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DOE OSTI2022

Kimberlina 1.2 CCUS Geophysical Models and Synthetic Data Sets

This synthetic multi-scale and multi-physics data set was produced in collaboration with teams at the Lawrence Berkeley National Laboratory, National Energy Technology Laboratory, Los Alamos National Laboratory, and Colorado School of Mines through the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative. Data are associated with the following publication: Alumbaugh, D., Gasperikova, E., Crandall, D., Commer, M., Feng, S., Harbert, W., Li, Y., Lin, Y., and Samarasinghe, S., “The Kimberlina Synthetic Geophysical Model and Data Set for CO2 Monitoring Investigations”, The Geoscience Data Journal, 2023, DOI: 10.1002/gdj3.191. The dataset uses the Kimberlina 1.2 CO2 reservoir flow model simulations based on a hypothetical CO2 storage site in California (Birkholzer et al., 2011; Wainwright et al., 2013). Geophysical properties models (P- and S-wave seismic velocities, saturated density, and electrical resistivity) were produced with an approach similar to that of Yang et al. (2019) and Gasperikova et al. (2022) for 100 Kimberlina 1.2 reservoir models. Links to individual resources are provided below: [CO2 Saturation Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-co2-saturation-models); Resistivity Models – [part 1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-1), [part 2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-2), and [part 3](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-resistivity-models-part-3); [Vp Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vp-velocity-models); [Vs Velocity Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-vs-velocity-models); [Density Models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-density-models). The 3D distributions of geophysical properties for the 33 time stamps of the SIM001 model were used to generate synthetic seismic, gravity, and electromagnetic (EM) responses for 33 times between zero and 200 years. Synthetic surface seismic data were generated using 2D and 3D finite-difference codes that simulate the acoustic wave equation (Moczo et al., 2007). 2D data were simulated for six point-pressure sources along a 2D line with 10 m receiver spacing and a time spacing of 0.0005 s. 3D simulations were completed for 25 surface pressure sources using a source separation of 1 km in both the x and y directions and a time spacing of 0.001 s. Links to individual resources are provided below: [2D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-velocity-models) and [2D surface seismic data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-2d-surface-seismic-data). [3D velocity models](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-velocity-models), and 3D seismic data [year0](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year0), [year1](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year1), [year2](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year2), [year5](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year5), [year10](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year10), [year15](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year15), [year20](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year20), [year25](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year25), [year30](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year30), [year35](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year35), [year40](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year40), [year45](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year45), [year49](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year49), [year50](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year50), [year51](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year51), [year52](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year52), [year55](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year55), [year60](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year60), [year65](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year65), [year70](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year70), [year75](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year75), [year80](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year80), [year85](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year85), [year90](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year90), [year95](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year95), [year100](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year100), [year110](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year110), [year120](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year120), [year130](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year130), [year140](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year140), [year150](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year150), [year175](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year175), [year200](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-seismic-data-year200). The Python scripts to read these models and data are provided [here](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-python-scripts). EM simulations used a borehole-to-surface survey configuration, with the source located near the reservoir level and receivers on the surface using the code developed by Commer and Newman (2008). Pseudo-2D data for the source at [2500 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz2500m) and [3025 m](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-pseudo-2d-csem-data-tz3025m), used a 2D inline receiver configuration to simulate a response over 3D resistivity models. The [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-3d-csem-data) contain electric fields generated by borehole sources at monitoring well locations and measured over a surface receiver grid. Vector gravity data, both on the surface and in boreholes, were simulated using a modeling code developed by Rim and Li (2015). The simulation scenarios were parallel to those used for the EM: [pseudo-2D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were calculated along the same lines and within the same boreholes, and [3D data](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-gravity-data) were simulated over 3D models on the surface and in three monitoring wells. A series of [synthetic well logs](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-well-logs) of CO2 saturation, acoustic velocity, density, and induction resistivity in the injection well and three monitoring wells are also provided at 0, 1, 2, 5, 10, 15, and 20 years after the initiation of injection. These were constructed by combining the low-frequency trend of the geophysical models with the high-frequency variations of actual well logs collected in the Kimberlina 1 well that was drilled at the proposed site. Measurements of permeability and pore connectivity were made on cores of Vedder Sandstone, which forms the primary reservoir unit: [CT micro scans](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-ct-micro-scans-of-vedder-formation) and [Industrial CT Images](https://edx.netl.doe.gov/dataset/kimberlina-1-2-ccus-geophysical-models-and-synthetic-data-sets-industrial-ct-images-vedder-formation). These measurements provide the range of scales in the otherwise synthetic data set to be as close to a real-world situation as possible. References: Birkholzer, J.T., Zhou, Q., Cortis, A. and Finsterle, S., 2011. A sensitivity study on regional pressure buildup from large-scale CO2 storage projects. Energy Procedia, 4, 4371-4378. Commer, M., and Newman, G.A., 2008. New advances in three-dimensional controlled-source electromagnetic inversion, Geophysical Journal International, 172, 513-535. Gasperikova, E., Appriou, D., Bonneville, A., Feng, Z., Huang, L., Gao, K., Yang, X., Daley, T., 2022, Sensitivity of geophysical techniques for monitoring secondary CO2 storage plumes, Int. J. Greenh. Gas Control, Volume 114, 103585, ISSN 1750-5836, https://doi.org/10.1016/j.ijggc.2022.103585. Moczo, P., J.O. Robertsson and L. Eisner, 2007, The finite-difference time-domain method for modeling of seismic wave propagation: Advances in geophysics, 48, 421-516. Rim, H., and Y. Li, 2015, Advantages of borehole vector gravity in density imaging, Geophysics, 80, G1-G13. Wainwright, H. M.; Finsterle, S.; Zhou, Q.; Birkholzer, J. T., 2013. Modeling the Performance of Large-Scale CO2 Storage Systems: A Comparison of Different Sensitivity Analysis Methods. International Journal of Greenhouse Gas Control, 17, 189205. https://doi.org/10.1016/j.ijggc.2013.05.007, DOI: 10.18141/1603331. Yang, X., Buscheck, T.A., Mansoor, K., Wang, Z., Gao, K., Huang, L., Appriou, D., and Carroll, S.A., 2019. Assessment of geophysical monitoring methods for detection of brine and CO2 leakage in drinking water aquifers, International Journal of Greenhouse Gas Control, 90, 102803, https://doi.org/10.1016/j.ijggc.2019.102803.

CCUS↗
DOE OSTI2013

X-ray Diffraction and Neutron Scattering Analysis of Natural and Synthetic Spider Silk Fibers

Spider silks have the potential to provide new bio-inspired materials for numerous applications in bioenergetics and products ranging from protective clothing to artificial ligaments and tendons. A number of spider silk genes have been cloned and sequenced by the Lewis laboratory revealing the basis for understanding the key elements of spider silk proteins with respect to their materials performance. In particular, specific amino acid motifs have been identified which have been conserved for over 125 million years in all spiders that use their silk to physically trap prey. The key element in taking the next step toward generating bio-based materials from spider silks will be to move from the current descriptive data to predictive knowledge. Current efforts are focused on mimicking spider silk through synthetic proteins. In developing synthetic silk fibers, we first need to understand the complete secondary and tertiary structure of natural silk so that we can compare synthetic constructs to the natural material. Being able to compare the structure on a single fiber level is critical to the future of molecular directed mimic development because we can vary mechanical properties by different spinning methods. The new generation of synchrotron x-ray diffraction and neutron beamlines will allow, for the first time, determination of the molecular structure of silk fibers and synthetic mimics. We propose an exciting new collaborative research team working jointly between Argonne National Laboratory, Arizona State U. and the University of Wyoming to address the ?characterization of synthetic and natural spider silk fibers using x-ray and neutron diffraction.? Thus these new methodologies will provide understanding of current fibers and determine changes needed to produce fibers with specific properties. The following specific aims are proposed: ? Synthesize spider silk fibers with molecular structures mimicking that of natural silks. Test the mechanic properties of these materials and compare them to natural silk fibers. ? Develop x-ray and neutron diffraction techniques to better determine the structure in amorphous and semicrystalline biopolymers, such as spider silk fibers. ? Combine mechanical testing and structural x-ray and neutron diffraction data to develop a molecular understanding of the structure-function relationship in spider silk materials. ? Elucidate the role water plays in spider silk fiber formation and structure. Emphasis will be placed on combined neutron and NMR studies. ? Use solid-state Nuclear Magnetic Resonance (NMR) to characterize synthetic and natural spider silk materials that show potential as a biomimetic material or bio-inspired polymer architecture. ? Develop EPSCoR student and postdoctoral training and exposure to national laboratory facilities. ? Further develop scientific outreach and chemical education programs and research.

36 MATERIALS SCIENCE↗
DOE OSTI2014

CRADA Final Report For CRADA NO. CR-12-006 [Operation and Testing of an SO 2 -depolarized Electrolyzer (SDE) for the Purpose of Hydrogen and Sulfuric Acid Production]

Over the past several years, Savannah River National Laboratory (SRNL) has led a team of collaborators under the Department of Energy’s (DOE) nuclear hydrogen production program to develop the Hybrid Sulfur (HyS) Process. HyS is a 2-step water-splitting process consisting of high temperature decomposition of sulfuric acid to generate SO 2 , followed by the electrolysis of aqueous SO 2 to generate hydrogen and sulfuric acid. The latter is fed back into the high temperature reactor. SRNL designed and built an SO 2 -depolarized electrolyzer (SDE) and a test facility. Over 40 SDE’s were tested using different catalysts, membranes and other components. SRNL demonstrated that an SDE could be operated continuously for approximately 200 hours under certain conditions without buildup of sulfur at the SDE’s cathode, thus solving a key technical problem with SDE technology. Air Products and Chemicals, Inc. (APCI) is a major supplier of hydrogen production systems, and they have proprietary technology that could benefit from the SDE developed by SRNS, or some improved version thereof. However, to demonstrate that SRNL’s SDE is a truly viable approach to the electrolyzer design, continuous operation for far greater periods of time than 200 hours must be demonstrated, and the electrolyzer must be scaled up to greater hydrogen production capacities. SRNL and Air Products entered into a Cooperative Research and Development Agreement with the objective of demonstrating the effectiveness of the SDE for hydrogen and sulfuric acid production and to demonstrate long-term continuous operation so as to dramatically increase the confidence in the SDE design for commercial operation. SRNL prepared a detailed technical report documenting previous SDE development, including the current SDE design and operating conditions that led to the 200-hour sulfurfree testing. SRNL refurbished its single cell SDE test facility and qualified the equipment for continuous operation. A new membrane electrode assembly (MEA) was fabricated and installed in the single cell electrolyzer (60 cm 2 active cell area). Shakedown testing was conducted, and several modifications were made to the test facility equipment. Seven different MEAs were used during testing. Beginning on May 20, 2013, SRNL was able to test the SDE continuously for 1200 hours, including 1000 hours under power to generate hydrogen at an average rate of 10.8 liters per hour. The SDE was not removed or repaired during the 50-day test and was successfully restarted after each shutdown. The test was intentionally stopped after 1200 hours (1000 hours of hydrogen production) due to funding constraints. Post-test examination of the MEA using Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Microanalysis (EDAX) showed no elemental sulfur deposits or sulfur layer inside the cell, thus successfully achieving the test goals. The results demonstrated that the SDE could be operated for extended periods without major performance degradation or the buildup of sulfur inside the MEA. Air Products conducted an assessment of the economic viability of the SDE based on the “as tested” design. The results indicated that the SDE faces significant economic obstacles in its current state. Further development and scale-up are necessary before the SDE is ready for commercialization.

08 HYDROGEN↗
DOE OSTI2014

Impact of a Vertically Polarized Undulator on LCLS Hard X-ray Experiments

The LCLS-II project will install two variable gap, horizontally polarized undulators into the LCLS undulator hall. One undulator is designed to produce soft x-rays spanning an energy range of 200-1250 eV (SXU) while the other is designed for the hard spectral range of 1-25 keV (HXU). The hard x-ray LCLS instruments (X-ray Pump- Probe [XPP], X-ray correlation Spectroscopy [XCS], Coherent X-ray Imaging [CXI], Matter in Extreme Conditions [MEC]) will be repurposed to operate on the HXU line while two new soft x-ray beamlines will be created for the SXU line. An alternate HXU undulator design is being considered that could provide advantages over the present design choice. In particular, the project team is collaborating with Argonne National Laboratory to develop a vertically polarized undulator (VPU). A 1-m prototype VPU device was successfully constructed this year and a full size prototype is in process. A decision to alter the project baseline, which is the construction of a horizontally polarized device, must be made in the coming weeks to not impact the present project schedule. Please note that a change to the soft x-ray undulator is not under discussion at the moment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2013

Strategy Guideline: Partnering for High Performance Homes

High performance houses require a high degree of coordination and have significant interdependencies between various systems in order to perform properly, meet customer expectations, and minimize risks for the builder. Responsibility for the key performance attributes is shared across the project team and can be well coordinated through advanced partnering strategies. For high performance homes, traditional partnerships need to be matured to the next level and be expanded to all members of the project team including trades, suppliers, manufacturers, HERS raters, designers, architects, and building officials as appropriate. This guide is intended for use by all parties associated in the design and construction of high performance homes. It serves as a starting point and features initial tools and resources for teams to collaborate to continually improve the energy efficiency and durability of new houses.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

American Fuel Cell Bus Project Evaluation. Second Report

This report presents results of the American Fuel Cell Bus (AFCB) Project, a demonstration of fuel cell electric buses operating in the Coachella Valley area of California. The prototype AFCB was developed as part of the Federal Transit Administration's (FTA's) National Fuel Cell Bus Program. Through the non-profit consortia CALSTART, a team led by SunLine Transit Agency and BAE Systems developed a new fuel cell electric bus for demonstration. SunLine added two more AFCBs to its fleet in 2014 and another in 2015. FTA and the AFCB project team are collaborating with the U.S. Department of Energy (DOE) and DOE's National Renewable Energy Laboratory to evaluate the buses in revenue service. This report summarizes the performance results for the buses through June 2015.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2016

Computational time-resolved and resonant x-ray scattering of strongly correlated materials

Basic-Energy Sciences of the Department of Energy (BES/DOE) has made large investments in x-ray sources in the U.S. (NSLS-II, LCLS, NGLS, ALS, APS) as powerful enabling tools for opening up unprecedented new opportunities for exploring properties of matter at various length and time scales. The coming online of the pulsed photon source, literally allows us to see and follow the dynamics of processes in materials at their natural timescales. There is an urgent need therefore to develop theoretical methodologies and computational models for understanding how x-rays interact with matter and the related spectroscopies of materials. The present project addressed aspects of this grand challenge of x-ray science. In particular, our Collaborative Research Team (CRT) focused on developing viable computational schemes for modeling x-ray scattering and photoemission spectra of strongly correlated materials in the time-domain. The vast arsenal of formal/numerical techniques and approaches encompassed by the members of our CRT were brought to bear through appropriate generalizations and extensions to model the pumped state and the dynamics of this non-equilibrium state, and how it can be probed via x-ray absorption (XAS), emission (XES), resonant and non-resonant x-ray scattering, and photoemission processes. We explored the conceptual connections between the time-domain problems and other second-order spectroscopies, such as resonant inelastic x-ray scattering (RIXS) because RIXS may be effectively thought of as a pump-probe experiment in which the incoming photon acts as the pump, and the fluorescent decay is the probe. Alternatively, when the core-valence interactions are strong, one can view K-edge RIXS for example, as the dynamic response of the material to the transient presence of a strong core-hole potential. Unlike an actual pump-probe experiment, here there is no mechanism for adjusting the time-delay between the pump and the probe. However, the core hole predominantly decays via Auger processes, thereby providing an internal time-scale, which limits intermediate-state processes to timescales of a few femtoseconds. Accordingly, a number of activities directed at modeling K-, L- and M-edge RIXS in correlated materials were also pursused by our CRT. Our research effort supported by this CMCSN grant substantially advanced the understanding of x-ray scattering processes in the time-domain as well as in the more conventional scattering channels, including time-resolved photoemission, and how such processes can be modeled realistically in complex correlated materials more generally. The modeling of relaxation processes involved in time-domain spectroscopies is important also for understanding photoinduced effects such as energy conversion in photosynthesis and solar cell applications, and thus impacts the basic science for energy needs.

36 MATERIALS SCIENCE↗
DOE OSTI2017

American Fuel Cell Bus Project Evaluation: Third Report

This report presents results of the American Fuel Cell Bus (AFCB) Project, a demonstration of fuel cell electric buses operating in the Coachella Valley area of California. The prototype AFCB, which was developed as part of the Federal Transit Administration's (FTA) National Fuel Cell Bus Program, was delivered to SunLine in November 2011 and was put in revenue service in mid-December 2011. Two new AFCBs with an upgraded design were delivered in June/July of 2014 and a third new AFCB was delivered in February 2015. FTA and the AFCB project team are collaborating with the U.S. Department of Energy (DOE) and DOE's National Renewable Energy Laboratory to evaluate the buses in revenue service. This report covers the performance of the AFCBs from July 2015 through December 2016.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

SunLine Transit Agency American Fuel Cell Bus Progress Report (Jan 2017-Jul 2019)

This report presents results of the American Fuel Cell Bus (AFCB) project, a deployment of fuel cell electric buses (FCEBs) operating in the Coachella Valley area of California. The prototype AFCB, which was developed as part of the Federal Transit Administration’s National Fuel Cell Bus Program, was put in revenue service in mid-December 2011. This report is focused on the upgraded design buses, which include two FCEBs delivered in June/July of 2014, one delivered in February 2015, and five delivered in 2018. The project team is collaborating with the U.S. Department of Energy (DOE) and DOE’s National Renewable Energy Laboratory to evaluate the buses in revenue service. This final report on the AFCBs updates the data through July 2019.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Orange County Transportation Authority Fuel Cell Electric Bus Progress Report (Feb-Jul 2020) [Slides]

This report presents early results from a deployment of fuel cell electric buses (FCEBs) operated by Orange County Transportation Authority (OCTA) in Southern California. The ten FCEBs, produced by New Flyer, feature an electric drive propulsion system powered by a Ballard fuel cell system. The project team is collaborating with the U.S. Department of Energy (DOE) and DOE's National Renewable Energy Laboratory (NREL) to evaluate the buses in revenue service. The goal of this evaluation is to compare the FCEB performance to that of conventional technology and to track progress over time toward meeting the technical targets set by DOE and the Department of Transportation (DOT). The FCEBs were delivered beginning in late-2019, and were placed in service on February 9, 2020. The data period covers February 2020 through July 2020. NREL collects data on ten 2016 model year compressed natural gas (CNG) buses as a baseline comparison at OCTA.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

SunLine Transit Agency Fuel Cell Electric Bus Progress Report (Data Period Focus Jan-Jun 2020) [Slides]

This report presents early results from a deployment of fuel cell electric buses (FCEBs) operated by SunLine Transit Agency in the Coachella Valley area of California. The five FCEBs, produced by New Flyer, feature an electric drive propulsion system powered by a Ballard fuel cell system. The project team is collaborating with the U.S. Department of Energy (DOE) and DOE's National Renewable Energy Laboratory (NREL) to evaluate the buses in revenue service. The goal of this evaluation is to compare the FCEB performance to that of conventional technology and to track progress over time toward meeting the technical targets set by DOE and the Department of Transportation (DOT). The FCEBs were delivered beginning in mid-2019. The data period covers January 2020 through July 2020. NREL collects data on five 2019 model year compressed natural gas (CNG) buses as a baseline comparison at SunLine. These new CNG buses were phased into service beginning in April 2020.

25 ENERGY STORAGE↗
DOE OSTI2022

Orange County Transportation Authority Fuel Cell Electric Bus Progress Report - Data Period Focus: Feb. 2020 through Jul. 2021 [Slides]

This report presents early results from a deployment of fuel cell electric buses (FCEBs) operated by Orange County Transportation Authority (OCTA) in Southern California. The ten FCEBs, produced by New Flyer, feature an electric drive propulsion system powered by a Ballard fuel cell system. The project team is collaborating with the U.S. Department of Energy (DOE) and DOE's National Renewable Energy Laboratory (NREL) to evaluate the buses in revenue service. The goal of this evaluation is to compare the FCEB performance to that of conventional technology and to track progress over time toward meeting the technical targets set by DOE and the Department of Transportation (DOT). The FCEBs were delivered beginning in late-2019, and were placed in service on February 9, 2020. The data period covers February 2020 through July 2021. NREL collects data on ten 2016 model year compressed natural gas (CNG) buses as a baseline comparison at OCTA.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

SunLine Transit Agency Fuel Cell Electric Bus Progress Report - Data Period Focus: Jan. 2020 through Dec. 2021 [Slides]

This report presents early results from a deployment of fuel cell electric buses (FCEBs) operated by SunLine Transit Agency in the Coachella Valley area of California. The five FCEBs, produced by New Flyer, feature an electric drive propulsion system powered by a Ballard fuel cell system. The project team is collaborating with the U.S. Department of Energy (DOE) and DOE's National Renewable Energy Laboratory (NREL) to evaluate the buses in revenue service. The goal of this evaluation is to compare the FCEB performance to that of conventional technology and to track progress over time toward meeting the technical targets set by DOE and the Department of Transportation (DOT). The FCEBs were delivered beginning in mid-2019. The data period covers January 2020 through December 2021. NREL collects data on five 2019 model year compressed natural gas (CNG) buses as a baseline comparison at SunLine. These new CNG buses were phased into service beginning in April 2020.

08 HYDROGEN↗
DOE OSTI2021

AC Transit Fuel Cell Electric Bus Progress Report (Data Period Focus: Jan. 2020 through Dec. 2020) [Slides]

This report presents early results from a deployment of fuel cell electric buses (FCEBs) operated by Alameda Contra-Costa Transit (AC Transit) in the east bay area of California. The ten FCEBs, produced by New Flyer, feature an electric drive propulsion system powered by a Ballard fuel cell system. The project team is collaborating with the U.S. Department of Energy (DOE) and DOE's National Renewable Energy Laboratory (NREL) to evaluate the buses in revenue service. The goal of this evaluation is to compare the FCEB performance to that of conventional technology and to track progress over time toward meeting the technical targets set by DOE and the Department of Transportation (DOT). The FCEBs were delivered beginning in late-2019. The data period covers January 2020 through July 2020. NREL collects data on two different baseline bus fleets for comparison: five 2017 model year diesel buses and five 2016 model year diesel hybrid buses.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

MITR & NBSR DDE Irradiations in BR2 – Fluence in LEU Cladding and Structural Materials

The BR2 nuclear reactor is a material testing reactor (MTR) located in Mol, Belgium, and operated by the Belgian Nuclear Research Centre (SCK CEN) since 1963. The reactor is highly versatile as the number and location of fuel elements and control rods can change significantly from cycle to cycle to accommodate different needs. Argonne National Laboratory (ANL or Argonne) Reactor Conversion (RC) team has collaborated with SCK CEN for over a decade on the conversion of domestic and international research reactors from highly enriched uranium (HEU, ≥20 wt.% of 235 U) to low enriched uranium (LEU, <20 wt.% of 235 U) fuel. The U.S. High-Performance Research Reactor (USHPRR) project within the M3 Reactor Conversion Program aims at converting five U.S. high performance research reactors (MITR, MURR, NBSR, HFIR, and ATR) and one critical facility (ATR-C) to LEU fuel. These USHPRRs still use and regularly refuel with HEU fuel. Each facility has a unique reactor design, operating conditions, and fuel element design to accomplish its mission. The goal of the USHPRR project is to convert the USHPRRs and the critical facility to LEU fuel while maintaining experimental performance and ensuring safe facility operation. The current technical report focuses on two reactors requiring very high-density LEU fuel: the Massachusetts Institute of Technology Reactor (MITR) and the National Bureau of Standards Reactor (NBSR). To support the conversion of these reactors, so-called design demonstration elements (DDE) are planned to be irradiated in the BR2 reactor under conditions similar to the targeted reactors and using a prototypic geometry. In support of this experiment, SCK CEN studied and modeled the DDE irradiations using MCNP6.2 to investigate the feasibility of irradiating the MITR DDE and NBSR DDE in BR2. Argonne reviewed and confirmed the conclusions of this study. Structural analysis is another step toward converting USHPRR to LEU fuel. The objective of the current report is to provide information useful to the structural analysis of the NBSR & MITR DDEs to support its irradiation in BR2. Specifically, the goal is to provide the fast neutron (E>0.1MeV) fluence in the cladding of the fuel plates in BR2 for the whole period of irradiation (8 cycles for MITR DDE and 10 cycles for NBSR DDE). Additionally, fast neutron fluences in the side plates and in the NBSR DDE’s outside plates were calculated and reported. Neutronic calculations were performed using MCNP6.2 on the RTRHPC cluster.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Strengthening Connections Between Research and Deployment [Slides]

This slide deck provides a high-level review of Clean Cities, Clean Energy to Communities, and Technologists in Communities and the ways these DOE-funded efforts work to translate research into deployment opportunities across the United States through community engagement, industry partnerships, and collaborative project teams.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Report on the HP-CAT Workshop-2023 held at the Advanced Photon Source

The conceptual framework and the founding partner and institutional agreements for the High Pressure Collaborative Access Team (HP-CAT) were established in late 1990’s. In the following years, core infrastructure of HP-CAT was built at sector 16 of the Advanced Photon Source (APS) and the first x-ray light was delivered on July 19, 2002 at 7:00pm – followed by an official commemoration ceremony on July 26, 2002.

36 MATERIALS SCIENCE↗
DOE OSTI2025

2024 Stor4Build Annual Meeting: Exploring Challenges and Opportunities in Thermal Energy Storage for Buildings

In late August 2024, Stor4Build brought nearly 80 stakeholders from the thermal energy storage industry to Oak Ridge National Laboratory (ORNL), including researchers, startups, electric utilities, nonprofits, implementers, state energy efficiency offices, and original equipment manufacturers. During the two-day Stor4Build Annual Meeting, participants engaged in vital discussions about the current challenges and opportunities for scaling thermal energy storage solutions in buildings. The event featured panel discussions led by leading technology experts and industry practitioners, as well as updates on Stor4Build–funded projects from national laboratories, highlighting advancements in the thermal energy storage field crucial to achieving the consortium’s mission.

25 ENERGY STORAGE↗