SEARCH · Engineering Papers

Results for “Integrated Simulation”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 217 records · Page 12

All sources NASA NTRS DOE OSTI

DOE OSTI2023

An AI-driven microstructure optimization framework for elastic properties of titanium beyond cubic crystal systems

Materials design aims to identify the material features that provide optimal properties for various engineering applications, such as aerospace, automotive, and naval. One of the important but challenging problems for materials design is to discover multiple polycrystalline microstructures with optimal properties. This paper proposes an end-to-end artificial intelligence (AI)-driven microstructure optimization framework for elastic properties of materials. In this work, the microstructure is represented by the Orientation Distribution Function (ODF) that determines the volume densities of crystallographic orientations. The framework was evaluated on two crystal systems, cubic and hexagonal, for Titanium (Ti) in Joint Automated Repository for Various Integrated Simulations (JARVIS) database and is expected to be widely applicable for materials with multiple crystal systems. The proposed framework can discover multiple polycrystalline microstructures without compromising the optimal property values and saving significant computational time.

36 MATERIALS SCIENCE↗

DOE OSTI2011

Effect of air breakdown with a focusing lens on ultrashort laser ablation

The effect of air breakdown on ultrashort laser ablation is investigated in this letter using an integrated simulation method on atomistic level. The generation of air breakdown with different laser peak power densities in the range from 10{sup 13} to 10{sup 16} W/cm{sup 2} and various focusing conditions is analyzed. Air breakdown is generated directly from laser energy absorption through avalanche ionization at a high power density (over 10{sup 14} W/cm{sup 2}), while at a lower power density, air breakdown is assisted by a metal target near the focal region. The laser energy loss due to air breakdown and its effect on laser ablation are studied.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Extraction of mechanical properties of materials through deep learning from instrumented indentation

Instrumented indentation has been developed and widely utilized as one of the most versatile and practical means of extracting mechanical properties of materials. This method is particularly desirable for those applications where it is difficult to experimentally determine the mechanical properties using stress–strain data obtained from coupon specimens. Such applications include material processing and manufacturing of small and large engineering components and structures involving the following: three-dimensional (3D) printing, thin-film and multilayered structures, and integrated manufacturing of materials for coupled mechanical and functional properties. Here, we utilize the latest developments in neural networks, including a multifidelity approach whereby deep-learning algorithms are trained to extract elastoplastic properties of metals and alloys from instrumented indentation results using multiple datasets for desired levels of improved accuracy. We have established algorithms for solving inverse problems by recourse to single, dual, and multiple indentation and demonstrate that these algorithms significantly outperform traditional brute force computations and function-fitting methods. Moreover, we present several multifidelity approaches specifically for solving the inverse indentation problem which 1) significantly reduce the number of high-fidelity datasets required to achieve a given level of accuracy, 2) utilize known physical and scaling laws to improve training efficiency and accuracy, and 3) integrate simulation and experimental data for training disparate datasets to learn and minimize systematic errors. The predictive capabilities and advantages of these multifidelity methods have been assessed by direct comparisons with experimental results for indentation for different commercial alloys, including two wrought aluminum alloys and several 3D printed titanium alloys.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Integrated model predictions on the impact of substrate damage on gas dynamics during ITER burning-plasma operations

Divertor design and choice of plasma-facing materials (PFM) will be essential to the success of next-generation fusion reactors as they operate under more powerful scenarios. Understanding and controlling interactions between the plasma and PFM is essential to making these choices. Within these plasma–material interactions and especially in tungsten (W), the interplay between the most abundant plasma species (hydrogen isotopes and helium, He) with the wall material alters fuel retention. However, this interplay is yet to be sufficiently understood to confidently project fuel retention levels to future fusion devices. The paper presents a series of integrated simulations of fusion plasmas and their interaction with tungsten. Specifically, this study assesses the impact of He plasma pre-exposure on hydrogenic species retention during 100 s of burning plasma operations (BPO) in ITER. Multiple pre-exposure scenarios are considered, including sub-surface damage resulting from exposures in the linear device PISCES and from early ITER He-operation. The predictions from these consecutive He-BPO exposures show that fuel content and spatial distribution in the material are largely determined by the He-induced damage, as manifest in: (i) changes in surface temperature expected during BPO have little effect on fuel retention in the presence of He-induced damage; (ii) gas content stabilizes quickly in substrates pre-exposed in PISCES, at levels set by the concentration of pre-existing vacancies, while it continues to increase in substrates initially pristine or pre-exposed to ITER He plasmas; (iii) the presence of He and He–V clusters in the near-surface region locally increases hydrogenic retention, but decreases its permeation; this results in hydrogenic species that remain closer to the surface in pre-damaged substrates, while the bulk content is higher for initially pristine cases. In summary, the interaction and binding of D and T with the pre-existing He–V clusters modifies retention and permeation of hydrogen species during ITER BPO.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Radiative pulsed L-mode operation in ARC-class reactors

Abstract A new ARC-class, highly-radiative, pulsed, L-mode, burning plasma scenario is developed and evaluated as a candidate for future tokamak reactors. Pulsed inductive operation alleviates the stringent current drive requirements of steady-state reactors, and operation in L-mode affords ELM-free access to ∼ 90 % core radiation fractions, significantly reducing the divertor power handling requirements. In this configuration the fusion power density can be maximized despite L-mode confinement by utilizing high-field to increase plasma densities and current. This allows us to obtain high gain in robust scenarios in compact devices with P fus > 1000 MW despite low confinement. We demonstrate the feasibility of such scenarios here; first by showing that they avoid violating 0D tokamak limits, and then by performing self-consistent integrated simulations of flattop operation including neoclassical and turbulent transport, magnetic equilibrium, and radiofrequency current drive models. Finally we examine the potential effect of introducing negative triangularity with a 0D model. Our results show high-field radiative pulsed L-mode scenarios are a promising alternative to the typical steady state advanced tokamak scenarios which have dominated tokamak reactor development.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2018

Ice I h revisited: No proton tunneling observed in a quasielastic neutron scattering experiment

A large broadening (${\sim}0.4\mathrm{meV}$) of quasielastic neutron scattering (QENS) signal in ${\mathrm{H}}_{2}\mathrm{O}$ ice ${I}_{h}$ at $T=5\mathrm{K}$ was observed by Bove et al. [Phys. Rev. Lett. 103, 165901 (2009)] and explained by a model of concerted proton tunneling. This result was rather unexpected, as prior studies never showed significant mobility in water at low temperatures and ambient pressure. There were a few attempts of theoretical understanding of the effect. Recent path-integral simulations as well as quantum lattice-gauge theory supported the possibility of the collective tunneling of protons in ice ${I}_{h}$, however other studies stated that concerted tunneling in ice ${I}_{h}$ should have very low frequency. In this paper, we report on QENS measurements of ${\mathrm{H}}_{2}\mathrm{O}$ ice ${I}_{h}$ at 1.8 and 5 K by using neutron scattering spectrometers with the energy resolution similar to and four times better than the energy resolution in the original experiment of Bove and co-workers. We did not observe any QENS broadening, and the measured spectra for the ice ${I}_{h}$ and the reference vanadium sample were almost identical. Therefore, we conclude that there is no proton tunneling in ice ${I}_{h}$ at temperatures down to 1.8 K measurable on an energy scale of 3.5 ${\mu}\mathrm{eV}$ and above. Finally, the literature data on low-temperature heat capacity of ice ${I}_{h}$ support this conclusion.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

Design and Analysis of Short Period 2G-HTS Undulators

Recent advancements in second-generation high-temperature superconducting (2G-HTS) materials have opened new possibilities for superconducting undulator (SCU) technology, particularly in achieving shorter periods and higher magnetic fields. Here, this paper presents the design and analysis of a short-period, as small as 10 mm, 2G-HTS undulator, focusing on magnetic performance, mechanical force minimization, and quench protection. A force-balanced coil pack design is introduced to significantly reduce mechanical stresses on the conductors, eliminating the need for heavy support structures. Rapid prototyping techniques such as3D printing is employed to refine the design for scalability and manufacturability. Correction schemes for end-field effects are developed using a combination of 2G-HTS tapes and NbTi conductors to optimize field integrals. Simulation results demonstrated that optimized magnetic performance and enhanced mechanical stability, positioning 2G-HTS undulators as promising candidates for storage ring and free-electron based light sources.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2018

T2Well/ECO2N Version 1.0: Multiphase and Non-Isothermal Model for Coupled Wellbore-Reservoir Flow of Carbon Dioxide and Variable Salinity Water

T2Well/ECO2N is a coupled wellbore and reservoir model for simulating the dynamics of CO2 injection and leakage through wellbores. It can be seen as an extension to standard TOUGH/ECO2N V2.0, and can be applied to situations relevant to geologic CO2 storage involving upward flow (e.g., leakage) and downward flow (injection). The new simulator integrates a wellbore-reservoir system by assigning the wellbore and reservoir to two different sub-domains in which flow is controlled by appropriate physical laws. In the reservoir, we model flow using a standard multiphase Darcy flow approach. In the wellbores, we use the Drift-Flux Model and related conservation equations for describing transient two-phase non-isothermal wellbore flow of CO2-water mixtures. The mass and thermal energy balance equations are solved numerically by a finite difference scheme with wellbore heat transmission to the surrounding rock handled either semi-analytically or numerically. The momentum balance equation for the flow in the wellbore is solved numerically with a semi-explicit scheme.

Oldenburg, CurtM↗

DOE OSTI2023

Fabrication-conscious neural network based inverse design of single-material variable-index multilayer films

Multilayer films with continuously varying indices for each layer have attracted great deal of attention due to their superior optical, mechanical, and thermal properties. However, difficulties in fabrication have limited their application and study in scientific literature compared to multilayer films with fixed index layers. In this work we propose a neural network based inverse design technique enabled by a differentiable analytical solver for realistic design and fabrication of single material variable-index multilayer films. This approach generates multilayer films with excellent performance under ideal conditions. We furthermore address the issue of how to translate these ideal designs into practical useful devices which will naturally suffer from growth imperfections. By integrating simulated systematic and random errors just as a deposition tool would into the optimization process, we demonstrated that the same neural network that produced the ideal device can be retrained to produce designs compensating for systematic deposition errors. Furthermore, the proposed approach corrects for systematic errors even in the presence of random fabrication imperfections. The results outlined in this paper provide a practical and experimentally viable approach for the design of single material multilayer film stacks for an extremely wide variety of practical applications with high performance.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Accelerating Science Driven System Design With RAMP

Researchers from UC Berkeley, in collaboration with the Lawrence Berkeley National Lab, are engaged in developing an Infrastructure for Synthesis with Integrated Simulation (ISIS). The ISIS Project was a cooperative effort for “application-driven hardware design” that engages application scientists in the early parts of the hardware design process for future generation supercomputing systems. This project served to foster development of computing systems that are better tuned to the application requirements of demanding scientific applications and result in more cost-effective and efficient HPC system designs. In order to overcome long conventional design-cycle times, we leveraged reconfigurable devices to aid in the design of high-efficiency systems, including conventional multi- and many-core systems. The resulting system emulation/prototyping environment, in conjunction with the appropriate intermediate abstractions, provided both a convenient user programming experience and retained flexibility, and thus efficiency, of a reconfigurable platform. We initially targeted the Berkeley RAMP system (Research Accelerator for Multiple Processors) as that hardware emulation environment to facilitate and ultimately accelerate the iterative process of science-driven system design. Our goal was to develop and demonstrate a design methodology for domain-optimized computer system architectures. The tangible outcome is a methodology and tools for rapid prototyping and design-space exploration, leading to highly optimized and efficient HPC systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Fusion Energy Sciences Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Fusion Energy Sciences, January 27-29, 2016, Gaithersburg, Maryland

The additional computing power offered by the planned exascale facilities could be transformational across the spectrum of plasma and fusion research — provided that the new architectures can be efficiently applied to our problem space. The collaboration that will be required to succeed should be viewed as an opportunity to identify and exploit cross-disciplinary synergies. To assess the opportunities and requirements as part of the development of an overall strategy for computing in the exascale era, the Exascale Requirements Review meeting of the Fusion Energy Sciences (FES) community was convened January 27–29, 2016, with participation from a broad range of fusion and plasma scientists, specialists in applied mathematics and computer science, and representatives from the U.S. Department of Energy (DOE) and its major computing facilities. This report is a summary of that meeting and the preparatory activities for it and includes a wealth of detail to support the findings. Technical opportunities, requirements, and challenges are detailed in this report (and in the recent report on the Workshop on Integrated Simulation). Science applications are described, along with mathematical and computational enabling technologies. Also see http://exascaleage.org/fes/ for more information.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Learning Interactions in Complex Biological Systems

In this project, we developed novel methods for integrating simulation and data-driven methods to accelerate biomedical discovery. In particular, we exploit agent-based models of disease processes and deep reinforcement learning to identify potential novel multi-drug, patient-specific, and adaptive therapeutic strategies. We use the Innate Immune Response agent-based model (IIRABM) to model sepsis as a demonstration of our approach. We first calibrate the agent-based model using novel stochastic optimization algorithms develop in this project, then use the calibrated model to identify optimal cytokine mediation strategies using deep reinforcement learning (DRL). The learned policy achieves a dramatic reduction in mortality over a set of 500 simulated patients relative to standalone antibiotic therapy. Advantages of our approach are three-fold: 1) the use of simulation allows exploring therapeutic strategies beyond clinical practice and available data, 2) advances in DRL accommodate learning complex therapeutic strategies for complex biological systems, and 3) optimized treatments respond to a patient’s individual disease progression over time, therefore capturing both differences across patients and the inherent randomness of disease progression within a single patient. We hope that this work motivates both considering adaptive, personalized multi-cytokine mediation therapy for sepsis and exploiting simulation with DRL for precision medicine more broadly.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

FY20 Third Milestone Report for Advanced Techno-Economic Modeling for Geothermal Heat Pump Applications in Residential, Commercial, and Industry Buildings

This report summarizes the developments of an integrated simulation program for enabling simulation, auto-sizing, and optimization of geothermal heat pump systems. This work fulfills the following FY20 third milestone for WBS 2.5.5.3: Advanced Techno-Economic Modeling for Geothermal Heat Pump Applications in Residential, Commercial, and Industry Building.

15 GEOTHERMAL ENERGY↗

DOE OSTI2015

FUSION ENERGY SCIENCES WORKSHOP ON PLASMA MATERIALS INTERACTIONS: Report on Science Challenges and Research Opportunities in Plasma Materials Interactions

The realization of controlled thermonuclear fusion as an energy source would transform society, providing a nearly limitless energy source with renewable fuel. Under the auspices of the U.S. Department of Energy, the Fusion Energy Sciences (FES) program management recently launched a series of technical workshops to “seek community engagement and input for future program planning activities” in the targeted areas of (1) Integrated Simulation for Magnetic Fusion Energy Sciences, (2) Control of Transients, (3) Plasma Science Frontiers, and (4) Plasma-Materials Interactions aka Plasma-Materials Interface (PMI). Over the past decade, a number of strategic planning activities1-6 have highlighted PMI and plasma facing components as a major knowledge gap, which should be a priority for fusion research towards ITER and future demonstration fusion energy systems. There is a strong international consensus that new PMI solutions are required in order for fusion to advance beyond ITER. The goal of the 2015 PMI community workshop was to review recent innovations and improvements in understanding the challenging PMI issues, identify high-priority scientific challenges in PMI, and to discuss potential options to address those challenges. The community response to the PMI research assessment was enthusiastic, with over 80 participants involved in the open workshop held at Princeton Plasma Physics Laboratory on May 4-7, 2015. The workshop provided a useful forum for the scientific community to review progress in scientific understanding achieved during the past decade, and to openly discuss high-priority unresolved research questions. One of the key outcomes of the workshop was a focused set of community-initiated Priority Research Directions (PRDs) for PMI. Five PRDs were identified, labeled A-E, which represent community consensus on the most urgent near-term PMI scientific issues. For each PRD, an assessment was made of the scientific challenges, as well as a set of actions to address those challenges. No prioritization was attempted amongst these five PRDs. We note that ITER, an international collaborative project to substantially extend fusion science and technology, is implicitly a driver and beneficiary of the research described in these PRDs; specific ITER issues are discussed in the background and PRD chapters. For succinctness, we describe these PRDs directly below; a brief introduction to magnetic fusion and the workshop process/timeline is given in Chapter I, and panelists are listed in the Appendix.

Maingi, Rajesh↗

DOE OSTI2018

Picking the Best from the All-Resources Menu: Advanced Tools for Resource Planning

Introduces the wide range of electric power systems modeling types and associated questions they can help answer. The presentation focusses on modeling needs for high levels of Distributed Energy Resources (DERs), renewables, and inverter-based technologies as alternatives to traditional centralized power systems. Covers Dynamics, Production Cost/QSTS, Metric Assessment, Resource Planning, and Integrated Simulations with examples drawn from NREL's past and on-going projects. Presented at the McKnight Foundation workshop on 'An All-Resources Approach to Planning for a More Dynamic, Low-Carbon Grid' exploring grid modernization options to replace retiring coal plants in Minnesota.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Extraction of mechanical properties of materials through deep learning from instrumented indentation

Instrumented indentation has been developed and widely utilized as one of the most versatile and practical means of extracting mechanical properties of materials. This method is particularly desirable for those applications where it is difficult to experimentally determine the mechanical properties using stress–strain data obtained from coupon specimens. Such applications include material processing and manufacturing of small and large engineering components and structures involving the following: three dimensional (3D) printing, thin-film and multilayered structures, and integrated manufacturing of materials for coupled mechanical and functional properties. Here, we utilize the latest developments in neural networks, including a multifidelity approach whereby deep-learning algorithms are trained to extract elastoplastic properties of metals an d alloys from instrumented indentation results using multiple datasets for desired levels of improved accuracy. We have established algorithms for solving inverse problems by recourse to single, dual, and multiple indentation and demonstrate that these algorithms significantly outperform traditional brute force computations and function-fitting methods. Moreover, we present several multifidelity approaches specifically for solving the inverse indentation problem which 1) significantly reduce the number of high-fidelity datasets required to achieve a given level of accuracy, 2) utilize known physical and scaling laws to improve training efficiency and accuracy, and 3) integrate simulation and experimental data for training disparate datasets to learn and minimize systematic errors. The predictive capabilities and advantages of these multifidelity methods have been assessed by direct comparisons with experimental results for indentation for different commercial alloys, including two wrought aluminum alloys and several 3D printed titanium alloys.

3D printed materials, stress-strain behavior, mult↗

DOE OSTI2016

Development of SiC-based Cladding for Accident Tolerant Fuels

Fuels and core structures in current light water reactors (LWR's) are vulnerable to catastrophic failure in severe accidents. This vulnerability is attributed primarily to the rapid oxidation kinetics of zirconium alloys in a water vapor environment at very high temperatures. Alternative materials to zirconium alloys with reduced oxidation kinetics are sought to enable enhanced accident-tolerant fuels and cores. Among the candidate alternatives, silicon carbide (SiC) - based materials, in particular continuous SiC fiber-reinforced SiC matrix ceramic composites (SiC/SiC composites), are considered to offer outstanding safety benefits. The primary objective of this work is to provide with updated overviews of the concepts, development status, and future prospect for the SiC-based accident-tolerant fuel (ATF) claddings. A systematic technology evaluation program plan was developed and updated to review the technologies needed, to identify and analyze critical gaps, and to lay out a road-map toward establishing key technologies. The technology review and the gap analysis in this exercise were based on an early study and community workshops. Many of the technical gaps identified are related with the three key feasibility issues: hydrothermal corrosion, mechanical failure, and fuel compatibility. Additional performance issues including accident-tolerance features and fission product retention during the normal operation have also been identified. The program plan was designed to systematically address the key gap issues and is formulated in a work breakdown structure. Simultaneously, the plan is being established to set a technical program for advancing the technological readiness levels of concept non-specific essential technologies in three top-level categories of Design and Failure, Environmental Effects, and Off-normal Behavior. The execution of the program plan is in progress across the U.S. Department of Energy laboratories, industries, universities, and international collaborators. The critical issues for SiC composite-based fuel cladding concepts were found to be related to the performance in the normal operation. In particular, radiation-assisted hydrothermal corrosion and the gaseous fission product (FP) retention are identified to be the most critical issues. The primary ORNL concept pursues the use of dual-purpose coating on the SiC composite cladding wall to mitigate the corrosion and the gas permeation issues at the same time, whereas the alternative approaches such as the dense monolithic SiC protective layer combined with the water chemistry control may be feasible. Surface metallization through variations of physical vapor deposition and electroplating are being demonstrated. The FP gas retention is an issue associated with the cracking for the ceramic matrix composite cladding. To establish the probabilistic failure behavior, the relevant test methods were developed in ASTM Committee C28 on Advanced Ceramics. Toward the end-plugging technology development, various methods for joining SiC to SiC had been developed and tested for mechanical properties, irradiation effects, and environmental effects. Multiple methods including the pressureless transient eutectic SiC joining and CVD-based SiC joining were identified particularly promising. In addition, a multi-physics, three-dimensional finite element-based modeling is in progress toward an integrated simulation of the SiC composite-cladded fuel evolutions. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2021

Model based co-simulation platform for integrated building system control and design optimization

Both steady-state and dynamic simulations have been widely used by HVAC&R industry to support product/equipment development for decades. Steady-state simulation focuses on the system mass, energy and momentum balance of an equilibrium state. It is based on high-fidelity components models, and thus is suitable for system and component design optimization. Dynamic simulation studies the system transient response and is generally used for controls development and verification. It usually does not require rigorous component models of high accuracy because 1) the commonly used PID control is feedback control whose control performance evaluation doesn’t require high fidelity system/plant model; 2) high-fidelity dynamic model significantly increases the number of equations and variables and creates tremendous challenge for math solver. For supervisory control, transactive control or optimization of an integrated building system, the HVAC&R equipment is often one of the sub-components to be controlled. High-fidelity equipment models are required for accurately evaluating control strategies. In addition, building equipment manufacturers have developed a lot of high-fidelity steady-state equipment/component models per their expertise. Thus, a platform that can integrate OEM high-fidelity steady-state model with dynamic building simulation and/or electric power system & grid simulation to support the development and verification of supervisory control for integrated building systems is necessary. In this study, ORNL’s heat pump design tool (HPDM) is utilized to develop a co-simulation platform for supervisory control and optimization in integrated building systems. It is based on a model that integrates high-fidelity steady-state simulation equipment models with dynamic building simulation. A practical case of using the proposed co-simulation platform to develop and evaluate the supervisory control and optimization is presented and discussed.

Sun, Jian↗