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DOE OSTI2021

Dual Function Solid State Battery with Self-Forming Self-Healing Electrolyte and Separator (Final Scientific/Technical Report)

Over the course of this program, we have demonstrated an improved rechargeable Li/I2 battery with reduced impedance, improved cyclability, improved Coulombic Efficiency, and the ability to “self-heal” during shorting events. Multi-year efforts have led to the development and improvements in the composition, fabrication, and preparation of the solid state electrolyte, the role of the interface, and design of appropriate test conditions. These investigations have led to significant improvements in Coulombic efficiency. By systematic development of a composite solid state electrolyte, this system is able to self-form upon charge, thus lending itself to long shelf life before use. The initial project objective was to demonstrate a solid-state rechargeable battery based on a Li-metal anode and iodine cathode with a self-forming, self-healing electrolyte and separator with high gravimetric and volumetric energy density. The final deliverables of this project build on a multi-year effort beginning with materials development and design to generate a suitable solid state electrolyte composite with demonstrated higher ionic conductivity compared to the baseline (LiI). Development in cell design and interface modification leading to the generation of rechargeable solid electrolyte cells with Coulombic efficiency improvements of ~3X over initial tests, as well as demonstration of self-healing behavior, where the cells retained their ability to continue extended cycling after shorting events. The hypothesis put forward as part of the initial concept for the project was that the cell chemistry would be self-healing. For example, if a lithium dendrite formed during charge of the cell and reached the iodine cathode, the reaction of the lithium dendrite with the iodine would consume the tip of the dendrite to form lithium iodide, more of the solid electrolyte. The formation of the solid electrolyte would allow the cell to recover and continue to function. This type of self-healing during cycling has been demonstrated and has the potential to improve on safety considerations that stem from shorting events in other Li- containing systems.

25 ENERGY STORAGE↗

DOE OSTI2020

Flexible Service Contracting for Risk Management within Integrated Transmission and Distribution Systems

The general objective of our project has been to investigate the ability of Independent Distribution System Operators (IDSOs), functioning as linkage agents for Integrated Transmission and Distribution (ITD) systems, to facilitate the flexible availability and usage of reserve in support of ITD system operations. This general objective is in accordance with Order 2222 of the U.S. Federal Energy Regulatory Commission (FERC), titled “Participation of Distributed Energy Resource Aggregations in Markets Operated by Regional Transmission Organizations and Independent System Operators”. The Final Rule for FERC Order 2222 was issued on September 17, 2020. The primary contribution of our project is that we have formulated an innovative energy management Transactive Energy Design (TES) approach for ITD systems that provides promising support for our project objective. Specifically, we have developed a new type of IDSO-managed TES design for distribution system operations, as well as new types of swing contracts permitting IDSOs to participate in transmission system operations as providers of reserve harnessed from distribution system resources in return for appropriate compensation. Together, these design elements constitute a scalable market-based approach facilitating efficient reserve procurement for ITD system operations from a fuller range of power resources. The efficacy of our approach has been demonstrated by means of detailed conceptual analyses as well as test case simulations. To implement the latter, we have developed the ITD TES Platform V2.0, a computational platform that permits the modeling and software implementation of ITD system operations over time. The Electric Reliability Council of Texas (ERCOT) energy region has been used as the empirical anchor for the development of this platform. Our conceptual and test-case work has been reported in a Wiley/IEEE Press book, two refereed book chapters, and seven refereed journal articles. The key components comprising the ITD TES Platform V2.0 have been released as documented open-source software at online GitHub repositories.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Characterizing Human Performance: Detecting Targets at High False Alarm Rates [Slides]

Analysts develop a “no threat” bias with high false alarms. If only shown alarms for actual attacks, may never actually see an alarm. We see this in the laboratory, but not often studied in applied environments. (TSA is an exception.) In this work, near-operational paradigms are useful, but difficult to construct well. Pilot testing is critical before engaging time-limited professionals. Experimental control is difficult to balance with operational realism. Grounding near-operational experiments in basic research paradigms has both advantages and disadvantages. Despite shortcomings in our second experiment, we now have a platform for experimental investigations into the human element of physical security systems.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2022

CEBAF Accelerator Tunnel Robot Project

Advancements in the field of robotics allow for the use of remotely controlled robots to perform tasks that have typically required human intervention. Jefferson Lab has explored the possibilities of robots placed in the accelerator tunnel to perform remote inspections that would otherwise require powering down equipment and completing lengthy radiological surveys that impact beam operations. A robotic solution ? driven by a human operator ? could not only reduce accelerator down time but also support the Lab's radiation exposure policy (known as "ALARA" - As Low As Reasonably Acceptable) by handling routine tunnel and beamline investigations in place of a human being. However, operating a remote device in a radioactive, high electronic-noise area is not a trivial task and drop-in solutions are rarely as simple as they seem. We will present the past prototypes that were tested as well follow-on technology developed from the project. We will also briefly survey current applications of robots at accelerator facilities with an eye toward future applications.

McGuckin, Theodore↗

DOE OSTI2024

Towards Marine Carbon Dioxide Removal (mCDR) Centers of Excellence

A diverse portfolio of carbon dioxide removal (CDR) technologies will be essential to meeting climate goals while supporting sustainable development. In particular, marine carbon dioxide removal (mCDR) methods can help diversify the existing portfolio, which currently relies heavily on engineered direct air capture systems for large-scale atmospheric removals. To fulfill their potential in the CDR ecosystem, these early-stage mCDR technologies require additional research and development. Here, we propose regional mCDR Technology Centers of Excellence that will provide inventors and developers with access to right-scale facilities and engineering expertise that will meet their needs wherever they are on the journey from bench- to pilot-scale development. To support innovation across the technological readiness level spectrum, these Centers will provide collaborative access to ocean-based mCDR testing sites; other opportunities for partnering with multidisciplinary experts in technology development and commercialization; provide meaningful pathways for integrated engagement with local industrial and regulatory systems; and help in developing tailored, impactful community benefit models. Ideal sites are co-located in areas with a favorable natural environment for testing mCDR, well studied baselines, accessible infrastructure for multidisciplinary marine research, and technology commercialization support. As a case study, we offer the Pacific Northwest as particularly suitable for a regional mCDR Technology Center of Excellence given existing and potential growth of all the characteristics of ideal sites listed above, and which could especially benefit from the region’s growing marine climate technology sector. Last, we offer a brief whole-of-government perspective for supporting and regulating these Centers of Excellence, including identification of mCDR Science Centers of Excellence to ensure that the development of mCDR technologies dovetails with much-needed advancements in oceanographic observation and simulation infrastructure.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Uncertainty Quantification for Component Modeling Using the Discrete-Direct Approach

Threaded fastener behavior can be an important aspect of complex component and system behavior, but there is no one-size-fits-all finite element analysis technique. Proper modeling of threaded fastener joints requires careful consideration of many details, from test setup and data acquisition to constitutive modeling and uncertainty quantification approaches. This report details analysis of a “mini-radax” bolted-joint exemplar where a Discrete-Direct uncertainty quantification approach is employed to evaluate margin of the component. The mini-radax geometry is tested to failure on a drop table, and single-coupon tests of individual fasteners serve as foundational data for the analysis. Analysis predictions complement the test data well and provide additional context for engineering decision-making.

42 ENGINEERING↗

DOE OSTI2024

Complete development of LAROMance-type surrogate models for Zircaloy, as well as initial integration and testing in MOOSE, which addresses industry needs for licensing advanced LWR fuels

This milestone report details the progress in the constitutive surrogate modeling framework for Zircaloy’s mechanical behavior under extreme conditions, within the NEAMS program throughout the U.S. fiscal year 2024 (FY24). The presented work expands on the spectral based mechanical solver and the mechanistic material model for Zircaloy, which were introduced in the NEAMS program during FY22 and detailed in the previous fiscal year (FY23). As part of the NEAMS program, the current effort described in this report focused on the development of a novel viscplastic (creep) surrogate for the mechanistic, polycrystal-based model. To this end, the work was subdivided into two interdependent components related to the necessary improvements to the LApx constitutive model and algorithm and, to the development and use of a surrogate model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Finite-Geometry Corrections for Neutron Scattering Cross Section Measurements

In this report, we describe the corrections necessary for neutron scattering cross section measurements in experiments which use finite-geometry scattering samples. A new Geant4 based framework was developed to calculate these corrections which has been benchmarked against a well-measured test case. This framework also calculates the outgoing neutron energy dependence of the correction factors, which is crucial when resolving individual final states in the scatterer is not possible.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

MEMS RF accelerators for nuclear energy and advanced manufacturing

Energetic ions are widely used to develop radiation hard structural materials and fuels for advanced nuclear energy. Ion beams are also used to generate neutrons for nuclear materials testing, as well as in a series of high impact, high value adding manufacturing processes (ranging from doping of semiconductors to hardening of materials against wear and to increase bio-compatibility of materials). But to date, high power beams of high energy ions are simply too expensive because they are delivered from large single beam accelerators. We have recently demonstrated that MEMS technology enables massively parallel, low cost batch fabrication of ion beams. We propose to scale intense ion accelerators based on MEMS (micro-electro mechanical systems) to high beam power (>10 kW). With our approach, hundreds to thousands of ion beamlets will be densely packed on silicon wafers. Ions are injected and accelerated across gaps formed in stacks of wafers, leading to uniquely high current densities for intense ion accelerators with variable kinetic energy (0.1 to 10 MeV) and variable ion species. Our team brings together experts in high power ion accelerators from Lawrence Berkeley National Laboratory and leading experts in MEMS technology from Cornell University. We will deliver a disruptive technology of low cost, flexible and massively scalable ion accelerators that will enable the rapid development of radiation hard nuclear materials for advanced nuclear energy and enable new applications in manufacturing.

43 PARTICLE ACCELERATORS↗

DOE OSTI2023

Enabling Floating Offshore VAWT Design by Coupling OWENS and OpenFAST

Vertical-axis wind turbines (VAWTs) have a long history, with a wide variety of turbine archetypes that have been designed and tested since the 1970s. While few utility-scale VAWTs currently exist, the placement of the generator near the turbine base could make VAWTs advantageous over tradition horizontal-axis wind turbines for floating offshore wind applications via reduced platform costs and improved scaling potential. However, there are currently few numerical design and analysis tools available for VAWTs. One existing engineering toolset for aero-hydro-servo-elastic simulation of VAWTs is the Offshore Wind ENergy Simulator (OWENS), but its current modeling capability for floating systems is non-standard and not ideal. This article describes how OWENS has been coupled to several OpenFAST modules to update and improve modeling of floating offshore VAWTs and discusses the verification of these new capabilities and features. The results of the coupled OWENS verification test agree well with a parallel OpenFAST simulation, validating the new modeling and simulation capabilities in OWENS for floating VAWT applications. These developments will enable the design and optimization of floating offshore VAWTs in the future.

17 WIND ENERGY↗

DOE OSTI2020

Image Collection Simulation Using High-Resolution Atmospheric Modeling

A new method is described for simulating the passive remote sensing image collection of ground targets that includes effects from atmospheric physics and dynamics at fine spatial and temporal scales. The innovation in this research is the process of combining a high-resolution weather model with image collection simulation to attempt to account for heterogeneous and high-resolution atmospheric effects on image products. The atmosphere was modeled on a 3D voxel grid by a Large-Eddy Simulation (LES) driven by forcing data constrained by local ground-based and air-based observations. The spatial scale of the atmospheric model (10–100 m) came closer than conventional weather forecast scales (10–100 km) to approaching the scale of typical commercial multispectral imagery (2 m). This approach was demonstrated through a ground truth experiment conducted at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. In this experiment, calibrated targets (colored spectral tarps) were placed on the ground, and the scene was imaged with WorldView-3 multispectral imagery at a resolution enabling the tarps to be visible in at least 9–12 image pixels. The image collection was simulated with Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, using the 3D atmosphere from the LES model to generate a high-resolution cloud mask. The high-resolution atmospheric model-predicted cloud coverage was usually within 23% of the measured cloud cover. The simulated image products were comparable to the WorldView-3 satellite imagery in terms of the variations of cloud distributions and spectral properties of the ground targets in clear-sky regions, suggesting the potential utility of the proposed modeling framework in improving simulation capabilities, as well as testing and improving the operation of image collection processes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Two Bright M Dwarfs Hosting Ultra-Short-Period Super-Earths with Earth-like Compositions

We present observations of two bright M dwarfs (TOI-1634 and TOI-1685: J = 9.5–9.6) hosting ultra-short-period (USP) planets identified by the TESS mission. The two stars are similar in temperature, mass, and radius (T {sub eff} ≈ 3500 K, M {sub ·} ≈ 0.45–0.46 M {sub ⊙}, and R {sub ·} ≈ 0.45–0.46 R {sub ⊙}), and the planets are both super-Earth size (1.25 R {sub ⊕} < R {sub p} < 2.0 R {sub ⊕}). For both systems, light curves from ground-based photometry exhibit planetary transits, whose depths are consistent with those from the TESS photometry. We also refine the transit ephemerides based on the ground-based photometry, finding the orbital periods of P = 0.9893436 ± 0.0000020 days and P = 0.6691416 ± 0.0000019 days for TOI-1634b and TOI-1685b, respectively. Through intensive radial velocity (RV) observations using the InfraRed Doppler (IRD) instrument on the Subaru 8.2 m telescope, we confirm the planetary nature of the TOIs and measure their masses: 10.14 ± 0.95 M {sub ⊕} and 3.43 ± 0.93 M {sub ⊕} for TOI-1634b and TOI-1685b, respectively, when the observed RVs are fitted with a single-planet circular-orbit model. Combining those with the planet radii of R {sub p} = 1.749 ± 0.079 R {sub ⊕} (TOI-1634b) and 1.459 ± 0.065 R {sub ⊕} (TOI-1685b), we find that both USP planets have mean densities consistent with an Earth-like internal composition, which is typical for small USP planets. TOI-1634b is currently the most massive USP planet in this category, and it resides near the radius valley, which makes it a benchmark planet in the context of discussing the size limit of rocky planet cores as well as testing the formation scenarios for USP planets. Excess scatter in the RV residuals for TOI-1685 suggests the presence of a possible secondary planet or unknown activity/instrumental noise in the RV data, but further observations are required to check those possibilities.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Hierarchical Inference of the Lensing Convergence from Photometric Catalogs with Bayesian Graph Neural Networks

Abstract We present a Bayesian graph neural network (BGNN) that can estimate the weak lensing convergence ( κ ) from photometric measurements of galaxies along a given line of sight (LOS). The method is of particular interest in strong gravitational time-delay cosmography (TDC), where characterizing the “external convergence” ( κ ext ) from the lens environment and LOS is necessary for precise Hubble constant ( H 0 ) inference. Starting from a large-scale simulation with a κ resolution of ∼1′, we introduce fluctuations on galaxy–galaxy lensing scales of ∼1″ and extract random sight lines to train our BGNN. We then evaluate the model on test sets with varying degrees of overlap with the training distribution. For each test set of 1000 sight lines, the BGNN infers the individual κ posteriors, which we combine in a hierarchical Bayesian model to yield constraints on the hyperparameters governing the population. For a test field well sampled by the training set, the BGNN recovers the population mean of κ precisely and without bias (within the 2 σ credible interval), resulting in a contribution to the H 0 error budget well under 1%. In the tails of the training set with sparse samples, the BGNN, which can ingest all available information about each sight line, extracts a stronger κ signal compared to a simplified version of the traditional method based on matching galaxy number counts, which is limited by sample variance. Our hierarchical inference pipeline using BGNNs promises to improve the κ ext characterization for precision TDC. The code is available as a public Python package, Node to Joy ⏬ .

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

New Measurements of the Lyα Forest Continuum and Effective Optical Depth with LyCAN and DESI Y1 Data

Abstract We present the Ly α Continuum Analysis Network (LyCAN), a convolutional neural network that predicts the unabsorbed quasar continuum within the rest-frame wavelength range of 1040–1600 Å based on the red side of the Ly α emission line (1216–1600 Å). We developed synthetic spectra based on a Gaussian mixture model representation of nonnegative matrix factorization (NMF) coefficients. These coefficients were derived from high-resolution, low-redshift ( z < 0.2) Hubble Space Telescope/Cosmic Origins Spectrograph (COS) quasar spectra. We supplemented this COS-based synthetic sample with an equal number of DESI Year 5 mock spectra. LyCAN performs extremely well on testing sets, achieving a median error in the forest region of 1.5% on the DESI mock sample, 2.0% on the COS-based synthetic sample, and 4.1% on the original COS spectra. LyCAN outperforms principal component analysis (PCA) and NMF-based prediction methods using the same training set by 40% or more. We predict the intrinsic continua of 83,635 DESI Year 1 spectra in the redshift range of 2.1 ≤ z ≤ 4.2 and perform an absolute measurement of the evolution of the effective optical depth. This is the largest sample employed to measure the optical depth evolution to date. We fit a power law of the form τ ( z ) = τ 0 ( 1 + z ) γ to our measurements and find τ 0 = (2.46 ± 0.14) × 10 −3 and γ = 3.62 ± 0.04. Our results show particular agreement with high-resolution, ground-based observations around z = 2, indicating that LyCAN is able to predict the quasar continuum in the forest region with only spectral information outside the forest.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Design and Development of a High-Efficiency Single Cylinder Natural Gas-Fueled Jet Ignition Engine

The current energy climate has created a push toward reducing consumption of fossil fuels and lowering emissions output in power generation applications. Combined with the desire for a more distributed energy grid, there is currently a need for small displacement, high efficiency engines for use in stationary power generation. An enabling technology for achieving high efficiencies with spark ignited engines for such applications is the use of jet ignition which enables ultra-lean (λ > ~1.6) combustion via air dilution.This paper provides a comprehensive review of the development of a 390cc, high efficiency single cylinder natural gas-fueled jet ignition engine operating ultra-lean. The engine was developed as part of the Department of Energy’s Advanced Research Projects Agency–Energy (DOE ARPA-E) GENSETS program. Design choices for minimizing friction are highlighted as well as test results showing further friction reduction through downspeeding. Extensive hardware optimization of the combustion system has been performed and results are presented for air-flow path optimization and the jet igniter. The efficiency benefits related to enleanment and downspeeding are analyzed using an efficiency loss breakdown based on the First Law of Thermodynamics. Through optimization efforts a peak brake thermal efficiency in excess of 34% was achieved, representing an increase of greater than 20% over the current state-of-the-industry for comparably sized CNG engines.

Peters, Nathan↗

DOE OSTI2021

Multi-species collisions for delta-f gyrokinetic simulations: Implementation and verification with GENE

A multi-species linearized collision operator based on the model developed by Sugama et al. has been implemented in the nonlinear gyrokinetic code, GENE. Such a model conserves particles, momentum, and energy to machine precision, and is shown to have negative definite free energy dissipation characteristics, satisfying Boltzmann’s H-theorem, including for realistic mass ratio. Finite Larmor Radius (FLR) effects have also been implemented into the local version of the code. For the global version of the code, the collision operator has been developed to allow for block-structured velocity space grids, allowing for computationally tractable collisional global simulations. The validity of the collision operator has been demonstrated by relaxation and conservation tests, as well as appropriate benchmarks. The newly implemented operator shall be used in future simulations to study magnetically confined fusion plasma turbulence and transport in more extreme regions with higher collisionality.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

GOOML - Real World Applications of Machine Learning in Geothermal Operations

GOOML (Geothermal Operational Optimization with Machine Learning) is a machine-learning based framework that enables geothermal power plant operators to explore optimization opportunities for their assets in an efficient and robust digital environment. Backed by real-world data sources, thermodynamic constraints and steamfield intelligence, the GOOML environment provides new tools to explore how to best operate steamfields as well as test new scenarios and configurations prior to implementation in the field. To prove the effectiveness of GOOML, we have undertaken optimization experiments using reinforcement learning (RL) to generate operational suggestions using a balance of mass-take targets, sustainability considerations and net generation. Our experiments use the GOOML construct to explore different field parameters and perform multiple reinforcement learning experiments. Like a comprehensive laboratory workbench, we can change out components of a steamfield to perform testing under a variety of conditions (restrict mass, increase pressure, reroute steam, etc.). This flexibility allows us to explore conditions that would require significant infrastructure changes in a real-world setting at a fraction of the cost and time in a digital environment. The results highlight the benefits of using digital twins and advanced data analytics for the geothermal industry.

forecasting↗

DOE OSTI2020

Prediction for Pressure Differential Across HEPA Filter Media Based on Media Characteristics and Particle Size Distribution

A new method for predicting the pressure drop across High Efficiency Particulate Air (HEPA) filter media is proposed based upon mass deposited onto the filter and known physical characteristics of the filter media. Detailed are the methods used in conjunction with current filter loading models to predict the pressure drop, as well as tests conducted to validate the methods. The benefit of a prediction model for practical use lies in the manufacturing and service life of nuclear grade HEPA filters. HEPA filters for use in nuclear facilities have a prescribed expiration date and a maximum allowable operating pressure drop. Therefore, the ability to predict the pressure drop across a filter and relate it to an expected length of service time can enable a reduction in wasted filters. This will allow for more informed decisions to be made based upon the dictated life cycle of the filters. Also, understanding and predicting how the pressure drop of HEPA filter media behaves as a function of physical characteristics and loaded mass can assist in future design and manufacturing of filter media. Currently, most existing pressure drop models are either computationally based or analytical methods relying on data gathered during tests. Neither are practical for prediction; the computational methods are difficult to implement, and the current analytical methods are more useful as tools for analysis. The current analytical model developed by Bergman et al. is based upon the pressure drop from each media fiber and modeling the deposited particles as newly formed fibers. Using Bergman's model and the media properties, air properties, and known aerosol particle size distribution, a pressure drop curve as a function of loaded mass can be created. This curve implies initial loading in the depth of the filter media with a transition to pure surface loading on the filter face, and a sensitivity to an evolving particle size distribution as mass continues to load onto the filter. To implement the predictive model, knowledge of the mean filter fiber diameter and porosity of the filter media is required. Traditionally, the mean fiber diameter is calculated as an effective diameter from prior media testing, however, in this study a Scanning Electron Microscope (SEM) technique is used to acquire this variable. Validation of the predictive model is provided by flat sheet media tests under a controlled environment with a measured particle size distribution of the challenge aerosol and shows reasonable preliminary agreement.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗