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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Commercialization of Distribution System Load Modeling Tool for Improved DER Interconnection Studies

Residential and commercial buildings have huge potential to contribute value to improve grid resilience by participating grid services. To reveal the significant value, it is critical to estimate the grid service capability from these buildings. Unlike the large-scale distributed energy resources such as wind and solar farms, those buildings need to participate grid services in aggregation, not by individual. Therefore, it is important to appropriately group buildings for aggregation. The load profiles in the same group will have similar characteristics at the same time step, so grid operators can send the grid service signal to the customer group with a higher chance to respond at that time step. In this paper, we develop a load profile clustering method to classify the building-level load profiles for grid service capability estimation. In our two-step clustering approach, we first calculate the total load consumption for each building, clustering the load profiles based on energy consumption level. Then, we further cluster the load profiles in each energy cluster based on the load shape. The parameter selection for each clustering step is discussed. The proposed method is applied on actual building-level load profiles, and the results have proved the effectiveness of this method.

14 SOLAR ENERGY↗
DOE OSTI2026

Cluster infall for mass calibration in the stage-IV era

The outskirts of galaxy clusters present a promising avenue for constraining cluster masses in a way that is robust to the impact of baryonic physics. We assess the accuracy to which the cluster infall regions can be used for cluster mass calibration. Building on previous work, we parametrize the velocity distribution 𝑃⁡(𝑣r,𝑣tan|𝑟,𝑀) of dark matter halos on scales 𝑟 ≥ 5⁢ℎ −1 Mpc as the product of the marginalized distribution 𝑃⁡(𝑣 r |𝑟,𝑀) and the conditional distribution 𝑃⁡(𝑣 tan |𝑣 r ,𝑟,𝑀), calibrating the radial and mass dependence of these distributions in numerical simulations. We then project our model along the line of sight to obtain accurate predictions for the distributions of line-of-sight velocities at a given projected radius and cluster mass 𝑃⁡(𝑣 LOS |𝑅,𝑀), which we can observe with spectroscopic survey data. Furthermore, with our model, we forecast that spectra from the Dark Energy Spectroscopic Instrument can constrain cluster masses with subpercent-level precision, comparable to that of stage-IV weak lensing surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Unified Communication Optimization Strategies for Sparse Triangular Solver on CPU and GPU Clusters

This paper presents a unified communication optimization framework for sparse triangular solve (SpTRSV) algorithms on CPU and GPU clusters. The framework builds upon a 3D communication-avoiding (CA) layout of Px × Py × Pz processes that divides a sparse matrix into Pz submatrices, each handled by a Px × Py 2D grid with block-cyclic distribution. We propose three communication optimization strategies: First, a new 3D SpTRSV algorithm is developed, which trades the inter-grid communication and synchronization with replicated computation. This design requires only one inter-grid synchronization, and the inter-grid communication is efficiently implemented with sparse allreduce operations. Second, broadcast and reduction communication trees are used to reduce message latency of the intra-grid 2D communication on CPU clusters. Finally, we leverage GPU-initiated one-sided communication to implement the communication trees on GPU clusters. With these nested inter- and intra-grid communication optimization strategies, the proposed 3D SpTRSV algorithm can attain up to 3.45x speedups compared to the baseline 3D SpTRSV algorithm using up to 2048 Cori Haswell CPU cores. In addition, the proposed GPU 3D SpTRSV algorithm can achieve up to 6.5x speedups compared to the proposed CPU 3D SpTRSV algorithm with Pz up to 64. Finally it is remarkable that the proposed GPU 3D SpTRSV can scale to 256 GPUs using the Perlmutter system while the existing 2D SpTRSV algorithm can only scale up to 4 GPUs.

Sao, Piyush↗
DOE OSTI2023

Novel Co 5 Cluster Based Triazole Bridged Cobalt-Fluorophosphate: Synthesis, Structure, Magnetic and Heterogeneous Catalytic Epoxidation Studies

A novel triazole bridged cobalt fluorophosphate coordination polymer with the formula {Co 5 (1,2,4-triazole) 2 (OH) 2 (PO 3 F) 4 } n has been synthesized. Single crystal X-ray studies reveal that the compound comprises of Co 5 clusters which ultimately build the whole framework, here all cobalt centers are in octahedral geometry established from continuous shape analysis. All the cobalt centers are in Co(II) oxidation state and the results are supported by the bond valence sum (BVS) calculation. The sample has been characterized by single crystal X-ray, powder X-ray, FTIR and TGA analysis. The compound was tested for olefin catalysis performance and magnetism. Magnetization measurements reveal overall antiferromagnetic interactions among the Co(II) ions. The compound is very active in the catalytic transformation of olefins to their corresponding epoxides. In conclusion, catalytic epoxidation studies reveal that cyclohexene and styrene can be converted up to 97% with almost 65% selectivity of products with higher TON numbers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Multi-mechanistic Strategies for Novel Solid Electrolytes with Superior Properties

Despite a wide range of solid electrolyte phases, most of them only exist at high temperatures. The challenge is to tailor the chemical compositions of solid electrolyte materials that yield high ionic conductivities and low activation energies at ambient temperature. This is crucial for the development of all-solid-state batteries that are both powerful and safe. Here, we report our recent works to meet this challenge by utilizing multiple mechanistic principles and clusters as the building blocks. We show that the atomic-level interactions that govern the fast-ion conduction can be optimized by incorporating polyanion dynamics, non-stoichiometry, point defects and strong ionic correlations. Specifically, two case studies of Li/Na solid electrolytes will be covered, including lithium solid electrolytes (SE) with record-high ionic conductivities at room temperature (over 100 mS/cm) and sodium SE with record-low activation energies (< 0.1 eV).

Fang, Hong↗
DOE OSTI2020

Enhancing Superionic Conductivity in Cluster-Based Sodium-Rich Antiperovskites

Sodium (Na) superionic conductors are the key to developing next-generation solid-state batteries with safety and low cost. However, most of the known Na-conductors exhibit limited ionic conductivities at room temperature (RT), hindering their practical applications. To meet the challenge, a series of Li- and Na-rich antiperovskite superionic conductors based on cluster ions (e.g. BH4- and BCl4-) have been theoretically developed [e.g. Fang et al. PNAS 114, 11046, 2017; ACS App. Mat. Inter. 11, 963, 2018]. These materials exhibit superior properties as solid electrolytes with greatly enhanced ionic conductivities at RT. One cluster-based solid electrolyte of such, Na3O(BH)4, has been successfully synthesized for the first time most recently and its measured RT ionic conductivity is well above 10-3 S/cm which is four orders of magnitude higher than that of its halogen counterparts Na3OX (X = Cl, Br, I) [Sun et al. J. Am. Chem. Soc. 141, 5640, 2019]. In this work, we aim to further enhance the ionic conductivity of the Na-superionic conductor by using chemical mixing according to the size effect. The study further shows the advantage of utilizing cluster ions as building blocks, introducing additional degrees of freedom into tuning the properties of superionic conductors.

Fang, Hong↗
DOE OSTI2025

Using Apptainer in a Pilot-based Distributed Workload

GlideinWMS is a pilot and pressure-based workload manager for distributed scientific computing. Many experiments like CMS and Fermilab’s Neutrino experiments use it to provision elastic clusters for their analysis and simulations, split into close to a million concurrent jobs. Most user jobs require containers, and the pilots use Apptainer to set up the desired platform. For the pilots that run as regular batch jobs, Apptainer is safer, lighter, and easier to use than other containerization solutions. Many images used by the pilots are expanded SIF images distributed via the CernVM-FS: this combination is very efficient. At Fermilab, for example, we store on GitHub Dockerfiles that mimic the platform in the worker nodes of local clusters. GitHub workflows build and push the images to Docker Hub, and a service periodically pulls and converts them to the expanded SIF images in the CernVM-FS, so the scientists can find a familiar environment everywhere. Apptainer has also been used to run services inside the pilot jobs, like benchmarks that characterize the worker node being used, or a Triton Inference Server that allows sharing a GPU with all the jobs that run in parallel on a node.

Mambelli, Marco [Fermilab] (ORCID:0000000294892681↗
NASA NTRSDate not supplied

Effect of Aromaticity on Soot Formation: A Reactive Molecular Dynamics Study

This study investigates the formation of soot from n-dodecane and its blend with m-xylene under pyrolytic and low-oxygen conditions with reactive molecular dynamics (MD) simulations. ReaxFF force field is used to simulate the interactions of fuel and oxygen molecules at engine-relevant conditions (2500-3500 K and 70-75 bar). Fuel molecules with carbon atom density of 0.03 g/cm 3 are dispersed into a cube and constant temperature simulations are carried out with a Nosé-Hoover thermostat. Pyrolysis of n-dodecane and the chemical pathway towards the formation of aromatic hydrocarbons are investigated. The initial pyrolysis rate of n-dodecane is observed to be slightly higher with the addition of aromatic compounds and oxygen. While the first aromatics formed from the decomposed n-dodecane are phenyl radicals at 2500 K, decomposition of the aliphatic fuel compound is observed to be necessary to build a carbon cluster, and eventually soot. Morphological properties of the created soot particles are also analyzed. The maturity, size and aromatics content of the soot particle are slightly affected with the addition of m-xylene and oxygen at 3500 K within the 3 ns simulation time possibly due the formation of larger and more condensed aromatic rings, resulting in larger soot molecules. The outcomes of this study provide important insights into the formation mechanism of soot and its morphological characteristics depending on varying fuel concentrations at pyrolysis and low oxygen engine conditions. Results of this analysis will further contribute to the understanding of contrail formation on generated soot particles originated from the combustion of different chemical components with particle chemistry matching companion experiments.

soot formation↗
DOE OSTI2021

Power Sector Cybersecurity Building Blocks

The Power Sector Cybersecurity Building Blocks, developed through the USAID-NREL Partnership and the Resilient Energy Platform, are designed to help a variety of stakeholders improve security for the electrical grid. This effort grows out of USAID and NREL's discussions with utilities around the world, as well as past cybersecurity assessments performed by NREL on dozens of utilities and government agencies, with a focus on the cybersecurity challenges faced by small and under-resourced utilities. This document outlines eleven building blocks for power sector cyber security. It functions as a guide to help organizations develop a robust, balanced cybersecurity defense program. Individually, each building block represents a cluster of related activities within cybersecurity on which an organization should focus. Using the building blocks, organizations can effectively prioritize their cybersecurity efforts to best thwart a wide range of potential cyberattacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Resilient Energy Platform. Fact Sheet: Power Sector Cybersecurity Building Blocks

The Power Sector Cybersecurity Building Blocks, developed through the USAID-NREL Partnership and the Resilient Energy Platform, are designed to help a variety of stakeholders improve security for the electrical grid. This effort grows out of USAID and NREL's discussions with utilities around the world, as well as past cybersecurity assessments performed by NREL on dozens of utilities and government agencies, with a focus on the cybersecurity challenges faced by small and under-resourced utilities. This document outlines eleven building blocks for power sector cyber security. It functions as a guide to help organizations develop a robust, balanced cybersecurity defense program. Individually, each building block represents a cluster of related activities within cybersecurity on which an organization should focus. Using the building blocks, organizations can effectively prioritize their cybersecurity efforts to best thwart a wide range of potential cyberattacks.

building blocks↗
NASA NTRS2003

A Fast Implementation of the ISOCLUS Algorithm

Unsupervised clustering is a fundamental building block in numerous image processing applications. One of the most popular and widely used clustering schemes for remote sensing applications is the ISOCLUS algorithm, which is based on the ISODATA method. The algorithm is given a set of n data points in d-dimensional space, an integer k indicating the initial number of clusters, and a number of additional parameters. The general goal is to compute the coordinates of a set of cluster centers in d-space, such that those centers minimize the mean squared distance from each data point to its nearest center. This clustering algorithm is similar to another well-known clustering method, called k-means. One significant feature of ISOCLUS over k-means is that the actual number of clusters reported might be fewer or more than the number supplied as part of the input. The algorithm uses different heuristics to determine whether to merge lor split clusters. As ISOCLUS can run very slowly, particularly on large data sets, there has been a growing .interest in the remote sensing community in computing it efficiently. We have developed a faster implementation of the ISOCLUS algorithm. Our improvement is based on a recent acceleration to the k-means algorithm of Kanungo, et al. They showed that, by using a kd-tree data structure for storing the data, it is possible to reduce the running time of k-means. We have adapted this method for the ISOCLUS algorithm, and we show that it is possible to achieve essentially the same results as ISOCLUS on large data sets, but with significantly lower running times. This adaptation involves computing a number of cluster statistics that are needed for ISOCLUS but not for k-means. Both the k-means and ISOCLUS algorithms are based on iterative schemes, in which nearest neighbors are calculated until some convergence criterion is satisfied. Each iteration requires that the nearest center for each data point be computed. Naively, this requires O(kn) time, where k denotes the current number of centers. Traditional techniques for accelerating nearest neighbor searching involve storing the k centers in a data structure. However, because of the iterative nature of the algorithm, this data structure would need to be rebuilt with each new iteration. Our approach is to store the data points in a kd-tree data structure. The assignment of points to nearest neighbors is carried out by a filtering process, which successively eliminates centers that can not possibly be the nearest neighbor for a given region of space. This algorithm is significantly faster, because large groups of data points can be assigned to their nearest center in a single operation. Preliminary results on a number of real Landsat datasets show that our revised ISOCLUS-like scheme runs about twice as fast.

Memarsadeghi, Nargess↗
DOE OSTI2018

Syntheses, structures, and luminescence of a series of novel trimetallic coordination polymers constructed by Cu-I clusters and alkaline-carboxyl- alkaline-earth building units

Seven novel trimetallic coordination polymers, namely, [Li{sub 2}SrCu{sub 2}I{sub 2}(IN){sub 4}(DMF){sub 3}]{sub n}·nDMF (1), [LiSr{sub 2}Cu{sub 2}I{sub 2}(IN){sub 5}(DMF){sub 2}]{sub n} (2), [NaSr{sub 2}Cu{sub 2}I{sub 2}(IN){sub 4}(NO{sub 3})(DMF){sub 4}]{sub n}·nDMF·0.5nH{sub 2}O (3), [NaSr{sub 2}Cu{sub 2}I{sub 2}(IN){sub 5}(DMF){sub 4}]{sub n}·3nDMF·3nH{sub 2}O (4), [Li{sub 2}BaCu{sub 2}I{sub 2}(IN){sub 4}(DMF){sub 3}]{sub n}·nDMF (5), [Li{sub 2}Ba{sub 2}Cu{sub 2}I{sub 2}(IN){sub 4}(OAc){sub 2}(DMF){sub 3}]{sub n}·nDMF·0.5nH{sub 2}O (6), [Li{sub 2}Ba{sub 2}Cu{sub 2}I(IN){sub 7}(H{sub 2}O){sub 1.5}]{sub n}·0.5nH{sub 2}O (7) (IN = isonicotinic anion, DMF = N, N-dimethylformamide) have been synthesized via solvothermal method. All of the coordination polymers were characterized by single-crystal X-ray diffraction, FT-IR spectroscopy, elemental analysis and thermogravimetric analysis. Single-crystal X-ray diffraction determinations revealed that compounds 1–7 were three dimensional frameworks. Compounds 1–6 were assembled by Cu{sub 2}I{sub 2} units and different alkaline-carboxyl- alkaline-earth rod building units with different topologies; while, compound 7 was constructed by Cu{sub 2}I units and alkaline-carboxyl- alkaline-earth honeycomb layers. The photoluminscent investigations revealed that the compounds 1, 3, 5 and 6 emitted strong yellow, while compounds 2, 4 and 7 emitted strong orange light.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1982

Neutral and charged clusters in the atmosphere - Their importance and potential role in heterogeneous catalysis

An assessment is presented of current knowledge concerning the role and importance of neutral and charged clusters in atmospheric heterogeneous catalysis, with a view to the recommendation of future studies needed for progress in the quantification of aerosol formation and catalytic reactivity. It is established that nucleation from the gaseous to the aerosol state commences via the formation of clusters among molecules participating in the phase-transformation process. Nucleation may proceed in some cases by way of the formation of prenucleation embryos, which then evolve through the energy barrier and undergo phase transformation. In other cases, cluster-cluster interaction among neutral particles or stagewise building of alternate-sign ion clusters may be important in the gas-to-particle conversion process.

Castleman, A. W., Jr.↗
DOE OSTI2020

Seismology in the Cloud: A New Streaming Workflow

Data-intensive research in seismology is experiencing a recent boom, driven in part by large volumes of available data and advances in the growing field of data science. However, there are significant barriers to processing large data volumes, such as long retrieval times from data repositories, complex data management, and limited computational resources. New tools and platforms have reduced the barriers to entry for scientific cluster computing, including the maturation of the commercial cloud as an accessible instrument for research. Here, we build a customized research cluster in the cloud to test a new workflow for large-scale seismic analysis, in which data are processed as a stream (retrieved on-the-fly and acted upon without storing), with data from the Incorporated Research Institutions for Seismology Data Management Center. We use this workflow to deploy a spectral peak detection algorithm over 5.6 TB of compressed continuous seismic data from 2074 stations of the USArray Transportable Array EarthScope network. Using a 50-node cluster in the cloud, we completed the noise survey in 80 hr, with an average data throughput of 1.7 GB per minute. By varying cluster sizes, we find the scaling of our analysis to be sublinear, due to a combination of algorithmic limitations and data center response times. The cloud-based streaming workflow represents an order-of-magnitude increase in acquisition and processing speed compared to a traditional download-store-process workflow, and offers the additional benefits of employing a flexible, accessible, and widely used computing architecture. It is limited, however, due to its reliance on Internet transfer speeds and data center service capacity, and may not work well for repeated analyses or those for which even higher data throughputs are needed. These research applications will require a new class of cloud-native approaches in which both data and analysis are in the cloud.

58 GEOSCIENCES↗
DOE OSTI2019

Tuning the electronic properties of hexanuclear cobalt sulfide superatoms via ligand substitution

Molecular clusters are attractive superatomic building blocks for creating materials with tailored properties due to their unique combination of atomic precision, tunability and functionality. The ligands passivating these superatomic clusters offer an exciting opportunity to control their electronic properties while preserving their closed shells and electron counts, which is not achievable in conventional atoms. Here we demonstrate this concept by measuring the anion photoelectron spectra of a series of hexanuclear cobalt sulfide superatomic clusters with different ratios of electron-donating and electron-withdrawing ligands, Co 6 S 8 (PEt 3 ) 6-x (CO) x (x = 0–3). We find that Co 6 S 8 (PEt 3 ) 6 has a low electron affinity (EA) of 1.1 eV, and that the successive replacement of PEt3 ligands with CO gradually shifts its electronic spectrum to lower energy and increases its EA to 1.8 eV. Density functional theory calculations reveal that the increase of EA results from a monotonic lowering of the cluster highest occupied and lowest unoccupied molecular orbitals (HOMO and LUMO). Our work provides unique insights into the electronic structure and tunability of superatomic building blocks.

Chemistry↗
DOE OSTI2019

Nailing the Peak: City-Scale, Building-Specific Load Factor and Contribution to a Utility’s Hour of Critical Generation

Maintaining electrical generation assets to meet peak demand increases the cost of providing electricity to a country’s buildings and insufficient assets can result in power outages. In order to keep reliable electricity costs low for consumers and demand charges low for utilities, there exist markets and financial incentives for limiting consumption during peak demand.The team has partnered with an electrical distributor servicing a 1,390 km2 area and 178,368 buildings with the aim of using urban-scale building energy modelling to inform business decisions necessary for the operation of their electric grid. A suite of software has been developed that allows the scalable creation of a “digital twin” for all buildings in the utility’s service area. This virtual utility area is analysed for targeted deployment of new technologies or policies to assess building-specific savings, effects on critically-loaded grid infrastructure (e.g. feeders, substations), and aggregated impact to utility-scale operations.This work leverages 15-minute data from each building to compare actual and simulated monthly peak-hour demand and assessment of the load factor for each building. Findings include market characterization via clustering of relative energy use profiles for ~180,000 buildings as well as simulation-informed savings opportunities indicating residential load factors of 0.17, commercial load factors of 0.2-0.4 depending on year of construction, and general load factors of 0.16-0.5 depending on building type.

New, Joshua↗
DOE OSTI2021

The superatomic state beyond conventional magic numbers: Ligated metal chalcogenide superatoms

The field of cluster science is drawing increasing attention due to the strong size and composition-dependent properties of clusters and the exciting prospect of clusters serving as the building blocks for materials with tailored properties. However, identifying a unifying central paradigm that provides a framework for classifying and understanding the diverse behaviors is an outstanding challenge. One such central paradigm is the superatom concept that was developed for metallic and ligand-protected metallic clusters. The periodic electronic and geometric closed shells in clusters result in their properties being based on the stability they gain when they achieve closed shells. This stabilization results in the clusters having a well-defined valence allowing them to be classified as superatoms – thus, extending the periodic table to a third dimension. This perspective focuses on extending the superatomic concept to ligated metal-chalcogen clusters that have recently been synthesized in solutions and form assemblies with counterions that have wide-ranging applications. Here we illustrate that the periodic patterns emerge in the electronic structure of ligated metal-chalcogenide clusters. The stabilization gained by the closing of their electronic shells allows for the prediction of their redox properties. Further investigations reveal how the selection of ligands may control the redox properties of the superatoms. These ligated clusters may serve as chemical dopants for two-dimensional semiconductors to control their transport characteristics. Superatomic molecules of multiple metal-chalcogen superatoms allow for the formation of nano pn junctions ideal for directed transport and photon harvesting. As a result, the perspective outlines future developments, including the synthesis of magnetic superatoms.

36 MATERIALS SCIENCE↗