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At least 811 records · Page 45

NA-22 Quarterly Report: April-June, 2020

At LLNL we contribute to two projects in NNSA-IAEC Science and Technology Working Group Area V: Basic Science of Waste Management & Subsurface Science. The motivation behind Topic Area V is to evaluate the scientific and safety case for an intermediate borehole to house Israel’s nuclear waste. WM1 (SNL lead) is Thermomechanical Damage (initially called Damage Accumulation and Wellbore Stability). This work focuses on evaluating the damage to the host rock induced by excavation and heat released from a possible radioactive waste repository/borehole. WM2 (LLNL lead) is Radionuclide Facilitated Transport in Carbonate Rock (initially called Colloidal Transport of Radionuclides). This work focuses on better understanding the transport of radionuclides and colloids from a nuclear waste repository/borehole in a vadose zone environment through experimentation and modeling. In the second quarter (this report) our work has been delayed in part due to COVID-19. LLNL went into shelter in place (SIP), minimum safe operations mid-March. Operations at LLNL have been slowly ramping up with 50% of the workforce back onsite in limited capacity and telecommuting widely used. The good news is that our labs opened up the last week in June and experiments are expected to start up again for WM2 Radionuclide Facilitated Transport in July. LLNL’s contribution to WM1 Thermochemical Damage modeling efforts also started back up in late June. We expect to be able to catch up on much of our work by the end of next quarter. The three national laboratories communication on a bi-monthly basis to make sure Area V projects remain on track and we have a monthly conference call with our Israeli counterparts to make sure we are communicating priorities and coordinating project details.

54 ENVIRONMENTAL SCIENCES↗

Nuclear Computational Low Energy Initiative (NUCLEI)

The NUCLEI project, as defined by the scope of work, developed, implemented and run codes for large-scale computations of many topics in low-energy nuclear physics. Physics studied include the properties of nuclei and nuclear decays, nuclear structure and reactions, and the properties of nuclear matter. The computational techniques used include Quantum Monte Carlo, Configuration Interaction, Coupled Cluster, and Density Functional methods. The research program emphasized areas of high interest to current and possible future DOE nuclear physics facilities, including ATLAS and FRIB (nuclear structure and reactions, and nuclear astrophysics), TJNAF (neutron distributions in nuclei, few body systems, and electroweak processes), NIF (thermonuclear reactions), MAJORANA and FNPB (neutrinoless double-beta decay and physics beyond the Standard Model), and LANSCE (fission studies).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Spectroscopic evaluation of tribologically-induced changes in surface chemistry of Zr-based bulk metallic glass

Bulk metallic glasses (BMGs) are promising structural materials owing to their high elastic limit and yield strength-to-weight ratio. While BMGs also exhibit attractive tribological properties (e.g., high wear resistance), the scientific basis for this behavior is not yet established. In particular, tribologically-induced changes in surface chemistry upon sliding are still an open topic of research. Here, we evaluated by X-ray photoelectron spectroscopy (XPS) the evolution of the surface chemistry of Vitreloy 105 (a Zr-rich BMG) upon sliding under different contact conditions against a tungsten carbide countersurface. The spectroscopic results indicate that the relative fraction of the metallic elements in the near-surface region is not affected by the sliding speed when the applied contact pressure is lower than 1.37 GPa, while a decrease in metallic zirconium was observed at lower sliding speeds and higher applied contact pressure (i.e., 1.71 GPa). Based on the spectroscopic results, a model is proposed for the effect of mechanical stress on the extent of oxidation of the near-surface region of Zr-based BMGs. In conclusion, the results of this work provide novel insights into the surface phenomena occurring on BMGs upon sliding and add significantly to our understanding of the tribological response of this class of promising structural materials.

Bulk metallic glasses↗

Light rain exacerbates extreme humid heat

Abstract Humid heat waves pose significant risks to human health and the ecosystem. Intuitively, rainfall often alleviates extreme humid heat. However, here we show that light rain often accompanies extreme humid heat, exacerbating its frequency and intensity, especially over arid and semi-arid regions compared to no rain and moderate-to-heavy rain cases. This is because light rain does not dramatically reduce solar radiation but increases near-surface humidity through enhanced surface evaporation. The water replenishment from light rain as well as a shallower planetary boundary layer is crucial for consecutive extremes where there are commonly sporadic drizzle days amidst several rain-free days. These extremes last longer than rain-free extremes. Current global climate models (GCMs) overestimate light rain. After reducing this bias in a GCM, underestimations of humid heat waves in energy-limited regions and overestimations in water-limited regions are largely alleviated. These findings underscore the underappreciated impact of light rain on extreme humid heat.

Science & Technology - Other Topics↗

Programmable heating and quenching for efficient thermochemical synthesis

Conventional thermochemical syntheses by continuous heating under near-equilibrium conditions face critical challenges in improving the synthesis rate, selectivity, catalyst stability and energy efficiency, owing to the lack of temporal control over the reaction temperature and time, and thus the reaction pathways. As an alternative, we present a non-equilibrium, continuous synthesis technique that uses pulsed heating and quenching (for example, 0.02 s on, 1.08 s off) using a programmable electric current to rapidly switch the reaction between high (for example, up to 2,400 K) and low temperatures. The rapid quenching ensures high selectivity and good catalyst stability, as well as lowers the average temperature to reduce the energy cost. Using CH4 pyrolysis as a model reaction, our programmable heating and quenching technique leads to high selectivity to value-added C2 products (>75% versus <35% by the conventional non-catalytic method and versus <60% by most conventional methods using optimized catalysts). Our technique can be extended to a range of thermochemical reactions, such as NH 3 synthesis, for which we achieve a stable and high synthesis rate of about 6,000 μmol g Fe –1 h –1 at ambient pressure for >100 h using a non-optimized catalyst. Furthermore, this study establishes a new model towards highly efficient non-equilibrium thermochemical synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

New Opportunities to Study Earthquake Precursors

The topic of earthquake prediction has a long history, littered with failed attempts. Part of the challenge is that possible precursory signals are usually reported after the event, and the systematic relationships between potential precursors and main events, should they exist, are unclear. Furthermore, several recent studies have shown the potential of new approaches to simultaneously detect earthquake foreshocks and slow-slip phenomena through ground deformation, seismic, and gravitational transients—weeks to months before large subduction zone earthquakes. The entire international community of earthquake researchers should be engaged in deploying instrumentation, sharing data in real time, and improving physical models to resolve the extent to which slow slip events and earthquake swarms enhance the likelihood (or not) for later, larger earthquakes.

58 GEOSCIENCES↗

Power Sector Transformation Pathways: Exploring Objectives, Factors, and Technology Innovations to Inform Power Sector Pathway Decisions

The power and heating sectors are responsible for around 30% of global CO2 emissions and this share is likely to grow as countries move towards electrification of the transportation and building sectors. Therefore, enabling forward-thinking, long term strategies in the power sector is a crucial area for international collaboration and support. The rapid transition of power systems toward modern, low-carbon pathways and technologies will be necessary to meet key climate goals while also enabling other critical objectives such as economic development, energy access, and energy system resiliency, among others. Many developed and developing countries are well-poised to champion power sector transformation (PST), however, further support is needed to identify pathways and implement critical near and long-term actions. To address this need, the Low Emission Development Strategies Global Partnership (LEDS GP) together with an expert team including Agora Energiewende, Energy Innovation, European Climate Foundation, Fraunhofer Institute for Systems and Innovation Research , Prayas Energy Group and LEDS Latin America and Caribbean Platform, developed a framework identifying four key pathways that can be integrated and combined to support low-carbon PST. These four pathways are: (1) Distributed Energy Resource Revolution, (2) Bulk Power Transformation, (3) Transmission and Distribution Interactivity, and (4) Distributed Transactional Future. To support exploration of pathways, this study examines PST objectives and factors that may lead countries or jurisdictions to place a greater relative emphasis on certain pathways as well as a framework and complementary tool for considering the emphasis in a hands on manner. The report provides case studies on application of the approach to bring life to the topic. The case studies include Haiti, Kenya, Mexico, Southeast Asia, and the European Union, among others. The report also presents actions to-be-taken in the near-, medium- and long-term to support the realization of pathways and long-term transformation of the power sector. The report, together with a complementary spreadsheet tool developed under the effort, can be used to enable stakeholder engagement and visioning for the power sector over the long-term, taking into account key factors and potential innovations. It can also be used to understand and inform relevant analysis tools and models based on which pathways are emphasized, and to identify key actions in the near- and medium-term to avoid lock-in of carbon-intensive technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Optimizing the Design of Diatom Biosilica-Targeted Fusion Proteins in Biosensor Construction for Bacillus anthracis Detection

In vivo functionalization of diatom biosilica frustules by genetic manipulation requires careful consideration of the overall structure and function of complex fusion proteins. Although we previously had transformed Thalassiosira pseudonana with constructs containing a single domain antibody (sdAb) raised against the Bacillus anthracis Sterne strain, which detected an epitope of the surface layer protein EA1 accessible in lysed spores, we initially were unsuccessful with constructs encoding a similar sdAb that detected an epitope of EA1 accessible in intact spores and vegetative cells. This discrepancy limited the usefulness of the system as an environmental biosensor for B. anthracis. We surmised that to create functional biosilica-localized biosensors with certain constructs, the biosilica targeting and protein trafficking functions of the biosilica-targeting peptide Sil3T8 had to be uncoupled. We found that retaining the ER trafficking sequence at the N-terminus and relocating the Sil3T8 targeting peptide to the C-terminus of the fusion protein resulted in successful detection of EA1 with both sdAbs. Homology modeling of antigen binding by the two sdAbs supported the hypothesis that the rescue of antigen binding in the previously dysfunctional sdAb was due to removal of steric hindrances between the antigen binding loops and the diatom biosilica for that particular sdAb.

59 BASIC BIOLOGICAL SCIENCES↗

Inherent Anharmonicity of Harmonic Solids

Atomic vibrations, in the form of phonons, are foundational in describing the thermal behavior of materials. The possible frequencies of phonons in materials are governed by the complex bonding between atoms, which is physically represented by a spring-mass model that can account for interactions (spring forces) between the atoms (masses). The lowest-order, harmonic , approximation only considers linear forces between atoms and is thought incapable of explaining phenomena like thermal expansion and thermal conductivity, which are attributed to nonlinear, anharmonic , interactions. Here, we show that the kinetic energy of atoms in a solid produces a pressure much like the kinetic energy of atoms in a gas does. This vibrational or phonon pressure naturally increases with temperature, as it does in a gas and therefore results in a thermal expansion. Because thermal expansion thermodynamically defines a Grüneisen parameter γ , which is a typical metric of anharmonicity, we show that even a harmonic solid will necessarily have some anharmonicity. A consequence of this phonon pressure model is a harmonic estimation of the Grüneisen parameter as γ ≈ 3 / 2 3 − 4 x 2 / 1 + 2 x 2 , where x = v t / v l is the ratio of the transverse and longitudinal speeds of sound. We demonstrate the immediate utility of this model by developing a high-throughput harmonic estimate of lattice thermal conductivity that is comparable to other state-of-the-art estimations. By linking harmonic and anharmonic properties explicitly, this study provokes new ideas about the fundamental nature of anharmonicity, while also providing a basis for new material engineering design metrics.

42 ENGINEERING↗

Application of Orthogonal Defect Classification for Software Reliability Analysis

The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify if the software is reliable (or unreliable) while still leveraging the strength of the existing methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Application of Orthogonal Defect Classification for Software Reliability Analysis

The modernization of existing and new nuclear power plants with digital instrumentation and control systems (DI&C) is a recent and highly trending topic. However, there lacks strong consensus on best-estimate reliability methodologies by both the United States (U.S.) Nuclear Regulatory Commission (NRC) and the industry. This has resulted in hesitation for further modernization projects until a more unified methodology is realized. In this work, we develop an approach called Orthogonal-defect Classification for Assessing Software Reliability (ORCAS) to quantify probabilities of various software failure modes in a DI&C system. The method utilizes accepted industry methodologies for software quality assurance that are also verified by experimental or mathematical formulations. In essence, the approach combines a semantic failure classification model with a reliability growth model to predict (and quantify) the potential failure modes of a DI&C software system. The semantic classification model is used to address the question: How do latent defects in software contribute to different software failure root causes? The use of reliability growth models is then used to address the question: Given the connection between latent defects and software failure root causes, how can we quantify the reliability of the software? A case study was conducted on a representative I&C platform (ChibiOS) running a smart sensor acquisition software developed by Virginia Commonwealth University (VCU). The testing and evidence collection guidance in ORCAS was applied, and defects were uncovered in the software. Qualitative evidence, such as condition coverage, was used to gauge the completeness and trustworthiness of the assessment while quantitative evidence was used to determine the software failure probabilities. The reliability of the software was then estimated and compared to existing operational data of the sensor device. It is demonstrated that by using ORCAS, a semantic reasoning framework can be developed to justify software reliability (or unreliability) while still leveraging the strength of the existing methods.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Cooperative Research and Infectious Disease Surveillance: A 2021 Epilogue

As the world looks forward to turning a corner in the face of the COVID-19 pandemic, it becomes increasingly evident that international research cooperation and dialogue is necessary to end this global catastrophe. Last year, we initiated a research topic: “Infectious Disease Surveillance: Cooperative Research in Response to Recent Outbreaks, Including COVID-19,” which aimed at featuring manuscripts focused on the essential link between surveillance and cooperative research for emerging and endemic diseases, and highlighting scientific partnerships in countries under-represented in the scientific literature. Here we recognize the body of work published from our manuscript call that resulted in over 50 published papers. This current analysis describes articles and authors from a variety of funded and unfunded international sources. The work exemplifies successful research and publications which are frequently cooperative, and may serve as a basis to model further global scientific engagements.

60 APPLIED LIFE SCIENCES↗

Exact-Factorization-Based Surface Hopping for Multistate Dynamics

A surface-hopping algorithm recently derived from the exact factorization approach, SHXF, introduces an additional term in the electronic equation of surface hopping that couples electronic states through the quantum momentum. Furthermore, this term not only provides a first-principles description of decoherence, but here we show it is crucial to accurately capture nonadiabatic dynamics when more than two states are occupied at any given time. Using a vibronic coupling model of the uracil cation, we show that the lack of this term in traditional surface-hopping methods, including those with decoherence corrections, leads to failure to predict the dynamics through a three-state intersection, while SHXF performs similarly to the multiconfiguration time-dependent Hartree quantum dynamics benchmark.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Design of intrinsically disordered protein variants with diverse structural properties

Intrinsically disordered proteins (IDPs) perform a broad range of functions in biology, suggesting that the ability to design IDPs could help expand the repertoire of proteins with novel functions. Computational design of IDPs with specific conformational properties has, however, been difficult because of their substantial dynamics and structural complexity. We describe a general algorithm for designing IDPs with specific structural properties. We demonstrate the power of the algorithm by generating variants of naturally occurring IDPs that differ in compaction, long-range contacts, and propensity to phase separate. We experimentally tested and validated our designs and analyzed the sequence features that determine conformations. We show how our results are captured by a machine learning model, enabling us to speed up the algorithm. Our work expands the toolbox for computational protein design and will facilitate the design of proteins whose functions exploit the many properties afforded by protein disorder.

Science & Technology - Other Topics↗

Cooperative Research and Development Agreement among National Energy Technology Laboratory, The Board of Regents of the University System of Georgia by and on behalf of Georgia Institute of Technology, and University of Texas at El Paso [Abstract]

Georgia Institute of Technology (GIT), University of Texas at El Paso (UTEP), and the National Energy Technology Laboratory (NETL) will collaborate and develop cyber-physical systems for advanced power systems. GIT will test virtual models on hybrid power system hardware and cyber physical components. UTEP will test novel actuators on hybrid power system hardware. NETL will access GIT’s expertise in the engineering and real time simulation of power system processes for cyber-physical systems and simulations to control hardware. NETL will establish a relationship to promote UTEP’s capabilities in additive manufacturing and high-temperature piezo-electric devices with the potential for controlling high-temperature flows with a light and inexpensive device at high response rates. This project is the result of an EERE Advanced Manufacturing Office open Multi-Topic awarded proposal led by GIT titled, “Robust Combined Heat and Hybrid Power (CHHP) for High Electrical Efficiency Cogeneration”.

42 ENGINEERING↗

Increased power gains from wake steering control using preview wind direction information

Abstract. Yaw controllers typically rely on measurements taken at the wind turbine, resulting in a slow reaction to wind direction changes and subsequent power losses due to misalignments. Delayed yaw action is especially problematic in wake steering operation because it can result in power losses when the yaw misalignment angle deviates from the intended one due to a changing wind direction. This study explores the use of preview wind direction information for wake steering control in a two-turbine setup with a wind speed in the partial load range. For these conditions and a simple yaw controller, results from an engineering model identify an optimum preview time of 90 s. These results are validated by forcing wind direction changes in a large-eddy simulation model. For a set of six simulations with large wind direction changes, the average power gain from wake steering increases from only 0.44 % to 1.32 %. For a second set of six simulations with smaller wind direction changes, the average power gain from wake steering increases from 1.24 % to 1.85 %. Low-frequency fluctuations are shown to have a larger impact on the performance of wake steering and the effectiveness of preview control, in particular, than high-frequency fluctuations. From these results, it is concluded that the benefit of preview wind direction control for wake steering is substantial, making it a topic worth pursuing in future work.

17 WIND ENERGY↗

Simulation and Development of the Radial Time Projection Chamber For the Bonus12 Experiment in CLAS12

Knowledge of the structure of nucleons (i.e. protons and neutrons) is a central topic of interest to nuclear/particle physicists. Much more is known about the structure of the proton than the neutron due to the lack of high-density free neutron targets. The Barely Off-shell Nucleon Structure experiment (BONuS12) at Jefferson Lab (JLab) is a second generation experiment upgraded/optimized to advance our knowledge of the neutron's structure using the deep-inelastic scattering of electrons off deuterium. Typically, since deuterium is a nuclear target, corrections for off-shell and nuclear binding effects must be taken into account in order to extract results on the neutron. These corrections are model-dependent and therefore have limited our success in extracting neutron information using deuterium targets. In the BONuS12 experiment, 10.6 GeV electrons are scattered off of a deuterium target. By detecting the low momentum spectator proton at backward angles, the uncertainty due to final state interactions is minimized. The goal of the experiment is to measure the ratio of the neutron to proton structure functions ($F^n_2/F^p_2$) as the Bjroken scaling variable x approaches 1. The newly designed Radial Time Projection Chamber (RTPC) for BONuS12 detects the spectator proton in coincidence with the scattered electron, which is detected in the CEBAF Large Acceptance Spectrometer (CLAS12). This work presents the simulation and development of the new BONuS12 RTPC. The design, construction, and testing of the Drift-gas Monitoring Sysytem (DMS) for the BONuS12 experiment is also described. The results of the DMS operation as well as the first preliminary data from the BONuS12 experimental run are given. Because the BONuS12 data analysis depends on CLAS12 working effectively, an effort to verify the CLAS12 operation with the extraction of the inclusive deep inelastic cross section from the first experiment in CLAS12 (Run Group A) will be presented.

Dzbenski, Nathan↗

Full-waveform tomography reveals iron spin crossover in Earth’s lower mantle

Abstract Three-dimensional models of Earth’s seismic structure can be used to identify temperature-dependent phenomena, including mineralogical phase and spin transformations, that are obscured in 1-D spherical averages. Full-waveform tomography maps seismic wave-speeds inside the Earth in three dimensions, at a higher resolution than classical methods. By providing absolute wave speeds (rather than perturbations) and simultaneously constraining bulk and shear wave speeds over the same frequency range, it becomes feasible to distinguish variations in temperature from changes in composition or spin state. We present a quantitative joint interpretation of bulk and shear wave speeds in the lower mantle, using a recently published full-waveform tomography model. At all depths the diversity of wave speeds cannot be explained by an isochemical mantle. Between 1000 and 2500 km depth, hypothetical mantle models containing an electronic spin crossover in ferropericlase provide a significantly better fit to the wave-speed distributions, as well as more realistic temperatures and silica contents, than models without a spin crossover. Below 2500 km, wave speed distributions are explained by an enrichment in silica towards the core-mantle boundary. This silica enrichment may represent the fractionated remains of an ancient basal magma ocean.

58 GEOSCIENCES↗