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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Wind Energy High-Fidelity Model Verification and Validation Roadmap

The development of a next generation high-fidelity modeling code for wind plant applications is one of the central focus areas of the U.S. Department of Energy Atmosphere to Electrons (A2e) initiative. The code is based on a highly scalable framework, currently called Nalu-Wind. One key aspect of the model development is a coordinated formal validation program undertaken specifically to establish the predictive capability of Nalu-Wind for wind plant applications. The purpose of this document is to define the verification and validation (V&V) plan for the A2e high-fidelity modeling capability. It summarizes the V&V framework, identifies code capability users and use cases, describes model validation needs, and presents a timeline to meet those needs.

17 WIND ENERGY↗
DOE OSTI2023

BEYONDPLANCK III. Commander3

We describe the computational infrastructure for end-to-end Bayesian cosmic microwave background (CMB) analysis implemented by the BeyondPlanck Collaboration. The code is called Commander3. It provides a statistically consistent framework for global analysis of CMB and microwave observations and may be useful for a wide range of legacy, current, and future experiments. The paper has three main goals. Firstly, we provide a high-level overview of the existing code base, aiming to guide readers who wish to extend and adapt the code according to their own needs or re-implement it from scratch in a different programming language. Secondly, we discuss some critical computational challenges that arise within any global CMB analysis framework, for instance in-memory compression of time-ordered data, fast Fourier transform optimization, and parallelization and load-balancing. Thirdly, we quantify the CPU and RAM requirements for the current BEYONDPLANCK analysis, finding that a total of 1.5 TB of RAM is required for efficient analysis and that the total cost of a full Gibbs sample for LFI is 170 CPU-hrs, including both low-level processing and high-level component separation, which is well within the capabilities of current low-cost computing facilities. The existing code base is made publicly available under a GNU General Public Library (GPL) license.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Identification and quantification of multinuclear Cu active sites derived from monomeric Cu moieties for dry NO oxidation over Cu-SSZ-13

The identification and quantification of multinuclear Cu-oxo cations in Cu-zeolites is a challenge amidst the dynamic nature of Cu ions in Cu-zeolites. Herein, we synthesized Cu-SSZ-13 zeolites containing varying densities of monomeric Cu cations (Z 2 Cu and ZCuOH, where Z represents an anionic site on the zeolite framework). The number of Cu-oxo cations, quantified using carbon monoxide temperature programmed reduction (CO-TPR), quadratically increased with increasing ZCuOH density, evidencing that proximal ZCuOH sites are precursors to Cu-oxo dimers. We also find that dehydrated proximal ZCuOH with overlapping diffusion radii of at most 0.5 nm can form Cu-oxo dimers. CO-TPR also revealed the presence of three distinct pools (i.e types) of Cu-oxo dimers; these pools catalyze dry NO oxidation at different turnover rates, with the fastest pool 2 to 30 times faster than the slowest pool. Finally, from reaction kinetics and rate law analysis, we also proposed a cohesive dry NO oxidation mechanism and demonstrated that nitrates detected by in situ FTIR are a spectator species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Dynamically Exploring the QCD Matter at Finite Temperatures and Densities: A Short Review

We provide a concise review on recent theory advancements towards full-fledged (3+1)D dynamical descriptions of relativistic nuclear collisions at finite baryon density. Heavy-ion collisions at different collision energies produce strongly coupled matter and probe the QCD phase transition at the crossover, critical point, and first-order phase transition regions. Dynamical frameworks provide a quantitative tool to extract properties of hot QCD matter and map fireballs to the QCD phase diagram. Outstanding challenges are highlighted when confronting current theoretical frameworks with current and forthcoming experimental measurements from the RHIC beam energy scan programs.

Physics↗
DOE OSTI2022

Uncertainty-Informed Operation Coordination in a Water-Energy Nexus

The widespread deployment of smart heterogeneous technologies and the growing complexity in our modern society calls for effective coordination of the interdependent lifeline networks. In particular, operation coordination of electric power and water infrastructures is urgently needed as the water system is one of the most energy-intensive networks, an interruption in which may quickly evolve into a dramatic societal concern. This paper develops a novel analytic for uncertainty-aware day-ahead operation optimization of the interconnected power and water systems (PaWS). Joint probabilistic constraint (JPC) programming is employed to capture the uncertainties in wind resources and water demand forecasts. The proposed integrated stochastic model is presented as a non-linear non-convex optimization problem, where the non-linear hydraulic constraints in the water network are linearized using piece-wise linearization technique, and the non-convexity is efficiently tackled with a solution methodology to convert the proposed model with JPCs to a tractable mixed-integer linear programming (MILP) formulation that can be quickly solved to optimality. Here, the suggested framework is applied to a 15-node commercial-scale water network jointly operated with a power transmission system using a modified IEEE 57-bus test system. The numerical results demonstrate the of the proposed stochastic framework, resulting in cost reduction (13% on average when compared to the traditional setting) and energy saving of the integrated model under different realizations of uncertain renewable energy sources (RESs) and water demand scenarios. Additionally, the scalability of the proposed model is tested on a modified IEEE 118-bus test system connected to five water networks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Flutter

The following repositories are a set of libraries that are needed for applications that are being developed for users of the Accelerator control system. The programming language used is Dart and for the user interface use the Flutter framework. URL for code repositories: - https://github.com/fermi-ad/flutter-controls-core - https://github.com/fermi-ad/flutter-controls-plotting - https://github.com/fermi-ad/flutter-controls-auth - https://github.com/fermi-ad/flutter-gql-acsys - https://github.com/fermi-ad/flutter-gql-faas - https://github.com/fermi-ad/dart-gql-acsys - https://github.com/fermi-ad/dart-explicit-imports - https://github.com/fermi-ad/dart-gql-faas - https://github.com/fermi-ad/design-system

Neswold, Rich [Fermi National Accelerator Laborato↗
DOE OSTI2021

OpenOA: An Open-Source Codebase For Operational Analysis of Wind Farms

OpenOA is an open source framework for operational data analysis of wind energy plants, implemented in the Python programming language. OpenOA provides a common data model, high level analysis workflows, and low-level convenience functions that engineers, analysts, and researchers in the wind energy industry can use to facilitate analytics workflows on operational data sets. OpenOA contains documentation, worked out examples in Jupyter notebooks, and a corresponding example dataset from the Engie Renewable’s La Haute Borne Dataset.

17 WIND ENERGY↗
DOE OSTI2021

Thermal Energy Storage Model Development within the Integrated Energy Systems Hybrid Repository

This publication details newly created energy storage models developed within the HYBRID Modelica repository as part of the Department of Energy Office of Nuclear Energy (DOE-NE) Integrated Energy Systems (IES) program, led by Idaho National Laboratory (INL). Model development to-date includes creation of dynamic systems-level models of concrete, latent heat, and packed-bed thermocline energy storage technologies for deployment in the IES-based HYBRID repository. Models are developed using the latest publicly available data and incorporate the possibility of control strategy inclusion for use with the existing IES modeling, analysis, and optimization toolset. Simulations showcase the abilities of each technology to cyclically charge and discharge when exposed to time-varying boundary conditions. In addition, low-level surrogate models for some of the thermal energy storage technologies were created using Python. These lower order Python files are much cheaper to run (i.e., computationally faster) and thus operate well when incorporated within the stochastic optimization problems run for the IES program. Moreover, economic data was collected for use within the INL-developed Framework for Optimization of ResourCes and Economics (FORCE). This information is incorporated within the FORCE platform. This work has resulted in creation of systems-level models for concrete, latent heat, and thermocline thermal energy storage systems with associated control systems. Now that these models are available, they can be utilized within different integrated energy park concepts to understand optimal system operation, control, and dispatching. Moreover, given the generic nature of the models, industrial partner technologies (e.g., Storworks Power, EnergyNest) can be quickly added to the repository using the existing models as a basis. Additional dynamic models for thermal energy storage concepts can be developed and added to the HYBRID repository as needed.

25 ENERGY STORAGE↗
DOE OSTI2021

Neuromorphic Graph Algorithms

Graph algorithms enable myriad large-scale applications including cybersecurity, social network analysis, resource allocation, and routing. The scalability of current graph algorithm implementations on conventional computing architectures are hampered by the demise of Moore’s law. We present a theoretical framework for designing and assessing the performance of graph algorithms executing in networks of spiking artificial neurons. Although spiking neural networks (SNNs) are capable of general-purpose computation, few algorithmic results with rigorous asymptotic performance analysis are known. SNNs are exceptionally well-motivated practically, as neuromorphic computing systems with 100 million spiking neurons are available, and systems with a billion neurons are anticipated in the next few years. Beyond massive parallelism and scalability, neuromorphic computing systems offer energy consumption orders of magnitude lower than conventional high-performance computing systems. We employ our framework to design and analyze new spiking algorithms for shortest path and dynamic programming problems. Our neuromorphic algorithms are message-passing algorithms relying critically on data movement for computation. For fair and rigorous comparison with conventional algorithms and architectures, which is challenging but paramount, we develop new models of data-movement in conventional computing architectures. This allows us to prove polynomial-factor advantages, even when we assume a SNN consisting of a simple grid-like network of neurons. To the best of our knowledge, this is one of the first examples of a rigorous asymptotic computational advantage for neuromorphic computing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Resilience Development for Electric Energy Delivery Sytems (ResDEEDS): A Tool for Power System Resilience Planning (Rev. 1)

The INL Resilience Framework is built to be customized to a particular system’s characteristics, resilience goals, and hazards that it is likely to face. The challenge with a framework that is built to be customized is that it requires more effort from the user to understand the framework and apply it correctly to a particular system. The goal of the web application described here is to automate the framework application as much as possible. Inputs from users are standardized into a common format, but the modeling platform used is a modular framework built to adapt to any system. Baseline effects from common hazards are programmed with stochastic variables to allow for quick exploration of hazard impacts, but can be customized down to component-level impact if a user desires a high level of detail and specificity.

17 WIND ENERGY↗
DOE OSTI2020

Energy-Efficient Self-Organization and Swarm Behavior in Active Matter

Living systems have the unique ability to form hierarchical assemblies, in which individual constituents can perform tasks cooperatively and emergently. Harnessing such properties is a long-standing challenge for the rational design of dynamic materials, that can respond to their environment, communicate with one another, and undergo a rapid, reversible, assembly through the transduction of energy. Recent developments in the design of smart and active colloidal building blocks have led to tremendous breakthroughs, with, for instance, the onset of synthetic photoactivated active assemblies. In this project, we develop a combined experimental, computational, theoretical and Machine Learning framework to shed light on the physical underpinnings of such assembly processes and program the assembly of smart active materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A perspective on Bayesian methods applied to materials discovery and design

For more than two decades, there has been increasing interest in developing frameworks for the accelerated discovery and design of novel materials that could enable promising and transformative technologies. The Integrated Computational Materials Engineering (ICME) program called for integrating computational tools to establish linkages along process-structure-property-performance (PSPP) chains. The Materials Genome Initiative called for integrating experiments and computations within data science frameworks as a strategy to accelerate the materials development cycle. While these frameworks and paradigms have been quite influential, traditional ICME or data science-based approaches tend to have some limitations, mainly when querying the materials space is costly and very little information is available. Bayesian methods are more suitable in this context due to their efficiency gains. To this end, the materials discovery problem is framed as a Bayesian Optimization (BO). Different examples in which BO has been applied to solve materials discovery problems are presented. The methods/examples discussed include BO under model uncertainty, multi-information source BO, multi-objective and multi-constraint BO, and batch BO. Bayesian Materials Discovery is a promising area of research that is likely to become more influential as more attention is put on autonomous materials discovery platforms. Therefore, a discussion is provided on the potential development of such methods to increase the ability of existing platforms in materials discovery. Here, the ultimate goal is to pave the way to autonomous materials discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Universal Optimization and Tighter Fidelity Bounds for Approximate Quantum Error Correction

Approximate quantum error correction (AQEC) not only dictates the performance of discrete- and continuous-variable quantum error correction codes but also serves as a unifying framework across various physical disciplines. Identifying the optimal recovery channel to maximize the entanglement fidelity via standard semidefinite programming is computationally bottlenecked by the exponentially growing number of Kraus operators with system size, rendering large-scale optimization prohibitive. While analytical near-optimal maps exist, they typically work only when the Knill-Laflamme conditions are nearly satisfied. In this Letter, we establish an efficient framework by leveraging the duality between recovery and environment decoupling. This framework yields a tighter analytical lower bound on entanglement fidelity than the conventional limit set by the transpose channel. Furthermore, by exploiting the decayed weights of noise Kraus operators, we introduce a framework based on principal component analysis to reduce the dimension. In thermal loss channels where the weights decay exponentially, our approach achieves a 33-fold computational speedup while maintaining rigorous accuracy. Our approach enables high-precision optimization for AQEC codes that were previously intractable due to the curse of dimensionality.

Wu, Jing [Fermilab] (ORCID:0000000249460732)↗
DOE OSTI2023

Extensions to the SENSEI In situ Framework for Heterogeneous Architectures

The proliferation of GPUs and accelerators in recent supercomputing systems, so called heterogeneous architectures, has led to increased complexity in execution environments and programming models as well as to deeper memory hierarchies on these systems. In this work, we discuss challenges that arise in in situ code coupling on these heterogeneous architectures. In particular, we present data and execution model extensions to the SENSEI in situ framework that are targeted at the effective use of systems with heterogeneous architectures. We then use these new data and execution model extensions to investigate several in situ placement and execution configurations and to analyze the impact these choices have on overall performance.

Loring, Burlen↗
DOE OSTI2024

IRIS: A Performance-Portable Framework for Cross-Platform Heterogeneous Computing

From edge to exascale, computer architectures are becoming more heterogeneous and complex. The systems typically have fat nodes, with multicore CPUs and multiple hardware accelerators such as GPUs, FPGAs, and DSPs. This complexity is causing a crisis in programming systems and performance portability. Several programming systems are working to address these challenges, but the increasing architectural diversity is forcing software stacks and applications to be specialized for each architecture. As we show, all of these approaches critically depend on their software framework for discovery, execution, scheduling, and data orchestration. To address this challenge, we believe that a more agile and proactive software framework is essential to increase performance portability and improve user productivity. To this end, we have designed and implemented IRIS: a performance-portable framework for cross-platform heterogeneous computing. IRIS can discover available resources, manage multiple diverse programming platforms (e.g., CUDA, Hexagon, HIP, Level Zero, OpenCL, OpenMP) simultaneously in the same execution, respect data dependencies, orchestrate data movement proactively, and provide for user-configurable scheduling. To simplify data movement, IRIS introduces a shared virtual device memory with relaxed consistency among different heterogeneous devices. IRIS also adds an automatic kernel workload partitioning technique using the polyhedral model so that it can resize kernels for a wide range of devices. Our evaluation on three architectures, ranging from Qualcomm Snapdragon to a Summit supercomputer node, shows that IRIS improves portability across a wide range of diverse heterogeneous architectures with negligible overhead.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Viable Economic Frameworks and Regulatory Barriers for Community Microgrids

Community microgrids – microgrids with more than one piece of customer- and utility-owned distribution equipment contained in the isolation boundary – are an option for providing resilience to meet targeted community and utility needs. Because multiple investors, including customers, are involved there is a lack of clarity around viable ownership models, roles and responsibilities, and compensation mechanisms. Together, these aspects describe an economic framework. To be viable, an economic framework not only needs to provide the possibility of all parties agreeing to the microgrid but also needs to meet regulatory guidelines. This report contains learnings from present-day community microgrid tariffs and programs, regulatory filings, and experiences shared within an interest group to highlight regulatory barriers to community microgrids and identify several viable economic frameworks for community microgrids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Vendor-Independent Design Requirements for a Boiling Water Reactor Safety System Upgrade

This Vendor-Independent License Amendment Request (LAR) Framework Document is a research product developed for the Idaho National Laboratory Light Water Reactor Sustainability (LWRS) Program. It was developed by MPR Associates, Inc. with technical input from LWRS and Exelon Generation personnel. To accomplish the purpose of this research, an operating plant (Limerick Generating Station [LGS]) was used as a reference to provide a concrete example and to present a "top-down" view of design concepts consistent with functional requirements baseline documents (references X and Y) also developed for this research. While this document is written in a framework to support a complete LAR submittal, its purpose is to communicate research concepts and provide an example of how to present digital information necessary to address expectations with regard to leveraging the Alternate Review Process as provided in Digital Instrumentation and Controls Interim Staff Guidance #06, Revision 2, Licensing Process. To leverage that process, this research document presupposes that a utility would select a vendor platform which has been prequalified for safety-related by the United States Nuclear Regulatory Commission. While this document is written using the Exelon Generation Limerick Generating Station (LGS) Units 1 and 2 as a baseline, this document is a research product. This document contains no commitments and makes no binding design decisions for Exelon Generation. Exelon Generation is leveraging this research to support their in-progress LGS Plant Protection System (PPS) upgrade efforts and plans to leverage it for their Redundant Reactor Control System (RRCS) replacement. The LWRS Program appreciates the research support provided by Exelon Generation in the generation of this document.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗