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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A fractional model for anomalous diffusion with increased variability: Analysis, algorithms and applications to interface problems

Fractional equations have become the model of choice in several applications where heterogeneities at the microstructure result in anomalous diffusive behavior at the macroscale. Here, we introduce a new fractional operator characterized by a doubly-variable fractional order and possibly truncated interactions. Under certain conditions on the model parameters and on the regularity of the fractional order we show that the corresponding Poisson problem is well-posed. Additionally, we introduce a finite element discretization and describe an efficient implementation of the finite-element matrix assembly in the case of piecewise constant fractional order. Through several numerical tests, we illustrate the improved descriptive power of this new operator across media interfaces. Furthermore, we present one-dimensional and two-dimensional h-convergence results that show that the variable-order model has the same convergence behavior as the constant-order model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Physics-informed neural networks for heterogeneous poroelastic media

This study presents a novel physics-informed neural network (PINN) framework for modeling poroelasticity in heterogeneous media with material interfaces. The approach introduces a composite neural network (CoNN) where separate neural networks predict displacement and pressure variables for each material. While sharing identical activation functions, these networks are independently trained for all other parameters. To address challenges posed by heterogeneous material interfaces, the CoNN is integrated with the Interface-PINNs (I-PINNs) framework (Sarma et al., Comput. Methods Appl. Mech. Eng. 429: 117135, 2024), allowing different activation functions across material interfaces. Further, this ensures accurate approximation of discontinuous solution fields and gradients. Performance and accuracy of this combined architecture were evaluated against the conventional PINNs approach, a single neural network (SNN) architecture, and the eXtended PINNs (XPINNs) framework through two one-dimensional benchmark examples with discontinuous material properties. The results show that the proposed CoNN with I-PINNs architecture achieves an RMSE that is two orders of magnitude better than the conventional PINNs approach and is at least 40 times faster than the SNN framework. Compared to XPINNs, the proposed method achieves an RMSE at least one order of magnitude better and is 40% faster.

42 ENGINEERING↗
DOE OSTI2018

Linking process and structure in the friction stir scribe joining of dissimilar materials: A computational approach with experimental support

We present that friction stir welding (FSW) is a popular technique to join dissimilar materials in numerous applications. The solid state nature of the process enables joining materials with strikingly different physical properties. For welds in lap configuration, an enhancement to this technology is made by introducing a short, hard insert, referred to as a cutting-scribe, at the bottom of the tool pin. The cutting-scribe induces deformation in the bottom plate which leads to the formation of mechanical interlocks or hook like structures at the interface of two materials. A thermo-mechanical computational model employing a coupled Eulerian-Lagrangian approach is developed to quantitatively capture the morphology of these interlocks during the FSW process. Simulations using this model are validated by experimental observations. In conclusion, the identified interface morphology coupled with the predicted temperature field from this process–structure model can be used to estimate the post-weld microstructure and joint strength.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Framework for Integrating Quantum Simulation and High Performance Computing

Scientific applications are starting to explore the viability of quantum computing. This exploration typically begins with quantum simulations that can run on existing classical platforms, albeit without the performance advantages of real quantum resources. In the context of high-performance computing (HPC), the incorporation of simulation software can often take advantage of the powerful resources to help scale-up the simulation size. The configuration, installation and operation of these quantum simulation packages on HPC resources can often be rather daunting and increases friction for experimentation by scientific application developers. We describe a framework to help streamline access to quantum simulation software running on HPC resources. This includes an interface for circuit-based quantum computing tasks, as well as the necessary resource management infrastructure to make effective use of the underlying HPC resources. The primary contributions of this work include a classification of different usage models for quantum simulation in an HPC context, a review of the software architecture for our approach and a detailed description of the prototype implementation to experiment with these ideas using two different simulators (TNQVM & NWQ-Sim). We include initial experimental results running on the Frontier supercomputer at the Oak Ridge Leadership Computing Facility (OLCF) using a synthetic workload generated via the SupermarQ quantum benchmarking framework.

Shehata, Amir [ORNL] (ORCID:0000000224531426)↗
DOE OSTI2021

An IIPG-Based Finite Element Framework in MOOSE for Modeling Fiber Reinforced Composite Failure Governed by Extrinsic Cohesive Laws

Many material and structure failures are initiated at the interface between two distinctive materials, such as the debonding of interfaces of matrix/fiber of composites or bulk matrix/inclusion in metals at micro-scales. Accurate and robust modeling of these interface failures is critical to the design of novel material and structure with improved functionality. This paper presents a robust implementation of a discontinuous Galerkin finite element method in MOOSE based on the Incomplete Interior Penalty Galerkin scheme for modeling material interface behavior. This DG-based interface method naturally accommodates important extrinsic cohesive zone material models and is capable of modeling the failures of material interfaces across which material properties are highly distinctive. We demonstrate a good performance of the proposed method using single fiber and multiple fiber debonding problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Cell-machine interfaces for characterizing gene regulatory network dynamics

Gene regulatory networks and the dynamic responses theyproduce offer a wealth of information about how biologicalsystems process information about their environment.Recently, researchers interested in dissecting these networkshave been outsourcing various parts of their experimentalworkflow to computers. Here we review how, using microfluidicor optogenetic tools coupled with fluorescence imaging, it isnow possible to interface cells and computers. These platformsenable scientists to perform informative dynamic stimulationsof genetic pathways and monitor their reaction. It is alsopossible to close the loop and regulate genes in real time,providing an unprecedented view of how signals propagatethrough the network. Finally, we outline new tools that can beused within the framework of cell–machine interfaces.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

A parallel and performance portable implementation of a full-field crystal plasticity model

We have developed a parallel implementation of an Elasto-Viscoplastic Fast Fourier Transform-based (EVPFFT) micromechanical solver to enable computationally efficient crystal plasticity modeling for polycrystalline materials. Our primary focus lies in achieving performance portability, allowing a single EVPFFT implementation to run optimally on various homogeneous architectures, including multi-core Central Processing Units (CPUs), as well as on heterogeneous computer architectures comprising multi-core CPUs and Graphics Processing Units (GPUs) from different vendors. To accomplish this goal, we have leveraged MATAR, a C++ software library that simplifies the creation and utilization of multidimensional dense or sparse matrix and array data structures. These data structures are designed to be portable across diverse architectures through the use of Kokkos, a performance-portable library. Additionally, we have employed the Message Passing Interface (MPI) to efficiently distribute the computational workload among processors. The heFFTe (Highly Efficient FFT for Exascale) library is used to facilitate the performance portability of the fast Fourier transforms (FFTs) computation. The computational performance of EVPFFT is evaluated and presented in terms of parallel scalability and simulation runtime on different high-performance computing (HPC) architectures. As a result, the utility of the developed framework to efficiently simulate the micro-mechanical fields in polycrystalline microstructures in engineering applications is discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Synergizing human expertise and AI efficiency with language model for microscopy operation and automated experiment design

With the advent of large language models (LLMs), in both the open source and proprietary domains, attention is turning to how to exploit such artificial intelligence (AI) systems in assisting complex scientific tasks, such as material synthesis, characterization, analysis and discovery. Here, we explore the utility of LLMs, particularly ChatGPT4, in combination with application program interfaces (APIs) in tasks of experimental design, programming workflows, and data analysis in scanning probe microscopy, using both in-house developed APIs and APIs given by a commercial vendor for instrument control. We find that the LLM can be especially useful in converting ideations of experimental workflows to executable code on microscope APIs. Beyond code generation, we find that the GPT4 is capable of analyzing microscopy images in a generic sense. At the same time, we find that GPT4 suffers from an inability to extend beyond basic analyses for more in-depth technical experimental design. We argue that an LLM specifically fine-tuned for individual scientific domains can potentially be a better language interface for converting scientific ideations from human experts to executable workflows. Such a synergy between human expertise and LLM efficiency in experimentation can open new doors for accelerating scientific research, enabling effective experimental protocols sharing in the scientific community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Stochastic multiscale flux basis for Stokes-Darcy flows

Three algorithms are developed for uncertainty quantification in modeling coupled Stokes and Darcy flows. The porous media may consist of multiple regions with different properties. The permeability is modeled as a non-stationary stochastic variable, with its log represented as a sum of local Karhunen-Loève (KL) expansions. The problem is approximated by stochastic collocation on either tensor-product or sparse grids, coupled with a multiscale mortar mixed finite element method for the spatial discretization. A non-overlapping domain decomposition algorithm reduces the global problem to a coarse scale mortar interface problem, which is solved by an iterative solver, for each stochastic realization. In the traditional domain decomposition implementation, each subdomain solves a local Dirichlet or Neumann problem in every interface iteration. To reduce this cost, two additional algorithms based on deterministic or stochastic multiscale flux basis are introduced. The basis consists of the local flux (or velocity trace) responses from each mortar degree of freedom. It is computed for each subdomain independently before the interface iteration begins. The use of the multiscale flux basis avoids the need for subdomain solves on each iteration. The deterministic basis is computed at each stochastic collocation and used only at this realization. The stochastic basis is formed by further looping over all local realizations of a subdomain's KL region before the stochastic collocation begins. It is used over multiple realizations. Numerical tests are presented to illustrate the performance of the three algorithms, with the stochastic multiscale flux basis showing significant savings in computational cost compared to the other two algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Modeling wave propagation in elastic solids via high-order accurate implicit-mesh discontinuous Galerkin methods

Here, a high-order accurate implicit-mesh discontinuous Galerkin framework for wave propagation in single-phase and bi-phase solids is presented. The framework belongs to the embedded-boundary techniques and its novelty regards the spatial discretization, which enables boundary and interface conditions to be enforced with high-order accuracy on curved embedded geometries. High-order accuracy is achieved via high-order quadrature rules for implicitly-defined domains and boundaries, whilst a cell-merging strategy addresses the presence of small cut cells. The framework is used to discretize the governing equations of elastodynamics, written using a first-order hyperbolic momentum-strain formulation, and an exact Riemann solver is employed to compute the numerical flux at the interface between dissimilar materials with general anisotropic properties. The space-discretized equations are then advanced in time using explicit high-order Runge–Kutta algorithms. Several two- and three-dimensional numerical tests including dynamic adaptive mesh refinement are presented to demonstrate the high-order accuracy and the capability of the method in the elastodynamic analysis of single- and bi-phases solids containing complex geometries.

42 ENGINEERING↗
DOE OSTI2016

Technical Note: SCUDA: A software platform for cumulative dose assessment

Purpose: Accurate tracking of anatomical changes and computation of actually delivered dose to the patient are critical for successful adaptive radiation therapy (ART). Additionally, efficient data management and fast processing are practically important for the adoption in clinic as ART involves a large amount of image and treatment data. The purpose of this study was to develop an accurate and efficient Software platform for CUmulative Dose Assessment (SCUDA) that can be seamlessly integrated into the clinical workflow. Methods: SCUDA consists of deformable image registration (DIR), segmentation, dose computation modules, and a graphical user interface. It is connected to our image PACS and radiotherapy informatics databases from which it automatically queries/retrieves patient images, radiotherapy plan, beam data, and daily treatment information, thus providing an efficient and unified workflow. For accurate registration of the planning CT and daily CBCTs, the authors iteratively correct CBCT intensities by matching local intensity histograms during the DIR process. Contours of the target tumor and critical structures are then propagated from the planning CT to daily CBCTs using the computed deformations. The actual delivered daily dose is computed using the registered CT and patient setup information by a superposition/convolution algorithm, and accumulated using the computed deformation fields. Both DIR and dose computation modules are accelerated by a graphics processing unit. Results: The cumulative dose computation process has been validated on 30 head and neck (HN) cancer cases, showing 3.5 ± 5.0 Gy (mean±STD) absolute mean dose differences between the planned and the actually delivered doses in the parotid glands. On average, DIR, dose computation, and segmentation take 20 s/fraction and 17 min for a 35-fraction treatment including additional computation for dose accumulation. Conclusions: The authors developed a unified software platform that provides accurate and efficient monitoring of anatomical changes and computation of actually delivered dose to the patient, thus realizing an efficient cumulative dose computation workflow. Evaluation on HN cases demonstrated the utility of our platform for monitoring the treatment quality and detecting significant dosimetric variations that are keys to successful ART.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Bringing OpenCL to Commodity RISC-V CPUs

The importance of open-source hardware has been increasing in recent years with the introduction of the RISC-V Open ISA. This has also accelerated the push for support of the open-source software stack from compiler tools to full-blown operating systems. Parallel computing with today’s Application Programming Interfaces such as OpenCL has proven to be effective at leveraging the parallelism in commodity multi-core processors and programmable parallel accelerators. However, to the best of our knowledge, there is currently no publicly available implementation of OpenCL targeting commodity RISC-V processors that is accessible to the open-source community. Besides opening RISC-V to the existing rich variety of scientific parallel applications, OpenCL also provides access to a unique genre of benchmarks useful in computer architecture research. In this work, we extended an Open-source implementation of OpenCL to target RISC-V CPUs. Our work not only cover commodity multi-core RISC-V processors, but also plethora of low- profile embedded RISC-V CPUs that often do not support atomic instructions or multi-threading.

Tine, Blaise↗
DOE OSTI2017

An Internet of Things Approach to Electrical Power Monitoring and Outage Reporting

The so-called Internet of Things concept has captured much attention recently as ordinary devices are connected to the Internet for monitoring and control purposes. One enabling technology is the proliferation of low-cost, single board computers with built-in network interfaces. Some of these are capable of hosting full-fledged operating systems that provide rich programming environments. Taken together, these features enable inexpensive solutions for even traditional tasks such as the one presented here for electrical power monitoring and outage reporting.

Internet of Things↗
DOE OSTI2024

Mitigating coherent loss in superconducting circuits using molecular self-assembled monolayers

In planar superconducting circuits, decoherence due to materials imperfections, especially two-level-system (TLS) defects at different interfaces, is a primary hurdle for advancing quantum computing and sensing applications. Traditional methods for mitigating TLS loss, such as etching oxide layers at metal and substrate interfaces, have proven to be inadequate due to the persistent challenge of oxide regrowth. In this work, we introduce a novel approach that employs molecular self-assembled monolayers (SAMs) to chemically bind at different interfaces of superconducting circuits. This technique is specifically tested here on coplanar waveguide (CPW) resonators, in which this method not only impedes oxide regrowth after surface etching but can also tailors the dielectric properties at different resonators interfaces. The deployment of SAMs results in a consistent improvement in the measured quality factors across multiple resonators, surpassing those with only oxide-etched resonators. The efficiency of our approach is supported by microwave measurements of multiple devices conducted at millikelvin temperatures and correlated with detailed X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) characterizations of SAM-passivated resonators. The compatibility of SAMs materials with the established fabrication techniques offers a promising route to improve the performance of superconducting quantum devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Surface tension models for a multi-material ALE code with AMR

A number of surface tension models have been implemented in a 3D multi-physics multi-material code, ALE–AMR, which combines Arbitrary Lagrangian Eulerian (ALE) hydrodynamics with Adaptive Mesh Refinement (AMR). ALE–AMR is unique in its ability to model hot radiating plasmas, cold fragmenting solids, and most recently, the deformation of molten material. The surface tension models implemented include a diffuse interface approach with special numerical techniques to remove parasitic flow and a height function approach in conjunction with a volume-fraction interface reconstruction package. These surface tension models are benchmarked with a variety of test problems. In conclusion, based on the results, the height function approach using volume fractions was chosen to simulate droplet dynamics associated with extreme ultraviolet (EUV) lithography.

42 ENGINEERING↗
DOE OSTI2020

Computationally-Aided Design of a Small-Scale Radioactive Waste Glass Melter

To provide mission support to the Hanford Waste Immobilization and Treatment Plant for the vitrification of legacy nuclear tank waste, a reduced-scale vitrification pilot system is being designed to process simulated and actual radioactive tank wastes. The tank waste will be separated into high-level waste (HLW) and low-activity waste (LAW) fractions, where the majority by mass (~90%) is LAW and by activity (>95%) is HLW. The first tank waste to be processed at the WTP will be LAW. Since Hanford tank waste and the resultant melter feed compositions are known to vary widely, pilot-scale operations are essential to identify potential problems, provide needed data, confirm assumptions, and determine impacts to full-scale melters and off-gas systems from these different feeds. In addition, the reduced-scale melter system must be capable of quickly providing results to operations without the typically high costs of radioactive operations and provide an engineering platform in close proximity to local operations staff. The objective is to produce similar process conditions to those encountered in the full-scale LAW melters and minimize the volume of radioactive waste necessary for the evaluations. To this end, melter design features are being explored to increase production without significantly increasing surface area, melter glass volumes or compromising data quality. In support of these objectives, a set of computational fluid dynamic models have been developed to provide insight into the flow patterns within these small melters and evaluate design features to increase production without significantly increasing glass inventory. Computed velocities were evaluated at the interface between the cold cap and the molten glass pool and within the bulk glass pool. A method was developed to correlate results to an estimated melt rate and down-select design features that produce the highest gains.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

RISMC Industry Application no. 1 (ECCS/LOCA) - Core Characterization Automation: Lattice Codes Interface for PHISICS/RELAP5-3D

The U.S. NRC is currently proposing rulemaking '10 CFR 50.46c' to revise the loss-of-coolant-accident (LOCA) and emergency core cooling system (ECCS) acceptance criteria to include the effects of higher burn-up on cladding performance. The key implications of this proposition are that the cladding performance cannot be evaluated in isolation anymore. Both cladding and ECCS performance need to be considered in a coupled manner. This also implies that models for cladding performance as well as LOCA methodologies will need to be updated for regulatory purposes. Furthermore, efforts need to be made to find the limiting case within the regulatory input space. The Risk-Informed Safety Margin Characterization (RISMC) Pathway, as part of the DOE Light Water Reactor Sustainability (LWRS) research and development program initialed several programs at the Idaho National Laboratory (INL) to support the industry in the transition to the new rule and to offer potential solutions to this LOCA/ECCS analysis. One of these programs is the Industry Application no. 1 (IA1). Its purpose is to provide to the plant owner/operator a vehicle to inform decisions to manage margins related to compliance with the proposed 10 CFR 50.46c rule. IA1's goal is to develop an Integrated Evaluation Model (IEM) to revisit how uncertainties are propagated across the physical disciplines and data involved, as well as well as how risks are evaluated in a LOCA under 10 CFR 50.46c. This IEM is called LOCA Tool-kit for the US (LOTUS) and it connects five major disciplines involved in LOCA analysis. The focus of LOTUS is to establish the automation interfaces among the five disciplines. LOTUS will utilize in a first step existing computer codes. The risk-informed margins management approach for IA1 will provide a means of quantifying the impact on the key LOCA analysis figures-of-merit like peak cladding temperature (PCT), equivalent cladding reacted (ECR), etc. of a change in LOCA analysis inputs. The information that the risk analysis and associated tools provide can then be used for decision-making and margin management. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Neutronics Analysis for ITER Diagnostic Generic Upper Port Plug

This paper presents new results of neutronics analysis performed for the updated design of the ITER Diagnostic Generic Upper Port Plug (DGUPP). Such analysis is performed regularly during the development of the ITER Ports design. Neutronics analysis is an important step in support of the development of ITER components irradiated by 14 MeV neutrons generated in D-T fusion thermonuclear reactions. The neutrons are born in the ITER tokamak plasma chamber and then impinge on the surrounding blanket and port plugs, after that they diffuse through shielding material of vacuum vessel components or could stream through the diagnostic channels and assembly gaps far away from plasma up to the bio-shield and in a small amount beyond it. While ITER machine is in operation it is inaccessible, after the shut-down it is planned to provide personnel access to the Upper Port Inter-Space Structure (UP ISS) behind the Port Plug via the corridors. Neutrons activate the ITER materials and those radioactive materials emit decay gammas during the shut-down causing a Shut-Down Dose Rate (SDDR) field distributed all around the activated materials. Decay gammas could also stream through the void channels. That emphasizes the need for calculation of decay gamma transport in evaluations of SDDR, which is reflected in the use of transport - activation interface code described in Section of Computational Modelling. The assessment of radiation environment (fluxes and SDDR) at DGUPP was focused on the port back-side area of UP ISS, where personnel access is planned along the ISS maintenance corridors. Minimization of SDDR at the front part of the ISS maintenance corridors was the target value for optimization of the DGUPP shielding and analysis of related neutronics effects. Following the dose ALARA (As Low As Reasonably Achievable) principle, every possibility to reduce SDDR should be investigated, emphasizing the importance of this analysis. The challenges of such analysis are inextricably connected with the engineering complexity of the ITER machine, with integration of many diagnostics systems having channels and gaps inside the ITER ports. Those gaps result in radiation streaming and negatively affect the shielding performance of the port plugs. The computational complication is caused by the need to model precisely the ITER geometry and then to run deep penetrating radiation transport in the substantially heterogenic toroidal geometry of ITER large-size tokamak, with 30 m height and diameter of its bio-shield. The whole mass of Upper Port Plug (UPP) could be up to 25 tons and it must be very precisely positioned inside the port opening in blanket and Vacuum Vessel. Facing the engineering challenges for the assembly of DGUPP, there were proposed two Project Change Requests (PCRs) No. 439 and 709 concerning the design updates of UPP/blanket interface and its remote handling.

61 RADIATION PROTECTION AND DOSIMETRY↗