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At least 973 records · Page 54

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations. To make advancements in all the aforementioned scientific areas, many technical aspects need to be more thoroughly studied and deeply understood in parallel discrete event simulation (PDES). The unique dynamics inherent in a discrete event modeling approach, by their very nature, intersect and influence the entire stack of the computing system, including (a) the unique nature of the instruction sets exercised in PDES workloads without a predominance of high-precision floating point operations, (b) virtual time-constrained multi-threaded execution of many logical processes per processor, (c) extremely variable and difficult to predict network traffic characteristics, (d) interfaces and inter-dependencies with machine learning and artificial intelligence codes at higher software layers, and (e) highly challenging load balancing needs, especially in effectively accounting for accelerated/extremely heterogeneous computing in current and future high-performance computing systems. Efficient and accurate parallel execution of PDES workloads is also dominated by challenges in dealing with their asynchronous concurrency fundamentally present at the model level. Conservative synchronization, optimistic/speculative synchronization, and their hybrid schemes open new questions in fundamental computer science with respect to reversibility of computation and prediction (lookahead) of behaviors inherent within model codes. On the implementation front, there are relatively few scalable, general-purpose parallel discrete event simulators in the world, and even fewer have been studied on emerging hardware platforms. To enable scientific advances using PDES, the research needs in computer science must also be pursued and met in the intersection of the algorithmic and hardware-aware aspects of scalable PDES engines. This report is aimed at capturing a computer science-oriented view of this important area of research in PDES, presenting a sample of important applications with their inherent discrete event technology elements. Needs are outlined in core areas of parallel discrete event research as well as cross-cutting directions in computer science research that positively impact scientific advancements across several important application areas. A selection of priority research opportunities in advanced computing for PDES is identified to serve as reference for key research topics and their order of importance for scientific advancements.

97 MATHEMATICS AND COMPUTING↗

BioSIGHT: Interactive Visualization Modules for Science Education

Redefining science education to harness emerging integrated media technologies with innovative pedagogical goals represents a unique challenge. The Integrated Media Systems Center (IMSC) is the only engineering research center in the area of multimedia and creative technologies sponsored by the National Science Foundation. The research program at IMSC is focused on developing advanced technologies that address human-computer interfaces, database management, and high-speed network capabilities. The BioSIGHT project at is a demonstration technology project in the area of education that seeks to address how such emerging multimedia technologies can make an impact on science education. The scope of this project will help solidify NASA's commitment for the development of innovative educational resources that promotes science literacy for our students and the general population as well. These issues must be addressed as NASA marches toward the goal of enabling human space exploration that requires an understanding of life sciences in space. The IMSC BioSIGHT lab was established with the purpose of developing a novel methodology that will map a high school biology curriculum into a series of interactive visualization modules that can be easily incorporated into a space biology curriculum. Fundamental concepts in general biology must be mastered in order to allow a better understanding and application for space biology. Interactive visualization is a powerful component that can capture the students' imagination, facilitate their assimilation of complex ideas, and help them develop integrated views of biology. These modules will augment the role of the teacher and will establish the value of student-centered interactivity, both in an individual setting as well as in a collaborative learning environment. Students will be able to interact with the content material, explore new challenges, and perform virtual laboratory simulations. The BioSIGHT effort is truly cross-disciplinary in nature and requires expertise from many areas including Biology, Computer Science Electrical Engineering, Education, and the Cognitive Sciences. The BioSIGHT team includes a scientific illustrator, educational software designer, computer programmers as well as IMSC graduate and undergraduate students.

Wong, Wee Ling↗

BioSIGHT: Interactive Visualization Modules for Science Education

Redefining science education to harness emerging integrated media technologies with innovative pedagogical goals represents a unique challenge. The Integrated Media Systems Center (IMSC) is the only engineering research center in the area of multimedia and creative technologies sponsored by the National Science Foundation. The research program at IMSC is focused on developing advanced technologies that address human-computer interfaces, database management, and high- speed network capabilities. The BioSIGHT project at IMSC is a demonstration technology project in the area of education that seeks to address how such emerging multimedia technologies can make an impact on science education. The scope of this project will help solidify NASA's commitment for the development of innovative educational resources that promotes science literacy for our students and the general population as well. These issues must be addressed as NASA marches towards the goal of enabling human space exploration that requires an understanding of life sciences in space. The IMSC BioSIGHT lab was established with the purpose of developing a novel methodology that will map a high school biology curriculum into a series of interactive visualization modules that can be easily incorporated into a space biology curriculum. Fundamental concepts in general biology must be mastered in order to allow a better understanding and application for space biology. Interactive visualization is a powerful component that can capture the students' imagination, facilitate their assimilation of complex ideas, and help them develop integrated views of biology. These modules will augment the role of the teacher and will establish the value of student-centered interactivity, both in an individual setting as well as in a collaborative learning environment. Students will be able to interact with the content material, explore new challenges, and perform virtual laboratory simulations. The BioSIGHT effort is truly cross-disciplinary in nature and requires expertise from many areas including Biology, Computer Science, Electrical Engineering, Education, and the Cognitive Sciences. The BioSIGHT team includes a scientific illustrator, educational software designer, computer programmers as well as IMSC graduate and undergraduate students. Our collaborators include TERC, a research and education organization with extensive k-12 math and science curricula development from Cambridge, MA.; SRI International of Menlo Park, CA.; teachers and students from local area high schools (Newbury Park High School, USC's Family of Five schools, Chadwick School, and Pasadena Polytechnic High School).

Wong, Wee Ling↗

Porous Media Approach for Modeling Closed Cell Foam

In order to minimize boil off of the liquid oxygen and liquid hydrogen and to prevent the formation of ice on its exterior surface, the Space Shuttle External Tank (ET) is insulated using various low-density, closed-cell polymeric foams. Improved analysis methods for these foam materials are needed to predict the foam structural response and to help identify the foam fracture behavior in order to help minimize foam shedding occurrences. This presentation describes a continuum based approach to modeling the foam thermo-mechanical behavior that accounts for the cellular nature of the material and explicitly addresses the effect of the internal cell gas pressure. A porous media approach is implemented in a finite element frame work to model the mechanical behavior of the closed cell foam. The ABAQUS general purpose finite element program is used to simulate the continuum behavior of the foam. The soil mechanics element is implemented to account for the cell internal pressure and its effect on the stress and strain fields. The pressure variation inside the closed cells is calculated using the ideal gas laws. The soil mechanics element is compatible with an orthotropic materials model to capture the different behavior between the rise and in-plane directions of the foam. The porous media approach is applied to model the foam thermal strain and calculate the foam effective coefficient of thermal expansion. The calculated foam coefficients of thermal expansion were able to simulate the measured thermal strain during heat up from cryogenic temperature to room temperature in vacuum. The porous media approach was applied to an insulated substrate with one inch foam and compared to a simple elastic solution without pore pressure. The porous media approach is also applied to model the foam mechanical behavior during subscale laboratory experiments. In this test, a foam layer sprayed on a metal substrate is subjected to a temperature variation while the metal substrate is stretched to simulate the structural response of the tank during operation. The thermal expansion mismatch between the foam and the metal substrate and the thermal gradient in the foam layer causes high tensile stresses near the metal/foam interface that can lead to delamination.

Ghosn, Louis J.↗

Feedstock-Conversion Interface Consortium: Failure Mode and Effects Analysis Summary Report (FY2022)

This report provides an overview of the development of failure modes and effects analysis (FMEA) and its implementation as a systematic criticality and risk assessment tool supporting a quality by design (QbD) approach for FCIC research. This report also provides a high-level overview of the results for the FMEA evaluation of two feedstock preprocessing system configurations: (1) generation of pine residue materials for high-temperature pyrolysis conversion and (2) generation of corn stover materials for low-temperature conversion using deacetylation and disc mechanical refining pretreatment for fermentation to hydrocarbons. For the results presented in this report, our FMEA interviews included two approaches. The first approach was to perform FMEA interviews for the entire system of unit operations giving a wholistic system level view. The second approach consisted of detailed interviews for each individual unit operation within the system allowing for a “deep dive” into the specific failures for the individual components within the configuration. These two approaches provide different resolutions of information. The FMEA results of this report were focused on failures associated with meeting critical quality attributes (CQAs) identified for the target conversion processes for each processed feedstock type. The information gathered through the FMEA interviews include estimations of risk scores for meeting each given CQA specification, identification of the impacts for not meeting a CQA specification, capturing causes associated with material attributes and process parameters for each failure, identification of current detection methods, and speculation of potential mitigation strategies for decreasing a failure’s risk score. The complete results of all FMEA interviews are provided in the Appendices of this report.

09 BIOMASS FUELS↗

Advancing representations of equity and justice in climate mitigation futures

THIS PAPER WAS PRIMARILY COMPLETED PRIOR TO THE AUTHOR JOINING PNNL AND NO DOE FUNDING WAS USED FOR THIS PAPER. In this work, we review how equity and justice issues in global climate mitigation scenarios are addressed within Integrated Assessment Models (IAMs) and propose a new research agenda to strengthen their integration in model development and application. We begin by examining prominent concerns at the science-policy interface. We introduce a typology of equity and justice limitations in climate mitigation scenarios, distinguishing among structural, methodological, and epistemological biases that shape what integrated assessment models can reveal at policy-relevant scales. Reflecting on these concerns, we propose a research agenda that describes new avenues of work and draws together distinct emerging initiatives. This agenda is based on the feasibility and depth of required interventions, from incremental improvements to structural reforms and alternative participatory approaches. Drawing on reflexive insights from integrated assessment practitioners, it addresses the operational challenges of translating justice concepts into metrics, including risks of reductionism, tokenism, and narrow definitions. Underlying this research agenda is a recognition that modeling communities must engage more critically with implicit assumptions in model design and use that have equity and justice implications. Achieving equitable climate futures will require transformative actions that integrate diverse justice concerns, advance sustainable development goals, and confront systemic inequities across both human and ecological dimensions. Although models will never capture all these aspects, they can be significantly enhanced to support more informed discussion and practical application. Our contribution proposes a way forward to achieving this goal.

Pachauri, Shonali↗

Software and Algorithms for Biomedical Image Data Processing and Visualization

A new software equipped with novel image processing algorithms and graphical-user-interface (GUI) tools has been designed for automated analysis and processing of large amounts of biomedical image data. The software, called PlaqTrak, has been specifically used for analysis of plaque on teeth of patients. New algorithms have been developed and implemented to segment teeth of interest from surrounding gum, and a real-time image-based morphing procedure is used to automatically overlay a grid onto each segmented tooth. Pattern recognition methods are used to classify plaque from surrounding gum and enamel, while ignoring glare effects due to the reflection of camera light and ambient light from enamel regions. The PlaqTrak system integrates these components into a single software suite with an easy-to-use GUI (see Figure 1) that allows users to do an end-to-end run of a patient s record, including tooth segmentation of all teeth, grid morphing of each segmented tooth, and plaque classification of each tooth image. The automated and accurate processing of the captured images to segment each tooth [see Figure 2(a)] and then detect plaque on a tooth-by-tooth basis is a critical component of the PlaqTrak system to do clinical trials and analysis with minimal human intervention. These features offer distinct advantages over other competing systems that analyze groups of teeth or synthetic teeth. PlaqTrak divides each segmented tooth into eight regions using an advanced graphics morphing procedure [see results on a chipped tooth in Figure 2(b)], and a pattern recognition classifier is then used to locate plaque [red regions in Figure 2(d)] and enamel regions. The morphing allows analysis within regions of teeth, thereby facilitating detailed statistical analysis such as the amount of plaque present on the biting surfaces on teeth. This software system is applicable to a host of biomedical applications, such as cell analysis and life detection, or robotic applications, such as product inspection or assembly of parts in space and industry.

Talukder, Ashit↗

Playbook Data Analysis Tool: Collecting Interaction Data from Extremely Remote Users

Typically, user tests for software tools are conducted in person. At NASA, the users may be located at the bottom of the ocean in a pressurized habitat, above the atmosphere in the International Space Station, or in an isolated capsule on a simulated asteroid mission. The Playbook Data Analysis Tool (P-DAT) is a human-computer interaction (HCI) evaluation tool that the NASA Ames HCI Group has developed to record user interactions with Playbook, the group's existing planning-and-execution software application. Once the remotely collected user interaction data makes its way back to Earth, researchers can use P-DAT for in-depth analysis. Since a critical component of the Playbook project is to understand how to develop more intuitive software tools for astronauts to plan in space, P-DAT helps guide us in the development of additional easy-to-use features for Playbook, informing the design of future crew autonomy tools.P-DAT has demonstrated the capability of discreetly capturing usability data in amanner that is transparent to Playbook’s end-users. In our experience, P-DAT data hasalready shown its utility, revealing potential usability patterns, helping diagnose softwarebugs, and identifying metrics and events that are pertinent to Playbook usage aswell as spaceflight operations. As we continue to develop this analysis tool, P-DATmay yet provide a method for long-duration, unobtrusive human performance collectionand evaluation for mission controllers back on Earth and researchers investigatingthe effects and mitigations related to future human spaceflight performance.

in-flight monitoring↗

Temperature Effects on Interdiffusion of Al and U-Mo under Irradiation

A high-energy Xe ion irradiation experiment was conducted to investigate the temperature dependence of interdiffusion in bilayer Al-UMo samples under irradiation. The amount of interdiffusion achieved at a fixed dose with the increase of temperature showed a clear transition at 175 degrees C (with an estimated error in the range of ± 10 degrees C) from temperature-independent to temperature-dependent behavior. The activation energy derived from the curve of interdiffusion quantity vs. irradiation temperature is 0.77 ± 0.16 eV. This information has been utilized to understand the temperature effect on the interdiffusion process that occurred at the interfaces of U-Mo particles and the Al matrix in U-Mo/Al dispersion fuels, whose magnitude significantly impacts the fuel's performance. Although this temperature effect was deemed important, it cannot be examined directly using in-pile irradiation data, as fuel temperatures cannot be measured in reactor irradiation and are highly correlated with fission rate and thermal conductivity evolution. To connect the knowledge accumulated from ion irradiation with in-pile irradiation data, simulation of a full-sized U-Mo/Al dispersion fuel plate irradiated in the FUTURE test in the BR2 reactor was performed with the Dispersion Analysis Research Tool (DART), a dispersion fuel performance code. DART is equipped with an interaction or interdiffusion layer (IL) growth correlation formulated to describe the temperature dependence of ion mixing results. The agreement between calculated and measured fuel meat constituent volume fractions and swelling data demonstrated that the temperature effect on in-pile Al-UMo interdiffusion is well captured with the correlation. In this case, the fitted activation energy is 0.70 eV. Considering the uncertainties associated with the ion irradiation data, the activation energy obtained from in-pile data fitting is in accord with that from ion irradiation results.

36 MATERIALS SCIENCE↗

Physics-informed Estimation of the Covariance Matrix for Various Neutron Spectra

A method for estimating covariance matrices which capture the uncertainties in calculated reactor spectra has been developed. This method is based on perturbing the parameters of a physics-based analytic model fitted to a calculated spectrum. The covariance of the perturbed analytic spectra imposes energy-dependent correlations due to the physics of the neutron processes in the reactor, i.e., a fission component, a 1/E down-scatting component, and a thermal Maxwellian component. An analytic model is developed which is shown to produce good fits to several reactor environments. The covariance matrices produced via this method are then used as the prior spectrum in STAYSL least squares spectrum adjustment where it is combined with integral metrics, such as activation measurements, to produce a high-fidelity neutron spectrum characterization. It was concluded that the methodology showed agreeable results for the ACRR free-field spectrum adjustment in STAYSL resulting in a 𝜒 2 value of 2.21 (per degree of freedom), but further work is needed to describe scattering and interface regions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Using Ensemble Data Assimilation to Estimate Transient Hydrologic Exchange Flow Under Highly Dynamic Flow Conditions

Abstract Quantifying dynamic hydrologic exchange flows (HEFs) within river corridors that experience high‐frequency flow variations caused by dam regulations is important for understanding the biogeochemical processes at the river water and groundwater interfaces. Heat has been widely used as a tracer to infer steady‐state flow velocities through analytical solutions of heat transport defined by the diurnal temperature signals. Under sub‐daily dynamic flow conditions, however, such analytical solutions are not applicable due to the violation of their fundamental assumptions. In this study, we developed a data assimilation‐based approach to estimate the sub‐daily flux under highly dynamic flow conditions using multi‐depth temperature observations at a 5‐min resolution. If the hydraulic gradient is measured, Darcy's law was used to calculate the flux with permeability estimated from temperature responses below the riverbed. Otherwise, flux was estimated directly by assimilating multi‐depth temperature data at 1‐ or 2‐hr time intervals assuming one‐dimensional flow and heat transport governing equation. By comparing estimated fluxes with model‐generated synthetic truth, we demonstrated that both schemes have robust performance in estimating fluxes under highly dynamic flow conditions. This data assimilation‐based flux estimation method was able to capture the vertical sub‐daily fluxes using multi‐depth high‐resolution temperature data alone, even in the presence of multi‐dimensional flow. This approach has been successfully applied to real field temperature data collected at the Hanford site, which experiences highly dynamic HEFs. Our study shows the promise of adopting distributed 1‐D temperature monitoring to capture spatial and temporal exchange dynamics in river corridors at a watershed scale or beyond.

54 ENVIRONMENTAL SCIENCES↗

Performance of Scintillation Detectors Based on Quantum Dots in a Semiconductor Matrix (Final Technical Report)

InAs Quantum Dots (QDs) embedded into GaAs semiconductor waveguide have unique scintillation properties, valuable for nuclear security, medical imaging, and high energy physics. In this work, we developed thick (~25um) epitaxial heterostructres with high luminescence efficiency composed of self-assembled nano-engineered InAs QDs grown by molecular beam epitaxy. In this type of detector, the GaAs matrix acts as a stopping material for charged particles or photons generating electrons captured by the QDs acting as luminescence centers. The QD medium is designed to provide fast capture of electrons into QDs (few ps), high QD luminescence efficiency at room temperature (>50%), and strong red-shift of photoluminescence (PL) from the GaAs absorption edge (>250nm). Typical devices consist of a 10-25um thick GaAs layer with embedded sheets of modulation p-type doped InAs QDs and an InGaAs photodetector tuned to the QD emission wavelength. The thick GaAs layer acts also as a waveguide when layer-transferred onto a low-index substrate. Waveguiding and self-absorption (~1cm -1 ) were studied using photoluminescence with scanning laser excitation and modeled with ray optics approximation and geometrical coupling of high-index waveguide to a collection fiber. Scintillating signals from α-particles were analyzed with both an external photodiode (PD) and an integrated PD which provided an improved optical coupling. In the former case, the external InGaAs PD was air-coupled to the scintillator and had the light collection efficiency of about 1% corresponding to limited light extraction through a planar interface with air due to total internal reflection. The mean charge collected by the integrated PD was in the range of (3÷5)×10 4 photoelectrons per 1 MeV of deposited energy, or ~13-20% of the theoretically achievable light yield. Timing of the integrated device was measured by wire-bonding it to the input of an 8 GHz IC. The scintillation response shows an extremely fast 0.3-0.6 ns decay constant and about 40-70 ps time resolution, limited by the system noise. The combined light yield and decay time makes the InAs/GaAs QD heterostructures the fastest high yield scintillation material reported making it valuable for high energy physics and medical imaging applications.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Tomographic optical emission spectroscopy of atmospheric pressure plasma interacting with complex surfaces

Plasma distribution in 3D space is heavily influenced by complex surfaces and the coupling interactions between plasma properties and interfacing material properties. For example, guided streamers that transition to surface ionization waves (SIWs) and propagate over structured dielectrics experience field enhancements that can lead to localized increases in ionization rates and complex 3D configurations that are difficult to analyze. Investigating these configurations requires techniques than can provide a more complete 3D picture. To help address this capability gap, a tomographic optical emission spectroscopy (tomo-OES) diagnostic system has been developed at Sandia National Laboratories that can resolve SIWs. The system includes four intensified cameras that measure the angular projections of the plasma light emission through bandpass filters. A dot calibration target co-registers each angular projection to the same voxel grid and an algebraic reconstruction technique (ART) recovers the light intensity at each voxel. An atmospheric pressure plasma jet (APPJ), provided by Peter Bruggeman, has been investigated and representative results are shown in Figure 1. Here, a bandpass filter was used to isolate emission from the N 2 second positive system (SPS) at 337.1 nm to capture the transition of the streamer to SIW on a planar dielectric surface (relative permittivity 3.3) located 3 mm below the APPJ [3]. The surface wave velocity was 3.5x10 4 (m/s), consistent with measurements made by Steven Shannon. Characterization of this APPJ will support the group effort of standing up a reproducible APPJ across institutions for applications such as liquid treatment, catalysis, and plasma aided combustion. Future work will investigate non-planar surfaces and eventually develop tomographic laser-induced fluorescence (tomo-LIF) approaches.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Hydro-mechanical coupled modeling of hydraulic fracturing using the mesh fragmentation technique

The inclusion of special interface elements between standard finite elements is becoming a common technique to model discontinuities in porous media using the finite element method (FEM). Recently, it was proved that high aspect ratio (HAR) elements can reproduce very satisfactorily the main features of behavior observed in a single hydraulically-induced fracture. In this paper, the mesh fragmentation technique (MFT) is proposed to extend the application of HAR elements to simulate more general problems involving the formation of hydraulic fractures in rocks by introducing this type of element in-between the standard FE of a typical mesh. The proposed framework makes use of standard FE techniques. Therefore, it is relatively easy to upgrade an existing FE program for continuous porous media to deal with evolving discontinuities. The proposed approach is verified and validated against available analytical and numerical solutions. The crack patterns predicted by the MFT are also compared with the ones observed in the laboratory. The formation of multiple fractures is also analyzed. In all cases, the proposed technique was able to properly capture the main features of rock behavior subjected to hydraulic fracturing.

58 GEOSCIENCES↗

Analysis of Technology for Compact Coherent Lidar

In view of the recent advances in the area of solid state and semiconductor lasers has created new possibilities for the development of compact and reliable coherent lidars for a wide range of applications. These applications include: Automated Rendezvous and Capture, wind shear and clear air turbulence detection, aircraft wake vortex detection, and automobile collision avoidance. The work performed by the UAH personnel under this Delivery Order, concentrated on design and analyses of a compact coherent lidar system capable of measuring range and velocity of hard targets, and providing air mass velocity data. The following is the scope of this work. a. Investigate various laser sources and optical signal detection configurations in support of a compact and lightweight coherent laser radar to be developed for precision range and velocity measurements of hard and fuzzy targets. Through interaction with MSFC engineers, the most suitable laser source and signal detection technique that can provide a reliable compact and lightweight laser radar design will be selected. b. Analyze and specify the coherent laser radar system configuration and assist with its optical and electronic design efforts. Develop a system design including its optical layout design. Specify all optical components and provide the general requirements of the electronic subsystems including laser beam modulator and demodulator drivers, detector electronic interface, and the signal processor. c. Perform a thorough performance analysis to predict the system measurement range and accuracy. This analysis will utilize various coherent laser radar sensitivity formulations and different target models.

Amzajerdian, Farzin↗

Improving Fidelity of Launch Vehicle Liftoff Acoustic Simulations

Launch vehicles experience high acoustic loads during ignition and liftoff affected by the interaction of rocket plume generated acoustic waves with launch pad structures. Application of highly parallelized Computational Fluid Dynamics (CFD) analysis tools optimized for application on the NAS computer systems such as the Loci/CHEM program now enable simulation of time-accurate, turbulent, multi-species plume formation and interaction with launch pad geometry and capture the generation of acoustic noise at the source regions in the plume shear layers and impingement regions. These CFD solvers are robust in capturing the acoustic fluctuations, but they are too dissipative to accurately resolve the propagation of the acoustic waves throughout the launch environment domain along the vehicle. A hybrid Computational Fluid Dynamics and Computational Aero-Acoustics (CFD/CAA) modeling framework has been developed to improve such liftoff acoustic environment predictions. The framework combines the existing highly-scalable NASA production CFD code, Loci/CHEM, with a high-order accurate discontinuous Galerkin (DG) solver, Loci/THRUST, developed in the same computational framework. Loci/THRUST employs a low dissipation, high-order, unstructured DG method to accurately propagate acoustic waves away from the source regions across large distances. The DG solver is currently capable of solving up to 4th order solutions for non-linear, conservative acoustic field propagation. Higher order boundary conditions are implemented to accurately model the reflection and refraction of acoustic waves on launch pad components. The DG solver accepts generalized unstructured meshes, enabling efficient application of common mesh generation tools for CHEM and THRUST simulations. The DG solution is coupled with the CFD solution at interface boundaries placed near the CFD acoustic source regions. Both simulations are executed simultaneously with coordinated boundary condition data exchange.

Liever, Peter↗

Perspectives on Quenching and Tempering 4340 Steel

Steels are ubiquitous due to their affordability and the landscape of useful properties that can be generated for engineering applications. But to further expand the performance envelope, one must be able to understand and control microstructure development by alloying and processing. In this paper we use multiscale, advanced characterization to better understand the structural and chemical evolution of AISI 4340 steel after quenching and tempering (Q&T), including the role of quench rate and short-time, isothermal tempering below 573 K (300 °C), with an emphasis on carbide formation. We compare the microstructure and/or property changes produced by conventional tempering to those produced by higher temperature, short-time “rapid” tempering. We underscore that no single characterization technique can fully capture the subtle microstructure changes like carbon redistribution, transition carbide and/or cementite formation, and retained austenite decomposition that occur during Q&T. Only the use of multiple techniques begins to unravel these complexities. After controlled fast or slow quenching, η transition carbides clearly exist in the microstructure, likely associated with autotempering of this high martensite start temperature (Ms) steel. Isothermal tempering below 598 K (325 °C) results in the relief of carbon supersaturation in the martensite, primarily by the formation of η transition carbides that exhibit a range of carbon levels, seemingly without substitutional element partitioning between the carbide and matrix phases. Hägg transition carbide is present between 300 °C and 325 °C. After conventional tempering at or above 598 K (325 °C) for 2 h, cementite is predominant, but small amounts of cementite are also present in other conditions, even after quenching. Previous work has indicated that silicon (Si) and substitutional elements partition between the cementite, which initially forms under paraequilibrium conditions, and the matrix. Phosphorous (P) may also be preferentially located at cementite/matrix interfaces after high temperature tempering. Slower quench rates result in greater amounts of retained austenite compared to those after fast quenching, which we attribute to increased austenite stability resulting from “autopartitioning”. Rapid, high temperature tempering is also found to diminish tempered martensite embrittlement (TME) believed to be associated with the extent of austenite decomposition, resulting in mechanical properties not attainable by conventional tempering, which may have important implications with respect to industrial heat treatment processes like induction tempering. Controlling the amount and stability of retained austenite is not only relevant to the properties of Q&T steels, but also next-generation advanced high strength steels (AHSS) with austenite/martensite mixtures.

36 MATERIALS SCIENCE↗

Dendrite Growth Morphology Modeling in Liquid and Solid Electrolytes

The main goal of this project is to develop a multi-scale modeling approach that connects micron-scale phase-field models and atomic-scale density functional theory (DFT)-based simulations via parameter- and relationship-passing in order to predict Li-metal dendrite morphology evolution, in both liquid and solid electrolytes. The key hypothesis of the DFT-informed phase-field multiscale modeling approach is that it can capture the electrochemical-mechanical driving forces and incorporate the roles of nano-meter-thin solid electrolyte interphase (SEI) in liquid electrolytes as well as of the microstructures of micro-meter-thick solid electrolytes (SEs) for all-solid-state batteries. In this project, we have formulated and implemented phase-field models to incorporate the electrochemical driving forces in liquid electrolytes and then incorporate mechanical driving forces to simulate dendrite growth in solid electrolytes with resolved microstructures. We have implemented two treatments for the SEI: an explicit model to include the microstructure of the SE or SEI in the phase field model and an implicit model to simulate the impact of nano-meter thick SEI in liquid electrolytes by varying the electrode/electrolyte interfacial properties. The key interfacial properties, including the electronic and ionic transport properties, the charge transfer reaction kinetics, and mechanical properties, were computed by DFT-based calculations. At the DFT-based model, one key advancement is to directly predict the charge transfer reaction kinetics at a complex Li/SEI/electrolyte interface by linking DFT with density functional tight binding (DFTB) calculations. As the main accomplishments, we have demonstrated two successful predictions in both solid electrolyte and liquid electrolyte based on this multiscale approach. The predicted intergranular Li dendrite growth in LLZO revealed the importance of trapped electrons at internal interfaces in the microstructure of LLZO. The predicted electroplating morphology of mossy Li and faceted Mg agreed well with experiments. The insights provided by the multiscale model and the model enabled electrolyte and SEI design will accelerate the development of Li-metal electrode for high energy density batteries, that meet DOE’s target on cell density (>350 Wh/kg) and cost below $100/kWhuse for EV applications.

25 ENERGY STORAGE↗