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At least 1,315 records · Page 73

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DOE OSTI2023

Science-Based Acceleration of the Full Value Stream for Metal Additive Manufacturing: Expedited Powder Development and Additive Manufacturing Deployment in the Areas of Ni-Base Superalloy and Custom Alloy Powders for AM (Final Report)

The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. Production of modified nickel-based superalloys and a Ni-containing alloy based on a high entropy composition, enhanced powder production methods, and optimized AM build parameterization provided critical steps in widespread adoption of AM technology for aerospace applications, in this case. The individual backgrounds and capabilities of the Parties are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and develop a close working relationship with the Participant in the area of nickel-based powder superalloys and custom alloys and their end use.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Science-Based Acceleration of the Full Value Stream for Metal Additive Manufacturing: Expedited Powder Development and Additive Manufacturing Deployment in the Areas of Ni-Base Superalloy and Custom Alloy Powders for AM

The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. Production of modified nickel-based superalloys and a Ni-containing alloy based on a high entropy composition, enhanced powder production methods, and optimized AM build parameterization provided critical steps in widespread adoption of AM technology for aerospace applications, in this case. The individual backgrounds and capabilities of the Parties are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and develop a close working relationship with the Participant in the areas of nickel-based powder superalloys and custom alloys and their end use.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Science-Based Acceleration of the Full Value Stream for Metal Additive Manufacturing: Expedited Powder Development and Additive Manufacturing Deployment in the Areas of Ni-Base Superalloy and Custom Alloy Powders for AM

The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. Production of modified nickel-based superalloys and a Ni-containing alloy based on a high entropy composition, enhanced powder production methods, and optimized AM build parameterization provided critical steps in widespread adoption of AM technology for aerospace applications, in this case. The individual backgrounds and capabilities of the Parties are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and develop a close working relationship with the Participant in the areas of nickel-based powder superalloys and custom alloys and their end use.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Developing a Framework for Valuation of Grid Services

The electric system is rapidly evolving and growing, raising new questions about how to define and value grid services delivered by a diverse set of resources, including customer-owned assets. This report advances a service–parameter–value framework that links what a grid service does to why it matters, and how its benefits are evidenced. We build upon prior efforts (Bender et al. 2021) and extend them to include value categories (reliability, resilience, cost & access, and security) with primary and secondary tiers, service-specific value streams that explain how benefits materialize, and metrics that make valuation traceable and comparable. We apply the framework to the six core grid services defined in (Kolln et al. 2023): Frequency Response, Regulation, Reserves, Energy, Voltage Management, and Blackstart and demonstrate it on three use cases to highlight the adaptability of these value streams. Further, we outline how the framework integrates with existing tools such as asset optimization, hosting capacity and cost-benefit analysis, and propose a path to portable qualifications and consistent stacking rules for use in tariffs and filings. Finally, we identify future pathways for research and application research needs to support standardization and decision-ready comparisons across services, assets, and architectures.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2010

A Principled Kernel Testbed for Hardware/Software Co-Design Research

Recently, advances in processor architecture have become the driving force for new programming models in the computing industry, as ever newer multicore processor designs with increasing number of cores are introduced on schedules regimented by marketing demands. As a result, collaborative parallel (rather than simply concurrent) implementations of important applications, programming languages, models, and even algorithms have been forced to adapt to these architectures to exploit the available raw performance. We believe that this optimization regime is flawed. In this paper, we present an alternate approach that, rather than starting with an existing hardware/software solution laced with hidden assumptions, defines the computational problems of interest and invites architects, researchers and programmers to implement novel hardware/software co-designed solutions. Our work builds on the previous ideas of computational dwarfs, motifs, and parallel patterns by selecting a representative set of essential problems for which we provide: An algorithmic description; scalable problem definition; illustrative reference implementations; verification schemes. This testbed will enable comparative research in areas such as parallel programming models, languages, auto-tuning, and hardware/software codesign. For simplicity, we focus initially on the computational problems of interest to the scientific computing community but proclaim the methodology (and perhaps a subset of the problems) as applicable to other communities. We intend to broaden the coverage of this problem space through stronger community involvement.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2018

Communication-avoiding optimization methods for distributed massive-scale sparse inverse covariance estimation

Across a variety of scientific disciplines, sparse inverse covariance estimation is a popular tool for capturing the underlying dependency relationships in multivariate data. Unfortunately, most estimators are not scalable enough to handle the sizes of modern high-dimensional data sets (often on the order of terabytes), and assume Gaussian samples. To address these deficiencies, we introduce HP-CONCORD, a highly scalable optimization method for estimating a sparse inverse covariance matrix based on a regularized pseudolikelihood framework, without assuming Gaussianity. Our parallel proximal gradient method uses a novel communication-avoiding linear algebra algorithm and runs across a multi-node cluster with up to 1k nodes (24k cores), achieving parallel scalability on problems with up to ≈819 billion parameters (1.28 million dimensions); even on a single node, HP-CONCORD demonstrates scalability, outperforming a state-of-the-art method. We also use HP-CONCORD to estimate the underlying dependency structure of the brain from fMRI data, and use the result to identify functional regions automatically. The results show good agreement with a clustering from the neuroscience literature.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2018

Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance Estimation.

Across a variety of scientific disciplines, sparse inverse covariance estimation is a popular tool for capturing the underlying dependency relationships in multivariate data. Unfortunately, most estimators are not scalable enough to handle the sizes of modern high-dimensional data sets (often on the order of terabytes), and assume Gaussian samples. To address these deficiencies, we introduce HP-CONCORD, a highly scalable optimization method for estimating a sparse inverse covariance matrix based on a regularized pseudolikelihood framework, without assuming Gaussianity. Our parallel proximal gradient method uses a novel communication-avoiding linear algebra algorithm and runs across a multi-node cluster with up to 1k nodes (24k cores), achieving parallel scalability on problems with up to ~819 billion parameters (1.28 million dimensions); even on a single node, HP-CONCORD demonstrates scalability, outperforming a state-of-the-art method. We also use HP-CONCORD to estimate the underlying dependency structure of the brain from fMRI data, and use the result to identify functional regions automatically. The results show good agreement with a clustering from the neuroscience literature.

Koanantakool, Penporn↗

DOE OSTI2022

Development of fast-running eighth core nodal solution

A fast-running, eighth-core solution technique has been developed for the quick core calculations in ANC, the Westinghouse core analysis code based on the nodal expansion method, and the BEACON{sup TM} Core Monitoring System (BEACON). This technique, referred to as 'Fast Eighth' (Fast8), enables users to obtain satisfactory macroscopic core calculation results such as reactivity, axial offset and assembly power much more quickly than calculations performed in the standard full-core or quarter-core geometry. Fast8 uses three techniques: folding the radial geometry into eighth-core geometry, reducing the axial geometry into a coarse axial mesh geometry, and smearing the spacer grids into nodes on-the-fly after the first calculation in the standard geometry. These geometry adjustments in Fast8 contribute to the reduction of the number of neutronic and material nodes while maintaining the reaction rates in each node. The axial mesh condition dependency in Fast8 is investigated in a xenon transient calculation in single assembly geometry, and the Fast8 maximum axial mesh size is determined based on these results. Fast8 is then applied to the load swing calculation, and the results are compared with the reference, full-core geometry, solution. The critical boron concentration and axial offset of Fast8 show good agreement with the reference solutions, and that Fast8 is a good technique for obtaining macroscopic core calculation results in significantly shorter time. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2011

Reservoir Engineering for Unconventional Gas Reservoirs: What Do We Have to Consider?

The reservoir engineer involved in the development of unconventional gas reservoirs (UGRs) is required to integrate a vast amount of data from disparate sources, and to be familiar with the data collection and assessment. There has been a rapid evolution of technology used to characterize UGR reservoir and hydraulic fracture properties, and there currently are few standardized procedures to be used as guidance. Therefore, more than ever, the reservoir engineer is required to question data sources and have an intimate knowledge of evaluation procedures. We propose a workflow for the optimization of UGR field development to guide discussion of the reservoir engineer's role in the process. Critical issues related to reservoir sample and log analysis, rate-transient and production data analysis, hydraulic and reservoir modeling and economic analysis are raised. Further, we have provided illustrations of each step of the workflow using tight gas examples. Our intent is to provide some guidance for best practices. In addition to reviewing existing methods for reservoir characterization, we introduce new methods for measuring pore size distribution (small-angle neutron scattering), evaluating core-scale heterogeneity, log-core calibration, evaluating core/log data trends to assist with scale-up of core data, and modeling flow-back of reservoir fluids immediately after well stimulation. Our focus in this manuscript is on tight and shale gas reservoirs; reservoir characterization methods for coalbed methane reservoirs have recently been discussed.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2024

Strength stability at high temperatures for additively manufactured alumina forming austenitic alloy

Several fast-spectrum nuclear reactors designed to generate high power (~450 MWe) rely on forced convection of media such as supercritical CO 2 , sodium, or liquid lead to cool the nuclear core, operating at temperatures up to 600 °C. Cost-effective, high-strength Fe-based alumina forming austenitic (AFA) alloys are a promising candidate for the fabrication of critical nuclear components. This study investigated laser powder bed fusion (LPBF) processing of an AFA alloy composition optimized for improved creep resistance. Electron microscopy revealed an elongated grain structure along the build direction with a fine sub-grain cellular structure decorated with (Cr,Fe,Nb) 23 C 6 carbide precipitates at the intercellular boundaries. Finally, at temperatures of 20–900 °C, the LPBF alloy's superior tensile properties compared to its arc-melted counterpart and other advanced steels (e.g., SS316) were attributed to the distribution of nano-sized carbide precipitates, whereas the high ductility was attributed to the LPBF alloy's elongated grain structure.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Impurity temperature screening in stellarators close to quasisymmetry

Impurity temperature screening is a favourable neoclassical phenomenon involving an outward radial flux of impurity ions from the core of fusion devices. Quasisymmetric magnetic fields lead to intrinsically ambipolar neoclassical fluxes that give rise to temperature screening for low enough $\unicode[STIX]{x1D702}^{-1}\equiv d\ln n/d\ln T$ . In contrast, neoclassical fluxes in generic stellarators will depend on the radial electric field, which is predicted to be inward for ion-root plasmas, potentially leading to impurity accumulation. Here, we examine the impurity particle flux in a number of approximately quasisymmetric stellarator configurations and parameter regimes while varying the amount of symmetry breaking in the magnetic field. For the majority of this work, neoclassical fluxes have been obtained using the SFINCS drift-kinetic equation solver with electrostatic potential $\unicode[STIX]{x1D6F7}=\unicode[STIX]{x1D6F7}(r)$ , where $r$ is a flux-surface label. Results indicate that achieving temperature screening is possible, but unlikely, at low-collisionality reactor-relevant conditions in the core. Thus, the small departures from symmetry in nominally quasisymmetric stellarators are large enough to significantly alter the neoclassical impurity transport. A further look at the magnitude of these fluxes when compared to a gyro-Bohm turbulence estimate suggests that neoclassical fluxes are small in configurations optimized for quasisymmetry when compared to turbulent fluxes.

Physics↗

DOE OSTI2012

THE CLUSTER LENSING AND SUPERNOVA SURVEY WITH HUBBLE: AN OVERVIEW

The Cluster Lensing And Supernova survey with Hubble (CLASH) is a 524-orbit Multi-Cycle Treasury Program to use the gravitational lensing properties of 25 galaxy clusters to accurately constrain their mass distributions. The survey, described in detail in this paper, will definitively establish the degree of concentration of dark matter in the cluster cores, a key prediction of structure formation models. The CLASH cluster sample is larger and less biased than current samples of space-based imaging studies of clusters to similar depth, as we have minimized lensing-based selection that favors systems with overly dense cores. Specifically, 20 CLASH clusters are solely X-ray selected. The X-ray-selected clusters are massive (kT > 5 keV) and, in most cases, dynamically relaxed. Five additional clusters are included for their lensing strength ({theta}{sub Ein} > 35'' at z{sub s} = 2) to optimize the likelihood of finding highly magnified high-z (z > 7) galaxies. A total of 16 broadband filters, spanning the near-UV to near-IR, are employed for each 20-orbit campaign on each cluster. These data are used to measure precise ({sigma}{sub z} {approx} 0.02(1 + z)) photometric redshifts for newly discovered arcs. Observations of each cluster are spread over eight epochs to enable a search for Type Ia supernovae at z > 1 to improve constraints on the time dependence of the dark energy equation of state and the evolution of supernovae. We present newly re-derived X-ray luminosities, temperatures, and Fe abundances for the CLASH clusters as well as a representative source list for MACS1149.6+2223 (z 0.544).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

HPC4Energy Final Report : GE Energy

Power System planning tools are being used today to simulate systems that are far larger and more complex than just a few years ago. Advances in renewable technologies and more pervasive control technology are driving planning engineers to analyze an increasing number of scenarios and system models with much more detailed network representations. Although the speed of individual CPU’s has increased roughly according to Moore’s Law, the requirements for advanced models, increased system sizes, and larger sensitivities have outstripped CPU performance. This computational dilemma has reached a critical point and the industry needs to develop the technology to accurately model the power system of the future. The hpc4energy incubator program provided a unique opportunity to leverage the HPC resources available to LLNL and the power systems domain expertise of GE Energy to enhance the GE Concorda PSLF software. Well over 500 users worldwide, including all of the major California electric utilities, rely on Concorda PSLF software for their power flow and dynamics. This pilot project demonstrated that the GE Concorda PSLF software can perform contingency analysis in a massively parallel environment to significantly reduce the time to results. An analysis with 4,127 contingencies that would take 24 days on a single core was reduced to 24 minutes when run on 4,217 cores. A secondary goal of this project was to develop and test modeling techniques that will expand the computational capability of PSLF to efficiently deal with systems sizes greater than 150,000 buses. Toward this goal the matrix reordering implementation time was sped up 9.5 times by optimizing the code and introducing threading.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2017

FY17 Status Report for the Development of Infrared Thermography for In-Pile Fuel Behavior Applications

Under a Department of Energy Office of Nuclear Energy (DOE-NE) initiative to develop in-pile instrumentation, an activity has been initiated to develop an infrared thermography (IRT) approach for in-reactor monitoring of fuel behaviors. The project will focus on leveraging mature, mainstream IRT techniques for use on nuclear fuel systems inside a nuclear reactor through unique adaptations for remote applications – an extremely challenging engineering and measurement objective – never before accomplished in-pile. To this end, some of the most important issues to be addressed include identifying an optimal IRT configuration (of many possible) and components for detecting specific structural evolutions such as fuel cracking and fuel void formation and migration; developing a long distance imaging system to transmit high resolution infrared images from a small specimen surface in the harsh environment of a reactor core to a IR camera or other detector array; and ultimately, integrating a complete experimental system to create a full in-reactor experiment. This document provides an overview of potential in-pile applications of IRT, a brief overview of IRT techniques, a detailed research plan and schedule for the project, and a summary of activities that have been initiated in the closing months of fiscal year 2017.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing: Expedited Powder Development in the Area of Aluminum Powder Alloys and their End Use (Final Report)

The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. A new aluminum (Al) alloy based on high entropy composition, enhanced powder production, and optimized AM build parameterization provided a critical step in widespread adoption of AM technology for automotive applications, in this case. The individual backgrounds and capabilities of the Parties are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and develop a close working relationship with the Participant in the area of aluminum powder alloys and their end use.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment in the Area of Aluminum Alloys for AM Powder Production (Final Report)

The overall Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment (“X-P4AM”) project objective is to drastically reduce the time-to-market barriers for new additive alloys of interest in automotive and aerospace applications, through computational alloy design with rapid screening and down- selection via synthesis of candidate alloys with rapid solidification. The project will also refine the technology in high pressure gas atomization to improve the production of commercial quantities of selected powders with high powder yields and enhanced powder quality. A new aluminum (Al) alloy based on an Al-Ce-X composition, enhanced powder production, and optimized AM build parameterization provided a critical step in widespread adoption of AM technology for automotive applications, in this case. The individual background and capabilities of the Party are ideally suited to the successful execution of this work. The included work enhanced the Contractors’ AM capabilities, a core competency of the Contractors, and developed a close working relationship with the Participant in the area of aluminum powder alloys and their end use.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Science-based Acceleration of the Full Value Stream for Metal Additive Manufacturing (AM): Expedited Powder Development and Additive Manufacturing Deployment in the Area of Aluminum Powder Alloys

36 MATERIALS SCIENCE↗

DOE OSTI2024

A Field-Deployable Magnetic Resonance Imaging Rhizotron for Modeling and Enhancing Root Growth and Biogeochemical Function

A collaborative team from Texas A&M AgriLife Research, ABQMR Inc., the Soil Health Institute, the Athinoula A. Martinos Center for Biomedical Imaging, and NIST developed low-field magnetic resonance imaging (LF-MRI) instrumentation capable of imaging intact soil-root systems. The system measured root biomass, architecture, 3D mass distribution, and growth rates, providing a non-destructive means to evaluate ideal plant characteristics based on root metrics. It also successfully generated three-dimensional images of soil water content, a key property influencing root growth and exploration. Operating much like an MRI used in a medical setting, the system functioned in field conditions without damaging plants, overcoming the limitations of traditional methods such as trenching, soil coring, and root excavation. Over the course of the project, the team designed and built three functional prototype systems. These prototypes provided new insights into root–water–soil interactions that drive processes such as nutrient uptake, water use, and carbon management. This information contributed to efforts to optimize plants for carbon sequestration without sacrificing economic yield. The project also supported the identification of desirable traits for energy sorghum, including high root growth rates, more vertical root angles, and enhanced drought resilience under water-limiting conditions.

09 BIOMASS FUELS↗