fungi, a select group termed “dual-mycorrhizal plants” associate with both arbuscular mycorrhizal and ectomycorrhizal fungi. Although a shift from predominance of arbuscular mycorrhizal to ectomycorrhizal colonization with plant development has been demonstrated on other dual-mycorrhizal hosts, it is not known how mycorrhizal colonization shifts with plant age in Populus species. We performed a controlled growth experiment with natural field-sourced inocula to test for age-dependent shifts in fungal colonization rates and for host-specific patterns of colonization in two species of Populus (P. tremuloides and P. trichocarpa). We found that only P. trichocarpa displayed dual-mycorrhizal colonization, while P. tremuloides associated with ectomycorrhizal fungi, but not arbuscular mycorrhizal fungi. Both guilds of mycorrhizal fungi increased in abundance with plant age, while root endophytic fungal colonization decreased. Many of the early-colonizing endophytic fungi that we documented have strong saprotrophic capabilities, which may be an important trait for fast colonization. Dark septate endophytes were more abundant than either guild of mycorrhizal fungi, and are likely to be functionally important members of the Populus root fungal community. Our findings represent a novel pattern in the development of dual-mycorrhizal colonization and illustrate that Populus species vary in their association with arbuscular mycorrhizal fungi. In conclusion, our results also highlight the importance of dark septate endophyte colonization dynamics on dual-mycorrhizal plants.

59 BASIC BIOLOGICAL SCIENCES↗

High-precision mass measurements of the isomeric and ground states of 44 V: Improving constraints on the isobaric multiplet mass equation parameters of the A=44, 0 + quintet

Background: The quadratic isobaric multiplet mass equation (IMME) has been very successful at predicting the masses of isobaric analog states in the same multiplet, while its coefficients are known to follow specific trends as functions of mass number. The Atomic Mass Evaluation 2016 [Chin. Phys. C 41, 030003 (2017)] 44 V mass value results in an anomalous negative c coefficient for the IMME quadratic term; a consequence of large uncertainty and an unresolved isomeric state. The b and c coefficients can provide useful constraints for construction of the isospin-nonconserving Hamiltonians for the pf shell. In addition, the excitation energy of the 0 + , T = 2 level in 44 V is currently unknown. This state can be used to constrain the mass of the more exotic 44 Cr. Purpose: The aim of the experimental campaign was to perform high-precision mass measurements to resolve the difference between 44 V isomeric and ground states, to test the IMME using the new ground state mass value and to provide necessary ingredients for the future identification of the 0 + , T = 2 state in 44 V. Method: High-precision Penning trap mass spectrometry was performed at LEBIT, located at the National Superconducting Cyclotron Laboratory, to measure the cyclotron frequency ratios of [ 44g,m VO] + versus [ 32 SCO] + , a well-known reference mass, to extract both the isomeric and ground state masses of 44 V. Results: The mass excess of the ground and isomeric states in 44 V were measured to be -23 804.9(80) keV/c 2 and -23 537.0(55) keV/c 2 , respectively. This yielded a new proton separation energy of S p = 1 773(10) keV. Conclusion: The new values of the ground state and isomeric state masses of 44 V have been used to deduce the IMME b and c coefficients of the lowest 2 + and 6 + triplets in A = 44. The 2 + c coefficient is now verified with the IMME trend for lowest multiplets and is in good agreement with the shell-model predictions using charge-dependent Hamiltonians. The mirror energy differences were determined between 44 V and 44 Sc, in line with isospin-symmetry for this multiplet. Finally, the new value of the proton separation energy determined, to an uncertainty of 10 keV, will be important for the determination of the 0 + , T = 2 state in 44 V and, consequently, for prediction of the mass excess of 44 Cr.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Salt Vessel-Sample Generator Interface

The goal of the salt sampling program at Argonne is to develop and deploy automated molten salt sampling approaches for interfacing relevant unit operations with salt analysis to improve the timeliness and accuracy of sampling-based accountancy measurements. One technology under development is a vacuum sampler loop module. In this system, molten salt is drawn from a process vessel through a heated sampling line and into a charge vessel. Next, one or more samples are split from the volume in the charge vessel and the remaining salt is returned to the process. The vacuum sampler loop module is being developed to interface with other sample processing and analysis modules to enable rapid at-line sample characterization. The main purpose of the vacuum sampling loop module is to enable the collection of samples that are more representative of the bulk salt by replacing traditional point samplers (i.e., dip probes) with a sampling approach that captures a larger cross section of salt. Additionally, the vacuum sampling approach eliminates the risk of dross contamination of samples and avoids the use of moving parts in the salt. Two methods of interfacing the vacuum sampling loop with a precision pneumatic sample generator were investigated in FY21. This report covers the testing of fluidic coupling between the two modules. Two iterations of the fluidically coupled modules were tested. The first iteration system coupled the two modules using a freeze valve to seal the vacuum sampler during filling and to control flow into the pneumatic sample generator. While this integrated system functioned as intended, some changes were implemented to make the system more robust and better suited to remote deployment. Specifically, the system was made to be more modular and active control of the vacuum filling operation was replaced with a passive control mechanism. For passive filling, the salt charge vessel was vented to a small gas tank that was at negative pressure, causing salt to be drawn into the vessel until the force of the fluid head was in equilibrium with the gas pressure. The passive control system performed well and will be used in future iterations. Another change in the second system was a newly configured pneumatic sample generator in which sample ejection occurred through a hole in the reservoir’s stainless-steel side wall instead of through a non-wetted sapphire orifice on the bottom. This alternate configuration may be better suited for near-process deployment because it enables on-line orifice maintenance and an orifice bypass drain back to the process. A third change in the second iteration system was the transition to a two-chamber charge vessel which split off a fraction of the sampled salt as a liquid aliquot. The goal was to create a buffer mechanism that would allow reproducible aliquoting of samples, independently of variability in the charge vessel fill height. While the two-chamber design was functional, the sample size reproducibility was below target values. To improve reproducibility and overcome many of the impediments to remote deployment of the vacuum sampling loop module, separate work was conducted to replace the two-chamber liquid aliquoting mechanism with aliquoting into single-use sample tubes. Solid salt transfer in the sample tubes will replace fluidic coupling for integrating the vacuum sampler with downstream modules. Because the proposed operations can all be executed with simple overhead actuation mechanisms or other existing hot-cell technology, there will be no need for large investments in novel hot cell sample handling technologies using this alternate approach. As such, near-term deployment of the vacuum sampling technology will be achievable. This new approach for automated coupling of sample tubes with down-stream modules is covered in a separate FY21 report, and a remotely operated version of the vacuum sampler loop module with the tube aliquoting feature is planned for FY22.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Pattern Dictionary Method for Anomaly Detection

In this paper, we propose a compression-based anomaly detection method for time series and sequence data using a pattern dictionary. The proposed method is capable of learning complex patterns in a training data sequence, using these learned patterns to detect potentially anomalous patterns in a test data sequence. The proposed pattern dictionary method uses a measure of complexity of the test sequence as an anomaly score that can be used to perform stand-alone anomaly detection. We also show that when combined with a universal source coder, the proposed pattern dictionary yields a powerful atypicality detector that is equally applicable to anomaly detection. The pattern dictionary-based atypicality detector uses an anomaly score defined as the difference between the complexity of the test sequence data encoded by the trained pattern dictionary (typical) encoder and the universal (atypical) encoder, respectively. We consider two complexity measures: the number of parsed phrases in the sequence, and the length of the encoded sequence (codelength). Specializing to a particular type of universal encoder, the Tree-Structured Lempel–Ziv (LZ78), we obtain a novel non-asymptotic upper bound, in terms of the Lambert W function, on the number of distinct phrases resulting from the LZ78 parser. This non-asymptotic bound determines the range of anomaly score. As a concrete application, we illustrate the pattern dictionary framework for constructing a baseline of health against which anomalous deviations can be detected.

97 MATHEMATICS AND COMPUTING↗

Comparison of Eco-Friendly Ionic Liquids and Commercial Bio-Derived Lubricant Additives in Terms of Tribological Performance and Aquatic Toxicity

Approximately half of the lubricants sold globally find their way into the environment. The need for Environmentally Acceptable Lubricants (EALs) is gaining increased recognition. A lubricant is composed of a base oil and multiple functional additives. The literature has been focused on EAL base oils, with much less attention given to eco-friendly additives. This study presents the tribological performance and aquatic toxicity of four short-chain phosphonium-phosphate and ammonium-phosphate ionic liquids (ILs) as candidate anti-wear and friction-reducing additives for EALs. The results are benchmarked against those of four commercial bio-derived additives. The four ILs, at a mere 0.5 wt% concentration in a synthetic ester, demonstrated a 30–40% friction reduction and >99% wear reduction, superior to the commercial baselines. More impressively, all four ILs showed significantly lower toxicity than the bio-derived products. In an EPA-standard chronic aquatic toxicity test, the sensitive model organism, Ceriodaphnia dubia, had 90–100% survival when exposed to the ILs but 0% survival in exposure to the bio-derived products at the same concentration. This study offers scientific insights for the future development of eco-friendly ILs as lubricant additives.

36 MATERIALS SCIENCE↗

An efficient explicit implementation of a near-optimal quantum algorithm for simulating linear dissipative differential equations

We propose an efficient block-encoding technique for the implementation of the Linear Combination of Hamiltonian Simulations (LCHS) for simulating dissipative initial-value problems. This algorithm approximates a target nonunitary operator as a weighted sum of Hamiltonian evolutions, thereby emulating a dissipative problem by mixing various time scales. We introduce an efficient encoding of the LCHS into a quantum circuit based on a simple coordinate transformation that turns the dependence on the summation index into a trigonometric function. Classically, this method is equivalent to the use of a highly accurate Fejér-Clenshaw-Curtis quadrature formula. Quantumly, this significantly simplifies block-encoding of a dissipative problem and allows one to perform an exponential number of Hamiltonian simulations by a single Quantum Signal Processing (QSP) circuit. The resulting LCHS circuit has high success probability and the selector scales logarithmically with the number of terms in the LCHS sum and linearly with time. Careful analysis of error convergence proves that this method is more efficient than other LCHS circuits that have recently appeared in the literature. We verify the quantum circuit and its scaling by simulating it on a digital emulator of fault-tolerant quantum computers and, as a test problem, solve the advection-diffusion equation. The proposed algorithm can be used for simulating a wide class of nonunitary initial-value problems including the Liouville equation with added dissipation and linear embeddings of nonlinear systems, such as the Koopman-von Neumann and Carleman embeddings.

Novikau, I [Lawrence Livermore National Laboratory↗

Toward the Understanding of the Reaction Mechanism of Zn/MnO2 Batteries Using Non-alkaline Aqueous Electrolytes

Zn/MnO 2 systems using non-alkaline aqueous electrolytes have attracted tremendous interest as rechargeable aqueous Zn ion batteries due to their safety and high specific capacities. Despite their promising electrochemical performance, however, their reaction mechanism has remained elusive. Here in this paper, we examined the structural evolution of cryptomelane α-MnO 2 cathode by ex situ transmission electron microscopy after electrochemical testing using two different non-alkaline aqueous Zn electrolytes with acetate and triflate salts of different pH values. We have discovered that the systems tested in both electrolytes exhibit a dissolution–deposition reaction mechanism through dissolution–deposition of Mn 2+ ions from/on the cathodes with a display of similar discharge/charge product formation. We have also found that the cell tested using the acetate electrolyte shows evidence of structural irreversibility that might contribute to its rapid capacity degradation. This finding offers an important insight into optimizing the cathode design for enhanced electrochemical function of aqueous Zn/MnO 2 batteries.

25 ENERGY STORAGE↗

Development of a high current density, high temperature superconducting cable for pulsed magnets

Abstract A low AC loss Rare Earth Barium Copper Oxide (REBCO) cable, based on the VIPER cable technology has been developed by Commonwealth Fusion Systems for use in high field, REBCO based tokamaks. The new cable is composed of partitioned and transposed copper ‘petals’ shaped to fit together in a circular pattern with each petal containing a REBCO tape stack and insulated from each other to reduce AC losses. A stainless steel jacket adds mechanical robustness—also serving as a vessel for solder impregnation—while a tube runs through the middle for cooling purposes. Additionally, fiber optic sensors are placed under the tape stacks for quench detection. To qualify this design, a series of experiments were conducted as part of the SPARC tokamak Central Solenoid Model Coil program—to retire the risks associated with full scale, fast ramping, high flux HTS Central Solenoid (CS) and Poloidal Field (PF) coils for tokamak fusion power plants and net energy demonstrators. These risk study and risk reduction experiments include (1) AC loss measurement and model validation in the range of ~5 T/s, (2) an IxB electromagnetic loading of over 850 kN/m at the cable level and up to 300 kN/m at the stack level, (3) a transverse compression resilience of over 350 MPa, (4) manufacturability at tokamak relevant speeds and scales, (5) cable to cable joint performance, (6) fiber optic based quench detection speed, accuracy, and feasibility, and (7) overall winding pack integration and magnet assembly. The result is a cable technology, now referred to as PIT VIPER, with AC losses that measure fifteen times lower (at ~5 T/s) than its predecessor technology; a 2% or lower degradation of critical current (Ic) at high IxB electromagnetic loads; no detectable Ic degradation up to 570 MPa of transverse compression on the cable unit cell; end to end magnet manufacturing, consistently producing Ic values within 7% of the model prediction; cable to cable joint resistances at 20 K on the order of ~15 nΩ; and fast, functional quench detection capabilities that do not involve voltage taps. This cable technology will be tested comprehensively in a Central Solenoid Model Coil to prove its readiness for compact, high field tokamak operation.

Sanabria, Charlie (ORCID:0000000150175309)↗

Autonomous System Subversion Tactics: Prototypes and Recommended Countermeasures

One of the fielding requirements for Advanced and Small Modular Reactors (AR/SMR) is the ability to support remote and autonomous operations. Autonomous Control Systems (ACS) are found on platforms such as Autonomous Space Vehicles, Cruise Missiles, and advanced driver-assistance systems. Each of these ACS implementations depends upon a set of decision support subsystems responsible for supporting Autonomous Mission Managers (names vary based upon field and author preferences). These Autonomous Mission Managers receive inputs from system sensors (e.g., LIDAR collection from an automobile travelling down a street; transients from a nuclear reactor), and perform a set of classifications (e.g., Red Traffic Light; Small Pedestrian at 10m; Load Rejection; Single Coolant Pump Trip), and then use these classifications in combination with recommendation algorithms to achieve platform goals (e.g., Stop the Vehicle at the Traffic Light, Avoid the Small Pedestrian; Trip the Reactor to prevent a Safety Event). The design, implementation, and fielding of an ACS capability will alter the cyber-attack surface such that existing risk management plans will need to be updated to include how to protect and defend against data-science and decision-support-system attack classes. These attack classes would include protection of the design and training environments where algorithm selection and testing and training data would be obvious attack vectors. These attack classes would also require an informed set of detection and response procedures to identify anomalous behaviors and document best practices for anomaly assessment and vulnerability mitigation and remediation. Last year we published a Cyber Threat Assessment Methodology for Autonomous and Remote Operations for AR/SMRs along with a companion publication on Cyber Attack and Defense Use Cases. The focus of the methodology was on describing and enumerating ACS processes, components, and functions such that security engineers could: evaluate subversion options against the target; identify threat actor attributes and capabilities derived from each subversion option; and identify security controls and response countermeasures. The Use Cases document offered detailed methodology examples including an assessment of a Military Base SMR, an Autonomous System Decision Loop, and implementation of AR/SMR Machine Learning algorithms. Our proposal at the end of last year was to focus on implementation of subversion prototypes related to the last Use Case area: AR/SMR Machine Learning (ML) Algorithms. We included six attack scenarios in our Use Cases paper: a Poisoning Attack against ML functions implemented using an FPGA; a Trojaning Attack against ML classifiers exploiting the excitability of Nuclear Engineers; a Backdooring Attack against ML Training environments to ensure persistence of an attack vector; a False Positive Evasion Attack against multi-factor Access Control Systems using clever inputs; an Inference Attack against ML models by an Insider with access to the Operational environment; and an Adversarial Reprogramming Attack against a Material Access Control Video Surveillance System. At the beginning of this year these six attack scenarios were provided to our research teams at Georgia Tech and Idaho State University and each team successfully implemented a subversion attack against a ML implementation to include transient misclassifications. While this is a notable outcome from this type of research, this paper offers the reader insight into not only how to structure and execute these types of attacks, but into the thought process behind how the researcher investigated the problem space, performed initial algorithm implementation, and the trial-and-error behind arriving at the successful subversion prototypes. We include in this paper a set of associated Scenarios on how these subversion prototypes could be implemented and an initial set of guidance for AR/SMR architects, Nuclear Regulators, and Cyber Defenders to implement awareness and defense capabilities into their current operational portfolios.

42 ENGINEERING↗

Machine learning defect properties in Cd-based chalcogenides

Impurity energy levels in the band gap can have serious consequences for a semiconductor's performance as a photovoltaic absorber. Data-driven approaches can help accelerate the prediction of point defect properties in common semiconductors, and thus lead to the identification of potential deep lying impurity states. In this work, we use density functional theory (DFT) to compute defect formation energies and charge transition levels of hundreds of impurities in CdX chalcogenide compounds, where X = Te, Se or S. We apply machine learning techniques on the DFT data and develop on-demand predictive models for the formation energy and relevant transition levels of any impurity atom in any site. The trained ML models are general and accurate enough to predict the properties of any possible point defects in any Cd-based chalcogenide, as we prove by testing on a few selected defects in mixed chalcogen compounds CdTe 0.5 Se 0.5 and CdSe 0.5 S 0.5 . The ML framework used in this work can be extended to any class of semiconductors.

density functional theory↗

Towards a Unified Low-Cost Flow Plate, Flow-Field, PTL Solution for Proton Exchange Membrane Electrolyzers

Proton exchange membrane (PEM) water electrolysis is a highly efficient method for hydrogen production. Research cells typically consist of one proton exchange membrane, two catalyst layers, two porous transport layers, two flow-field plates, and two endplates. In commercial systems, the machined flow-field plates that are employed in research cells are typically replaced by stamped parts or open mesh material solutions to reduce manufacturing cost at scale. Nonetheless, the cell contains about 8 total interfaces: bipolar plate / flow plate material / porous transport medium / electrode / membrane / electrode / porous transport medium / flow plate material / bipolar plate. All these materials and interfaces need to be optimized for maximum performance and efficiency. Reducing the amount of interfaces by combining individual cell components directly benefits the fabrication cost (by reducing the parts count and the needs for surface coatings) and the electrochemical performance (by reducing ohmic losses). We have designed a novel PEM electrolysis cell with a piece of channeled titanium felt functioning as both the anode flow-field and the PTL, referred to as the channeled diffusion layer (CDL). The pores of the felt facilitate both in-plane and through-plane diffusion, ensuring maximum catalyst utilization while also minimizing mass transport loss. The titanium felt can be mass manufactured with existing stamping and forming methods and is therefore a promising candidate to reduce the capital cost of PEM electrolyzers whilst improving hydrogen production efficiency. Experiments conducted with 3mg IrOx/cm2 loading MEAs have shown a approximately 40% boost in peak current by implementing the CDL design. Low catalyst-loading MEAs are being tested in ongoing experiments and their results will be discussed and compared.

08 HYDROGEN↗

Quantitative assessment of eddy viscosity rans models for turbulent mixed convection in a differentially heated plane channel

Turbulent mixed convection between two vertical, infinite parallel plates at different temperatures is studied using various two-equation turbulence models. The numerical simulations are performed at a turbulent Reynolds number of Re τ = 150 and a Grashof number of Gr = 9.6 × 10 5 . Comparisons are made against the highly trusted DNS results. Consistent with the DNS approach, the current simulations are performed using constant properties and the Boussinesq approximation to predict the influence of buoyancy. Previous studies have provided assessments of two-equation turbulence models for various scenarios, but often rely on a qualitative “eye” test in order to determine the most appropriate model to predict a given flow. This study aims to provide a new form of quantitative assessment that accounts for both the physics captured by the turbulence model as well as the magnitude of the system response quantities (SRQ) using a modified symmetric mean absolute percent error (SMAPE) method. This method is designed to be approachable to researchers at any level and can be applied to system response quantities from multiple research fields. Uncertainty quantification is also performed to determine the discretization error for each turbulence model. Recommendations are made as to which turbulence models best capture the physics – hydrodynamically and thermally – using both local and global validation metrics. Lastly, a sensitivity analysis is performed on the damping functions used in the most accurate models. This underpins the potential of model developments and adjustments most worth pursuing for buoyant flows. Finally, this framework provides a more physics-based comparative analysis of the selected turbulence models.

42 ENGINEERING↗

The gallium anomaly

In order to test the end-to-end operations of gallium solar neutrino experiments, intense electron-capture sources were fabricated to measure the responses of the radiochemical SAGE and GALLEX/GNO detectors to known fluxes of low-energy neutrinos. Such tests were viewed at the time as a cross-check, given the many tests of 71 Ge recovery and counting that had been routinely performed, with excellent results. However, the four 51 Cr and 37 Ar source experiments yielded rates below expectations, a result commonly known as the Ga anomaly. As the intensity of the electron-capture sources can be measured to high precision, the neutrino lines they produce are fixed by known atomic and nuclear rates, and the neutrino absorption cross section on 71 Ga is tightly constrained by the lifetime of 71 Ge, no simple explanation for the anomaly has been found. To check these calibration experiments, a dedicated experiment BEST was performed, utilizing a neutrino source of unprecedented intensity and a detector optimized to increase statistics while providing some information on counting rate as a function of distance from the source. The results BEST obtained are consistent with the earlier solar neutrino calibration experiments, and when combined with those measurements, yield a Ga anomaly with a significance of approximately 4𝜎, under conservative assumptions. But BEST found no evidence of distance dependence and thus no explicit indication of new physics. In this review we describe the extensive campaigns carried out by SAGE, GALLEX/GNO, and BEST to demonstrate the reliability and precision of their experimental procedures, including 71 Ge recovery, counting, and analysis. We also describe efforts to define uncertainties in the neutrino capture cross section, which now include estimates of effects at the ≲ 0.5% level such as radiative corrections and weak magnetism. With the results from BEST, an anomaly remains even if one retains only the transition to the 71 Ge ground state, whose strength is fixed by the known lifetime of 71 Ge. We then consider the new-physics solution most commonly suggested to resolve the Ga anomaly, oscillations into a sterile fourth neutrino, 𝜈 𝑒 → 𝜈 𝑠 . We find such a solution generates substantial tension with several null experiments, owing to the large mixing angle required. While this does not exclude such solutions – the sterile sector might include multiple neutrinos as well as new interactions – it shows the need for more experimental constraints, if we are to make progress in resolving the Ga and other low-energy neutrino anomalies. We conclude by consider the role future low-energy electron-capture sources could play in this effort.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Experimental and Numerical Investigation of Flow Boiling in Additive Manufactured Foam Structures With Vapor Pathways

Abstract The unique properties of metal foams make them potential candidates for a range of applications, including microsystem thermal management. Using additive manufacturing to create foam-type structures can improve upon prior thermal solutions by eliminating thermal interface materials and allowing for customization/local control of parameters. In the present investigation, flow boiling in additive-manufactured metal foams is investigated both experimentally and numerically. Two test samples, one with uniform structure and the other with pathways for vapor removal, are compared both experimentally and numerically. A conjugate computational fluid dynamics and heat transfer (CFD-HT) model utilizing a three-dimensional volume of fluid (VOF) model with accompanying evaporation/condensation model provided in-depth visualization of the boiling flow phenomena. The experiments generated the thermohydraulic performance over a range of heat fluxes, demonstrating that the sample incorporating dedicated vapor pathways performed better in both pressure and heat transfer performance metrics compared to the uniform foam. Additionally, negative system-level effects (i.e., hydraulic oscillations) were shown to be abated using the vapor removal structures. The numerical model yielded further insight into the factors contributing to the improved performance. Results indicated the pathways functioned as vapor removal channels, allowing the generated vapor to vent from the foam structure into the lanes. Further computational investigations demonstrated changes in flow regimes, where the addition of vapor channels caused the flow to change from churn to annular. Bubble behavior unique to the vapor pathway structure was studied, showing stagnant regions that eject vapor into the channel.

Engineering↗

Utilizing coal-derived solid carbon materials towards next-generation smart and multifunction pavements

This project focused on developing an eco-friendly, multifunctional pavement system, called Coal-Derived Carbon Enabled Smart Pavement (CDC-SP), using coal-derived materials. The system utilizes coal-derived pyrolyzed char as a key component to create electrically conductive asphalt concrete for smart pavements that offer self-heating, self-sensing, and self-healing capabilities. These functions are made possible by the conductive properties of coal-char, which enable Ohmic heating for snow and ice deicing, piezoresistivity for self-sensing, and induction heating for self-healing of cracks caused by stress or aging. The team successfully created CDC-SP samples with over 50% coal char composition, demonstrating desirable mechanical properties such as rutting resistance, moisture susceptibility, and cracking resistance. These samples also exhibited strong electrical and thermal conductivity, making them ideal for heating applications. Extensive tests confirmed the pavement’s effectiveness in melting ice and snow and maintaining durability under environmental conditions. The CDC-SP presents a promising approach to integrating U.S. domestic coal resources into infrastructure projects, providing environmental and economic benefits by enhancing pavement performance while utilizing low-cost coal-derived materials. Further research and compliance with industry standards are recommended before commercial scaling.

01 COAL, LIGNITE, AND PEAT↗

Anomaly Detection in Liquid Sodium Cold Trap Operation with Multisensory Data Fusion Using Long Short-Term Memory Autoencoder

Sodium-cooled fast reactors (SFR), which use high temperature fluid near ambient pressure as coolant, are one of the most promising types of GEN IV reactors. One of the unique challenges of SFR operation is purification of high temperature liquid sodium with a cold trap to prevent corrosion and obstructing small orifices. We have developed a deep learning long short-term memory (LSTM) autoencoder for continuous monitoring of a cold trap and detection of operational anomaly. Transient data were obtained from the Mechanisms Engineering Test Loop (METL) liquid sodium facility at Argonne National Laboratory. The cold trap purification at METL is monitored with 31 variables, which are sensors measuring fluid temperatures, pressures and flow rates, and controller signals. Loss-of-coolant type anomaly in the cold trap operation was generated by temporarily choking one of the blowers, which resulted in temperature and flow rate spikes. The input layer of the autoencoder consisted of all the variables involved in monitoring the cold trap. The LSTM autoencoder was trained on the data corresponding to cold trap startup and normal operation regime, with the loss function calculated as the mean absolute error (MAE). The loss during training was determined to follow log-normal density distribution. During monitoring, we investigated a performance of the LSTM autoencoder for different loss threshold values, set at a progressively increasing number of standard deviations from the mean. The anomaly signal in the data was gradually attenuated, while preserving the noise of the original time series, so that the signal-to-noise ratio (SNR) averaged across all sensors decreased below unity. Results demonstrate detection of anomalies with sensor-averaged SNR < 1.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗