Results for “Engineering - Particle accelerators” — Page 80

DOE OSTI2021

Seismic isolation: A pathway to standardized advanced nuclear reactors

Standardizing advanced nuclear reactors is a pathway to substantially reducing their overnight capital cost and achieving parity with other power sources, including renewables and fossil fuels. The seismic load case has thwarted standardization of nuclear power plants because site-specific seismic hazard and local near-surface geology has triggered soil-structure-interaction analysis, design, equipment qualification, regulatory review, and licensing, ensuring that each build is different. To achieve standardized or site-independent certified advanced reactor designs, the impact of the seismic load case on the engineering and construction cost and time must be substantially mitigated. Seismic isolation is a mature technology that has been used for more than 30 years in non-nuclear sectors to substantially reduce earthquake demands in buildings and other infrastructure. In this paper, seismic isolation is used to enable standardization of advanced reactor designs, aimed at the complete re-use of a site-independent, certified design and repeated procurement of safety-class equipment. A pathway to standardized designs using seismic isolation is demonstrated for two fundamentally different advanced reactors: a molten salt reactor and a high temperature gas reactor. Each reactor building is equipped with three specialized pieces of safety-class equipment, namely, a reactor vessel, a steam generator, and a control rod drive mechanism housing that is attached to the reactor head. Analysis is performed per ASCE and ASME standards to design the buildings and the equipment for two base conditions: conventional (fixed base) and base isolated. The impact of the seismic load case is characterized for the reinforced concrete walls in the buildings and for the equipment, measured using vessel wall thickness and horizontal accelerations. Here the analysis results show that the fixed-base buildings, designed for a site of low seismic hazard (peak ground acceleration, PGA = 0.15 g) could be constructed at a site of much greater seismic hazard (PGA = 0.7 g) if seismic base isolation is employed. Importantly, the scope of the site-specific analysis, design, and qualification would be limited to the seismic isolators and the isolated substructure, drastically reducing plant-specific engineering, review, and licensing, and time to construction start. Regulatory challenges and opportunities with standardized reactor designs are identified.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2021

Using Demanded Power and RDE Aggressiveness Metrics to Analyze the Impact of CACC Aggressiveness on Heavy Duty Platooning Power Consumption

Presently, a main mobility sector objective is to reduce its impact on the global greenhouse gas emissions. While there are many techniques being explored, a promising approach to improve fuel economy is to reduce the required energy by using slipstream effects. This study analyzes the demanded engine power and mechanical energy used by heavy-duty trucks during platooning and non-platooning operation to determine the aerodynamic benefits of the slipstream. A series of platooning tests utilizing class 8 semi-trucks platooning via Cooperative Adaptive Cruise Control (CACC) are performed. Comparing the demanded engine power and mechanical energy used reveals the benefits of platooning on the aerodynamic drag while disregarding any potential negative side effects on the engine. However, energy savings were lower than expected in some cases. It was hypothesized that the CACC may have amplified transient platooning events relative to the individual truck baseline results, hampering the potential energy savings. Therefore, the impact of the controller on the observed driving style was analyzed in detail. In order to quantify the transient operational characteristics of the experimental trials, metrics from the European Real Driving Emissions (RDE) legislation were modified to serve as metrics of aggressiveness during platooning. The metrics (v · apos)95 and Relative Positive Acceleration (RPA) were calculated for platooning and non-platooning runs. These results indicate that the CACC induces small acceleration events during platooning to retain the commanded longitudinal separation between vehicles. These small acceleration events increase following vehicle aggressiveness during platooning and prevent the following vehicles from obtaining maximum energy savings. Moreover, a correlation between the RDE metric (v · apos)95 and energy savings is developed. Hence, this work establishes the ability of RDE metrics to assess CACC impacts on platoon energy savings.

European Real Driving Emissions, RDE, greenhouse g↗

NASA NTRS2022

Application Table: A Bridge Connecting the Designing “With-The-Material” and “The-Material” Paradigms

Over the last few decades, advances in high-performance computing, new material characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. In 2016 NASA sponsored a 2040 Vision study (which appeared in 2018) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. The study envisions a cyber-physical-social ecosystem comprised of experimentally verified and validated (V & V) computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of “fit-for-purpose” materials, components, and systems. Consequently, the development of a robust information management system that incorporates (across the full life cycle) both experimental (real data) and virtual data resulting from the application of various simulation tools (at single or multiple length scales), therefore enabling the virtual design and optimization of materials throughout their processing – internal structure – property – performance envelope, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. This is particularly true when attempting to merge ICME practices with recent additive manufacturing technology which will enable production of the resulting 2040 Vision material and structural designs. At NASA Glenn Research Center we are exploring the future of material science through the use of novel characterization methodologies, high performance computing, and recently an emphasis on integrated computational materials engineering (ICME). Herein, recent efforts to incorporate an Application Table within NASA Glenn Research Center’s ICME Granta MI database is presented. The goal is to provide a place where material and structural application information/requirements can be linked so as to marry the “design the-material” and the “design-with-material” paradigms and thereby enable application-driven design and optimization of materials and structures by providing a central location that links material processing at various length scales to the application’s performance requirements. This paper discusses the specifics of this Application Table as well as best practices and key principles for the development of a robust materials information management system to enable the 2040 Vision integrated materials and structures ecosystem. Furthermore, it presents the intended role of the Application Table in the future of ICME design of “fit-for-purpose” materials, showing the need for a well-established framework that can successfully bridge the gap between the design “the material” and design “with-the-material” paradigms.

Materials↗

NASA NTRSDate not supplied

Application Table: A Bridge Connecting the Designing “With-the-Material” and “the-Material”

Over the last few decades, advances in high-performance computing, new material characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. In 2016 NASA sponsored a 2040 Vision study (which appeared in 2018) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. The study envisions a cyber-physical-social ecosystem comprised of experimentally verified and validated (V & V) computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of “fit-for-purpose” materials, components, and systems. Consequently, the development of a robust information management system that incorporates (across the full life cycle) both experimental (real data) and virtual data resulting from the application of various simulation tools (at single or multiple length scales), therefore enabling the virtual design and optimization of materials throughout their processing – internal structure – property – performance envelope, has become critical. This need is also fueled by the demands for higher efficiency in material testing; consistency, quality, and traceability of data; product design; engineering analysis; as well as control of access to proprietary or sensitive information. This is particularly true when attempting to merge ICME practices with recent additive manufacturing technology which will enable production of the resulting 2040 Vision material and structural designs. At NASA Glenn Research Center we are exploring the future of material science through the use of novel characterization methodologies, high performance computing, and recently an emphasis on integrated computational materials engineering (ICME). Herein, recent efforts to incorporate an Application Table within NASA Glenn Research Center’s ICME Granta MI database is presented. The goal is to provide a place where material and structural application information/requirements can be linked so as to marry the “design the-material” and the “design-with-material” paradigms and thereby enable application-driven design and optimization of materials and structures by providing a central location that links material processing at various length scales to the application’s performance requirements. This paper discusses the specifics of this Application Table as well as best practices and key principles for the development of a robust materials information management system to enable the 2040 Vision integrated materials and structures ecosystem. Furthermore, it presents the intended role of the Application Table in the future of ICME design of “fit-for-purpose” materials, showing the need for a well-established framework that can successfully bridge the gap between the design “the material” and design “with-the-material” paradigms.

Materials↗

DOE OSTI2023

Genomic materials design: CALculation of PHAse Dynamics

The CALPHAD system of fundamental phase-level databases, now known as the Materials Genome, has enabled a mature technology of computational materials design and qualification that has already met the acceleration goals of the national Materials Genome Initiative. Here, as first commercialized by QuesTek Innovations, the methodology combines efficient genomic-level parametric design of new material composition and process specifications with multidisciplinary simulation-based forecasting of manufacturing variation, integrating efficient uncertainty management. Recent projects demonstrated under the multi-institutional CHiMaD Design Center notably include novel alloys designed specifically for additive manufacturing. With the proven success of the CALPHAD-based Materials Genome technology, current university research emphasizes new methodologies for affordable accelerated expansion of more accurate CALPHAD databases. Rapid adoption of these new capabilities by US apex corporations has compressed the materials design and development cycle to under 2 years, enabling a new “materials concurrency” integrated into a new level of concurrent engineering supporting an unprecedented level of manufacturing innovation.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Nanochannel electrodes facilitating interfacial transport for PEM water electrolysis

Proton-exchange membrane water electrolyzers (PEMWEs) are a promising technology for green hydrogen production; however, interfacial transport behaviors are poorly understood, hindering device performance and longevity. Here, we first utilized finite-gap electrolyzer to demonstrate the possibility of proton transfer through water in PEMWEs. The measured high-frequency resistances (HFRs) exhibit a linear trend with increasing gap distance, where extrapolation shows a lower value compared with HFRs in regular zero-gap electrolyzers, indicating that ohmic resistance could be further reduced. We introduce nanochannels to facilitate mass transport, as evidenced by both liquid-fed and vapor-fed electrolysis. Nanochannel electrodes achieve a voltage reduction of 190 mV at 9 A·cm –2 compared with the Ir-PTEs without nanochannels. Furthermore, nanochannel electrodes show negligible degradation through 100,000 accelerated-stress tests and over 2,000 h of operation at 1.8 A·cm –2 with a decay rate of 11.66 μV·h –1 . These results provide new insights into localized transport dynamics for PEMWEs and highlight the significance of interfacial engineering for electrochemical devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Time domain probabilistic seismic risk analysis using ground motion prediction equations of Fourier amplitude spectra

Modeling of Fourier amplitude spectra (FAS) of seismic motions has gained much attention in engineering seismology. In the past few years, several ground motion prediction equations (GMPEs) and inter-frequency correlation structure of FAS have been established. Due to many preferable characteristics of FAS, probabilistic seismic hazard/risk analysis is rapidly changing from ergodic, spectrum acceleration Sa(T 0 )-based approach to non-ergodic, site-specific, FAS-based approach. This paper presents time domain intrusive framework for probabilistic seismic risk analysis using GMPE of FAS. Herein, methodology for time domain stochastic ground motion modeling based on GMPEs of FAS is presented in some detail. The simulated uncertain motions are modeled as a random process and represented by polynomial chaos Karhunen-Loève expansion. The random process excitations are further propagated into the uncertain structural system using Galerkin stochastic finite element method (SFEM). Probabilistic evolution of structural response is solved, and such solution is used to develop seismic risk for any damage state. The presented framework is illustrated through seismic risk analysis of a four-story building subjected to possible earthquakes from two strike slip faults. The influences of the epistemic uncertainties in source stress drop Δσ and site attenuation κ0 on seismic risk are investigated. The need for non-ergodic seismic risk analysis with source-specific and site specific characterizations is emphasized.

58 GEOSCIENCES↗

DOE OSTI2026

Q-IRIS: The Evolution of the IRIS Task-Based Runtime to Enable Classical-Quantum Workflows

Extreme heterogeneity in emerging HPC systems are starting to include quantum accelerators, motivating runtimes that can coordinate between classical and quantum workloads. We present a proof-of-concept hybrid execution framework integrating the IRIS asynchronous task-based runtime with the XACC quantum programming framework via the Quantum Intermediate Representation Execution Engine (QIR-EE). IRIS orchestrates multiple programs written in the quantum intermediate representation (QIR) across heterogeneous backends (including multiple quantum simulators), enabling concurrent execution of classical and quantum tasks. Although not a performance study, we report measurable outcomes through the successful asynchronous scheduling and execution of multiple quantum workloads. To illustrate practical runtime implications, we decompose a four-qubit circuit into smaller subcircuits through a process known as quantum circuit cutting, reducing per-task quantum simulation load and demonstrating how task granularity can improve simulator throughput and reduce queueing behavior -- effects directly relevant to early quantum hardware environments. We conclude by outlining key challenges for scaling hybrid runtimes, including coordinated scheduling, classical-quantum interaction management, and support for diverse backend resources in heterogeneous systems.

Miniskar, Narasinga Rao [ORNL] (ORCID:000000018259↗

DOE OSTI2020

An Analytical Model of Erosive Wear of BioMass Comminution Components

An analytical erosion model that relates critical process parameters (speed and impingement angle) to critical material attributes of inorganic mineral species in feedstock (density, size, aspect ratio) and substrate (hardness, toughness, and fatigue ductility) was applied to model wear in pretreatment milling operations. Results of the model were compared to experimental measurements of wear produced using the Accelerated Wear Test (AWT) rig at Idaho National Laboratory (INL). Results showed that there is good agreement between predicted and measured performance, and that a quality-by-design (QbD) tool can be developed to predict component reliability based on scientific engineering principles in lieu of trial-and-error approaches.

09 BIOMASS FUELS↗

NASA NTRS1986

Analytical determination of space station response to crew motion and design of suspension system for microgravity experiments

The objective of this investigation is to make analytical determination of the acceleration produced by crew motion in an orbiting space station and define design parameters for the suspension system of microgravity experiments. A simple structural model for simulation of the IOC space station is proposed. Mathematical formulation of this model provides the engineers a simple and direct tool for designing an effective suspension system.

Liu, F. C.↗

NASA NTRS1987

Analytical determination of space station response to crew motion and design of suspension system for microgravity experiments

The objective of this investigation is to make analytical determination of the acceleration produced by crew motion in an orbiting space station and define design parameters for the suspension system of microgravity experiments. A simple structural model for simulation of the IOC space station is proposed. Mathematical formulation of this model provides the engineers a simple and direct tool for designing an effective suspension system.

Liu, Frank C.↗

NASA NTRS1956

Initial results of a flight investigation of the wing and tail loads on an airplane equipped with a vane-controlled gust-alleviation system

Results are given of an analysis of wing and horizontal-tail spar strains measured on a twin-engine light transport airplane which was modified for the installation of a control system to alleviate airplane motions in turbulent air and thus improve passenger comfort. From a sample of the measurements obtained in flight through clear-air turbulence, normal acceleration at the airplane center of gravity was reduced 43 percent, wing main-spar bending strains were reduced, and wing-spar shear strains were increased. Horizontal-tail shear and bending strains were increased. Measurements of aerodynamic loads obtained in a pull-up with the gust-alleviation system in operation are also presented.

LOADS AND STRESSES, STRUCTURAL - DYNAMIC↗

NASA NTRS2000

Ordering Unstructured Meshes for Sparse Matrix Computations on Leading Parallel Systems

The ability of computers to solve hitherto intractable problems and simulate complex processes using mathematical models makes them an indispensable part of modern science and engineering. Computer simulations of large-scale realistic applications usually require solving a set of non-linear partial differential equations (PDES) over a finite region. For example, one thrust area in the DOE Grand Challenge projects is to design future accelerators such as the SpaHation Neutron Source (SNS). Our colleagues at SLAC need to model complex RFQ cavities with large aspect ratios. Unstructured grids are currently used to resolve the small features in a large computational domain; dynamic mesh adaptation will be added in the future for additional efficiency. The PDEs for electromagnetics are discretized by the FEM method, which leads to a generalized eigenvalue problem Kx = AMx, where K and M are the stiffness and mass matrices, and are very sparse. In a typical cavity model, the number of degrees of freedom is about one million. For such large eigenproblems, direct solution techniques quickly reach the memory limits. Instead, the most widely-used methods are Krylov subspace methods, such as Lanczos or Jacobi-Davidson. In all the Krylov-based algorithms, sparse matrix-vector multiplication (SPMV) must be performed repeatedly. Therefore, the efficiency of SPMV usually determines the eigensolver speed. SPMV is also one of the most heavily used kernels in large-scale numerical simulations.

Oliker, Leonid↗

NASA NTRS2005

Foundations of Tensor Analysis for Students of Physics and Engineering With an Introduction to the Theory of Relativity

Tensor analysis is one of the more abstruse, even if one of the more useful, higher math subjects enjoined by students of physics and engineering. It is abstruse because of the intellectual gap that exists between where most physics and engineering mathematics leave off and where tensor analysis traditionally begins. It is useful because of its great generality, computational power, and compact, easy to use, notation. This paper bridges the intellectual gap. It is divided into three parts: algebra, calculus, and relativity. Algebra: In tensor analysis, coordinate independent quantities are sought for applications in physics and engineering. Coordinate independence means that the quantities have such coordinate transformations as to leave them invariant relative to a particular observer s coordinate system. Calculus: Non-zero base vector derivatives contribute terms to dynamical equations that correspond to pseudoaccelerations in accelerated coordinate systems and to curvature or gravity in relativity. These derivatives have a specific general form in tensor analysis. Relativity: Spacetime has an intrinsic geometry. Light is the tool for investigating that geometry. Since the observed geometry of spacetime cannot be made to match the classical geometry of Euclid, Einstein applied another more general geometry differential geometry. The merger of differential geometry and cosmology was accomplished in the theory of relativity. In relativity, gravity is equivalent to curvature.

Kolecki, Joseph C.↗

NASA NTRS1994

Atmospheric Disturbance Environment Definition

Traditionally, the application of atmospheric disturbance data to airplane design problems has been the domain of the structures engineer. The primary concern in this case is the design of structural components sufficient to handle transient loads induced by the most severe atmospheric "gusts" that might be encountered. The concern has resulted in a considerable body of high altitude gust acceleration data obtained with VGH recorders (airplane velocity, V, vertical acceleration, G, altitude, H) on high-flying airplanes like the U-2 (Ehernberger and Love, 1975). However, the propulsion system designer is less concerned with the accelerations of the airplane than he is with the airflow entering the system's inlet. When the airplane encounters atmospheric turbulence it responds with transient fluctuations in pitch, yaw, and roll angles. These transients, together with fluctuations in the free-stream temperature and pressure will disrupt the total pressure, temperature, Mach number and angularity of the inlet flow. For the mixed compression inlet, the result is a disturbed throat Mach number and/or shock position, and in extreme cases an inlet unstart can occur (cf. Section 2.1). Interest in the effects of inlet unstart on the vehicle dynamics of large, supersonic airplanes is not new. Results published by NASA in 1962 of wind tunnel studies of the problem were used in support of the United States Supersonic Transport program (SST) (White, at aI, 1963). Such studies continued into the late 1970's. However, in spite of such interest, there never was developed an atmospheric disturbance database for inlet unstart analysis to compare with that available for the structures load analysis. Missing were data for the free-stream temperature and pressure disturbances that also contribute to the unStart problem.

Tank, William G.↗

DOE OSTI2021

MACHINE LEARNING BASED CHEMICAL EXPLOSIVE MODE ANALYSIS (ML-CEMA)

The software consists of a Machine Learning based Chemical Explosive Mode Analysis (ML-CEMA) tool for advanced computational flame diagnostics. CEMA, originally based on eigen-analysis of the local thermochemical system, is capable of identifying reaction fronts and limit phenomena such as auto-ignition and extinction in practical combustion systems, such as internal combustion engines and gas turbine combustors. However, the original CEMA is computationally expensive for large reaction mechanisms that are typically needed to describe fuel chemistry of practical large-hydrocarbon fuels. This novel ML-CEMA tool employs a ML technique to accelerate the eigen-analysis of the basic CEMA approach by orders of magnitude, thus making it suitable for practical fuels. In ML-CEMA,zero-dimensional (0D) reactors and one-dimensional (1D) premixed flames are first used to generate a large number of data points for neural network based ML training. The trained ML model is then used to perform CEMA prediction. This ML-CEMA tool has been demonstrated in canonical 0D and 1D configurations as well as highly-transient three-dimensional spray flames exhibiting multi-mode turbulent combustion, showing promising results. ML-CEMA, as a standalone tool, can be used for computationally-efficient diagnostics of massive datasets generated from both experiments and simulations. For example, based on spatially resolved measurements of a small set of reactive scalars(such as temperature, hydroxyl radical and formaldehyde), ML-CEMA can effectively identify flame fronts and rare events. ML-CEMA also provides a robust online or offline flame feature detection tool. When used for on-the-fly simulations, ML-CEMA further enables zone-adaptive combustion modeling, in which the predicted eigenvalue is used as a robust mode indicator for judicious assignment of locally-valid combustion models. This ML-CEMA based zone-adaptive model can lead to substantial computational cost savings when used for large-scale simulations of multi-mode combustion systems. Third Party Code Web Page to Download Code Web Page Location of Third Party License

Xu, Chao↗

DOE OSTI2026

All Systems Go: Regional Collaborations for Scaling AEC Innovation: Preprint

The high and rising cost of preserving and delivering housing in the U.S. requires changes to existing practices of finance, design, and construction. Innovative methods such as industrialized construction could offer the means to address housing undersupply while reducing delivery costs, operational costs and material waste in the building industry, but they face challenges to success and to scale. Simultaneously, construction and cleantech innovators themselves face skepticism from the traditional entrepreneurial ecosystem such as incubators and accelerators while attempting to navigate systems level challenges. To respond to this need, various public and private sector stakeholders have launched initiatives to support innovative companies. These include nonprofits such as Terner Labs and Ivory Innovations offering curated programming to architecture, engineering, and construction (AEC) startups; housing developers in Minnesota and California "bundling" multiple projects together to reach economies of scale with a consistent project team; public and private sector entities developing "catalogues" of pre-approved home designs in the U.S. and Canada. This exploratory paper documents several of these emerging ecosystem-development efforts to support innovative housing approaches, characterizing them by leading stakeholder and intervention strategy based on publicly available information. The paper finds that these initiatives share similar high level goals but vary in implementation, reflecting different stakeholder priorities, regional market and policy dynamics, and housing typologies. The early stage of these efforts offer limited data for comparing actual outcomes, but the paper highlights common qualitative themes and identifies opportunities for further research and potential coordination among these efforts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Ascribe XR v0.1.0

Ascribe XR is an immersive visualization software designed for scientists and engineers working with 3D data sets. Its key features include interactive exploration, multi-user collaboration, and flexible data import capabilities, supporting various formats such as meshes, volumes, and terrain maps. The software utilizes Godot, OpenXR and PC-VR technology to provide an immersive experience. Ascribe XR is used for data analysis, visualization, and collaboration in various fields, enabling users to gain deeper insights into complex data sets. Its advantages over similar technologies include its flexibility, customizability, and ease of use. Ascribe XR's interactive and immersive environment facilitates collaboration and accelerates the discovery process. Compared to traditional 2D visualization tools, Ascribe XR offers a more engaging and intuitive experience, allowing users to explore complex data sets in a more natural and interactive way. Its ability to support multi-user collaboration and flexible data import capabilities make it a versatile tool for various applications. Overall, Ascribe XR provides a unique combination of features, usability, and performance, making it an attractive solution for scientists and engineers working with 3D data sets.

Pandolfi, Ronald [Lawrence Berkeley National Labor↗