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At least 235 records · Page 13

Strategies to Deploy and Scale Deep Learning on the Summit Supercomputer

The rapid growth and wide applicability of Deep Learning (DL) frameworks poses challenges to computing centers which need to deploy and support the software, and also to domain scientists who have to keep up with the system environment and scale up scientific exploration through DL. We offer recommendations for deploying and scaling DL frameworks on the Summit supercomputer, currently atop the Top500 list, at the Oak Ridge National Laboratory Leadership Computing Facility (OLCF). We discuss DL software deployment in the form of containers, and compare performance of native-built frameworks and containerized deployment. Software containers show no noticeable negative performance impact and exhibit faster Python loading times and promise easier maintenance. To explore strategies for scaling up DL model training campaigns, we assess DL compute kernel performance, discuss and recommend I/O data formats and staging, and identify communication needs for scalable message exchange for DL runs at scale. We recommend that users take a step-wise tuning approach beginning with algorithmic kernel choice, node I/O configuration, and communications tuning as best-practice. We present baseline examples of scaling efficiency 87% for a DL run of ResNet50 running on 1024 nodes (6144 V100 GPUs).

Yin, Junqi↗

Real-Time Evolution and Deployment of Neuromorphic Computing at The Edge

Extremely low power neuromorphic systems are well-suited for deployment to the edge for many applications. In many use cases of neuromorphic computing for control, a spiking neural network is trained off-line using a simulation and then deployed to a neuromorphic system at the edge, where it will operate without ongoing training or learning. However, it may be desirable to continue training or learning at the edge to refine or adapt to the real-world system. In this work, we propose an approach for performing real-time evolutionary optimization for spiking neural networks for neuromorphic deployment at the edge. In particular, we propose a combination of simulation and real-world evaluations, along with feedback from the real-world environment, to train spiking neural networks for continuous deployment to the edge. We show that the real-time evolution at the edge approach achieves comparable performance to an evolution approach that requires constant evaluation in the realworld environment.

Schuman, Catherine↗

Generating Sequential PV Deployment Scenarios for High Renewable Distribution Grid Planning

This paper introduces a novel approach for generating solar photovoltaic (PV) plant deployment scenarios for grid integration planning. The approach guarantees consistency among scenarios of the same deployment by ensuring that higher penetration scenarios contain PV units deployed in lower penetration scenarios. It also constrains the size and spatial distribution of the PV plants and considers three placement types. A case study on a real-world distribution system proves that the precepts of scenario consistency, deployment diversity, and placement are met. The study further investigates the impact of the resulting scenarios via a stochastic hosting capacity analysis. Results indicate that the ratio between PV and load sizes, referred to as the nodal PV penetration factor (NPPF), is a key driver of the grid integration impact. By reducing the NPPF from 5 to 2, the maximum hosting capacity increased by at least 112%. The study also reveals that scenarios under random placement can lead to higher hosting capacity values.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗

Best Practices and Lessons Learned from Deploying and Operating Large-Scale Data-Centric Parallel File Systems, In: SC '14: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis

The Oak Ridge Leadership Computing Facility (OLCF) has deployed multiple large-scale parallel file systems (PFS) to support its operations. During this process, OLCF acquired significant expertise in large-scale storage system design, file system software development, technology evaluation, benchmarking, procurement, deployment, and operational practices. Based on the lessons learned from each new PFS deployment, OLCF improved its operating procedures, and strategies. This paper provides an account of our experience and lessons learned in acquiring, deploying, and operating large-scale parallel file systems. We believe that these lessons will be useful to the wider HPC community.

Computer Science↗

Transactive Energy System Deployment Over Insecure Communication Links

Here, in this paper, the privacy and security issues associated with the transactive energy system (TES) deployment over insecure communication links are addressed. In particular, it is ensured that 1) individual agents’ bidding information is kept private throughout hierarchical market-based interactions; and 2) any extraneous data injection attack can be quickly and easily detected. An implementation framework is proposed to enable the cryptography-based enhancement of privacy and security for the deployment of any general hierarchical systems including TESs. Under the proposed framework, a unified cryptography-based approach is developed to achieve both privacy and security simultaneously. Specifically, privacy preservation is realized by an enhanced Paillier encryption scheme, where a block design is proposed to significantly improve computational efficiency. Attack detection is further achieved by an enhanced Paillier digital signature scheme, where a stamp-concatenation mechanism is proposed to enable detection of data replace and reorder attacks. Simulation results verify the effectiveness of the proposed cyber-resilient design for transactive energy systems. Note to Practitioners—This paper is motivated by addressing the issues of cyber resiliency for practically deploying transactive energy system (TES) but it is also applicable to the problem of enhancing the privacy and security for any general hierarchical control systems. TES is an emerging control approach that engages energy suppliers and customers through market operations and uses the price to optimally allocate energy resources. While it has been shown to be promising for power system applications, the underlying market-based interactions raise significant concerns of privacy (data leakage) and security (data tampering). However, existing TES works only focus on the coordination mechanism instead of privacy and security issues. This paper proposes a new cryptography-based TES design for practical deployment. Specifically, to protect privacy, individual supply and demand amounts to be exchanged are all encrypted in a particular way such that the original amounts cannot be inferred from the encrypted amounts, while the desired computation for setting the market clearing price can be carried out over the encrypted amounts, thus generating an encrypted result which, when decrypted, matches that of the same computation over the original amounts. To achieve security, for each exchanged data, its sender generates a particular digital signature which is exchanged together with the data. This enables the receiver to automatically detect the integrity by checking whether a mathematical relationship holds for the pair of data and signature. In our future research, we will investigate more challenging scenarios where some suppliers and customers themselves could be corrupted and purposely submit distorted amounts.

97 MATHEMATICS AND COMPUTING↗

Field expedient stool collection methods for gut microbiome analysis in deployed military environments

ABSTRACT Field expedient devices and protocols for the collection, storage, and shipment of stool samples in deployed settings are needed for the advancement of microbiome research in military health. Relevant assessments include the evaluation of microbiome signatures associated with susceptibility to travelers’ diarrhea and recovery of gut function following infection. However, inherent biases in microbial measurements due to preservatives and sampling methods are unclear and should be assessed for an accurate evaluation of the microbiome. We performed shotgun metagenomic sequencing and compared the microbiome composition in paired fecal samples collected using Flinters Technology Associates (FTA) cards and OMNIgene (OG) Gut tubes, prior to and during international travel, from 49 adult participants, 39 of whom remained asymptomatic and 10 experienced travelers’ diarrhea. Higher concentrations of nucleic acid and sequencing libraries were observed in OG samples. A majority of genera (82.9%) were detected with both methods, and detections of genera limited to one collection method were not highly prevalent across samples and were present in extremely low relative abundances (<0.01%). Differences in beta diversity were largely explained by inter-individuality of microbiome composition, followed by the effect of collection method and timepoint-disease states. Differential abundance analysis indicated that Corynebacterium and Blautia were consistently higher in abundance across all groups with FTA and OG collection, respectively. The observed differences in microbiome composition between methods suggest the need for consistent and standardized protocols within a study. Overall, the data presented here could help guide the future design of fecal microbiome study protocols in field and military deployment settings. IMPORTANCE The assessment of field-deployable methods for fecal sample collection and storage is required to reliably capture samples collected in remote and austere locations. This study describes a comparative metagenomics analysis between samples collected by two different commercially available methods in a military-deployed setting. The results presented here are foundational for the future design of fecal microbiome study protocols in an operational context.

field study↗

Distributed Acoustic Sensing for Whale Vocalization Monitoring: A Vertical Deployment Field Test

Abstract There is growing interest in floating offshore wind turbine (FOWT) technology, where turbines are installed on floating structures anchored to the seabed, allowing wind energy development in areas unsuitable for traditional fixed-platform turbines. Responsible development requires monitoring the impact of FOWTs on marine wildlife, such as whales, throughout the operational lifecycle of the turbines. Distributed acoustic sensing (DAS)—a technology that transforms fiber-optic cables into vibration sensor arrays—has been demonstrated for acoustic monitoring of whales using seafloor telecommunications cables. However, no studies have yet evaluated DAS performance in dynamic, engineered environments, such as floating platforms or moving vessels with complex, dynamic strain loads, despite their relevance to FOWT settings. This study addresses that gap by deploying DAS aboard a boat in Monterey Bay, California, where a fiber-optic cable was lowered using a weighted and suspended mooring line, enabling vertical deployment. Humpback whale vocalizations were captured and identified in the DAS data, noise sources were identified, and DAS data were compared to audio captured by a standalone hydrophone attached to the mooring line and a nearby hydrophone on a cabled observatory. This study is unique in: (1) deploying DAS in a vertical deployment mode, where noise from turbulence, cable vibrations, and other sources posed additional challenges compared to seafloor DAS applications; (2) demonstrating DAS in a dynamic, nonstationary setup, which is uncommon for DAS interrogators typically used in more stable environments; and (3) leveraging looped sections of the cable to reduce the noise floor and mitigate the effects of excessive cable vibrations and strain. This research demonstrates DAS’s ability to capture whale vocalizations in challenging environments, highlighting its potential to enhance underwater acoustic monitoring, particularly in the context of renewable energy development in offshore environments.

Saw, Jaewon↗

Coastal Ohio Wind Project for Reduced Barriers to Deployment of Offshore Wind Energy

The Coastal Ohio Wind Project was created to establish the viability of wind turbines on the coastal and offshore regions of Northern Ohio. The project’s main goal was to improve operational unit strategies used for environmental impact assessment of offshore turbines on lake wildlife by optimizing and fusing data from the multi-instrument surveillance system and providing an engineering analysis of potential design/operational alternatives for offshore wind turbines. The project also developed a general economic model for offshore WTG deployment to quantify potential revenue losses due to wind turbine shutdown related to ice and avian issues. In a previous phase of this project (Award Number: DE-FG36-06GO86096), we developed a surveillance system that was used to collect different parameters such as passage rates, flight paths, flight directions, and flight altitudes of nocturnal migrating species, movements of birds and bats, and bird calls for assessing patterns and peak passage rates during migration. To derive such parameters we used thermal IR imaging cameras, acoustic recorders, and marine radar Furuno (XANK250), which was coupled with a XIR3000B digitizing card from Russell Technologies and open source radR processing software. The integration yielded a development of different computational techniques and methods, which we further developed and optimized as a combined surveillance system. To accomplish this task we implemented marine radar calibration, optimization of processing parameters, and fusion of the multi-sensor data in order to make inferences about the potential avian targets. The main goal of the data fusion from the multi-sensor environment was aimed at reduction of uncertainties while providing acceptable confidence levels with detailed information about the migration patterns. Another component comprised of an assessment of wind resources in a near lake environment and an investigation of the effectiveness of ice coating materials to mitigate adverse effects of ice formation on wind turbine structures. Firstly, a Zephir LiDAR system was acquired and installed at Woodlands School in Huron, Ohio, which is located near Lake Erie. Wind resource data were obtained at ten measurement heights, 200m, 150m, 100m, 80m, 60m, 40m, 38m, 30m, 20m, and 10m. The Woodlands School’s wind turbine anemometer also measured the wind speed at the hub height. These data were collected for approximately one year. The hub anemometer data correlated well with the LiDAR wind speed measurements at the same height. The data also showed that on several days different power levels were recorded by the turbine at the same wind speed as indicated by the hub anemometer. The corresponding LiDAR data showed that this difference can be attributed to variability in the wind over the turbine rotor swept area, which the hub anemometer could not detect. The observation suggests that single point hub wind velocity measurements are inadequate to accurately estimate the power generated by a turbine at all times since the hub wind speed is not a good indicator of the wind speed over the turbine rotor swept area when winds are changing rapidly. To assess the effectiveness of ice coatings to mitigate the impact of ice on turbine structures, a closed-loop icing research tunnel (IRT) was designed and constructed. By controlling the temperature, air speed, water content and liquid droplet size, the tunnel enabled consistent and repeatable ice accretion under a variety of conditions with temperatures between approximately 0°C and -20°C and wind speeds up to 40 miles per hour in the tunnel’s test section. The tunnel’s cooling unit maintained the tunnel temperature within ±0.2°C. The coatings evaluated in the study were Boyd Coatings Research Company’s CRC6040R3, MicroPhase Coatings Inc.’s PhaseBreak TP, ESL and Flex coatings. Similar overall performance was observed in all coatings tested in that water droplets form on the test articles beginning at the stagnation region and spreading in the downstream direction in time. When comparing ice accumulation characteristics for the four coatings tested, for ice thickness during accumulation the CRC6040R3 had the least, followed by the ESL, Flex, and TP. However, when comparing the coatings’ ability to reduce ice adhesion, the Flex showed the highest adhesion reduction, followed by the ESL, TP and CRC 6040R3 coatings. The ice accumulated on the Flex coated surface shed under gravity when rotated 90 degrees following the tests while the other coatings required application of varying degrees of force to remove the ice. In conclusion, the ice coatings tested were not sufficient in preventing ice accumulation on all surfaces. However, Flex coating shows promise in mitigating ice on the rotor blades under the gravitational and centrifugal forces. Only the effect of gravity in shedding the ice was considered in this study. Further research will be needed to evaluate this coating on rotating blades in the icing tunnel to characterize its effectiveness. Lastly, the development of economic feasibility models used existing approaches adapted for offshore deployment in marine settings to one more suitable for Lake Erie deployment. Two different wind turbine models were tested and dynamic return on investment (ROI) model scenarios were generated. For the purpose of estimating power generation three bladed wind turbines of 3 MW capacity were selected including Model1- Leitwind LTW101-3.000-kW and Model2-Vostro V90-3.0 MW. The analysis were based on the revenue aspect of decision making of deploying wind turbines in the Ohio coastal region. The installation cost, maintenance and operational aspects were disregarded due to unavailability of data. The adjusted varying price (residential and industrial sector) and projected future price of electricity in different years suggested that the Leitwind model could generate $\$ $32.4 million of revenue in 25 years if the supply electricity is in the residential sector, while it would be $\$ $14.7million if the supply is in the industrial sector. For the Vostro model these figures are $\$ $28.6 million for residential sector and $\$ $12.9 million for industrial sector for 25 years.

17 WIND ENERGY↗

Implications of a PTC Extension on U.S. Wind Deployment

This analysis explores the potential effects of wind production tax credit expiration and various extension scenarios on future wind deployment with the Regional Energy Deployment System (ReEDS), a model of the U.S. electricity sector. The analysis does not estimate the potential implications on government tax revenue associated with the PTC. Key findings include: Under a scenario in which the PTC is not extended and all other policies remain unchanged, wind capacity additions are expected to be between 3 and 5 GW per year from 2013-2020; PTC extension options that ramp-down from the current level to zero-credit by year-end 2022 appear to be insufficient to support deployment at the recent historical average; Extending the PTC at its historical level may provide the best opportunity to support deployment consistent with recent levels across a range of potential market conditions; it therefore may also provide the best opportunity to sustain wind power installation and manufacturing sector at current levels.

17 WIND ENERGY↗

The VolturnUS 1:8 Floating Wind Turbine: Design, Construction, Deployment, Testing, Retrieval, and Inspection of the First Grid-Connected Offshore Wind Turbine in US

Volume II of the Final Report for the DeepCwind Consortium National Research Program funded by US Department of Energy Award Number: DE-EE0003278.001 summarizes the design, construction, deployment, testing, numerical model validation, retrieval, and post-deployment inspection of the VolturnUS 1:8-scale floating wind turbine prototype deployed off Castine, Maine on June 2nd, 2013. The 1:8 scale VolturnUS design served as a de-risking exercise for a commercial multi-MW VolturnUS design. The American Bureau of Shipping Guide for Building and Classing Floating Offshore Wind Turbine Installations was used to design the prototype. The same analysis methods, design methods, construction techniques, deployment methods, mooring, and anchoring planned for full-scale were used. A commercial 20kW grid-connected turbine was used and was the first offshore wind turbine in the US.

17 WIND ENERGY↗

Scoping study to expedite development of a field deployable and portable instrument for UF6 enrichment assay

The primary objective of the present study is to identity the most promising, viable technologies that are likely to culminate in an expedited development of the next-generation, field-deployable instrument for providing rapid, accurate, and precise enrichment assay of uranium hexafluoride (UF6). UF6 is typically involved, and is arguably the most important uranium compound, in uranium enrichment processes. As the first line of defense against proliferation, accurate analytical techniques to determine the uranium isotopic distribution in UF6 are critical for materials verification, accounting, and safeguards at enrichment plants. As nuclear fuel cycle technology becomes more prevalent around the world, international nuclear safeguards and interest in UF6 enrichment assay has been growing. At present, laboratory-based mass spectrometry (MS), which offers the highest attainable analytical accuracy and precision, is the technique of choice for the analysis of stable and long-lived isotopes. Currently, the International Atomic Energy Agency (IAEA) monitors the production of enriched UF6 at declared facilities by collecting a small amount (between 1 to 10 g) of gaseous UF6 into a sample bottle, which is then shipped under chain of custody to a central laboratory (IAEA’s Nuclear Materials Analysis Laboratory) for high-precision isotopic assay by MS. The logistics are cumbersome and new shipping regulations are making it more difficult to transport UF6. Furthermore, the analysis is costly, and results are not available for some time after sample collection. Hence, the IAEA is challenged to develop effective safeguards approaches at enrichment plants. In-field isotopic analysis of UF6 has the potential to substantially reduce the time, logistics and expense of sample handling. However, current laboratory-based MS techniques require too much infrastructure and operator expertise for field deployment and operation. As outlined in the IAEA Department of Safeguards Long-Term R&D Plan, 2012–2023, one of the IAEA long-term R&D needs is to “develop tools and techniques to enable timely, potentially real-time, detection of HEU (Highly Enriched Uranium) production in LEU (Lowly Enriched Uranium) enrichment facilities” (Milestone 5.2). Because it is common that the next generation of analytical instruments is driven by technologies that are either currently available or just now emerging, one reasonable and practical approach to project the next generation of chemical instrumentation is to track the recent trends and to extrapolate them. This study adopted a similar approach, and an extensive literature review on existing and emerging technologies for UF6 enrichment assay was performed. The competitive advantages and current limitations of different analytical techniques for in-field UF6 enrichment assay were then compared, and the main gaps between needs and capabilities for their field use were examined. Subsequently, based on these results, technologies for the next-generation field-deployable instrument for UF6 enrichment assay were recommended. The study was organized in a way that a suite of assessment metric was first identified. Criteria used in this evaluation are presented in Section 1 of this report, and the most important ones are described briefly in the next few paragraphs. Because one driving force for in-field UF6 enrichment assay is related to the demanding transportation regulation for gaseous UF6, Section 2 contains a review of solid sorbents that convert and immobilized gaseous UF6 to a solid state, which is regarded as more transportation friendly and is less regulated. Furthermore, candidate solid sorbents, which show promise in mating with existing and emerging assay technologies, also factor into technology recommendations. Extensive literature reviews on existing and emerging technologies for UF6 enrichment assay, covering their scientific principles, instrument options, and current limitations are detailed in Sections 3 and 4, respectively. In Section 5, the technological gaps as well as start-of-the-art and commercial off-the-shelf components that can be adopted to expedite the development of a fieldable or portable UF6 enrichment-assay instrument are identified and discussed. Finally, based on the results of the review, requirements and recommendations for developing the next-generation field-deployable instrument for UF6 enrichment assay are presented in Section 6.

36 MATERIALS SCIENCE↗

Deploy Nalu/Kokkos algorithmic infrastructure with performance benchmarking.

The former Nalu interior heterogeneous algorithm design, which was originally designed to manage matrix assembly operations over all elemental topology types, has been modified to operate over homogeneous collections of mesh entities. This newly templated kernel design allows for removal of workset variable resize operations that were formerly required at each loop over a Sierra ToolKit (STK) bucket (nominally, 512 entities in size). Extensive usage of the Standard Template Library (STL) std::vector has been removed in favor of intrinsic Kokkos memory views. In this milestone effort, the transition to Kokkos as the underlying infrastructure to support performance and portability on many-core architectures has been deployed for key matrix algorithmic kernels. A unit-test driven design effort has developed a homogeneous entity algorithm that employs a team-based thread parallelism construct. The STK Single Instruction Multiple Data (SIMD) infrastructure is used to interleave data for improved vectorization. The collective algorithm design, which allows for concurrent threading and SIMD management, has been deployed for the core low-Mach element- based algorithm. Several tests to ascertain SIMD performance on Intel KNL and Haswell architectures have been carried out. The performance test matrix includes evaluation of both low- and higher-order methods. The higher-order low-Mach methodology builds on polynomial promotion of the core low-order control volume nite element method (CVFEM). Performance testing of the Kokkos-view/SIMD design indicates low-order matrix assembly kernel speed-up ranging between two and four times depending on mesh loading and node count. Better speedups are observed for higher-order meshes (currently only P=2 has been tested) especially on KNL. The increased workload per element on higher-order meshes bene ts from the wide SIMD width on KNL machines. Combining multiple threads with SIMD on KNL achieves a 4.6x speedup over the baseline, with assembly timings faster than that observed on Haswell architecture. The computational workload of higher-order meshes, therefore, seems ideally suited for the many-core architecture and justi es further exploration of higher-order on NGP platforms. A Trilinos/Tpetra-based multi-threaded GMRES preconditioned by symmetric Gauss Seidel (SGS) represents the core solver infrastructure for the low-Mach advection/diffusion implicit solves. The threaded solver stack has been tested on small problems on NREL's Peregrine system using the newly developed and deployed Kokkos-view/SIMD kernels. fforts are underway to deploy the Tpetra-based solver stack on NERSC Cori system to benchmark its performance at scale on KNL machines.

97 MATHEMATICS AND COMPUTING↗

Industrializing Offshore Wind Power with Serial Assembly and Lower-cost Deployment - Final Report

A team of engineers and contractors has developed a method to move offshore wind installation toward lower cost, faster deployment, and lower environmental impact. A combination of methods, some incremental and some breaks from past practice, interact to yield multiple improvements. Three designs were evaluated based on detailed engineering: 1) a 5 MW turbine on a jacket with pin piles (base case), 2) a 10 MW turbine on a conventional jacket with pin piles, assembled at sea, and 3) a 10 MW turbine on tripod jacket with suction buckets (caissons) and with complete turbine assembly on-shore. The larger turbine, assembly ashore, and the use of suction buckets together substantially reduce capital cost of offshore wind projects. Notable capital cost reductions are: changing from 5 MW to 10 MW turbine, a 31% capital cost reduction, and assembly on land then single-piece install at sea an additional 9% capital cost reduction. An estimated Design 4) estimates further cost reduction when equipment and processes of Design 3) are optimized, rather than adapted to existing equipment and process. Cost of energy for each of the four Designs are also calculated, yielding approximately the same percentage reductions. The methods of Design 3) analyzed here include accepted structures such as suction buckets used in new ways, innovations conceived but previously without engineering and economic validation, combined with new methods not previously proposed. Analysis of Designs 2) and 3) are based on extensive engineering calculations and detailed cost estimates. All design methods can be done with existing equipment, including lift equipment, ports and ships (except that design 4 assumes a more optimized ship). The design team consists of experienced offshore structure designers, heavy lift engineers, wind turbine designers, vessel operators, and marine construction contractors. Comparing the methods based on criteria of cost and deployment speed, the study selected the third design. That design is, in brief: a conventional turbine and tubular tower is mounted on a tripod jacket, in turn atop three suction buckets. Blades are mounted on the tower, not on the hub. The entire structure is built in port, from the bottom up, then assembled structures are queued in the port for deployment. During weather windows, the fully-assembled structures are lifted off the quay, lashed to the vessel, and transported to the deployment site. The vessel analyzed is a shear leg crane vessel with dynamic positioning like the existing Gulliver, or it could be a US-built crane barge. On site, the entire structure is lowered to the bottom by the crane vessel, then pumping of the suction buckets is managed by smaller service vessels. Blades are lifted into place by small winches operated by workers in the nacelle without lift vessel support. Advantages of the selected design include: cost and time at sea of the expensive lift vessel are significantly reduced; no jack up vessel is required; the weather window required for each installation is shorter; turbine structure construction is continuous with a queue feeding the weather-dependent installation process; pre-installation geotechnical work is faster and less expensive; there are no sound impacts on marine mammals, thus minimal spotting and no work stoppage Industrializing Offshore Wind Power 6 of 96 9 for mammal passage; the entire structure can be removed for decommissioning or major repairs; the method has been validated for current turbines up to 10 MW, and a calculation using simple scaling shows it usable up to 20 MW turbines.

17 WIND ENERGY↗

RPM Deployment Requirements for State and Local Use

Radiation Portal Monitors (RPMs) are instruments that passively detect gamma and neutron radiation for screening people, objects, cargo and transports. RPMs have been deployed around the U.S. and other international borders, for the interdiction of radioactive materials that are deemed as threats. Instruments such as RPMs need to be deployed and operated in a specified manner in order to correctly execute their purpose. The deployment and operation of RPMs can be based on national and international standards and specifications. This document provides guidance on the appropriate deployment of RPMs for State and Local Government use, specifically for Ludlum Technology (Sweetwater, TX) model 4500 RPMs provided by the Department of Homeland Security.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Market Opportunities for Deployable Wind Systems for Defense and Disaster Response

This report is the first public deliverable from the Defense and Disaster Deployable Turbine project, funded through the distributed wind portfolio of the U.S. Department of Energy Wind Energy Technologies Office. The objective of the project is to explore the opportunity for deployable turbine technologies to meet the operational energy needs of the U.S. military and global disaster response efforts. This report provides a market assessment that was conducted over a year using public reports, presentations at topical conferences, and direct stakeholder engagement interviews with both military and industry representatives. It begins with the high- level operational energy strategy of the Department of Defense that provides the context for alternatives to diesel fuel to meet energy needs. The report then provides an estimate of the energy use of the military in missions where a deployable turbine could potentially serve as an alternative to the baseline use of diesel fuel in generators to provide electricity in remote locations. An overview of domestic and international disaster response is provided with a focus on the role of the military in providing energy to those events. Finally, the report summarizes the technical considerations that would enable a deployable turbine to meet military and disaster response energy needs including the global wind resource, the technical design of the turbine, and the operational constraints of various military missions.

17 WIND ENERGY↗

FTS3: Data Movement Service in containers deployed in OKD [Slides]

The File Transfer Service (FTS3) is a data movement service developed at CERN which is used to distribute the majority of the Large Hadron Collider's data across the Worldwide LHC Computing Grid (WLCG) infrastructure. At Fermilab, we have deployed FTS3 instances for Intensity Frontier experiments (e.g. DUNE) to transfer data in America and Europe, using a container-based strategy. In this article we summarize our experience building docker images based on work from the SLATE project (slateci.io) and deployed in OKD, the community distribution of Red Hat OpenShift. Additionally, we discuss our method of certificate management and maintenance utilizing Kubernetes CronJobs. Finally, we also report on the two different configurations currently running at Fermilab, comparing and contrasting a Docker-based OKD deployment against a traditional RPM-based deployment.

97 MATHEMATICS AND COMPUTING↗

Michigan Hydrogen and Fuel Cell Electric Vehicle Deployment Plan: H2 FCEV Roadmap 2022

This report describes a roadmap for hydrogen fuel cell electric vehicles in the state of Michigan. This plan provides links to relevant information to assess, plan, and initiate hydrogen and FCEV deployment to help meet the energy, economic, and environmental goals for the State of Michigan. Policies and incentives that support hydrogen and fuel cell technology will increase deployment, thus increasing production and creating jobs throughout the supply chain. As deployment increases, an economy of scale will develop and manufacturing costs will decline, positioning hydrogen and fuel cell technology to compete more effectively in a global market without incentives. Policies and incentives to purchase and support the deployment of FCEVs, FCEBs, and hydrogen refueling can be coordinated regionally to maintain this advanced clean transportation sector as a global exporter for long-term growth and economic development. Overall, the execution of this plan will maintain Michigan's role as a global showcase for regionally manufactured transportation technology while reducing NOx and CO 2 emissions and as new jobs are created for businesses and industry.

08 HYDROGEN↗

Deployment of Dynamic Neural Network Optimization to Minimize Heat Rate During Ramping for Coal Power Plants (Final Technical Report)

Much success was achieved throughout the course of this project. A successful implementation of Dynamic Neural Network Optimization (D-NNO) was coupled with Adaptive Predictive Controls (APC) and a novel hardware installation comprised of an advanced sensor network (ASN) measuring mass-weighted averages of flue gas constituents above the horizontal superheater of a coal-fired utility boiler. From 2019 through 2023 (including an extension due to COVID delays), the team was able to prototype, evaluate, deploy, iterate, and ultimately finalize an advanced closed-loop control D-NNO system which demonstrated the ability to: •improve unit efficiency ~2.0% relative to unoptimized operation (represented as total fuel fired per MWh generated) •improve unit NOx emission rates 10%+ beyond static optimization baselines •improve unit temperature stability as much as 58% and on average 12% •improve operating load stability as much as 35% The culmination of this project has generated an advanced methodology of deploying specially designed recurrent neural networks (long short-term memory, gated recurrent unit, encoder-decoder networks, transformers, etc.), customized trajectory planning and closed-loop optimization modules capable of adapting to live electric grid responses and demands, self-tuning and adaptive expert controls constantly adjusting prediction parameters to real-time unit behavior, and a hardware/software package able to reliably calculate net unit heat rate (NUHR) in real-time using flue gas constituents, machine learning, and known combustion relationships. Through this real-time NUHR value, immediate feedback on system adjustments relative to operating efficiency was available, allowing for rapid improvements to system performance. In addition to development and deployment of the advanced D-NNO system, the approach methodology has been readily commercialized through the project platform Griffin Open Systems, LLC, the D-NNO software platform host. Similar methodologies to those developed by this project have already been deployed at 5 other units across the United States, with another 6 implementations scheduled, and more expected. Over the course of the project, multiple academic papers were submitted and accepted for publication within esteemed academic journals, and PhD students were trained and graduated, as well as undergraduate students becoming involved and participating to project objectives.

01 COAL, LIGNITE, AND PEAT↗