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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

V&V Of CFD Modeling Of The Argonne Bubble Experiment: FY15 Summary Report

In support of the development of accelerator-driven production of the fission product Mo 99, computational fluid dynamics (CFD) simulations of an electron-beam irradiated, experimental-scale bubble chamber have been conducted in order to aid in interpretation of existing experimental results, provide additional insights into the physical phenomena, and develop predictive thermal hydraulic capabilities that can be applied to full-scale target solution vessels. Toward that end, a custom hybrid Eulerian-Eulerian-Lagrangian multiphase solver was developed, and simulations have been performed on high-resolution meshes. Good agreement between experiments and simulations has been achieved, especially with respect to the prediction of the maximum temperature of the uranyl sulfate solution in the experimental vessel. These positive results suggest that the simulation methodology that has been developed will prove to be suitable to assist in the development of full-scale production hardware.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

A Lagrangian Study of the Transition from Shallow to Deep Convection Using ASR Observations and Les Simulations (Final Report)

With the support from this grant, we have made the following accomplishments. We have found that a formula for fractional entrainment rate, a key aspect for parameterization moist convection, that works for both shallow and deep convection, which provide a promising direction for unified treatment of entrainment for both shallow and deep convection. We also examined the formulation of vertical velocity and showed that the effect of non-hydrostatic pressure and entrainment on vertical velocity are not constants, as assumed in past studies, but can be computed using a simple model for the cloudy updrafts. These results also apply to both deep and shallow convection, which opens the door for a more physically based parameterization of the updraft vertical velocity. We have also conducted extensive analysis of the RACORO aircraft data and have published the results in Wei et al. (2020). We have made extensive effort scrutinizing the data in detail and examining the various hypotheses with the aid of the LES simulations. This was the first application of the modified Paluch diagram on modern aircraft data and the first comprehensive analysis of mixing in clouds using real data (instead of only LES output) in a very long time. These analyses enhanced the science return of the ASR aircraft measurements. This grant also supported a study of the collisions among cold pools and an effort to build parameterizations of moist convection using tools developed in control theory.

42 ENGINEERING↗
DOE OSTI2025

Prediction of Alpha-Particle-Immune Gate-All-Around Field-Effect Transistors (GAA-FET) Based SRAM Design

Alpha particles are known to be a major source of particles creating soft errors in semiconductor devices, such as content flipping in Static Random-Access Memory (SRAM). Recent advancements in transistor nodes have led to the introduction of Gate-All-Around Field Effect Transistors (GAA-FETs), which have better gate control, thus better electrostatics. Moreover, the introduction of bottom dielectric isolation (BDI) eliminates substrate leakage and thus is expected to enhance its radiation hardness. It is thus important to explore if one can design an SRAM that is completely radiation-hard to alpha particles. In this paper, using 3D Technology Computer-Aided-Design (TCAD) simulations, we show that it is possible to design an SRAM using GAA-FET technology so that it is immune to single alpha particle radiation error. In other words, with the design, there will be no single-event upset (SEU) due to alpha particles. We first use ab initio calculations in PHITS to show that there is a maximum linear energy transfer (LET), LET max , for the alpha particle in Si and Si x Ge 1-x . Based on that, by de signing a sub-7nm GAA-FET-based SRAM with BDI, we show that the SRAM does not flip even if the particle strike is in the worst-case scenario for LET > LET max .

42 ENGINEERING↗
DOE OSTI2016

V&V of Residual Stress for GTS

Residual stresses induced during forging and welding can cause detrimental failure in reservoirs due to enhanced possibility of crack propagation. Therefore, reservoirs must be designed with yield strengths in a tight range. This report summarizes an effort to verify and validate a computational tool that was developed to aid in prediction of the evolution of residual stresses throughout the manufacturing process. The application requirements are identified and summarized in the context of the Predictive Capability Maturity Model (PCMM). The phenomena of interest that the model attempts to capture are discussed and prioritized using the Phenomena Identification and Ranking Table (PIRT) to identify any gaps in our approach. The fidelity of the modeling approach is outlined and details on the implementation and boundary conditions are provided. The code verification requirements are discussed and solution verification is performed, including a mesh convergence study on the series of modeling steps (forging, machining and welding). Validation activities are summarized, including validation of the displacements, residual stresses, recrystallization, yield strength and thermal history. A sensitivity analysis and uncertainty quantification are also performed to understand how variations in the manufacturing process affect the residual stresses.

42 ENGINEERING↗
DOE OSTI2017

Aces4: A Platform for Computational Chemistry Calculations with Extremely Large Block-Sparse Arrays

Aces4 is a parallel programming platform comprising a DSL for Computational Chemistry and its runtime system. It offers a convenient way to express parallelism together with extensive support for extremely large, possibly sparse, distributed arrays. It aids scientists in the creation of performant, scalable, massively parallel programs that can effectively take advantage of leadership class computing systems to address important scientific questions. Aces4 has enabled the development and implementation of new methods in electronic structure theory which are breaking new ground in their ability to perform highly accurate calculations on ever larger molecular systems. In this paper the design of Aces4, which is based on the the Super Instruction Architecture approach, is described. Experimental scaling results for Molecular Cluster Perturbation Theory, a new method enabled by Aces4, and CCSD, a widely used computational chemistry method are given.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Effect of nozzle translation on a bounded vortex flow

A bounded vortex flow is generated by a nozzle that combines azimuthally tilted downward jets in a circular array and a central suction port. When the nozzle is directed toward a bottom surface (called the impingement surface), the flow develops a strong intake vortex spanning from the impingement surface to the suction port, which acts to generate strong shear stress on the impingement surface. This strong shear stress can aid in removing particles attached to the impingement surface or in enhancement of heat or mass transfer, where in typical applications, the nozzle would be translated along the impingement surface. This paper reports on a computational study of the effect of nozzle translation on the bounded vortex flow field. The nozzle translation induces a bending of the bounded vortex in the downstream flow direction, which becomes larger with increase in the nozzle translation speed. We identify an interesting oscillatory phenomenon by which the bounded vortex can resist the bending induced by the translational flow and rotate about a mean position downstream of the suction port. At sufficiently high translation speeds, the oscillatory process can no longer resist the downwash effect from nozzle translation and the vortex eventually detaches from the impingement surface, limiting the effectiveness of this flow device.

42 ENGINEERING↗
DOE OSTI2012

Structural, kinetic, and thermodynamic studies of specificity designed HIV-1 protease

HIV-1 protease recognizes and cleaves more than 12 different substrates leading to viral maturation. While these substrates share no conserved motif, they are specifically selected for and cleaved by protease during viral life cycle. Drug resistant mutations evolve within the protease that compromise inhibitor binding but allow the continued recognition of all these substrates. While the substrate envelope defines a general shape for substrate recognition, successfully predicting the determinants of substrate binding specificity would provide additional insights into the mechanism of altered molecular recognition in resistant proteases. We designed a variant of HIV protease with altered specificity using positive computational design methods and validated the design using X-ray crystallography and enzyme biochemistry. The engineered variant, Pr3 (A28S/D30F/G48R), was designed to preferentially bind to one out of three of HIV protease's natural substrates; RT-RH over p2-NC and CA-p2. In kinetic assays, RT-RH binding specificity for Pr3 increased threefold compared to the wild-type (WT), which was further confirmed by isothermal titration calorimetry. Crystal structures of WT protease and the designed variant in complex with RT-RH, CA-p2, and p2-NC were determined. Structural analysis of the designed complexes revealed that one of the engineered substitutions (G48R) potentially stabilized heterogeneous flap conformations, thereby facilitating alternate modes of substrate binding. Our results demonstrate that while substrate specificity could be engineered in HIV protease, the structural pliability of protease restricted the propagation of interactions as predicted. These results offer new insights into the plasticity and structural determinants of substrate binding specificity of the HIV-1 protease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Yet another parameter-free shape optimization method

The use of node coordinates as design variables in shape optimization offers a larger design space than computer-aided design (CAD)-based shape parameterizations. It also allows for the optimization of legacy designs, i.e., a finite element mesh from an existing design can be readily optimized to meet new performance requirements without involving a CAD model. However, it is well known that the node coordinate parameterization method is fraught with numerical difficulties, which makes it impractical to use. This has led to several of “parameter-free” shape optimization methods that seek the advantages and avoid the pitfalls of the naïve node coordinate parameterization method. These methods come in two main varieties: sensitivity filtering (or gradient smoothing) and consistent filtering. The latter is analogous to the density filter method used in topology optimization (TO). In this work, we use the PDE filter from TO and energy-based filters to implement consistent shape optimization filtering schemes easily and efficiently. Numerical experiments demonstrate that consistent methods are more robust than sensitivity filtering methods.

42 ENGINEERING↗
DOE OSTI2017

Water NSTF Design, Instrumentation, and Test Planning

The following report serves as a formal introduction to the water-based Natural convection Shutdown heat removal Test Facility (NSTF) program at Argonne. Since 2005, this US Department of Energy (DOE) sponsored program has conducted large scale experimental testing to generate high-quality and traceable validation data for guiding design decisions of the Reactor Cavity Cooling System (RCCS) concept for advanced reactor designs. The most recent facility iteration, and focus of this report, is the operation of a 1/2 scale model of a water-RCCS concept. Several features of the NSTF prototype align with the conceptual design that has been publicly released for the AREVA 625 MWt SC-HTGR. The design of the NSTF also retains all aspects common to a fundamental boiling water thermosiphon, and thus is well poised to provide necessary experimental data to advance basic understanding of natural circulation phenomena and contribute to computer code validation. Overall, the NSTF program operates to support the DOE vision of aiding US vendors in design choices of future reactor concepts, advancing the maturity of codes for licensing, and ultimately developing safe and reliable reactor technologies. In this report, the top-level program objectives, testing requirements, and unique considerations for the water cooled test assembly are discussed, and presented in sufficient depth to support defining the program’s overall scope and purpose. A discussion of the proposed 6-year testing program is then introduced, which outlines the specific strategy and testing plan for facility operations. The proposed testing plan has been developed to meet the toplevel objective of conducting high-quality test operations that span across a broad range of single- and two-phase operating conditions. Details of characterization, baseline test cases, accident scenario, and parametric variations are provided, including discussions of later-stage test cases that examine the influence of geometric variations and off-normal configurations. The facility design follows, including as-built dimensions and specifications of the various mechanical and liquid systems, design choices for the test section, water storage tank, and network piping. Specifications of the instrumentation suite are then presented, along with specific information on performance windows, measurement uncertainties, and installation locations. Finally, descriptions of the control systems and heat removal networks are provided, which have been engineered to support precise quantification of energy balances and facilitate well-controlled test operations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Hydraulic Capacity of an ADA Compliant Street Drain Grate

Resurfacing of urban roads with concurrent repairs and replacement of sections of curb and sidewalk may require pedestrian ramps that are compliant with the American Disabilities Act (ADA), and when street drains are in close proximity to the walkway, ADA compliant street grates may also be required. The Minnesota Department of Transportation ADA Operations Unit identified a foundry with an available grate that meets ADA requirements. Argonne National Laboratory’s Transportation Research and Analysis Computing Center used full scale three dimensional computational fluid dynamics to determine the performance of the ADA compliant grate and compared it to that of a standard vane grate. Analysis of a parametric set of cases was carried out, including variation in longitudinal, gutter, and cross street slopes and the water spread from the curb. The performance of the grates was characterized by the fraction of the total volume flow approaching the grate from the upstream that was captured by the grate and diverted into the catch basin. The fraction of the total flow entering over the grate from the side and the fraction of flow directly over a grate diverted into the catch basin were also quantities of interest that aid in understanding the differences in performance of the grates. The ADA compliant grate performance lagged that of the vane grate, increasingly so as upstream Reynolds number increased. The major factor leading to the performance difference between the two grates was the fraction of flow directly over the grates that is captured by the grates.

3D CFD↗
DOE OSTI2017

Applicability Analysis of Validation Evidence for Biomedical Computational Models

Computational modeling has the potential to revolutionize medicine the way it transformed engineering. However, despite decades of work, there has only been limited progress to successfully translate modeling research to patient care. One major difficulty which often occurs with biomedical computational models is an inability to perform validation in a setting that closely resembles how the model will be used. For example, for a biomedical model that makes in vivo clinically relevant predictions, direct validation of predictions may be impossible for ethical, technological, or financial reasons. Unavoidable limitations inherent to the validation process lead to challenges in evaluating the credibility of biomedical model predictions. Therefore, when evaluating biomedical models, it is critical to rigorously assess applicability, that is, the relevance of the computational model, and its validation evidence to the proposed context of use (COU). However, there are no well-established methods for assessing applicability. In this paper, we present a novel framework for performing applicability analysis and demonstrate its use with a medical device computational model. The framework provides a systematic, step-by-step method for breaking down the broad question of applicability into a series of focused questions, which may be addressed using supporting evidence and subject matter expertise. The framework can be used for model justification, model assessment, and validation planning. While motivated by biomedical models, it is relevant to a broad range of disciplines and underlying physics. Finally, the proposed applicability framework could help overcome some of the barriers inherent to validation of, and aid clinical implementation of, biomedical models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Development Of Thermodynamic and Kinetic Simulation Tools and Testing Procedures for Enhanced Durability of Concrete Containing Industrial By-Products

This project developed screening tools that enable evaluation of alternative cementitious binders that create concretes to significantly reduce energy and emissions while remaining cost competitive on both initial and long-term costs. The team began with the viewpoint that acceptance of new cementitious binder products has a substantially greater chance of successful implementation when capital investment is not excessive and the end product has customers that have experience and resources to use this. As such, a binder system that is based on portland cement with blended using industrial by-products (alternative cementitious materials) has the potential for dramatic and meaningful impact. The team has focused on developing implementable solutions in specifications and current practice. This however requires three main factors: 1) ability to screen byproducts and alternative materials for success, 2) ability to ‘treat’ materials chemically to enhance kinetics, and 3) ability to provide predictions of performance of both binders and concrete from first principles. The project developed/refined a state of the art and scientifically based screening test for SCM called the pozzolanic reactivity test. The team developed kinetic models to simulate these materials as well as experimental approaches to alter selected reactions. Simulation tools were developed that enable the performance of concrete to be predicted based on the chemistry and reactivity of the cement and alternative SCM. Specifically, this project: • enhanced the kinetic reactivity models for use in multi-scale computational programs that use thermodynamics to predict reaction products. 2 • developed scaling models to extend thermodynamic modeling to link these models with pore structure. This enables strength, transport property, and coupled transport prediction. • developed tools to predict performance of cementitious materials using the pozzolanic reactivity test and chemical composition. The predicted properties are consistent with AASHTO R101 and the CEB-FIP model code and can be measured using associated test procedures. • demonstrated mechanical and fracture based modeling tools that thermodynamic predictions and inputs to predict concrete service life. These results have been used to demonstrate the value of enabling specifications to include ASTM C 595 cement as well ASTM C150 cement. In addition, these products are being used to expedite the evaluation of alternative SCM to aide in determining which materials have potential value and what ‘compositions’ of blended cements merit further investment.

42 ENGINEERING↗
DOE OSTI2018

Machine learning materials physics: Surrogate optimization and multi-fidelity algorithms predict precipitate morphology in an alternative to phase field dynamics

Machine learning has been effective at detecting patterns and predicting the response of systems that behave free of natural laws. Examples include learning crowd dynamics, recommender systems and autonomous mobility. There also have been applications to the search for new materials that draw upon big-data classification problems. Though, when it comes to physical systems governed by conservation laws, the role of machine learning has been more limited. Here, we present our recent work in exploring the role of machine learning methods in discovering, or aiding, the search for physics. Specifically, we focus on using machine learning algorithms to represent high-dimensional free energy surfaces with the goal of identifying precipitate morphologies in alloy systems. Traditionally, this problem has been approached by combining phase field models, which impose first-order dynamics, with elasticity, to traverse a free energy landscape in search of minima. Equilibrium precipitate morphologies occur at these minima. Here, we exploit the machine learning methods to represent high-dimensional data, combined with surrogate optimization, sensitivity analysis and multifidelity modeling as an alternate framework to explore phenomena controlled by energy extremization. This combination of data-driven methods offers an alternative to the imposition of first-order dynamics via phase field methods, and represents one aspect of applying machine learning to materials physics.

42 ENGINEERING↗
DOE OSTI2021

A critical look at the prediction of the temperature field around a laser-induced melt pool on metallic substrates

The study of microstructure evolution in additive manufacturing of metals would be aided by knowing the thermal history. Since temperature measurements beneath the surface are difficult, estimates are obtained from computational thermo-mechanical models calibrated against traces left in the sample revealed after etching, such as the trace of the melt pool boundary. Here we examine the question of how reliable thermal histories computed from a model that reproduces the melt pool trace are. To this end, we perform experiments in which one of two different laser beams moves with constant velocity and power over a substrate of 17-4PH SS or Ti-6Al-4V, with low enough power to avoid generating a keyhole. We find that thermal histories appear to be reliably computed provided that (a) the power density distribution of the laser beam over the substrate is well characterized, and (b) convective heat transport effects are accounted for. Poor control of the laser beam leads to potentially multiple three-dimensional melt pool shapes compatible with the melt pool trace, and therefore to multiple potential thermal histories. Ignoring convective effects leads to results that are inconsistent with experiments, even for the mild melt pools here.

42 ENGINEERING↗
DOE OSTI2014

A Runtime Environment for Supporting Research in Resilient HPC System Software & Tools

The high-performance computing (HPC) community continues to increase the size and complexity of hardware platforms that support advanced scientific workloads. The runtime environment (RTE) is a crucial layer in the software stack for these large-scale systems. The RTE manages the interface between the operating system and the application running in parallel on the machine. The deployment of applications and tools on large-scale HPC computing systems requires the RTE to manage process creation in a scalable manner, support sparse connectivity, and provide fault tolerance. We have developed a new RTE that provides a basis for building distributed execution environments and developing tools for HPC to aid research in system software and resilience. This paper describes the software architecture of the Scalable runTime Component Infrastructure (STCI), which is intended to provide a complete infrastructure for scalable start-up and management of many processes in large-scale HPC systems. We highlight features of the current implementation, which is provided as a system library that allows developers to easily use and integrate STCI in their tools and/or applications. The motivation for this work has been to support ongoing research activities in fault-tolerance for large-scale systems. We discuss the advantages of the modular framework employed and describe two use cases that demonstrate its capabilities: (i) an alternate runtime for a Message Passing Interface (MPI) stack, and (ii) a distributed control and communication substrate for a fault-injection tool.

Computer Science↗
DOE OSTI2016

Verification and Validation of CFD Simulations involving Twin Rectangular Jets using Steady RANS in Star-CCM+

Analyses such as component design and safety analysis can be conducted through careful application of computational fluid dynamics (CFD) codes. Before these codes can be considered ready for specific analysis, benchmarking (validation) against applicable datasets is needed. The twin jet water facility (TJWF) developed originally at the University of Tennessee, Knoxville has been purposed for aiding in this type of work. The TJWF allows for large data sets to be created using state of the art non-invasive measurement techniques within a mostly transparent testing volume. Utilizing velocity data collected in the TJWF by Wang et. al., the Star-CCM+ code was benchmarked a using steady Reynolds averaged Navier Stokes (RANS) framework for a combining two jet case. Careful efforts to properly conduct verification of the numerical work was undertaken with a sample reported in this summary. The computational results were validated against the experimental work and found to be within acceptable limits. The parameters of interest were the merging and combining points (MP and CP) of the twin jets, and the velocity profiles at increasing heights after injection. Fig.1 provides a graphical depiction of the twin jets combining within a free shear volume with key geometric factors included. The MP and velocity profiles were predicted with reasonable agreement. Whereas, the combining point of the twin jets was found to be over-predicted by {approx}24% difference. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Computational Study of Droplet Dynamics in Dispersed Flow Film Boiling Regime in PWR Geometries

Dispersed flow film boiling (DFFB) regime is exhibited during low-flooding rate conditions following the postulated Loss-of-Coolant Accident (LOCA) in nuclear reactor flow channels. LOCA is a type of design-basis accident scenario, which is crucial for reactor design and licensing. Accurate models to predict the heat transfer in DFFB regime is critical for the reactor to maintain safety limits. The nominal operating linear heat rate is also set based on the maximum linear heat rate determined for a LOCA transient. It is understood that the behavior of entrained droplets in DFFB regime greatly affects the heat transfer by evaporating and desuperheating the surrounding steam. Furthermore, interaction with flow structures also aids in increasing the evaporation rate of entrained droplets. In order to quantify this enhancement in heat transfer, the size of droplets downstream of flow structures (Spacer Grids and Mixing Vanes) is of crucial importance. Thermal hydraulic analysis codes like COBRA-TF, CATHARE-3 and adopt a three-field equation model that allows them to model the droplet field separately. However, to ensure the accuracy of these field equations, various correlations and physical models are required. This paper proposes a method for characterizing the mean Sauter Diameter of droplets across spacer-grids and mixing vanes in PWR sub-channels using PHASTA - a high fidelity flow solver with multiphase capabilities using the level-set method. The PHASTA code is a finite element based computational fluid dynamics code designed for solving compressible and incompressible turbulent flows. It has been demonstrated to be massively scalable (up to 786,432 cores), which is crucial for simulating large realistic domains. The code incorporates the level-set method for interface tracking of the gas-liquid interface.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Tools for Large-Scale Mobile Malware Analysis

Analyzing mobile applications for malicious behavior is an important area of re- search, and is made di cult, in part, by the increasingly large number of appli- cations available for the major operating systems. There are currently over 1.2 million apps available in both the Google Play and Apple App stores (the respec- tive o cial marketplaces for the Android and iOS operating systems)[1, 2]. Our research provides two large-scale analysis tools to aid in the detection and analysis of mobile malware. The rst tool we present, Andlantis, is a scalable dynamic analysis system capa- ble of processing over 3000 Android applications per hour. Traditionally, Android dynamic analysis techniques have been relatively limited in scale due to the compu- tational resources required to emulate the full Android system to achieve accurate execution. Andlantis is the most scalable Android dynamic analysis framework to date, and is able to collect valuable forensic data, which helps reverse-engineers and malware researchers identify and understand anomalous application behavior. We discuss the results of running 1261 malware samples through the system, and provide examples of malware analysis performed with the resulting data. While techniques exist to perform static analysis on a large number of appli- cations, large-scale analysis of iOS applications has been relatively small scale due to the closed nature of the iOS ecosystem, and the di culty of acquiring appli- cations for analysis. The second tool we present, iClone, addresses the challenges associated with iOS research in order to detect application clones within a dataset of over 20,000 iOS applications.

97 MATHEMATICS AND COMPUTING↗