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At least 289 records · Page 16

Sensing Electrical Networks Securely & Economically (SENSE)

The growing adoption of distributed energy resources (DERs) like battery energy storage systems and roof top solar/PV and the rapid penetration of electric vehicles (EVs), the electric grid is undergoing a major transformation with elevated stress on legacy grid assets. Despite a lot of expenditure to address these challenges, both in dollars and manpower, utilities have not been able to receive the value that was promised. The gains have been most visible at the transmission and substation level, especially where the main objective was improving operational and economic efficiency for the utility. Improving visibility and control at a few select points enhances the existing and established paradigm of centralized command and control. With changing load patterns, load types and the overall transition to an “active grid”, the centralized control and coordination paradigm gets challenged. To address the challenges, a new architecture and mechanism is needed, one that supports decentralized control and decision making, extracting value streams at the grid edge, particularly as the changes are fueled by transitions occurring in the distribution system. To address this, a communications and data processing platform, “GAMMA” was developed and demonstrated through the project. At the heart of the platform, are distributed, intelligent edge nodes with sensing and compute capabilities, that can record and analyze information locally. They are embedded in sensors and actuators specific to different distribution system applications. Phase 1 of the project focused on developing novel sensor technology that can be used for monitoring utility pole top distribution transformers. The sensors were designed with the objective of being low-cost, communicating with the GAMMA cloud using novel “delay-tolerant” networking using Bluetooth and a secure mobile application. They were non-intrusive in nature so that they can be installed quickly in the field, resulting in overall low cost of deployment and operations. Following the successful completion of Phase 1, the team manufactured 100 units for a field demonstration in Phase 2. The field demonstration was carried out on two real feeder systems with the local utility partner. In total, 100 sensors were installed and operated over a period of 6 months in the state of Georgia. The platform is operational end to end, with the cloud infrastructure deployed on a distributed, serverless environment that can serve multiple data streams, an analytics engine and a portal to securely view the data from multiple assets. The data collected through the GAMMA Mobile Phone app showcased the viability of the novel delay tolerant networking architecture, and the data processing algorithms developed through the course of the project, were successful in extracting important information about the overall network, improving the utility’s visibility and situational awareness in the distribution feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multi-Probe FY25 Omega EP Shot Request [Slides]

The goal of the Multi-Probe experimental campaign is to assess the feasibility of using multiple probe types (x ray, proton, neutron, and electron) in future LANL radiographic facilities. X-ray and proton platforms have been demonstrated. The first attempts at simultaneous radiography were hampered by cross talk, which was the subject of FY23 & FY24 experiments. The major goal for FY25 is to demonstrate simultaneous radiography of both static and dynamic objects.

36 MATERIALS SCIENCE↗

Geospatial Data Workflow Orchestration and Architecture

In an era characterized by explosive growth in geospatial data, the selection of appropriate technologies for data storage, processing, and orchestration is critical for organizations aiming to maintain competitive advantages. This white paper provides a comprehensive analysis of how Oak Ridge National Laboratory (ORNL) has effectively employed various cloud technologies, including containerized applications, container orchestrators, and workflow orchestrators, to develop robust geospatial data processing solutions. We explore the fundamental concepts behind these technologies and compare multiple deployment models tailored to diverse use cases. Our findings conclude that while Kubernetes has emerged as the preferred platform for truly scalable and fault-tolerant production workflows, the choice of workflow orchestration tool requires careful consideration of team needs, pipeline complexity, and deployment environments. This paper aims to serve as a strategic guide for organizations leveraging geospatial data, articulating the balance between technology choices and practical implementation to enhance workflow efficacy and scalability.

97 MATHEMATICS AND COMPUTING↗

CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics

Abstract. Microbial activity and chemical reactions in porous media depend on the local conditions at the pore scale and can involve complex feedback with fluid flow and mass transport. We present a modeling framework that quantitatively accounts for the interactions between the bio(geo)chemical and physical processes and that can integrate genome-scale microbial metabolic information into a dynamically changing, spatially explicit representation of environmental conditions. The model couples a lattice Boltzmann implementation of Navier–Stokes (flow) and advection–diffusion-reaction (mass conservation) equations. Reaction formulations can include both kinetic rate expressions and flux balance analysis, thereby integrating reactive transport modeling and systems biology. We also show that the use of surrogate models such as neural network representations of in silico cell models can speed up computations significantly, facilitating applications to complex environmental systems. Parallelization enables simulations that resolve heterogeneity at multiple scales, and a cellular automaton module provides additional capabilities to simulate biofilm dynamics. The code thus constitutes a platform suitable for a range of environmental, engineering and – potentially – medical applications, in particular ones that involve the simulation of microbial dynamics.

58 GEOSCIENCES↗

Co-simulation of transactive energy markets: A framework for market testing and evaluation

The proliferation of distributed energy resources (DER)—and the ability to intelligently control these assets—is re-defining the electrical distribution system. As the number of controllable devices rapidly expands, grid operators must determine how to incorporate these assets while delivering reliable, equitable, and affordable electricity. One possible approach is to establish distribution-level electricity markets and allow devices/aggregations of devices to participate in price establishment. While this approach purports some of the same benefits as the highly successful wholesale electricity markets (i.e., open competition, efficient price discovery, reduced communication overhead), this needs to be researched and quantified via an analysis platform that models distribution-level markets at the appropriate fidelity. Specifically, the simultaneous evaluation of market performance, DER performance, DER bidding approaches, and distribution feeder power quality requires modeling that spans multiple technical areas. Co-simulation has emerged as a powerful tool in addressing this type of problem, where outputs depend on a range of underlying areas of expertise and associated models. In this paper we describe a solution, as implemented in the HELICS co-simulation platform, where we include (1) high fidelity house models, (2) intelligent bidding agents, (3) a modular market integration/design, and (4) a distribution feeder model. We then present a case study where we test two different market designs: (1) a pseudo-wholesale double-blind auction, and (2) an asynchronous matching market. In this work, the markets are run under two DER penetration levels and economic results are compared to full retail net energy metering and avoided cost net metering scenarios that bookend current approaches to remuneration of DER participation. We show the potential for transactive markets to provide increased value for most customers relative to net metering (and all customers relative to avoided cost scenarios) while decreasing costs for the utility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Fabrication of a novel 3D-printed perfusion bioreactor for complex cell culture models

We introduce a novel fabrication method for developing a 3D-printed perfusion bioreactor (3D-PBR) to facilitate the in situ growth and differentiation of human bone marrow (BM)-derived mesenchymal stem cells (MSCs) while enabling coculture with vascular cells. To recapitulate human physiology, in vitro platforms must incorporate several key features of their native target organ. This often entails a supportive 3D architecture for growing and differentiating multiple human cell types in situ under perfusion. Other essential characteristics include reproducibility, ease of customization, and biocompatibility. Our 3D-PBR combines these features and was fabricated using a biocompatible resin-based polymer, which was 3D-printed, followed by the addition of a permeable membrane to create a coculture microenvironment. MSCs were encapsulated in a collagen-fibrin gel alongside human endothelium within the 3D-PBR. The physical cues that our 3D-PBR provided facilitated the differentiation of MSCs into specific lineages, such as adipocytes and osteoblasts. Immunohistochemistry images demonstrated that cells grown in the 3D-PBR exhibited more physiologically relevant BM perivascular niche markers compared to static culture models. Our method utilizes emerging 3D printing techniques and alternative materials, departing from traditional PDMS-based soft lithography. These advancements in fabrication further enhance in vitro platforms for diverse cell culture models and vascular permeability assays.

59 BASIC BIOLOGICAL SCIENCES↗

Lead Isotope Fingerprinting of Nanoscale Mineral Particles via Single Particle Inductively Coupled Plasma Mass Spectrometry

Determining lead (Pb) isotopic ratios is of broad interest across chemical disciplines for source tracing and age determinations, but the technique is inherently limited when multiple sources of Pb are present in a single sample. Single particle methods offer a solution to directly resolve multiple distinct isotopic ratios within individual samples. In this study, single particle inductively coupled plasma-mass spectrometry (spICP-MS) was performed using time-of-flight (TOF) and multicollector (MC)-based platforms to measure the Pb isotopic composition of individual nanoscale particles. Distinct Pb isotope ratios were measured in particles from four powdered galena samples of different origins (average single-particle 206Pb/207Pb ratios ranging from 0.91 to 1.28) using both the TOF and the MC-based platforms. Differentiation of galena particles in a mixture (liberated grains and those hosted in a silicate matrix) was possible due to detecting their unique multielemental fingerprints. The differing behavior of the two galena samples during digestion was investigated; undigested galena particles trapped within silicate minerals were detected using spICP-MS, which has implications for Pb recovery in bulk-scale isotopic analysis. The multinuclide detection capability of the ICP-TOF-MS instrument allowed for the simultaneous detection of secondary constituent elements within the nanoparticles and the identification of multiple populations of isotopically distinct Pb-bearing particles in a copper ore sample, whereas the increased sensitivity of the MC instrument enabled quantification of 204Pb, allowing differentiation using multiple isotopic ratios. A single particle isotope ratio analysis module was developed within an open-source spICP-TOF-MS data processing platform, enabling its adoption across chemical disciplines.

Goodman, Aaron J. [University of Montreal, Quebec,↗

Field Validation of a Grid-Interactive Efficient Building Software Solution

The U.S. General Services Administration's (GSA's) Green Proving Ground (GPG) program, in partnership with the National Laboratory of the Rockies (NLR), completed a field study of a Grid-Interactive Efficient Buildings (GEB) software solution. The study focused on a single testbed facility to test the GEB functionality of the software solution, along with other features. The testbed facility - a courthouse - is a common building type in GSA's vast building portfolio, offering potentially impactful findings on a scalable level. The study evaluated Prescriptive Data's technology, Nantum OS, a connected building operating system ("GEB Solution") which aggregates multiple sources of previously siloed building data and combines that data with external sources, such as weather information or utility signals, into a single integrated platform. A GEB Solution is a type of Energy Management Information System (EMIS). EMIS is defined as a system of devices, data services, and software applications that communicates with any building system or third-party data source to aggregate and transform data into new capabilities to aid in the optimization of energy use at the building, campus, or agency level. This specific GEB Solution is an EMIS with ASO, automated system optimization, offering supervisory control of certain aspects of the Building Automation System (BAS). Multiple features were evaluated including, but not limited to, Continuous Demand Management to avoid setting new monthly kilowatt (kW) peaks, energy efficiency for reduction of kilowatt hours (kWh) and natural gas consumption, and automated demand response (ADR) for purposes of lowering demand during a utility called Demand Response (DR) event. The testbed facility was the Foley Federal Building and US Courthouse ("Foley Federal Building") located in Las Vegas, NV. This is a 209,496 sq. ft. building constructed in the 1960s with major renovations in 2004. The facility was a good candidate due to the large prevalence of office and courthouse spaces in the GSA portfolio of buildings. It also has many features which allow integration into and control of the building and a strong facilities team to assist with the study. Quantitative and qualitative performance objectives were developed using GSA's GPG GEB project template along with input from the vendor and building facility staff; these are outlined in Table 1. The quantitative performance objectives focused on continuous demand management, energy efficiency, and automated demand response. The qualitative performance objectives focused on the ease of installation and commissioning as well as the operability of the GEB solution. Other performance metrics that are reported on include carbon reduction, cost effectiveness, and occupant acceptance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Seamless Wireless Communication Platform for Internet of Things Applications

The rapid growth of the Internet of Things (IoT) devices resulted in the proliferation of wireless technologies to cater to their increasing data rate requirements and support multiple applications. However, such ever-increasing wireless technologies present numerous challenges such as incompatible wireless standards, increased energy consumption, and insecure communication. The traditional gateways proposed in the literature suffers from limitations such as computational complexity, resource requirements, increased cost, and device size. We vision an era of seamless wireless communication to alleviate the aforementioned challenges in IoT applications. through three inter-dependent functionalities namely detection and identification of wireless technologies, energy-efficient transmit power control, and secure end-to-end communication. To prove the concept, a new gateway is proposed to achieve these three functionalities with only physical layer measurements so that the different communication protocols in the higher layers can be avoided. Novel schemes are conceptualized for resource-limited seamless IoT applications. Moreover, the conceptual seamless IoT platform is validated through software-based computer simulation and software-defined radio-based testbed implementation. Finally, the preliminary analysis demonstrates that the proposed platform has great potential in advancing seamless IoT applications.

97 MATHEMATICS AND COMPUTING↗

Targeted mutagenesis with sequence–specific nucleases for accelerated improvement of polyploid crops: Progress, challenges, and prospects

Many of the world's most important crops are polyploid. The presence of more than two sets of chromosomes within their nuclei and frequently aberrant reproductive biology in polyploids present obstacles to conventional breeding. The presence of a larger number of homoeologous copies of each gene makes random mutation breeding a daunting task for polyploids. Genome editing has revolutionized improvement of polyploid crops as multiple gene copies and/or alleles can be edited simultaneously while preserving the key attributes of elite cultivars. Most genome–editing platforms employ sequence–specific nucleases (SSNs) to generate DNA double–stranded breaks at their target gene. Such DNA breaks are typically repaired via the error–prone nonhomologous end–joining process, which often leads to frame shift mutations, causing loss of gene function. Genome editing has enhanced the disease resistance, yield components, and end–use quality of polyploid crops. However, identification of candidate targets, genotyping, and requirement of high mutagenesis efficiency remain bottlenecks for targeted mutagenesis in polyploids. In this review, we will survey the tremendous progress of SSN–mediated targeted mutagenesis in polyploid crop improvement, discuss its challenges, and identify optimizations needed to sustain further progress.

60 APPLIED LIFE SCIENCES↗

Integrative Multi-PTM Proteomics Reveals Dynamic Global, Redox, Phosphorylation, and Acetylation Regulation in Cytokine-treated Pancreatic Beta Cells

Studying regulation of protein function at a systems level necessitates an understanding of the interplay among diverse post-translational modifications (PTMs). A variety of proteomics sample processing workflows are currently used to study specific PTMs but rarely characterize multiple types of PTMs from the same sample inputs. Method incompatibilities and laborious sample preparation steps complicate large-scale physiological investigations and can lead to variations in results. The single-pot, solid-phase-enhanced sample preparation (SP3) method for sample cleanup is compatible with different lysis buffers and amenable to automation, making it attractive for high-throughput multi-PTM profiling. Herein, we describe an integrative SP3 workflow for multiplexed quantification of protein abundance, cysteine thiol oxidation, phosphorylation, and acetylation. The broad applicability of this approach is demonstrated using cell and tissue samples, and its utility for studying interacting regulatory networks is highlighted in a time-course experiment of cytokine-treated ß-cells. We observed a swift response in global regulation of protein abundances consistent with rapid activation of JAK-STAT and NF-?B signaling pathways. Regulators of these pathways as well as proteins involved in their target processes displayed multi-PTM dynamics indicative of a complex cellular response stages: acute, adaptation, and chronic (prolonged stress). PARP14, a negative regulator of JAK-STAT, had multiple co-localized PTMs that may be involved in intraprotein regulatory crosstalk. Our workflow provides a high-throughput platform that can profile multi-PTMomes from the same sample set, which is valuable in unraveling the functional roles of PTMs and their co-regulation.

proteomics, PTM, automation, SP3, cysteine thiol o↗

Microbial Pathways for Cost-Effective Low-Carbon Renewable Indigoidine

Indigoidine is a bioadvantaged platform molecule with diverse applications, including use as a textile dye, biotransistor, biosolar cell, biosensor, and food coloring. There are multiple microbial hosts and carbon sources that can be used and optimized for its production, yet there is limited guidance for which options have the greatest commercial potential. Here, we consider five different host microbes and combine genome-scale metabolic models with techno-economic and lifecycle assessment models. Pseudomonas putida currently outperforms synthetic indigo production and other indigoidine-producing hosts, using glucose, xylose, and lignin-derived aromatics to produce indigoidine at a minimum selling price of $2.9/kg and a greenhouse gas (GHG) footprint of 3.5 kgCO 2e /kg. Optimizing pathways-achieving 90% of the theoretical indigoidine yield from sugars and aromatics-can reduce costs 6-7-fold and GHG emissions 3-10-fold. From a cost perspective, microbes that co-utilize aromatics are advantageous, while selecting hosts that coproduce other value-added molecules can reduce GHG emissions. System-wide improvements and the use of a low-cost, low-carbon nitrogen source are crucial for commercial viability in all cases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Strain-concentration for fast, compact photonic modulation and non-volatile memory

A critical figure of merit (FoM) for electro-optic (EO) modulators is the transmission change per voltage, d T / d V . Conventional approaches in wave-guided modulators maximize d T / d V via a high EO coefficient or longer light-material interaction lengths but are ultimately limited by material losses and nonlinearities. Optical and RF resonances improve d T / d V at the cost of spectral non-uniformity, especially for high- Q optical cavity resonances. Here, we introduce an EO modulator based on piezo-strain-concentration of a photonic crystal cavity to address both trade-offs: (i) it eliminates the trade-off between d T / d V and waveguide loss—i.e., enhancement of the resonance tuning efficiency d v c / d V for the fixed EO coefficient, waveguide length, and cavity Q —and (ii) at high DC strains it exhibits a non-volatile (NV) cavity tuning Δ v c ,NV for passive memory and programming of multiple devices into resonance despite fabrication variations. The device is fabricated on a scalable silicon nitride-on-aluminum nitride platform. We measure d v c / d V =177±1MHz/V, corresponding to Δ v c =40±0.32GHz for a voltage spanning ±120V with an energy consumption of δ U /Δ v c =0.17nW/GHz. The modulation bandwidth is flat up to ω BW,3dB /2 π =3.2±0.07MHz for broadband DC-AC and 142±17MHz for resonant operation near a 2.8 GHz mechanical resonance. Optical extinction up to 25 dB is obtained via Fano-type interference. Strain-induced beam-buckling modes are programmable under a “read-write” protocol with a continuous, repeatable tuning range of 5±0.25GHz, allowing for storage and retrieval, which we quantify with mutual information of 2.4 bits and a maximum non-volatile excursion of 8 GHz. Using a full piezo-optical finite-element-model (FEM) we identify key design principles for optimizing strain-based modulators and chart a path towards achieving performance comparable to lithium niobate-based modulators and the study of high strain physics on-chip.

Wen, Y. Henry (ORCID:0009000685423628)↗

Comparison of Coupled and Uncoupled Modeling of Floating Wind Farms with Shared Anchors

As design options for floating wind farms continue to be explored, shared (or multiline) anchors that secure mooring lines from multiple turbines remain a promising technology that can potentially reduce the number of anchors and overall mooring costs. This study evaluates two methods for analyzing the loads on shared anchors: one in which floating offshore wind turbines are simulated individually (using the software OpenFAST), and one in which an entire floating wind farm is simulated collectively (using the software FAST.Farm). A three-line shared anchor is evaluated for multiple loading scenarios in deep water, using the International Energy Agency 15 MW turbine on the VolturnUS-S semisubmersible platform. While the two methods produce broadly comparable results, the coupled wave loading on platforms within the farm results in wave force cancellations and amplifications that decrease multiline force directional ranges and increase multiline force extreme values (up to 7%) and standard deviations (up to 11%) for wave-driven load cases. The inclusion of wakes in FAST.Farm also reduces the net load on the shared anchor due to the velocity deficit, leading to larger differences between OpenFAST and FAST.Farm (up to 3% difference in mean loads) for load cases with operational turbines.

17 WIND ENERGY↗

Virtual and Augmented Realities to Support Development, Training, Deployment, and Operations of Remote Systems - 20516

Throughout the U.S. Department of Energy complex, there is a need to deploy new, unique equipment and systems for cleanup activities, waste processing, infrastructure repair, and decommissioning and demolition in radioactive and hazardous environments. The new equipment often consists of custom systems created by integrating and modifying commercial technologies. In addition, the systems are deployed in unique environments due to limited access, waste properties, and the presence of previously installed equipment or infrastructure that has been left in place. The deployment of custom systems that are 'turnkey' ready for first-time installation and application has its risks. Use of test platforms and mockups for cold (i.e., non-radioactive) testing is one method to mitigate that risk: however, full-scale test mockups for operations such as waste retrieval and tank inspection can be expensive and must be modified to incorporate the uniqueness of each application. An alternative to full-scale mockups is to use three-dimensional (3D) virtual environments and virtual reality (VR) technology to develop interactive virtual test beds. These can be used throughout the down-selection, development, system integration, operational planning, operator training, and mission execution phases of a task. Virtual test beds are readily reconfigured, can be used for multiple tasks, support multiple users in parallel, and can accommodate enhancements and changes not originally planned or conceived in the initial design. Virtual test beds also provide a platform for developing and testing augmented reality (AR) tools for improving operator efficiency. A VR experience has been generated for waste retrieval from a Hanford waste tank to present the potential applications of a virtual test bed. Features of the VR experience are presented, potential applications of VR and AR for remote applications are discussed, and development areas for improving future application are considered. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Enhanced Spatial Proteomics and Metabolomics from a Single Tissue Section Using MALDI-MSI and LCM-microPOTS Platforms

Spatially resolved mass spectrometry (MS)-based multi-omics workflows are becoming more utilized for revealing the complex biology that occurs within tissues. However, these approaches commonly require multiple independent tissue sections to analyze the metabolite and protein compositions of these samples. This poses a significant challenge in preserving cell- or region-specific molecular fidelity, as variations between tissue sections can compromise the accurate correlation of molecular data. Here, in this study, we developed workflows for comprehensive multi-omics profiling from a single tissue section (STS) using different MS modalities. We enhanced the functionality of an electrically insulated substrate by employing metal-assisted approaches that enabled both MS-based untargeted spatial metabolomics and proteomics from STS. This allowed metabolite imaging using matrix-assisted laser desorption/ionization-MS imaging (MALDI-MSI), without compromising it for subsequent proteome profiling with laser capture microdissection (LCM)-based technology. Specifically, implementing copper tape as a backing for polyethylene naphthalate (PEN) slides enabled the detection of >140 metabolites across a poplar root tissue section using MALDI-trapped ion mobility spectrometry time of flight (timsTOF)-MS. Afterwards, we detected 6,571 unique proteins from two distinct root regions by leveraging LCM technology coupled to our microdroplet based sample preparation approach. We also developed an alternative workflow utilizing gold-coated PEN substrates for imaging with MALDI-Fourier-transform ion cyclotron resonance (FTICR)-MS, which permitted the profiling of >170 metabolites and the identification of 6,542 unique proteins across a single poplar root tissue section. These results were comparable to using each assay independently without modifications. These approaches offer new opportunities for high-resolution molecular profiling of multiple omics-levels across biological tissues.

Veličković, Marija [Pacific Northwest National Lab↗

Future Vision for Autonomous Ocean Observations

Autonomous platforms already make observations over a wide range of temporal and spatial scales, measuring salinity, temperature, nitrate, pressure, oxygen, biomass; and many other parameters. However, the observations are not comprehensive. Future autonomous systems need to be more affordable, more modular, more capable and easier to operate. Creative new types of platforms and new compact, low power, calibrated and stable sensors are under development to expand autonomous observations. Communications and recharging need bandwidth and power which can be supplied by standardized docking stations. In situ power generation will also extend endurance for many types of autonomous platforms, particularly autonomous surface vehicles. Standardized communications will improve ease of use, interoperability, and enable coordinated behaviors. Improved autonomy and communications will enable adaptive networks of autonomous platforms. Improvements in autonomy will have three aspects: hardware, control, and operations. As sensors and platforms have more onboard processing capability and energy capacity, more measurements become possible. Control systems and software will have the capability to address more complex states and sophisticated reactions to sensor inputs, which allows the platform to handle a wider variety of circumstances without direct operator control. Operational autonomy is increased by reducing operating costs. To maximize the potential of autonomous observations new standards and best practices are needed. In some applications, focus on common platforms and volume purchases could lead to significant cost reductions. Cost reductions could enable order-of-magnitude increases in platform operations and increase sampling resolution for a given level of investment. Energy harvesting technologies should be integral to the system design, for sensors, platforms, vehicles, and docking stations. Connections are needed between the marine energy and ocean observing communities to coordinate among funding sources, researchers, and end users. Regional teams should work with global organizations such as IOC/GOOS in governance development. International networks such as EGO for the emerging glider operations should also provide a forum for addressing governance. Networks of multiple vehicles can improve operational efficiencies and transform operational patterns. There is a need to develop operational architectures at regional and global scales to provide a backbone for active networking of autonomous platforms.

47 OTHER INSTRUMENTATION↗

$\mathrm{RADICAL}$-Pilot and $\mathrm{PMIx}$/$\mathrm{PRRTE}$: Executing Heterogeneous Workloads at Large Scale on Partitioned $\mathrm{HPC}$ Resources

Execution of heterogeneous workflows on high-performance computing (HPC) platforms present unprecedented resource management and execution coordination challenges for runtime systems. Task heterogeneity increases the complexity of resource and execution management, limiting the scalability and efficiency of workflow execution. Re-source partitioning and distribution of tasks execution over portioned re-sources promises to address those problems but we lack an experimental evaluation of its performance at scale. Here this paper provides a performance evaluation of the Process Management Interface for Exascale (PMIx) and its reference implementation PRRTE on the leadership-class HPC plat-form Summit, when integrated into a pilot-based runtime system called RADICAL-Pilot. We partition resources across multiple PRRTE Distributed Virtual Machine (DVM) environments, responsible for launching tasks via the PMIx interface. We experimentally measure the work-load execution performance in terms of task scheduling/launching rate and distribution of DVM task placement times, DVM startup and termination overheads on the Summit leadership-class HPC platform. Integrated solution with PMIx/PRRTE enables using an abstracted, standardized set of interfaces for orchestrating the launch process, dynamic process management and monitoring capabilities. It extends scaling capabilities allowing to overcome a limitation of other launching mechanisms (e.g., JSM/LSF). Explored different DVM setup configurations provide insights on DVM performance and a layout to leverage it. Our experimental results show that heterogeneous workload of 65,500 tasks on 2048 nodes, and partitioned across 32 DVMs, runs steady with resource utilization not lower than 52%. While having less concurrently executed tasks resource utilization is able to reach up to 85%, based on results of heterogeneous workload of 8200 tasks on 256 nodes and 2 DVMs.

97 MATHEMATICS AND COMPUTING↗