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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 577 records · Page 32

Effect of fluorination and Li-excess on the Li migration barrier in Mn-based cathode materials

Disordered rocksalt (DRX) Li-rich transition metal (TM) oxides, especially those based on Mn, are prospective high-energy-density cathode materials for the next generation of Li-ion batteries that use earth abundant metals. Fluorine substitution on the oxygen sublattice has been shown to reduce oxygen redox by lowering the average anion valence and increasing the amount of redox-active TM, and simultaneously improve energy density, average voltage and capacity retention. While these benefits of fluorination are well established, it is not well understood how F affects Li transport and therefore the rate performance of Mn-based DRX cathodes. Herein, we investigate the effects of both F substitution and the accompanying Li-excess on Li migration barriers using first-principles calculations. Finally, we demonstrate that F has a small negative effect on Li migration barriers while Li-excess decreases Li migration barriers. Because fluorination enables more Li-excess, these results do not predict any detrimental impact on Li transport.

25 ENERGY STORAGE↗

Physics-informed KNN milling stability model with process damping effects

This paper describes a k-nearest neighbors, or KNN, model for milling stability including process damping effects. A physics-based, frequency domain milling stability solution is used to generate the training data, but does not incorporate process damping effects. The data set is then updated using limited tests to capture the process damping behavior. A “stair step” approach is used to select the test points, where a first spindle speed-axial depth combination is selected based on the physics-based stability map, subsequent tests are defined using the previous test result, and data points are updated by knowledge of process damping behavior and the test results. Furthermore, the KNN modeling approach demonstrates the ability to predict both stable and unstable results, including process damping behavior.

42 ENGINEERING↗

CoREC: Scalable and Resilient In-memory Data Staging for In-situ Workflows

The dramatic increase in the scale of current and planned high-end HPC systems is leading new challenges, such as the growing costs of data movement and IO, and the reduced mean time between failures (MTBF) of system components. In-situ workflows, i.e., executing the entire application workflows on the HPC system, have emerged as an attractive approach to address data-related challenges by moving computations closer to the data, and staging-based frameworks have been effectively used to support in-situ workflows at scale. However, the resilience of these staging-based solutions has not been addressed, and they remain susceptible to expensive data failures. Furthermore, naive use of data resilience techniques such as n-way replication and erasure codes can impact latency and/or result in significant storage overheads. In this article, we present CoREC, a scalable and resilient in-memory data staging runtime for large-scale in-situ workflows. CoREC uses a novel hybrid approach that combines dynamic replication with erasure coding based on data access patterns. It also leverages multiple levels of replications and erasure coding to support diverse data resiliency requirements. Furthermore, the article presents optimizations for load balancing and conflict-avoiding encoding, and a low overhead, lazy data recovery scheme. We have implemented the CoREC runtime and have deployed with the DataSpaces staging service on leadership class computing machines and present an experimental evaluation in the article. Here, the experiments demonstrate that CoREC can tolerate in-memory data failures while maintaining low latency and sustaining high overall storage efficiency at large scales.

97 MATHEMATICS AND COMPUTING↗

Real time lithium metal calendar aging in common battery electrolytes

Li metal anodes are highly sought after for high energy density applications in both primary commercial batteries and next-generation rechargeable batteries. In this research, Li metal electrodes are aged in coin cells for a year with electrolytes relevant to both types of batteries. The aging response is monitored via electrochemical impedance spectroscopy, and Li electrodes are characterized post-mortem. It was found that the carbonate-based electrolytes exhibit the most severe aging effects, despite the use of LiBF 4 -based carbonate electrolytes in Li/CF x Li primary batteries. Highly concentrated LiFSI electrolytes exhibit the most minimal aging effects, with only a small impedance increase with time. This is likely due to the concentrated nature of the electrolyte causing fewer solvent molecules available to react with the electrode surface. LiI-based electrolytes also show improved aging behavior both on their own and as an additive, with a similar impedance response with time as the concentrated LiFSI electrolytes. Since I − is in its most reduced state, it likely prevents further reaction and may help protect the Li electrode surface with a primarily organic solid electrolyte interphase.

25 ENERGY STORAGE↗

Quantum computing based hybrid deep learning for fault diagnosis in electrical power systems

Quantum computing (QC) and deep learning have shown promise of supporting transformative advances and have recently gained popularity in a wide range of areas. Here, this paper proposes a hybrid QC-based deep learning framework for fault diagnosis of electrical power systems that combine the feature extraction capabilities of conditional restricted Boltzmann machine with an efficient classification of deep networks. Computational challenges stemming from the complexities of such deep learning models are overcome by QC-based training methodologies that effectively leverage the complementary strengths of quantum assisted learning and classical training techniques. The proposed hybrid QC-based deep learning framework is tested on a simulated electrical power system with 30 buses and wide variations of substation and transmission line faults, to demonstrate the framework’s applicability, efficiency, and generalization capabilities. High computational efficiency is enjoyed by the proposed hybrid approach in terms of computational effort required and quality of diagnosis performance over classical training methods. In addition, superior and reliable fault diagnosis performance with faster response time is achieved over state-of-the-art pattern recognition methods based on artificial neural networks (ANN) and decision trees (DT).

42 ENGINEERING↗

Combination therapy with lenvatinib and radiation significantly inhibits thyroid cancer growth by uptake of tyrosine kinase inhibitor

Highlights: • Lenvatinib combined with radiation significantly inhibits thyroid cancer growth. • Combined therapy induced apoptosis and G2/M phase cell cycle arrest. • Irradiation increased cellular uptake of lenvatinib into cancer cells. • Combined therapy suggests a new therapeutic strategy for advanced thyroid cancer. Although surgical treatment cures >90% of differentiated thyroid cancer (DTC) patients, the remaining patients, including advanced DTC cases, have poor clinical outcomes. These patients with inoperable disease have only two choices of radioactive iodine therapy and tyrosine kinase inhibitors such as lenvatinib, which have a high incidence of treatment-related adverse events and can only prolong progression free survival by approximately 5–15 months. In this study, we investigated the antitumor effects of combination therapy with lenvatinib and radiation (CTLR) for DTC. CTLR synergistically inhibited cell replication and colony formation in vitro and tumor growth in nude mice without apparent toxicities and suppressed the expression of proliferation marker (Ki-67). CTLR also induced apoptosis and G2/M phase cell cycle arrest. Moreover, quantitative analysis of the intracellular uptake of lenvatinib using liquid chromatography and mass spectrometry demonstrated that intracellular uptake of lenvatinib was significantly increased 48 h following irradiation. These data suggest that increased membrane permeability caused by irradiation increases the intracellular concentration of levatinib, contributing to the synergistic effect. This mechanism-based potential of combination therapy suggests a powerful new therapeutic strategy for advanced thyroid cancer with fewer side effects and might be a milestone for developing a regimen in clinical practice.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Evaluating efficacy of indoor non-pharmaceutical interventions against COVID-19 outbreaks with a coupled spatial-SIR agent-based simulation framework

Contagious respiratory diseases, such as COVID-19, depend on sufficiently prolonged exposures for the successful transmission of the underlying pathogen. It is important that organizations evaluate the efficacy of non-pharmaceutical interventions aimed at mitigating viral transmission among their personnel. We have developed a operational risk assessment simulation framework that couples a spatial agent-based model of movement with an agent-based SIR model to assess the relative risks of different intervention strategies. By applying our model on MIT’s Stata center, we assess the impacts of three possible dimensions of intervention: one-way vs unrestricted movement, population size allowed onsite, and frequency of leaving designated work location for breaks. We find that there is no significant impact made by one-way movement restrictions over unrestricted movement. Instead, we find that reducing the frequency at which individuals leave their workstations combined with lowering the number of individuals admitted below the current recommendations lowers the likelihood of highly connected individuals within the contact networks that emerge, which in turn lowers the overall risk of infection. We discover three classes of possible interventions based on their epidemiological effects. By assuming a direct relationship between data on secondary attack rates and transmissibility in the agent-based SIR model, we compare relative infection risk of four respiratory illnesses, MERS, SARS, COVID-19, and Measles, within the simulated area, and recommend appropriate intervention guidelines.

60 APPLIED LIFE SCIENCES↗

Resting time effect on the rheological behavior of cement paste in presence of superplasticizer

Rheology has been widely used to describe the flow properties of fresh cement-based suspensions. Nevertheless, the effect of early hydration product formation on rheology, and the effect of shear on breaking of hydration bonds is not fully understood. Therefore, the characterization of the time-dependency of rheology has become necessary to predict precisely the behavior of concrete during placement. In this paper, variations in the resting time in between rheological tests were imposed to evaluate the effects on the development of internal structure of the mixture using different dispersing agents. Increasing resting time in between measurements mainly enhances viscosity, but the magnitude seems strongly dependent on the dispersant used. However, the effect of the employed procedure, as two procedures were evaluated, seems to have a stronger influence on the time-evolution of the rheological properties than changing the resting time in between measurements.

36 MATERIALS SCIENCE↗

Effectiveness-weighted control of cooling system components

Energy efficient control of cooling system cooling of an electronic system is provided based, in part, on weighted cooling effectiveness of the components. The control includes automatically determining speed control settings for multiple adjustable cooling components of the cooling system. The automatically determining is based, at least in part, on weighted cooling effectiveness of the components of the cooling system, and the determining operates to limit power consumption of at least the cooling system, while ensuring that a target temperature associated with at least one of the cooling system or the electronic system is within a desired range by provisioning, based on the weighted cooling effectiveness, a desired target temperature change among the multiple adjustable cooling components of the cooling system. The provisioning includes provisioning applied power to the multiple adjustable cooling components via, at least in part, the determined control settings.

42 ENGINEERING↗

Effectiveness-weighted control of cooling system components

Energy efficient control of cooling system cooling of an electronic system is provided based, in part, on weighted cooling effectiveness of the components. The control includes automatically determining speed control settings for multiple adjustable cooling components of the cooling system. The automatically determining is based, at least in part, on weighted cooling effectiveness of the components of the cooling system, and the determining operates to limit power consumption of at least the cooling system, while ensuring that a target temperature associated with at least one of the cooling system or the electronic system is within a desired range by provisioning, based on the weighted cooling effectiveness, a desired target temperature change among the multiple adjustable cooling components of the cooling system. The provisioning includes provisioning applied power to the multiple adjustable cooling components via, at least in part, the determined control settings.

Campbell, Levi A.↗

Model-based approach to investigate equipment-induced error in pressure-waveform derived hemodynamic measurements

Advanced hemodynamic monitoring systems have provided less invasive methods for estimating pressure-derived measurements such as pressure-derived cardiac output (CO) measurements. These devices apply algorithms to arterial pressure waveforms recorded via pressure recording components that transmit the pressure signal to a pressure monitor. While standards have been developed for pressure monitoring equipment, it is unclear how the equipment-induced error can affect secondary measurements from pressure waveforms. We propose an approach for modelling different components of a pressure monitoring system and use this model-based approach to investigate the effect of different pressure recording configurations on pressure-derived hemodynamic measurements. The proposed model-based approach is a three-step process. (1) Modelling the response of pressure recording components using bench tests; (2) verifying the identified models through nonparametric equivalence tests; and (3) assessing the effects of pressure recording components on pressure-derived measurements. To delineate the application of this approach, we performed a series of model-based analyses to quantify the combined effect of a wide range of tubing configurations with various damping ratios and natural frequencies and monitors with different bandwidths on pressure waveforms and CO measurements by six pulse contour algorithms. Model-based results show the error in pressure-derived CO measurements because of tubing configurations with different natural frequencies and damping ratios. Tubing configurations with low natural frequencies (<23 Hz) altered characteristics of pressure waveforms in a way that affected the CO measurement, some by as much as 20%. Our method can serve as a tool to quantify the performance of pressure recording systems with different dynamic properties. In conclusion, this approach can be applied to investigate the effects of physiologic signal recording configurations on various pressure-derived hemodynamic measurements.

42 ENGINEERING↗

A model for discrete fracture-clay rock interaction incorporating electrostatic effects on transport

Abstract A model based on the code CrunchClay is presented for a fracture-clay matrix system that takes electrostatic effects on transport into account. The electrostatic effects on transport include those associated with the development of a diffusion potential as captured by the Nernst-Planck equation, and the formation of a diffuse layer bordering negatively charged clay particles within which partial anion exclusion occurs. The model is based on a dual continuum formulation that accounts for diffuse layer and bulk water pore space, providing a more flexible framework than is found in the classical mean electrostatic potential models. The diffuse layer model is obtained by volume averaging ion concentrations in the Poisson-Boltzmann equation, but also includes the treatment of longitudinal transport within this continuum. The calculation of transport within the bulk and diffuse layer porosity is based on a new formulation for the Nernst-Planck equation that considers averaging of diffusion coefficients and accumulation factors at grid cell interfaces. Equations for function residuals and the associated Jacobian matrix are presented such that the system of nonlinear differential-algebraic equations can be solved with Newton’s method. As an example, we consider a 2D system with a single discrete fracture within which flow and advective transport occurs that is coupled to diffusion in the clay-rich matrix. The simulation results demonstrate the lack of retardation for anions (e.g., 36 Cl − ) of the contaminant plume within the fracture flow system because they are largely excluded from the charged clay rock, while the migration of cations (e.g., 90 Sr ++ ) is more strongly attenuated. The diffusive loss of divalent cations in particular from the fracture is accentuated by their accumulation in the diffuse layer within the clay-rich matrix.

58 GEOSCIENCES↗

Effect of annealing on the tribological behavior of Zr-based bulk metallic glass

Bulk Metallic Glasses (BMGs) are promising materials for several applications owing to their high elastic limit and resistance to permanent deformation. However, BMGs have lower wear resistance than their crystalline counterparts during dry sliding. The formation of a composite material with crystalline phases dispersed in the BMG matrix through devitrification and partial crystallization at elevated temperatures has recently been proposed as an effective way to improve the wear resistance. However, our understanding of the origin of the improved wear behavior of annealed BMGs is still elusive. Here, a systematic evaluation of the effect of annealing temperature (from temperatures lower than the BMG glass transition temperature to temperatures higher than the BMG recrystallization temperature) on the friction and wear response of a Zr-based BMG, namely Vit105 (Zr 52.5 Cu 17.9 Ni 14.6 Al 10 Ti 5 ), was performed. The results indicate that annealing Vit105 improves its wear resistance while also reducing the steady-state friction response when the annealing temperature is close to the glass transition temperature. Notably, the formation of a transfer film on the sapphire countersurface is highly dependent on the applied normal load and sliding time. Finally, the wear mechanism was found to be strongly dependent on the annealing temperature as a transition from a predominantly adhesive wear mechanism to an abrasive-dominated one was observed as the annealing temperature crossed the glass transition temperature. Altogether, the results of this work aid to our understanding of the tribological behavior of Zr-based BMGs in general, while also providing clues to strategies for the effective use of BMGs in tribological applications.

Lien, Hsu-Ming [Univ. of Texas, Austin, TX (United↗

Driver Distraction Behavior Detection using a Vision Transformer Model based on Transfer Learning Strategy

Driver distraction behavior is one of the critical factors in traffic accidents. Thus, advanced driver state detection system has become the focus in the field of intelligent vehicle. However, in practical applications, insufficient samples of driving distraction behaviors bring great challenges to training a personalized behavior distraction detection model for a specific driver. To this end, a novel transformer model based on a transfer learning strategy is proposed in this paper to accurately recognize driver distraction behavior. Inspired by the effect of the transformer network in visual recognition, we firstly present a transformer behavior distraction detection system to identify the behavior categories that cause driver distraction. Then, for the specific driving dataset in practical application scenarios, the transfer learning strategy is introduced into the driver distraction detection model to further train the general transformer network. The effectiveness of the transformer based on the transfer learning strategy is validated compared with other traditional deep learning methods. The results show that the proposed detection method has better generalization ability and higher accuracy.

Fang, Zhenwu↗

Composing preconditioners for multiphysics PDE systems with applications to Generalized MHD

New patch smoothers or relaxation techniques are developed for solving linear matrix equations coming from systems of discretized partial differential equations (PDEs). One key linear solver challenge for many PDE systems arises when the resulting discretization matrix has a near null space that has a large dimension, which can occur in generalized magnetohydrodynamic (GMHD) systems. Patch-based relaxation is highly effective for problems when the null space can be spanned by a basis of locally supported vectors. The patch-based relaxation methods that we develop can be used either within an algebraic multigrid (AMG) hierarchy or as stand-alone preconditioners. These patch-based relaxation techniques are a form of well-known overlapping Schwarz methods where the computational domain is covered with a series of overlapping sub-domains (or patches). Patch relaxation then corresponds to solving a set of independent linear systems associated with each patch. In the context of GMHD, we also reformulate the underlying discrete representation used to generate a suitable set of matrix equations. In general, deriving a discretization that accurately approximates the curl operator and the Hall term while also producing linear systems with physically meaningful near null space properties can be challenging. Unfortunately, many natural discretization choices lead to a near null space that includes non-physical oscillatory modes and where it is not possible to span the near null space with a minimal set of locally supported basis vectors. Further discretization research is needed to understand the resulting trade-offs between accuracy, stability, and ease in solving the associated linear systems.

97 MATHEMATICS AND COMPUTING↗

X-ray Multilayers for Next-Generation Astrophysics Missions

In this work, we proposed to demonstrate the feasibility of high-reflectivity multilayer coatings that will enable next-generation astrophysics missions in the x-ray region (2 – 7 nm wavelengths) where currently high-performance coatings largely do not exist. This paucity is due to multilayer interfacial effects that severely reduce the coating reflectance; our approach was based on understanding these interfacial effects and on tailored process modifications to control and minimize them. The experimental validation of our approach was made difficult by our multilayer deposition tool being down for a large portion of the project. The required repairs used significant amount of funding and time, which forced to reduce the scope of the project. Our experimental study focused on Cr/C multilayers and their optimization using N2 reactive sputtering. We showed that the highest reflectance was achieved when depositing the multilayers with 35% N2, and with a larger Cr thickness ratio than what was initially predicted by simulations. This result consists of a 13% relative increase in reflectivity compared to our previous work. It will benefit upcoming NASA proposals and LLNL’s leadership in this area, as well as topics highly relevant to LLNL/DOE’s priority areas, such as x-ray laser science and semiconductor manufacturing. This work will be further investigated as part of a Laboratory Directed Research and Development (LDRD) Exploratory Research (ER) project starting in Fiscal Year (FY) 2024.

36 MATERIALS SCIENCE↗

Salt Hydrate Eutectic Mixtures for Near-ambient Thermal Energy Storage Applications

In this work, we synthesized and characterized Na2SO4.10H2O – Na2CO3.10H2O eutectic salt hydrate phase change material (PCM) using Differential Scanning Calorimetry (DSC), Attenuated total reflectance infrared spectroscopy (ATR-IR), and X-ray Diffraction (XRD) techniques. The eutectic point of the PCM mixture was predicted based on binary eutectic effect and ion exchange theory. The XRD and ATR-IR results indicate that the eutectic PCM mixture was formed based on only physical mixing without chemical interaction. Moreover, DSC results showed that the eutectic concentration is 50wt% Na2SO4.10H2O – 50wt% Na2CO3.10H2O with melting temperature of 25.18°C and melting enthalpy of 187.46 J/g. Also, 78% of melting enthalpy was recoverable after 10 melt/freeze cycles. This eutectic mixture has the potential to be used in building thermal comfort applications.

Gluesenkamp, Kyle↗

Effect of inlet throttling on thermohydraulic instability in a large scale water-based RCCS: An experimental study

The objective of the present experimental study is to investigate the effect of inlet throttling on the thermohydraulic stability of a large scale water-based Reactor Cavity Cooling System (RCCS). The test was performed using the water-based Natural convection Shutdown heat removal Test Facility (NSTF) at Argonne, which represented a ½ axial scale and 12.5° sector slice of the full scale Framatome 625 MW t SC-HTGR RCCS concept. A two-phase steady state was first established through direct condensate refill, followed by increased inlet throttling over 10 stages, corresponding to a loss coefficient K over the range of 0.05–653. With the inlet throttling gradually increased, the system experienced a unique transition process between stabilization and destabilization. Through a stability analysis, three instability mechanisms were identified in the present test, including a compound mechanism due to both natural circulation oscillations (NCOs) and density wave oscillations (DWOs), Type-II DWOs, and geysering.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗