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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Single Carrier Modulation Resource Allocation for Massive MIMO with Virtual Antennas

Today’s Massive MIMO cellular operation is dominated by orthogonal frequency division multiplexing (OFDM) modulation. One of the advantages of OFDM is the flexibility to carve up the available spectrum into resource blocks (RBs) that can operate adjacent to one another. Massive MIMO adds spatial multiplexing layers on top of the RBs, enabling the simultaneous operation of dozens of UEs. Cyclic prefixed single carrier modulation (CP-SCM) is an alternative to OFDM that also benefits from massive MIMO and is useful as an OFDM alternative in specific scenarios. However, until recently, no resource allocation method has been proposed for CP-SCM. In this paper, we present a CP-SCM resource allocation scheme using virtual antennas in a massive MIMO time domain duplexed scenario. By creating several virtual antennas for each physical antenna, the benefits of massive MIMO are achieved with a smaller physical antenna count. Resources are quantized into data streams, and each user can be assigned a variable number of simultaneous streams. This paper presents a detailed development and analysis of multi-stream processing (MSP) for both uplink detection and downlink precoding. We also introduce heterogeneous MSP, where CP-SCM and OFDM signals can be processed in the same MSP framework.

5G and beyond communications↗
DOE OSTI2021

Geothermal Energy and Resilience in Arctic Countries

The eight Arctic countries have diverse energy systems but can be split into two distinct groups based on energy characteristics. The first group includes countries which are heavily gridconnected (Iceland, Norway, Sweden, and Finland); the second group includes countries with some grids as well as an abundance of remote microgrids, particularly in their more northern regions (Canada, Russia, the United States [Alaska], and Greenland). The primary energy source for both heat and power in remote communities is almost exclusively diesel. Geothermal energy is currently used in all eight Arctic countries, providing heat and sometimes electricity at utility scales and at the microgrid scale. However, the availability of geothermal resources is poorly defined in Arctic countries. We reframe geothermal heat and power as integrated energy systems, asking the question: are integrated geothermal energy systems - where available and economic - resilient solutions for communities in Arctic countries? Resilience attributes of integrated geothermal energy systems are identified, with a focus on microgrids and small-scale applications.

arctic energy↗
DOE OSTI2018

Economical and Environmentally Benign Extraction of Rare Earth Elements (REES) from Coal & Coal Byproducts

This final report provides a complete summary of the activities, results, analytical discussion, and overall evaluation of the project titled “Economical and Environmentally Benign Extraction of Rare Earth Elements (REES) from Coal & Coal Byproducts” under DOE Award Number DE-FE-0027155 that started in March 2016 and ended December 2017. Fly ash was selected as the coal-byproduct source material due to fact that it is readily available with no need for extensive methods to obtain the material, it is produced in large quantities (>50 million tons per year) and had REE concentrations similar to other coal-byproducts. The selected fly ash used throughout this project was from the Mill Creek power generating facility operated by Louisville Gas and Electric located in Louisville, KY and was subjected to a variety of physical and chemical characterization tests. Results from fusion extractions showed that the selected fly-ash had a TREE+Y concentration of 480 ppm with critical REEs concentration of 200 ppm. The fly ash had an outlook ratio of 1.25 and an estimated value of $16-$18 worth of salable REEs per 1-tonne of fly ash. Additional characterizations by optical evaluation, QEMSCAN, XRD, size fractionation, and SEM analysis showed the fly ash consisted of small glassy spherules with a size range between 1 to 110 µm (ave. diam. of 13 um), was heterogeneous in chemical composition (main crystalline phases: aluminum oxides and iron oxides) and was primarily an amorphous material (75 to 80%). A simple stepped approach was completed to estimate the total REE resource quantity. The approach included REE characterization of the representative samples, evaluation of fly-ash availability, and final determination estimated resource availability with regards to REE grade on a regional and national scale. This data represents the best available information and is based upon the assumptions that the power generating facility where the fly-ash was obtained will use the same coal sources (actual mines were identified), the coal materials will have relatively consistent REE concentrations, and the REE extraction process developed during this project can achieve 42% REE recovery (validated and confirmed). Calculations indicated that the estimated REE resource is approximately 175,000 tonnes with a current estimated value of $3,330MM. The proposed REE extraction and production process developed during this project used four fundamental steps; 1) fly-ash pretreatment to enhance REE extraction, 2) REE extraction by acid digestion, 3) REE separation/concentration by carbon adsorption and column chromatography, and 4) REE oxide production. Secondary processing steps to manage process residuals and additional processing techniques to produce value-added products were incorporated into the process during the project. These secondary steps were not only necessary to manage residuals, but also provided additional revenue streams that offset operational and capital expenditures. The process produces one value product stream (production of zeolite Na-P1), a solids waste stream, and one liquid stream that met RCRA discharge requirements. Based upon final design criteria and operational parameters, the proposed system could produce approximately 200 grams of REOs from 1-tonne of fly-ash, thereby representing a TREE+Y recovery of 42% (project target of > 25%). A detailed economic model was developed to evaluate both CAPEX and OPEX estimates for systems with varying capacities between 100 kg to 200 tonnes of fly ash processed per day. Using a standard system capacity of 10 tonne/day system, capital costs were estimated at $88/kg fly ash while operating costs were estimated at approximately $450/kg fly ash. This operating cost estimate includes a revenue of $495/tonne of fly ash processed from the value-added product produced from the system (zeolite Na-P1). Although operating cost savings due to zeolite production were significant, the capital + operating cost for a 10 tonne system was more expensive than the total dollar value of REEs present in the fly ash material. Specifically, the estimated cost per 1-tonne of fly ash treated is approximately $540 while the estimated value of REEs in the fly ash is $18-$20/tonne. This is an excessive difference showing that the proposed process is not economically feasible strictly on the basis of REE revenue compared to extraction costs. Although the current proposed system does not produce sufficient quantities of REEs or additional revenue sources to offset operational and capital costs, supplementary factors including US strategic concerns, commercial demands, and defense department requirements must be factored. At this time, the process developed during this project provides foundational information for future development of simple processes that require low capital investment and one that will extract a valuable quality and quantity of REE oxides from industrial waste.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Portable, heterogeneous ensemble workflows at scale using libEnsemble

libEnsemble is a Python-based toolkit for running dynamic ensembles, developed as part of the DOE Exascale Computing Project. The toolkit utilizes a unique generator–simulator–allocator paradigm, where generators produce input for simulators, simulators evaluate those inputs, and allocators decide whether and when a simulator or generator should be called. The generator steers the ensemble based on simulation results. Generators may, for example, apply methods for numerical optimization, machine learning, or statistical calibration. libEnsemble communicates between a manager and workers. Flexibility is provided through multiple manager–worker communication substrates each of which has different benefits. These include Python’s multiprocessing, mpi4py, and TCP. Multisite ensembles are supported using Balsam or Globus Compute. We overview the unique characteristics of libEnsemble as well as current and potential interoperability with other packages in the workflow ecosystem. We highlight libEnsemble’s dynamic resource features: libEnsemble can detect system resources, such as available nodes, cores, and GPUs, and assign these in a portable way. These features allow users to specify the number of processors and GPUs required for each simulation; and resources will be automatically assigned on a wide range of systems, including Frontier, Aurora, and Perlmutter. Such ensembles can include multiple simulation types, some using GPUs and others using only CPUs, sharing nodes for maximum efficiency. We also describe the benefits of libEnsemble’s generator–simulator coupling, which easily exposes to the user the ability to cancel, and portably kill, running simulations based on models that are updated with intermediate simulation output. We demonstrate libEnsemble’s capabilities, scalability, and scientific impact via a Gaussian process surrogate training problem for the longitudinal density profile at the exit of a plasma accelerator stage. In conclusion, the study uses gpCAM for the surrogate model and employs either Wake-T or WarpX simulations, highlighting efficient use of resources that can easily extend to exascale.

Dynamic ensembles↗
DOE OSTI2015

Characterization of demand response in the commercial, industrial, and residential sectors in the United States

The goal of our study is to provide an overview of demand response (DR) technologies, including standards and end uses, in the United States and describe resource characteristics and the attributes of 14 specific DR resources in the U.S. commercial, residential, and industrial sectors. The attributes reviewed for the end uses being considered are response frequency, response time, the need for and impacts of energy pre- or recharge, the cost of enabling a resource to respond to a load-curtailment signal, and the magnitude of load curtailment in a given resource. We also describe controls and communications technologies that can enable end uses to participate in DR programs. The characterization was initially developed as a foundational work to quantify hourly availability of DR resources from the selected end uses followed by a multi-laboratory effort that quantified DR's value within the Western Interconnection.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Comparison of a Full-Scale and a 1:10 Scale Low-Speed Two-Stroke Marine Engine Using Computational Fluid Dynamics

International marine shipping is a growing component of international trade; a vast majority of all the world’s goods are being transported on large ocean-going vessels. The International Maritime Organization (IMO) introduced the Energy Efficiency Design Index in 2013, a regulatory framework of associated metrics for reducing emissions of CO 2 per tonne-mile from shipping by approximately 10% each decade. Therefore, decarbonizing the maritime sector requires the development of new fuel sources. Because of the extremely large physical size of the internal combustion engines present in shipping vessels, experimental iterative development of the engine and fuel system is cost-prohibitive. Thus, the ability to perform combustion system development in a scaled platform that can be more easily operated and modeled computationally is of interest. To that end, scaling relationships are needed to translate the results from a smaller engine to a larger counterpart. Scaling studies to date have been restricted to low scaling ratios, four-stroke light-duty engines, and under-resolved computational fluid dynamic simulations that likely do not accurately capture the physics of scaling. In this work, computational models of a 1:10 scale and a full-scale two-stroke crosshead low-speed marine engine were created and validated against experiments obtained in a real 1:10 scale engine installed at Oak Ridge National Laboratory. Further, due to the large size of the full-scale engine, the model required large high-performance computing resources to be evaluated. The availability of high-performance computing resources at the Department of Energy’s Leadership Computing Facilities is an enabler of the current work. The results of the small- and large-scale engine simulations were compared to analyze the effectiveness of the appropriate scaling laws under these extreme scaling ratio conditions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Marine Renewable Energy Applications for Restorative Ocean Farming: Kelp

Kelp farming and kelp forest restoration have both been proposed as a solution to locally decrease the impacts of ocean acidification and eutrophication, often with co-benefits to other forms of aquaculture and mariculture. Compared to global markets, the kelp industry in the United States is still in its early phases, with the first commercial kelp farm founded in Casco Bay, Maine in 2010. Since then, interest and effort in kelp production has been increasing, with farms now present in Maine, New Hampshire, Connecticut, Rhode Island, Massachusetts, New York, Washington, and Alaska. Many research projects are underway in the United States to explore benefits of 3D ocean farming, tackle logistical problems of working in the ocean, autonomous farming, and explore viable end uses for kelp products. In seaweed farming, to remove the stored carbon or excess nutrients from the system, the biomass needs to be harvested at the optimal time to avoid the release of CO 2 that comes with decomposition. Timing of the harvest is also important for maximum crop yield, which can vary based on the final product. Additional monitoring needs can include a variety of water quality metrics, growth measurements, and visuals to ensure the health of the farm, comply with permits, support operations and maintenance functions. The variables measured may vary by desired end use of the product, location of farm, and operational design. Monitoring all of these parameters requires specialized devices that can be costly and challenging to maintain. Monitoring devices often face power and logistical constraints that could prevent kelp farmers from adopting these technologies or receiving accurate, efficient monitoring to assess ecosystem benefits and valuation. Marine energy has been identified as a possible power source for these devices. This project investigates the power needs for conducting kelp farm environmental monitoring compared with the available marine energy resource to evaluate if locally generated ocean energy could provide a solution to these monitoring challenges and benefit kelp farmers. This process was structured as follows: 1. Define what data is needed for farmers and their communities through desk research and interviews with end users. 2. Identify sensors and power requirements currently in use or available for commercial purchase. 3. Analyze current kelp and other mariculture farm locations for the potential marine energy resource. 4. Analyze farm designs and associated structures to make recommendations for marine energy design. 5. Quantify value that investment in sensors could provide in terms of carbon credit possibilities.

09 BIOMASS FUELS↗
DOE OSTI2021

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Third Edition

As the world looks for low-carbon sources of energy, solar power stands out as the single most abundant energy resource on Earth. Harnessing this energy is the challenge for this century. Photovoltaics, solar heating and cooling, and concentrating solar power (CSP) are primary forms of energy applications using sunlight. These solar energy systems use different technologies, collect different fractions of the solar resource, and have different siting requirements and production capabilities. Reliable information about the solar resource is required for every solar energy application. This holds true for small installations on a rooftop as well as for large solar power plants; however, solar resource information is of particular interest for large installations because they require substantial investment, sometimes exceeding 1 billion dollars in construction costs. Before such a project is undertaken, the best possible information about the quality and reliability of the fuel source must be made available. That is, project developers need reliable data about the solar resource available at specific locations, including historic trends with seasonal, daily, hourly, and (preferably) subhourly variability to predict the daily and annual performance of a proposed power plant. Without these data, an accurate financial analysis is not possible. Additionally, with the deployment of large amounts of distributed photovoltaics, there is an urgent need to integrate this source of generation to ensure the reliability and stability of the grid. Forecasting generation from the various sources will allow for larger penetrations of these generation sources because utilities and system operators can then ensure stable grid operations. Developed by the foremost experts in the field who have come together under the umbrella of the International Energy Agency’s Solar Heating and Cooling Task 46, this handbook summarizes state-of-the-art information about all these topics.

14 SOLAR ENERGY↗
DOE OSTI2020

stovertillage2019-bc1040-060

As part of the Billion Ton resource assessment projections created in 2016 (see https://www.energy.gov/sites/prod/files/2016/12/f34/2016_billion_ton_rep...), this dataset was produced and titled a "base-case" scenario. This broader dataset provided an updated assessment of the potential economic availability of biomass resources from agricultural lands reported at the farmgate under conservative assumptions. Crop residues quantified in this dataset include corn stover, cereal (wheat, oats, and barley) straws, and sorghum stubble. We have isolated corn stover in this dataset. What is the purpose of the data set? Why were the data collected?* Per request for use in subsequent research, we have isolated corn stover in 2019 from the broader base-case projections and have provided tillage classification details from this projection. Tillage classification assumptions in this scenario allow a moderate deviation from a baseline situation (using historic CTIC data on tillage type used in counties for each crop). This dataset allowed moderate flexibility of farmers to put land into another tillage type (no till, conservation till, and reduced till) where a higher net present value was calculated.

Davis, Maggie R.↗
DOE OSTI2012

Price Projections of Feedstocks for Biofuels and Biopower in the U.S.

The economic availability of biomass resources is a critical component in evaluating the commercial viability of biofuels. To evaluate projected farmgate prices and grower payments needed to procure 295 million dry Mg (325 million dry tons) of biomass in the U.S. by 2022, this research employs POLYSYS, an economic model of the U.S. agriculture sector. A price-run simulation suggests that a farmgate price of $58.42 Mg{sup -1} ($53.00 dry ton{sup -1}) is needed to procure this supply, while a demand-run simulation suggests that prices of $34.56 and $71.61 Mg{sup -1} ($30.00 and $62.00 dry ton{sup -1}) in are needed in 2012 and 2022, respectively, to procure the same supply, under baseline yield assumptions. Grower payments are reported as farmgate price minus resource-specific harvest costs.

09 BIOMASS FUELS↗
DOE OSTI2017

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Second Edition

As the world looks for low-carbon sources of energy, solar power stands out as the single most abundant energy resource on Earth. Harnessing this energy is the challenge for this century. Photovoltaics, solar heating and cooling, and concentrating solar power (CSP) are primary forms of energy applications using sunlight. These solar energy systems use different technologies, collect different fractions of the solar resource, and have different siting requirements and production capabilities. Reliable information about the solar resource is required for every solar energy application. This holds true for small installations on a rooftop as well as for large solar power plants; however, solar resource information is of particular interest for large installations, because they require substantial investment, sometimes exceeding 1 billion dollars in construction costs. Before such a project is undertaken, the best possible information about the quality and reliability of the fuel source must be made available. That is, project developers need reliable data about the solar resource available at specific locations, including historic trends with seasonal, daily, hourly, and (preferably) subhourly variability to predict the daily and annual performance of a proposed power plant. Without this data, an accurate financial analysis is not possible. Additionally, with the deployment of large amounts of distributed photovoltaics, there is an urgent need to integrate this source of generation to ensure the reliability and stability of the grid. Forecasting generation from the various sources will allow for larger penetrations of these generation sources because utilities and system operators can then ensure stable grid operations. Developed by the foremost experts in the field who have come together under the umbrella of the International Energy Agency's Solar Heating and Cooling Task 46, this handbook summarizes state-of-the-art information about all the above topics.

14 SOLAR ENERGY↗
DOE OSTI2017

Hydrodynamic Design Optimization and Wave Tank Testing of a Self-Reacting Two-Body Wave Energy Converter

As worldwide energy consumption continues to increase, so does the demand for renewable energy sources. The total available wave energy resource for the United States alone is 2,640 TWh/yr; nearly two thirds of the 4,000 TWh of electricity used in the United States each year. It is estimated that nearly half of that available energy is recoverable through wave energy conversion techniques. In this thesis, a two-body ‘point absorber’ type wave energy converter with a mechanical power-takeoff is investigated. The two-body wave energy converter extracts energy through the relative motion of a floating buoy and a neutrally buoyant submerged body. Using a linear frequency-domain model, analytical solutions of the optimal power and the corresponding power-takeoff components are derived for the two-body wave energy converter. Using these solutions, a case study is conducted to investigate the influence of the submerged body size on the absorbed power of the device in regular and irregular waves. Here it is found that an optimal mass ratio between the submerged body and floating buoy exists where the device will achieve resonance. Furthermore, a case study to investigate the influence of the submerged body shape on the absorbed power is conducted using a time-domain numerical model. Here it is found that the submerged body should be designed to reduce the effects of drag, but to maintain relatively large hydrodynamic added mass and excitation force. To validate the analytical and numerical models, a 1/30th scale model of a two-body wave energy converter is tested in a wave tank. The results of the wave tank tests show that the two-body wave energy converter can absorb nearly twice the energy of a single-body ‘point absorber’ type wave energy converter.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Logistics simulation of a remediation effort for a hypothetical radiological contamination scenario

To mitigate the effects following a large-scale nuclear or radiological material release in an urban environment and to expedite recovery, the Integrated Wash-Aid Treatment Emergency Reuse System (IWATERS) was developed. IWATERS consists of three operations: washing contaminated surfaces with an ionic wash solution, collecting, and treating the contaminated wash solution on-site to remove contaminants, and reusing the treated solution throughout operations to preserve the clean water resource. This study develops a framework to simulate the logistics of IWATERS deployment, thereby gaining an understanding of the timeline for decontamination operations. For this purpose, the Analysis of Mobility Platform and GoldSim were leveraged for a hypothetical contamination scenario covering 65,200 m 2 of an urban center. The framework reveals that remediation progress is limited by several resources, notably the availability of vermiculite, a reactive clay that is required to treat the contaminated wash solution. Further, this study also presents how the simulation approach can be used to characterize alternatives to reduce the influence of limited resources on operational progress. Overall, this work lays the foundation for evaluating different decontamination methods through detailed logistics simulation, i.e., by refining simulation assumptions and expanding the range of scenarios the simulation can depict.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2015

Delta: Data Reduction for Integrated Application Workflows

Integrated Application Workflows (IAWs) run multiple simulation workflow components concurrently on an HPC resource connecting these components using compute area resources and compensating for any performance or data processing rate mismatches. These IAWs require high frequency and high volume data transfers between compute nodes and staging area nodes during the lifetime of a large parallel computation. The available network band-width between the two areas may not be enough to efficiently support the data movement. As the processing power available to compute resources increases, the requirements for this data transfer will become more difficult to satisfy and perhaps will not be satisfiable at all since network capabilities are not expanding at a comparable rate. Furthermore, energy consumption in HPC environments is expected to grow by an order of magnitude as exascale systems become a reality. The energy cost of moving large amounts of data frequently will contribute to this issue. It is necessary to reduce the volume of data without reducing the quality of data when it is being processed and analyzed. Delta resolves the issue by addressing the lifetime data transfer operations. Delta removes subsequent identical copies of already transmitted data during transfers and restores those copies once the data has reached the destination. Delta is able to identify duplicated information and determine the most space efficient way to represent it. Initial tests show about 50% reduction in data movement while maintaining the same data quality and transmission frequency.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Enhanced Shuffling and Fuel Management Capability in PHISICS code

PHISICS (Parallel and Highly Innovative Simulation for the INL Code System) code is a reactor physics package, under development at the Idaho National Laboratory since few years ago. This package is aimed to provide a modern analysis and design tool for reactor physics investigation. It has been designed with the idea to maximize accuracy for a given availability of computational resources and to give state of the art tools and advanced solutions to the nuclear engineer. This is obtained through the implementation of several different solution algorithms and meshing approaches among which the user will be able to choose, in order to balance his computational resources and accuracy needs. PHISICS has been coded following an object-oriented mindset, evolving in a complete modular design; this determines remarkable simplifications in the development of modules by different teams and future maintenance. The different modules currently available in the PHISICS package are a nodal and semi-structured transport core solver (INSTANT), a depletion and burn-up module (MRTAU), a time-dependent solver (Time Integrator), a cross section interpolation and manipulation framework (MIXER), a criticality search module (Criticality) and a fuel management and shuffling component (Shuffle), which is the subject of this paper, having been recently redesigned and improved. PHISICS is fully parallelized to take advantage of multi-core workstations and High Performance Computing systems (4 to 500 cores). In addition, the package is coupled with the system safety analysis code RELAP5-3D. Using the coupling between PHISICS and RELAP5-3D is possible to drive a accurate dynamic analysis switching between a steady state and time-dependent calculations. The main purpose of this paper is to present the redesigned module Shuffle, within the PHISICS tool-kit. All the functionality limitations of the old design have been faced and resolved. The functionality of the module has been fully tested and represented a key development in order to face a challenging problems, such as the revision of the requirements in 10 CFR 50.46C rules, focused on the ECCS rule in LOCA scenarios. The renovated Shuffle module is now completed and represents a key feature of the PHISICS for fuel cycle studies and optimization. Currently it is possible to perform multi-cycle full core analysis including accounting for the thermal-hydraulic feedback by the coupling with RELAP-5. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

RACB: Resource Aware Cache Bypass on GPUs

Caches are universally used in computing systems to hide long off-chip memory access latencies. Unlike CPUs, massive threads running simultaneously on GPUs bring a tremendous pressure on memory hierarchy. As a result, the limitation of cache resources becomes a bottleneck for a GPU to exploit thread-level parallelism (TLP) and memory-level parallelism (MLP) and achieve high performance. In this paper, we propose a mechanism to bypass L1D and L2 cache based on the availability of cache resources. Our proposed mechanism is based on the observation that a huge number of stalls coming from limited cache resources prohibit GPUs from providing a higher throughput. So we propose Resource Aware Cache Bypass (RACB) with minor hardware changes to eliminate such stalls to improve performance. We examine the effectiveness of this approach when applied to L1D and L2 cache separately as well as together. Evaluation results with NVIDIA Computing SDK show that RACB generally improves performance the most when applied to both L1D and L2 cache, which is up to 88.05% and on an average of 16.73%, additionally, energy is saved up to 22.35% and on an average of 5.88% with minor hardware overheads.

Dai, Hongwen↗
DOE OSTI2021

Using Pilot Jobs and CernVM File System for Simplified Use of Containers and Software Distribution

High Energy Physics (HEP) experiments entail an abundance of computing resources, i.e. sites, to run simulations and analyses by processing data. This requirement is fulfilled by local batch farms, grid sites, private/commercial clouds, and supercomputing centers via High Throughput Computing (HTC). The growing needs of such experiments and resources being prone to trends of heterogeneity make it difficult for physicists to handle these resources directly. Additionally, HEP collaborations heavily rely on data and software releases, typically in the order of tens of gigabytes, while conducting simulations and analyses. Hence, aspects of scalability, reliability, and maintenance become crucial with regards to the distribution of the necessary data and software stack. The GlideinWMS [4] framework helps with the resource management problem by using pilot jobs, aka Glideins, to provision reliable elastic virtual clusters. Glideins are submitted to unreliable heterogeneous resources which are validated and customized by the Glideins to make the worker nodes available for end-user job execution. On the other hand, the CernVM File System (CernVM-FS or CVMFS) [1] helps with data distribution. It is a write-once, read-everywhere filesystem used to deploy scientific software to thousands of nodes on a worldwide distributed computing infrastructure. CVMFS is based on the Hyper Text Transfer Protocol and has been widely used within the particle physics community for (1) distributing experiment software and data such as calibrations, and (2) facilitating containerization by efficiently hosting container images along with providing containerization software, especially Singularity [3] GlideinWMS relies on CVMFS installed locally on the computing resources to satisfy the experiments' software needs. This requires system administrators' effort to install and maintain CVMFS at the sites and limits the use of sites, especially HPC resources, that do not have CVMFS installed. This poster presents a solution, taking advantage of Glideins to provide CVMFS at most sites without the need for a local installation. Doing so expands the pool of resources available for HEP experiments and reduces the effort of system administrators for current resources. Additionally, the proposed solution allows GlideinWMS to also start Singularity [3], a containerization software that can run unprivileged, on sites where neither CVMFS nor Singularity are available, including HPC sites. The benefits provided by this solution are: (1) lower overhead for site administrators in that they have less software to install, (2) an expanded pool of resources that run user jobs with easy access to software and data provided by CVMFS, thus making life easier for the scientists, and (3) improved flexibility to use HPC resources by enabling GlideinWMS pilot jobs to support HPC sites.

Urs, Namratha↗