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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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Smart Spectral Matching (SSM)

Smart Spectral Matching (SSM) catalogs spectroscopic data and, within the platform, investigates subtle attributes of spectral signatures from Raman and infrared spectroscopic data and enables statistical identification of connections between underlying structural units and spectroscopic information, particularly in fuel cycle materials that are amorphous or a mixture of several phases. Catalogs spectroscopic data, provides UIs for machine learning training either via JupyterHub for notebooks or domain scientist-specific views, machine learning and catalog REST API Python client libraries, and ability to identify features in files uploaded using pre-trained machine learning models. This is a "service-based" architecture with multiple applications represented by each repository in the group https://github.com/smart-spectral-matching

McDonnell, Marshall [Oak Ridge National Lab. (ORNL↗

LivChat.....So Far

This presentation provides an overview of LivChat, a managed ChatGPT service developed by Lawrence Livermore National Laboratory (LLNL) under the auspices of the U.S. Department of Energy. The initiative was driven by a high demand for generative AI services, the need for enhanced security, and the goal of increasing productivity across various use cases. The development journey involved exploring open-source models and iterating with OpenAI/Azure solutions. The presentation delves into the architecture of LivChat, highlighting its user interface (UI) and backend components. The backend is designed to be separate, RESTful, integrative, and scalable, ensuring robust performance and adaptability. Despite the advanced technology, the presentation emphasizes that LivChat is not a magical solution but a sophisticated tool that requires realistic expectations. Looking ahead, the presentation outlines future directions for LivChat, including training, retrieval-augmented generation (RAG), and innovative ingestion methods. These advancements aim to further enhance the capabilities and applications of LivChat, ensuring it remains at the forefront of generative AI services.

Computer science↗

Guest Editorial Special Issue on Emerging Topics of Power Electronics Interfaced Battery Energy Storage System

No doubt, battery energy storage systems have been the enabling solution to balance generation and consumption of power systems with high-penetration renewable energy resources, long-range electric vehicles, and various smart devices. Upon the battery has been manufactured, the rest of implementation issues become how to interface battery and related systems, how to regulate the charging/discharging power, and how to keep battery energy storage systems (BESSs) safe, reliable, and long-term service. In this editorial, we discuss how power electronic converters and associated control and optimization, which can maximize the value of BESSs, are devoted to provide cost-effective, efficient, and even revolutionary technologies.

25 ENERGY STORAGE↗

Enhancing Active Distribution Systems Resilience by Fully Distributed Self-Healing Strategy

Distributed restoration can exploit smart grid technologies to enhance the resilience of active distribution networks toward a self-healing smart grid. However, the large number of decision variables, especially the binary ones for reconfiguration, bring challenges to developing scalable distributed distribution service restoration (DDSR) strategies. This paper proposes a fully distributed solution procedure based on the alternating direction method of multipliers (ADMM) for mixed-integer programming problems and applies to develop the DDSR framework. The method consists of relax-drive-polish phases, 1) relaxing binary variables, and applying the convex ADMM as a warm start; 2) driving the solutions toward Boolean values through a proximal operator; 3) fixing the obtained binding binary variables and solving the rest of the problem to polish results and achieve a high-quality suboptimal solution. Then, an autonomous clustering strategy and consensus ADMM are integrated with the proposed method to realize the fully distributed cluster-based framework of DDSR. This framework can first determine DER scheduling and switch status for reconfiguration to energize the out-of-service areas from local faults, and then provide the load restoration solution in a distributed manner for total blackouts in large-scale distribution networks. Furthermore, the effectiveness and scalability of the proposed DDSR framework are demonstrated through testing on the IEEE 123-node, IEEE 8500-node, and synthetic 100k-node test feeders.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Alfalfa Virtual Building Service: Software Engineering Best Practices Applied to Runtime Interaction with Building Energy Models

Buildings are active participants in increasingly complex energy systems. Building Energy Modeling (BEM) has a key role to play in planning and de-risking an equitable energy transition, with BEM-backed "virtual buildings" critical path for diverse applications that include workforce training tools, Hardware-in-the-Loop (HIL) experimentation to study equipment performance under a range of conditions, Control-Hardware-in-the-Loop (CHIL) experimentation to de-risk commercial control implementations at equipment through grid orchestration levels, and integration of dynamic load profiles into grid modeling tools for energy system experimentation at the urban scale. Modeling requirements vary across these applications, but many software engineering tasks do not. The Alfalfa Virtual Building Service (AVBS, see https://github.com/NREL/alfalfa/wiki) is an open-source web service that solves these common tasks robustly in one place, providing a foundational platform for power users to bootstrap their own applications. AVBS abstracts the specifics of runtime interaction with OpenStudio, Modelica, and Spawn of EnergyPlus models behind a unified REST API. Additionally, AVBS provides resources for cloud deployment and scaling to 100s of parallel simulations, a growing library of modular Operational Technology (OT) integrations for emulation of real-world interfaces, and scripts to automate the population of communities of virtual buildings from URBANopt, ResStock and ComStock.

building automation↗

Opportunities to Implement Solutions to Achieve Remedial Action Objectives in Consideration of Stakeholder Interests - 20365

A case study in the implementation of a soils excavation and removal project conducted at a Formerly Utilized Sites Remedial Action Program (FUSRAP) Maywood Superfund Site (FMSS) vicinity property; an active commercial business, in a densely populated area, with significant operational, technical and, logistical constraints that were expected to limit areas that could be remediated. The United States Army Corps of Engineers-led (USACE) team successfully navigated complex overlapping stakeholder interests to achieve a more efficient and complete removal of contaminated soils and debris while minimizing unnecessary excess costs to the Government. This paper centers on FUSRAP activities at the FMSS vicinity property located at 149-151 Maywood Avenue, Maywood, Bergen County, New Jersey. For most of its FUSRAP history, this ∼109,000 square meter (27-acre) property housed a now-demolished ∼26,000 square meter (6.5-acre) warehouse operated by Sears Logistics Services, a unit of the Sears Roebuck Company (Figure 2). Sears ended its property lease and vacated the warehouse in December 2016. Given that long history and for the purposes of this paper, the property will be referred to as the 'Sears property' or simply 'the property.' The Sears property is approximately 109,000 square meters (27-acres) and is currently zoned for commercial use. The property is bound to the north and northwest by 100 West Hunter Avenue (the Stepan Company), to the northeast by 205 Maywood Avenue, to the east by Maywood Avenue, to the south by 23 West Howcroft Road, and to the west by businesses on NJ Route 17 and the NJ Route 17 roadway. Until December 2016, the property housed a warehouse and distribution center operated by Sears Logistical Services. On-site structures were demolished by the property owner in 2017. The warehouse covered the north section of the property along the Stepan Company property line. A railroad spur from the adjacent property now known as the Maywood Interim Storage Site (MISS) ended at the northeast corner of the warehouse. Wetlands were located east of the warehouse; the rest of the property was covered with paved parking lots and grassed areas. During remediation at the property, opportunities frequently arose where the project team was able to coordinate effectively with stakeholders to sequence remediation activities to facilitate removal of otherwise inaccessible soils and identify opportunities for materials reuse when supported by residual radiological and chemical levels. Some specific opportunities include: - remediating individual truck loading dock bays to maintain tenant operations; - working along a busy highway and in a utility corridor containing a 30-inch high pressure gas main; - remediating Lodi Brook and associated wetlands requiring bypass pumping and other diversionary structures to maintain local community stormwater drainage; - protecting during remediation and supporting access to facilitate tenant/owner maintenance of critical fire protection and water supply system service lines buried in contaminated soils and necessary for safe warehouse operations; and - coordinating with stakeholders to ensure non-radiological contaminants of concern for the site (unaffiliated with FUSRAP) were addressed by the responsible party in a manner that maximized benefit to all parties while supporting an efficient overall site remediation program. Once the property was vacant and the warehouse structure and radiologically non-impacted above-grade structures were demolished, the project identified an opportunity to significantly reduce the volume of waste associated with the foundation of the former warehouse, a foundation suspected of being partially constructed in radiologically contaminated soils. The project developed and implemented supplemental radiological verification survey and sampling strategies based on radiological cross-contamination risk potential with process flow-charts and screening-level based decision points; a program that classified saw-cut sections of concrete based on observed residual surface radioactivity conditions using a combination of gamma sensitive sodium-iodide scans and beta sensitive Geiger-Muller direct measurements. The proposed approach was reviewed with stakeholders with feedback, including consideration of applicable State of New Jersey Site Remediation Program criteria and guidance before implementation. Once classified, additional sampling was performed at frequencies driven by screening. The sampling methods, stockpile sampling frequencies, criteria and, approach to data evaluation were developed in consideration of existing site cleanup standards, regional background ranges, State of New Jersey radiological remediation program guidance, and specific stakeholder input With the property remediation and survey efforts nearly completed, it is relevant to examine retrospectively the objectives, assumptions and limitations in the remedial design (i.e., what was planned) versus what was able to be accomplished through effective teaming. Benefits to other environmental remediation site programs include better understanding of how to work effectively with stakeholders to achieve win-win outcomes, and approaches to site remediation, waste minimization and materials reuse that were successful in their overall outcomes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Levelized cost of charging of extreme fast charging with stationary LMO/LTO batteries

Extreme DC fast charging for electric vehicles (EVs) could be competitive with the internal combustion engine refueling experience and enable longer-distance travel, which could help with EV adoption and decarbonization, but these systems have high capital costs and extremely variable high-power demands. Behind-the-meter systems (BTMS) could support extreme-fast-charging (XFC) stations to increase nationwide adoption of EVs. Here, this study examines the optimal break-even levelized cost of charging (LCOC) across 96 BTMS scenarios to enable low-wait XFC stations providing 200 miles of charge in 10 min. This research simulates LCOC via synthetic XFC-capable EV loads, machine-learned battery life models from testing data, and nonlinear optimal controls, co-minimizing complex utility costs and battery replacements. An aggregate optimal BTMS design treating each EV load as equal likely gives an optimal LCOC per utility rate, the average of which is $\$$0.59/kWh. In addition, the sensitivity of optimal and off-optimal design factors, the long-life LMO/LTO chemistry, and optimized controls are analyzed. The battery control model, based on battery stressors to compare chemistries, optimizes LMO/LTO resting state of charge and cycle depth without compromising cost reduction, which enables greater flexibility in operation. The LCOC savings due to replacement reduction are small, up to $\$$0.035/kWh (6%), with an average of $\$$0.02/kWh (3.5%). Compared with gasoline stations, the aggregate XFC station design achieves comparable speed, experience of service, and cost at $\$$3.81/gal gasoline, showing that EVs can replace gasoline vehicles even for longer-distance travel.

25 ENERGY STORAGE↗

XACC: a system-level software infrastructure for heterogeneous quantum–classical computing

Quantum programming techniques and software have advanced significantly over the past five years, with a majority focusing on high-level language frameworks targeting remote REST library APIs. As quantum computing architectures advance and become more widely available, lower-level, system software infrastructures will be needed to enable tighter, co-processor programming and access models. In this work, we present XACC, a system-level software infrastructure for quantum–classical computing that promotes a service-oriented architecture to expose interfaces for core quantum programming, compilation, and execution tasks. Additionally, we detail XACC's interfaces, their interactions, and its implementation as a hardware-agnostic framework for both near-term and future quantum–classical architectures. We provide concrete examples demonstrating the utility of this framework with paradigmatic tasks. Our approach lays the foundation for the development of compilers, associated runtimes, and low-level system tools tightly integrating quantum and classical workflows.

97 MATHEMATICS AND COMPUTING↗

jupyterhub-announcement v0.8

This is an announcement service for JupyterHub that JupyterHub admins can manage through a JupyterHub-styled UI. JupyterHub administrators can use it to communicate with their hub's users about status, upcoming outages, or share news. It allows admins to post a current announcement, and show previous announcements in reverse chronological order. It provides a REST API hook that admins can use to post the latest announcement on JupyterHub itself (with custom templates).

Thomas, Rollin↗

Next generation experimental data access at NSLS-II

The NSLS-II network and computing infrastructure has been significantly updated recently. The re-IP process in 2020-2021 enabled the NSLS-II network to be routable to the rest of the BNL campus. Then, standardization of the operating systems and deployment procedures helped to deliver a consistent environment to workstations and servers used by all NSLS-II beamlines. In particular, the RedHat Enterprise Linux 8 was deployed to 700+ machines using the RedHat Satellite infrastructure management product, and all critical services (IOCs, databases, etc.) were migrated to the new OS. NFS users’ home directories are consistent across all of the machines, which eliminates the need for the individual configuration of the user environment on each host. The standard suite of software packages is available to the beamline staff and users, which includes the system packages (deployed via RPM) as well as the conda environments for data acquisition and analysis. Security measures were implemented to comply with the industry standards, which include multi-factor authentication (using Duo), secure screen lock for the beamline machines, and advanced access control to the experimental data that is stored in shared central storage available on all hosts. These major enhancements facilitated sharing the experimental data (currently for a number of selected beamlines, with a plan to extend it to the whole facility in the nearest future) with the users via an externally facing JupyterHub instance. The beamlines keep using the Bluesky data acquisition framework to orchestrate their experiments, and the new infrastructure enabled them to use a next-generation data access library called tiled.

36 MATERIALS SCIENCE↗

BigData Express: Toward Predictable, Schedulable, and High-Performance Data Transfer [Slides]

BigData Express: a schedulable, predictable, and high-performance data transfer service. A peer-to-peer, scalable, and extensible data transfer model; A visually appealing, easy-to-use web portal; A high-performance data transfer engine; On-demand provisioning of end-to-end network paths with guaranteed QoS; Robust and flexible error handling; CILogon-based security (certificate version); A rich set of REST APIs to support scientific workflows

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

A Path to 100 Percent Renewable Energy: Grid-Forming Inverters will Give Us the Grid We Need Now

This is a more urgent problem than it might sound. The westernmost Hawaiian island of significant size, Kauai is home to around 70,000 residents and 30,000 tourists at any given time. Renewable energy accounts for 70 percent of the energy produced in a typical year - a proportion that's among the highest in the world and that can be hard to sustain for such a small and isolated grid. During the day, the local system operator, the Kauai Island Utility Cooperative, sometimes reaches levels of 90 percent from solar alone. But on 2 April, the 26-MW generator was running near its peak output, to compensate for the drop in solar output as the sun set. At the moment when it failed, that single generator had been supplying 60 percent of the load for the entire island, with the rest being met by a mix of smaller generators and several utility-scale solar-and-battery systems.

battery management systems↗

Scalable, In-situ Data Clustering Data Analysis for Extreme Scale Scientific Computing (Final Report)

The objective of this project is to address challenges in the design and development of scalable in-situ data clustering and analytics algorithms and software. Our goal is to develop parallel software consisting of a set of spatio-temporal data clustering and anomaly detection functions, both of which are very important for large-scale analysis and have wide applicability for in-situ runs as well as post-processing analysis. Our design principles for in-situ analysis consider the following: (1) identify parts of the computation can be done close to the data within the nodes, while it is still in memory; (2) extract analysis components can (and should) be performed in remote staging and analysis nodes; (3) develop error-bound approximation methods for applications tolerable for small errors; (4) identify the type of derived distributions and statistics, for spatio-temporal data, that can be kept locally in order to both accelerate computations and meet energy constraints in subsequent iterations and phases; (5) use a self-describing data format so that data can be consistent and understood among local storage (memory and SSDs) and at staging and analysis nodes, thereby providing portability and flexibility; (6) develop service-oriented functions that can schedule in-situ and post-hoc analysis tasks based on the dynamic requirements of applications. Our development focus is to produce the parallel data analysis software/library that will be scalable, reusable, extensible, and generic for applications in different disciplines. The software will be able to run in-situ with the simulations as well as post-hoc analysis. This approach will satisfy many synergistic requirements for data intensive applications executed on data coming from instruments and experiments. In particular, the proposed multilevel approach is directly applicable to perform design tradeoffs for running part of the algorithms near the instruments and the rest on remote (analysis) systems.

97 MATHEMATICS AND COMPUTING↗

Performance Comparisons for Artificially Propagated and Wild Pacific Lamprey Juveniles and Larvae

ABSTRACT Artificially propagated Pacific lamprey ( Entosphenus tridentatus ) are produced for restoration and for use in dam passage studies to reduce the demand for wild fish. Such uses require that animals are representative of their wild counterparts. Previous work indicated that this is true for Pacific lamprey larvae and juveniles reared in the hatchery with respect to the length of sustained swimming. However, more subtle differences in behaviour and performance that lamprey need to survive have not been assessed. In this study, artificially propagated and wild fish were compared in laboratory tests under no‐flow conditions to examine light avoidance, burrowing speed, burst swim speed, volitional routine swim speed and time to come to rest. Most larvae burrowed in less than a minute, and we found highly significant differences ( p < 0.001) between artificially propagated and wild larvae burrowing times, a critical escape behaviour. This could have implications for studies of larval entrainment at irrigation diversion canals or in turbine boils at dams. Interestingly, all of the wild juveniles tested came to rest quickly after introduction to the chamber (1.5 min), while artificially propagated lamprey swam robotically near the surface and 48% did not come to rest in the first 10 min (median time to rest = 9.5 min). In contrast, wild juveniles quickly (median = 1.47 min) sought areas near the tank bottom and attached strongly with their oral disc. Such behavioural differences could have important survival consequences for artificially propagated lamprey as they approach turbine intakes, bypass screens and irrigation diversion headgates. This study highlights the need to conduct behavioural assays that examine subtleties of fish behaviour that can be missed with traditional swim tunnel comparisons.

Frick, Kinsey [Fish Ecology Division, Northwest Fi↗

Algorithm Theoretical Basis Document For PreMevE 2.0 Model

Man-made satellites operating in medium- and high-altitude Earth orbits are continuously exposed to hazardous space radiation originated from different sources. Among them, one major contributor is the relativistic electron population—with kinetic energies comparable to or larger than their rest energy of 0.511 Megaelectron-volt (MeV)—trapped inside Earth’s outer Van Allen belt. Owing to their high penetration capability, these MeV electrons are difficult to be fully stopped by normal shielding. Particularly, during MeV electron events when electron intensities across the outer belt are greatly elevated to sustaining high levels—up to 10 3 - 10 4 times as observed in the geosynchronous (GEO) orbit and low-Earth-orbits (LEOs), space-borne electronic systems with inadequate hardening are susceptible to deep-dielectric charging and discharging phenomenon caused by those electrons, and thus may suffer severe damages or even stop functioning. Therefore, protecting critical space infrastructures from harsh space weather conditions– including MeV electron events – has high priority for many space sectors, such as the aerospace industry, service providers and government agencies.

79 ASTRONOMY AND ASTROPHYSICS↗

WOMBAT (Windfarm Operations and Maintenance cost-Benefit Analysis Tool) WISDEM® [SWR-21-68]

The windfarm operations and maintenance cost-benefit analysis tool (WOMBAT) is software to simulate the operations and maintenance phase of either onshore or offshore windfarms. WOMBAT is a medium-fidelity tool that is designed to model turbine, cable, and substation failures at the subassembly level, but is flexible enough that individual component or asset-level modeling can also be performed. WOMBAT enables users to model technological improvements, the use of a wide range of service equipment from drone repairs and remote resets to heavy lift vessels and crawler cranes, to analyze cost trends with varying trade-offs in conjunction with energy production, availability and a growing range of metrics. This library provides a tool to simulate the operation and maintenance phase (O&M) of distributed, land-based, and offshore windfarms using a discrete event simulation framework. WOMBAT is written around the SimPy discrete event simulation framework. Additionally, this is supported using a flexible and modular object-oriented code base, which enables the modeling of arbitrarily large (or small) windfarms with as many or as few failure and maintenance tasks that can be encoded. Please note that this is still heavily under development, so you may find some functionality to be incomplete at the current moment, but rest assured the functionality is expanding. With that said, it would be greatly appreciated for issues or PRs to be submitted for any improvements at all, from fixing typos (guaranteed to be a few) to features to testing. Also available at: https://pypi.org/project/wombat/

Cooperman, Aubryn↗

Third-Party Aggregation Rulemaking in MISO and SPP Footprints

The report highlights key considerations for retail regulators in the footprints of the Southwest Power Pool (SPP) or Midcontinent Independent System Operator (MISO) in states that previously opted out of allowing third-party aggregation participation under FERC Order 719 and that may want to explore reversing the decision due to a changing policy environment under new FERC orders (i.e., 2222) and/or tightening resource adequacy constraints. Through a document review and a series of 27 interviews with regulators, aggregators, and other industry professionals, this document provides a high-level policy overview of the retail regulator’s role in a selection of processes, rules, and regulations to better understand how states have treated and/or integrated aggregators into wholesale markets. The report summarizes findings in two sections: General Findings and Specific Policy Findings. The General Findings offer high level takeaways such as the fact that 17 of the 20 states in MISO and SPP footprints opted out of third party aggregations following Order 719. Additionally, there is only one state that is fully restructured in the MISO and SPP footprints whereas the rest are vertically integrated, and the majority of third-party aggregations in the U.S. take place in restructured states outside of these footprints. Even so, third-party aggregations do take place in MISO and SPP albeit in small numbers and in an ad hoc regulatory environment. The specific policy findings delve deeper into specific examples of state actions on the topics of jurisdiction, registration and licensing, data governance, dual participation, and dispute resolution. Tables in each category organize state actions into Tiers I-III, which roughly correspond to the possible level of involvement or possible change necessary by state regulators and/or legislators to implement these actions. The tier level does not indicate any value judgement, as each state has respective regulatory limitations and each decision comes with various tradeoffs. One main tradeoff is between simplicity and quick implementation versus comprehensive and prolonged implementation. In many cases, actions in Tier I could be implemented without significant changes by relying on the use of existing processes for an aggregator context. On the other hand, many actions in Tier III are more narrowly designed to address aggregators specifically, but often require more significant changes including the involvement of additional parties through stakeholder engagement or legislative action. In some cases, these tiers are discrete. However, state regulators may also choose to progress through these various tiers sequentially as they phase in aggregators while learning from their experience. With the ability to stack bulk system level services, distributed energy resource aggregations in MISO and SPP could provide various private benefits (e.g., increased value streams to the owner) as well as societally beneficial grid services (e.g., peaking capacity, ancillary services, and other services that increase the grid’s overall operational efficiency). In deciding how to best to enable these benefits, states and retail regulators must weigh various tradeoffs if considering reversing a previous opt out.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗