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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Formulation of 8-moment plasma transport with application to the Nernst effect

8-moment plasma models using two different distribution functions are used to study the Nernst effect and heat transport in dense plasma. These models are presented in hyperbolic form in contrast to traditional parabolic systems derived from perturbing the distribution function, as in Braginskii [Rev. Plasma Phys. 1, 205 (1965)]. The hyperbolic moment formulation can be solved implicitly in time with straightforward and fast local solvers. The numerical implementation of 8-moment models with the relaxation method in the PERSEUS code is also presented. To test 8-moment PERSEUS compared to Braginskii’s transport equations, a verification test for the Nernst thermomagnetic wave by Velikovich et al. [Phys. Plasmas 26, 112702 (2019)] is performed that confirms the presence of the same physics, but with slight differences in the transport coefficients, which are tabulated in the limits of high and low magnetization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Design of a Novel Variable Geometry Divertor for Tokamaks

The divertor is a key component of fusion reactors, allowing exhaust of gas, impurities, and helium ash to preserve plasma purity. The divertor geometry strongly affects plasma performance, and it is designed to be compatible with different plasma shapes in present-day fusion experiments. Here, we present a novel concept for a variable geometry divertor, in which the divertor baffle tiles are reorientable by external actuation. Implementation of this concept in a medium-sized research tokamak would uniquely provide the flexibility to tailor divertor geometry to the plasma configuration and also enable study of the effect of divertor closure on plasma performance. To ensure compatibility with typical tokamak operations, the adjustable divertor must withstand the effects of significant mechanical and thermal stresses such as MW/m 2 -scale heat fluxes and large electromagnetic fields, e.g., disruption forces. The technological solutions for actuation mechanisms, cooling system, gas baffling and plasma-facing components are assessed. A functional reduced-scale model with movable outer divertor target baffle tiles is developed and the actuation mechanism is tested.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Modeling the Functional Forms of Grid Disturbances

This report introduces a functional form that may be used to quantitatively predict the impacts of new grid tools and changing system qualities on the likelihoods, durations, and depths of various grid disturbances. Each disturbance scenario is modeled to have three component stages—avoidance, reactance and recovery, which together parametrically estimate one disturbance’s impacts. The modeled scenario is then placed and replicated within an analysis period to represent the likelihood or frequency of the scenario and its consequent impacts. Whereas analysts have struggled to define and apply metrics for grid resilience, the functional form introduced by this report shares units of measurement with accepted grid-status measures (e.g., numbers of customers currently experiencing a service outage). Furthermore, the integrated and averaged functional form over an analysis period provides a meaningful normalized performance metric (e.g., customer outage minutes per year) that is ultimately independent of the duration of the period of. The approach may be applied similarly regardless of the severity or frequency of the disturbances that are being analyzed. Because metrics can be chosen to be identical in both the hypothetical future and the actual historical past, the historical past eventually becomes the test of the future predictions, at least in a statistical sense. The authors originally developed this approach to facilitate analysis of the effects of transactive energy (TE) systems effects on electric power grid resilience. TE systems invite energy suppliers and consumers to actively collaborate toward the discovery of, and their responses to, the locational value of energy. The findings from this process are often embodied as energy prices, the dynamics of which indicate the locational value of energy and can further represent important grid service needs. While some academic papers claim to quantify the value of a specific TE system design toward grid resilience, the answer, in general, has been elusive. Not only do multiple and conflicting definitions of resilience and reliability exist, but countless TE systems are being invented. We conclude the following: (1) The ideal analysis should harmonize rather than differentiate resilience and reliability. Therefore, this report uses the more general term disturbance whenever the overloaded terms resilience and reliability can be avoided. (2) The effectiveness of TE systems must be mapped to underlying qualities of a TE system, thereby avoiding presumptions that every TE design offers similar advantages. The authors seek to evaluate the parametric effects of TE system qualities (e.g., spatial granularity, granularity of time steps, length of future prediction horizon) on avoiding, reacting to, and recovering from grid disturbances. Furthermore, any advantages (or disadvantages) must be fairly compared with the many alternative tools, systems, and strategies that might offer comparable benefits.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Risk-Informed MultiPphysics BestEestimate Plus Uncertainties (BEPU) Application Development of RELAP5-3D Perturbation Model

The United States nuclear industry is facing a strong challenge to ensure maximum safety while enhancing economic benefit. Safety is a key parameter to all aspects related to light water reactor (LWR) nuclear power plants (NPPs), especially cost savings. Since the goal is to extend the lifetimes of these NPPs, the traditional deterministic safety concept may not guarantee a current economic asset. The Light Water Reactor Sustainability (LWRS) Program has been promoting a wide range of research and development (R&D) in this field to maximize the safety, economics, and performance of these NPPs through improved scientific understanding. One of the best practices to achieve this goal is to identify and optimize safety margins, which can lead to cost reduction. To do this, under the LWRS framework, the Risk-Informed Systems Analysis (RISA) Pathway will focus on the optimization of safety margin and minimization of uncertainties to ensure both safety and economics at the highest level. The RISA Pathway will provide enhanced capabilities for analyzing and characterizing LWR systems performance by developing and demonstrating methods, tools, and data to enable risk-informed margins management (RIMM). The goals of the RISA Pathway are twofold: (1) deploy the risk-informed tools and methods that enable better representation of safety margins and factors that contribute to cost and safety; and (2) conduct advanced risk assessment applications with industry to support margin management strategies that enable more cost-effective plant operation. The tools and methods provided by the RISA Pathway will support effective margin management for both active and passive safety systems, structures, and components (SSC) of an NPP. The tools and methods used in the RISA Pathway should have high confidence and highest technical maturity for and implementation to industry at its current setting. They should also have a capability to support risk-informed decision making for both probabilistic and deterministic elements of safety. The RISA Pathway will, therefore, perform a comprehensive assessment of verification and validation (V&V) status of RISA Toolkit to enhance credibility RISA Toolkit which be used by industry. This report summarizes RELAP5-3D development activities for best estimated and uncertainty (BEPU) capability to support ongoing RISA Pathway pilot projects for risk informed uncertainty quantification applications. Work scope includes (1) development of initial perturbation model for selected closure laws and (2) testing of suitable probability distribution functions (PDF) for the selected correlations. Developed BEPU modules are tested with selected separate effect cases and compared with conventional thermal-hydraulics model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Metagenome-assembled genomes provide insight into the metabolic potential during early production of Hydraulic Fracturing Test Site 2 in the Delaware Basin

Demand for natural gas continues to climb in the United States, having reached a record monthly high of 104.9 billion cubic feet per day (Bcf/d) in November 2023. Hydraulic fracturing, a technique used to extract natural gas and oil from deep underground reservoirs, involves injecting large volumes of fluid, proppant, and chemical additives into shale units. This is followed by a “shut-in” period, during which the fracture fluid remains pressurized in the well for several weeks. The microbial processes that occur within the reservoir during this shut-in period are not well understood; yet, these reactions may significantly impact the structural integrity and overall recovery of oil and gas from the well. To shed light on this critical phase, we conducted an analysis of both pre-shut-in material alongside production fluid collected throughout the initial production phase at the Hydraulic Fracturing Test Site 2 (HFTS 2) located in the prolific Wolfcamp formation within the Permian Delaware Basin of west Texas, USA. Specifically, we aimed to assess the microbial ecology and functional potential of the microbial community during this crucial time frame. Prior analysis of 16S rRNA sequencing data through the first 35 days of production revealed a strong selection for a Clostridia species corresponding to a significant decrease in microbial diversity. Here, we performed a metagenomic analysis of produced water sampled on Day 33 of production. This analysis yielded three high-quality metagenome-assembled genomes (MAGs), one of which was a Clostridia draft genome closely related to the recently classified Petromonas tenebris. This draft genome likely represents the dominant Clostridia species observed in our 16S rRNA profile. Annotation of the MAGs revealed the presence of genes involved in critical metabolic processes, including thiosulfate reduction, mixed acid fermentation, and biofilm formation. These findings suggest that this microbial community has the potential to contribute to well souring, biocorrosion, and biofouling within the reservoir. Our research provides unique insights into the early stages of production in one of the most prolific unconventional plays in the United States, with important implications for well management and energy recovery.

natural gas↗
DOE OSTI2020

Land Model Testbed: Accelerating Development, Benchmarking and Analysis of Land Surface Models

A Land Model Testbed (LMT), designed to provide a computational framework for systematically assessing model fidelity and supporting rapid development of complex multiscale models, offers a general-purpose workflow for conducting large ensemble simulations of multiple land surface models, post-processing large volumes of model output, and evaluating model results. It leverages existing tools for launching model simulations and the International Land Model Benchmarking (ILAMB) package for assessing model fidelity through comparison with best-available observational datasets. Increased complexity and proliferation of uncertain parameters in process representations in land surface models has driven the need for frequent and intensive testing and evaluating of models to quantify uncertainties and optimize parameters such that results are consistent with observations. The LMT described here meets these needs by providing tools to run thousands of ensemble simulations simultaneously and post-process their output files, by automating execution of an enhanced version of ILAMB with site-specific benchmarks and multivariate functional relationships, and by offering ensemble diagnostics and a customizable dashboard for displaying model performance metrics and associated graphics. We envision the LMT capabilities will serve as a foundational computational resource for a proposed user facility focused on terrestrial multiscale model--data integration.

Sreepathi, Sarat↗
DOE OSTI2022

Quantum model learning agent: characterisation of quantum systems through machine learning

Accurate models of real quantum systems are important for investigating their behaviour, yet are difficult to distil empirically. Here, we report an algorithm—the quantum model learning agent (QMLA)—to reverse engineer Hamiltonian descriptions of a target system. We test the performance of QMLA on a number of simulated experiments, demonstrating several mechanisms for the design of candidate Hamiltonian models and simultaneously entertaining numerous hypotheses about the nature of the physical interactions governing the system under study. QMLA is shown to identify the true model in the majority of instances, when provided with limited a priori information, and control of the experimental setup. Our protocol can explore Ising, Heisenberg and Hubbard families of models in parallel, reliably identifying the family which best describes the system dynamics. We demonstrate QMLA operating on large model spaces by incorporating a genetic algorithm to formulate new hypothetical models. The selection of models whose features propagate to the next generation is based upon an objective function inspired by the Elo rating scheme, typically used to rate competitors in games such as chess and football. In all instances, our protocol finds models that exhibit F 1 score ≥ 0.88 when compared with the true model, and it precisely identifies the true model in 72% of cases, whilst exploring a space of over 250 000 potential models. By testing which interactions actually occur in the target system, QMLA is a viable tool for both the exploration of fundamental physics and the characterisation and calibration of quantum devices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

3D printable polyvinyltoluene-based plastic scintillators with pulse shape discrimination

A feasibility of preparing bulk photopolymerized plastics scintillators that contain vinyltoluene with multifunctional monomers, pentaerythritol tetraacrylate is shown. This formulation offers a simple and fast way to prepare polyvinyltoluene-based plastics with efficient fast neutron/gamma pulse shape discrimination (PSD) within minutes. 30 wt% of 2,5-diphenyloxazole (PPO) was added in the mixtures of vinyltoluene and pentaerythritol tetraacrylate with different secondary dyes to understand the effect of dyes on the scintillation. Prepared resins were photopolymerized under different conditions, and the scintillation performance was compared to a commercially available standard, EJ-276. Additional functionality for thermal neutron sensitivity was introduced by the incorporation of 6 Li and 6 B nuclei. With optimized conditions, prepared plastics showed light output up to 90% relative to the same size of EJ-276. Here, the best plastic scintillators had PSD figures of merit (FoMs) up to 2.77 compared to 3.25 of EJ-276. The 3D-printability of the tested formulations was demonstrated.

36 MATERIALS SCIENCE↗
DOE OSTI2022

The MTA primary beamline description and performance [Slides]

The Muon Test Area (2003) was initially constructed to develop, test, and verify muon ionization apparatus using the 400-MeV proton beam from the Fermilab Linac. Since muon facilities involve the capture, collection and cooling of ~10 13 muons at a repetition conclusive tests require ~10 13 protons/pulse (full Linac beam): the original concept/request was for a full Linac capability (~10 14 p/sec). The beamline designed for MTA experiments, however, includes specialized insertions for linac beam diagnostics and beam measurements, greatly enhancing the functionality and complexity of the beamline. Installation of the beamline was complete fall, 2008. It represents the only facility in which experiments have direct access to a primary beam.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Thermal Hydraulic Experimental Test Article (FY21 Final Report)

The Thermal Hydraulic Experimental Test Article (THETA) is a facility that will be used to develop sodium components and instrumentation as well as acquire experimental data for validation of reactor thermal hydraulic and safety analysis codes. The facility will simulate nominal conditions as well as protected/unprotected loss of flow accidents in a sodium-cooled fast reactor (SFR). High fidelity distributed temperature profiles of the developed flow field will be acquired with Rayleigh backscatter based optical fiber temperature sensors. The facility is being designed in partnership with systems code experts to tailor the experiment to ensure the most relevant and highest quality data for code validation. THETA is comprised of a traditional primary and secondary system. The primary system is submerged in the pool of sodium and consists of a pump, electrically heated core, intermediate heat exchanger, and connected piping and thermal barriers (redan). The secondary system, located outside of the sodium pool, consists of a pump, sodium to air heat exchanger, and connected piping and valves. Figure 1 illustrates the main components of the primary system. THETA has been installed in the Mechanisms Engineering Test Loop (METL) with the primary system in the 28 inch Test Vessel #4, Figure 2 and Figure 3. Since the FY20 THETA status report, further water shakedown testing was performed, some final welding modifications were performed, all system components were sanitized, dry assembled, and commissioned. The THETA submersible electromagnetic flowmeter was welded closed to hermetically seal internal components from sodium followed by a helium leak check for the final time. Following installation of THETA into vessel #4, all data acquisition and control systems were brought online and commissioned at room temperature in the argon gas space of the empty vessel. The vessel zone 1 heaters were reinstalled and the flange was then insulated. The vessel 4 heaters were brought to a temperature of 100 °C and the THETA pump was jogged at 600 RPM to ensure it was functioning correctly. The secondary, AC Conduction based electromagnetic pump from CMI Novacast (product number CA-15) was ordered and will be delivered in late calendar year 2021. The custom designed permanent magnet based secondary flowmeter was designed, a drawing package and manufacturing specification created and quote requested from a machine shop. The intermediate heat exchanger design was completed and a drawing package is currently in progress. During the middle of calendar year 2021 the Building 308 sodium scrubber system was shut down in order to replaced some corroded piping and facilitate improvements on the system, thus requiring the sodium in METL to remain frozen. This has imposed a delay in filling vessel 4 with sodium to begin THETA testing. Sodium testing is expected to begin in early fiscal year 2022 as all THETA primary systems are operational.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Intrinsic (Trap‐Free) Transistors Based on Epitaxial Single‐Crystal Perovskites

Abstract The first experimental realization of the intrinsic (not dominated by defects) charge conduction regime in lead‐halide perovskite field‐effect transistors (FETs) is reported. The advance is enabled by: i) a new vapor‐phase epitaxy technique that results in large‐area single‐crystalline cesium lead bromide (CsPbBr 3 ) films with excellent structural and surface properties, including atomically flat surface morphology, essentially free from defects and traps at the level relevant to device operation; ii) an extensive materials analysis of these films using a variety of thin‐film and surface probes certifying the chemical and structural quality of the material; and iii) the fabrication of nearly ideal (trap‐free) FETs with characteristics superior to any reported to date. These devices allow the investigation of the intrinsic FET and (gated) Hall‐effect carrier mobilities as functions of temperature. The intrinsic mobility is found to increase on cooling from ≈30 cm 2 V −1 s −1 at room temperature to ≈250 cm 2 V −1 s −1 at 50 K, revealing a band transport limited by phonon scattering. Establishing the intrinsic (phonon‐limited) mobility provides a solid test for theoretical descriptions of carrier transport in perovskites, reveals basic limits to the technology, and points to a path for future high‐performance perovskite electronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Train, Inform, Borrow, or Combine? Approaches to Process–Guided Deep Learning for Groundwater–Influenced Stream Temperature Prediction

Although groundwater discharge is a critical stream temperature control process, it is not explicitly represented in many stream temperature models, an omission that may reduce predictive accuracy, hinder management of aquatic habitat, and decrease user confidence. We assessed the performance of a previously-described process-guided deep learning model of stream temperature in the Delaware River Basin (USA). We found lower accuracy (root mean square error [RMSE] of 1.71 versus 1.35°C) and stronger seasonal bias (absolute mean monthly bias of 1.06 vs. 0.68°C) for reaches primarily influenced by deep groundwater as compared to atmospheric conditions. We then tested four approaches for improving groundwater process representation: (a) a custom loss function leveraging the unique patterns of air and water temperature coupling characteristic of different temperature drivers, (b) inclusion of additional groundwater-relevant catchment attributes, (c) incorporation of additional process model outputs, and (d) a composite model. The custom loss function and the additional attributes significantly improved the predictive accuracy in groundwater-dominated reaches (RMSE of 1.37 and 1.26°C) and reduced the seasonal bias (absolute mean monthly bias of 0.44 and 0.48°C), but neither approach could identify holdout groundwater reaches. Variable importance analysis indicates the custom loss function nudges the model to use the existing inputs more efficiently, whereas with the added features the model relies on a broader suite of inputs. This analysis is a substantial step toward more accurately representing groundwater discharge processes in stream temperature models and will improve predictive accuracy and inform habitat management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deep-learning-enabled Bayesian inference of fuel magnetization in magnetized liner inertial fusion

Fuel magnetization in magneto-inertial fusion (MIF) experiments improves charged burn product confinement, reducing requirements on fuel areal density and pressure to achieve self-heating. By elongating the path length of 1.01 MeV tritons produced in a pure deuterium fusion plasma, magnetization enhances the probability for deuterium–tritium reactions producing 11.8-17.1 MeV neutrons. Nuclear diagnostics thus enable a sensitive probe of magnetization. Characterization of magnetization, including uncertainty quantification, is crucial for understanding the physics governing target performance in MIF platforms, such as magnetized liner inertial fusion (MagLIF) experiments conducted at Sandia National Laboratories, Z-facility. We demonstrate a deep-learned surrogate of a physics-based model of nuclear measurements. A single model evaluation is reduced from O ( 10 – 100 ) (10–100) CPU hours on a high-performance computing cluster down to O ( 10 – 100 ) (10) ms on a laptop. This enables a Bayesian inference of magnetization, rigorously accounting for uncertainties from surrogate modeling and noisy nuclear measurements. The approach is validated by testing on synthetic data and comparing with a previous study. We analyze a series of MagLIF experiments systematically varying preheat, resulting in the first ever systematic experimental study of magnetic confinement properties of the fuel plasma as a function of fundamental inputs on any neutron-producing MIF platform. We demonstrate that magnetization decreases from B R ∼ 0.2 ~0.5 to B R ∼ 0.2 ~0.2 MG cm as laser preheat energy deposited increases from E preheat ∼ 460 ~460 J to E preheat ∼ 460 ~1.4 kJ. This trend is consistent with 2D LASNEX simulations showing Nernst advection of the magnetic field out of the hot fuel and diffusion into the target liner.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

3d TQFTs from Argyres–Douglas theories

We construct a new class of three-dimensional topological quantum field theories (3d TQFTs) by considering generalized Argyres–Douglas theories on S 1 × M 3 with a non-trivial holonomy of a discrete global symmetry along the S 1 . For the minimal choice of the holonomy, the resulting 3d TQFTs are non-unitary and semisimple, thus distinguishing themselves from theories of Chern–Simons and Rozansky–Witten types respectively. Changing the holonomy performs a Galois transformation on the TQFT, which can sometimes give rise to more familiar unitary theories such as the ${\left({G}_{2}\right)}_{1}$ and ${\left({F}_{4}\right)}_{1}$ Chern–Simons theories. Our construction is based on an intriguing relation between topologically twisted partition functions, wild Hitchin characters, and chiral algebras which, when combined together, relate Coulomb branch and Higgs branch data of the same 4d $\mathcal{N}=2$ theory. Finally, we test our proposal by applying localization techniques to the conjectural $\mathcal{N}=1$ UV Lagrangian descriptions of the (A 1 , A 2 ), (A 1 , A 3 ) and (A 1 , D 3 ) theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Forecasting constraints on the high-z IGM thermal state from the Lyman-α forest flux autocorrelation function

ABSTRACT The autocorrelation function of the Lyman-$\alpha$ (Ly $\alpha$) forest flux from high-z quasars probes the small-scale structure of the intergalactic medium (IGM). The thermal state of the IGM, determined by the physics of reionization, sets the small-scale power observed in the Ly $\alpha$ forest. To explore the sensitivity of the autocorrelation function to the IGM’s thermal state, we compute the autocorrelation function from a cosmological hydrodynamical simulation with an instantaneous reionization model and 135 post-processed thermal states. Using mock data sets of 20 quasars, we forecast constraints on $T_0$ and $\gamma$, which characterize the post-processed IGM thermal state, at $5.4 \le z \le 6$. While this model simplifies the IGM’s thermal state, it serves as a key first step in assessing future observational prospects. We also perform an inference test on mocks and re-weight out posterior distributions to guarantee that they exhibit statistically correct behaviour. At $z = 5.4$, we find that an idealized data set constrains $T_0$ to 59 per cent and $\gamma$ to 16 per cent at the 1$\sigma$ equivalent confidence level. To explore more realistic, non-instantaneous reionization scenarios, we analyse four models combining temperature and ultraviolet background (UVB) fluctuations at $z = 5.8$. We find that mock data generated from a model with both temperature and UVB fluctuations can rule out a model with only temperature fluctuations at the $> 1\sigma$ level 73.9 per cent of the time.

Wolfson, Molly↗
DOE OSTI2022

Classification of bacterial plasmid and chromosome derived sequences using machine learning

Plasmids are important genetic elements that facilitate horizonal gene transfer between bacteria and contribute to the spread of virulence and antimicrobial resistance. Most bacterial genome sequences in the public archives exist in draft form with many contigs, making it difficult to determine if a contig is of chromosomal or plasmid origin. Using a training set of contigs comprising 10,584 chromosomes and 10,654 plasmids from the PATRIC database, we evaluated several machine learning models including random forest, logistic regression, XGBoost, and a neural network for their ability to classify chromosomal and plasmid sequences using nucleotide k-mers as features. Based on the methods tested, a neural network model that used nucleotide 6-mers as features that was trained on randomly selected chromosomal and plasmid subsequences 5kb in length achieved the best performance, outperforming existing out-of-the-box methods, with an average accuracy of 89.38% ± 2.16% over a 10-fold cross validation. The model accuracy can be improved to 92.08% by using a voting strategy when classifying holdout sequences. In both plasmids and chromosomes, subsequences encoding functions involved in horizontal gene transfer—including hypothetical proteins, transporters, phage, mobile elements, and CRISPR elements—were most likely to be misclassified by the model. This study provides a straightforward approach for identifying plasmid-encoding sequences in short read assemblies without the need for sequence alignment-based tools.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Equipment Qualification Report Environmental Qualification of GNB Absolyte Valve Regulated Lead Acid (VRLA) 1600 Ah100G33 Battery Rack Assembly (24590-QL-POA-EDB0-00001-11-00002_00A)

Greenberry Environmental Qualification Report 550001.001-35.0.5 provides basis for assignment of qualified life for: GNB Absolyte Valve Regulated Lead Acid (VRLA) 1600 Ah 100G33 Battery Rack Assembly in accordance with the requirements specified 24590-WTP-3PS-G000-T0015 (Rev 2) and Environmental Qualification Plan 550001.001-35.0.1 (Rev. 3). The equipment qualification basis represents the most conservative capability of the equipment. The analysis performed for the qualification is not less conservative than the bounding environmental conditions detailed in contract documents issued to Greenberry in contract 24509-QL-POA-EDB0-00001 Rev.0. The qualified life of 10 years has been established based upon an end-condition objective of the equipment condition indicators that correlate to the ability of equipment to perform its safety function. The VRLA Battery Cell Assembly was aged by 10 years (minimum) in accordance with conditions specified by Bechtel Equipment Qualification Datasheet 24590-LAW-EUQ-UPE 00003 Rev. 3 and the process conditions specified by the Instrument Data Sheet 24590-LAW EUD-UPE-00009 Rev. 2. Greenberry Industrial has contracted with GNB Industrial Battery Co located at 4115 S Zero St, Fort Smith, AR 72908 to perform age conditioning, monitoring, and capacity testing in accordance with Environmental Qualification Plan 550001.001-35.0.1 Rev. 1. The required process at the stated conditions set by the parameters established by the plan were completed satisfactorily. The details of the of the test process observed by Greenberry is detailed in the attached Seismic Test Log 550001.001-7.0.3, including examples of the objective evidence collected during the qualification process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

SD-WAN Evaluation Criteria for a Defense Information Systems Network Expeditionary Customer Edge

The Defense Information Systems Agency (DISA) has identified a service provision gap midway between the capacity and capability of a Defense Information Systems Network (DISN) transport Edge Points of Presence (POP) and U.S. Department of Defense (DoD) Enterprise Classified Travel Kit (DECTK). Some deployed force 100-user Tactical Operations Centers are in field locations far removed from the DISN transport core, in challenging environmental conditions with limitations on space, weight, power, and cooling for network equipment. As part of a multi-phase project, Pacific Northwest National Laboratory (PNNL) will gather and analyze requirements, design, develop, prototype, and test a miniaturized and ruggedized DISN Customer Edge POP scaled to support approximately 100 users in a field Tactical Operations Center. An Expeditionary Customer Edge (ECE) will be more suitable for field deployment than a DISN transport Edge POP, using ruggedized hardware and network function virtualization (NFV) to operate in challenging field environmental conditions, plus reduce weight, power, and cooling requirements. A key enabling technology for ECE is Software Defined Wide Area Networking (SD-WAN). This document provides: • A brief overview of SD-WAN use cases and how they apply to ECE • How SD-WAN technology compares to existing networks like DISN that use Optical Transport Networking (OTN) and Multiprotocol Label Switching (MPLS) • SD-WAN functional requirements relevant to ECE • A description of an ECE Virtual Prototype, including simulated wide area network paths and a DISN-representative implementation of MPLS, in Cisco Modeling Labs • Detailed network flow walkthroughs • Evaluation criteria based on ECE-relevant SD-WAN functional requirements Finally, an appendix provides an informal evaluation of Speedify—a commercial retail Virtual Private Network service—against the ECE SD-WAN evaluation criteria.

42 ENGINEERING↗