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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Energy Clusters Offshore: A Technology Feasibility Review

Globally, governments, companies, and other organizations have committed to achieving net-zero emissions targets in the coming decades. To achieve decarbonization at the scale and pace required to meet these targets, future energy systems will need renewable energy to serve 100% of the existing direct electricity demand, support additional electrification, and decarbonize the wider economy. An energy cluster offshore (ECO) is a concept that seeks to meet this challenge by integrating and optimizing large-scale renewable electricity generation, storage, and fuel production technologies and pairing them with other complementary uses, such as carbon capture or water desalination. This research project explores the techno-economic feasibility of ECO concepts by taking a holistic view of complex, multidisciplinary hybrid plant designs while considering different configurations and objectives. We will outline the most promising technology combinations and configurations, their functional requirements, and opportunities for optimization.

14 SOLAR ENERGY↗
DOE OSTI2025

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗
DOE OSTI2022

Negative hydrogen ion sources for particle accelerators: Sustainability issues and recent improvements in long-term operations

High brightness, negative hydrogen ion sources are used extensively in scientific facilities operating worldwide. Negative hydrogen beams have become the preferred means of filling circular accelerators and storage rings as well as enabling efficient extraction from cyclotrons. Several well-known facilities now have considerable experience with operating a variety of sources such as RF-, filament-, magnetron- and Penning-type H- ion sources. These facilities include the US Spallation Neutron Source (SNS), Japan Proton Accelerator Research Complex (J-PARC), Rutherford Appleton Laboratory (RAL-ISIS), Los Alamos Neutron Science Center (LANSCE), Fermi National Accelerator Laboratory (FNAL), Brookhaven National Laboratory (BNL), numerous installations of D-Pace (licenced by TRIUMF) ion sources used mainly on cyclotrons and, most recently, the CERN-LINAC-1 injector. This report first summarizes the current performance of these ion sources in routine, daily operations with attention toward source service-periods and availability metrics. Sustainability issues encountered at each facility are also reported and categorized to identify areas of common concern and key issues. Recent ion source improvements to address these issues are also discussed as well as plans for meeting future facility upgrade requirements.

Welton, Robert F.↗
DOE OSTI2021

2D-to-3D image translation of complex nanoporous volumes using generative networks

Image-based characterization offers a powerful approach to studying geological porous media at the nanoscale and images are critical to understanding reactive transport mechanisms in reservoirs relevant to energy and sustainability technologies such as carbon sequestration, subsurface hydrogen storage, and natural gas recovery. Nanoimaging presents a trade off, however, between higher-contrast sample-destructive and lower-contrast sample-preserving imaging modalities. Furthermore, high-contrast imaging modalities often acquire only 2D images, while 3D volumes are needed to characterize fully a source rock sample. In this work, we present deep learning image translation models to predict high-contrast focused ion beam-scanning electron microscopy (FIB-SEM) image volumes from transmission X-ray microscopy (TXM) images when only 2D paired training data is available. We introduce a regularization method for improving 3D volume generation from 2D-to-2D deep learning image models and apply this approach to translate 3D TXM volumes to FIB-SEM fidelity. We then segment a predicted FIB-SEM volume into a flow simulation domain and calculate the sample apparent permeability using a lattice Boltzmann method (LBM) technique. Results show that our image translation approach produces simulation domains suitable for flow visualization and allows for accurate characterization of petrophysical properties from non-destructive imaging data.

58 GEOSCIENCES↗
DOE OSTI2021

Low Carbon Technology Strategies: Secondary School

This document includes steps that building owners and operators can implement to achieve smart, healthy, and low-carbon secondary schools within their existing building portfolios. Secondary schools often include complex heating and cooling systems or packaged rooftop units and can include specialty equipment for gymnasiums, pools, and buses.

analytics↗
DOE OSTI2022

Battery Energy Storage Scenario Analyses Using the Lithium-Ion Battery Resource Assessment (LIBRA) Model

Meeting aggressive carbon emission goals will entail widespread deployment of renewable sources of electricity. Because these sources are variable, there is a need to develop scalable energy storage technologies. The U.S. Department of Energy is supporting efforts to increase U.S. manufacturing and recycling capabilities for LIBs and to decrease costs of stationary storage batteries. Many factors influence the domestic manufacturing and cost of stationary storage batteries, including availability of critical raw materials (lithium, cobalt, and nickel), competition from various demand sectors (consumer electronics, vehicles, and battery energy storage), resource recovery (recycling), government policies, and learning in the industry, among other factors. Understanding how these factors interact and identifying synergies and bottlenecks is important for developing effective strategies for the LIB stationary energy storage system. We developed the Lithium-Ion Battery Resource Analysis (LIBRA) model as a tool to help stakeholders better understand the following types of questions: What are the roles of R&D, industrial learning, and scaling of demand in lowering the cost of battery energy storage system production? How do the intersections between the EV and stationary storage sectors affect the battery supply chain? For various stationary storage and EV penetration scenarios, what volumes of critical materials might be required and what role can resource recovery play? What does expected demand for both EVs and stationary storage portend for mineral resources and overall mineral scarcity? The LIBRA model is developed using a System dynamics (SD) modeling approach to represent interactions across the segments of the battery materials supply chain. System dynamics models can capture the complex interactions and feedback between the various system components that influence supply and demand. The LIBRA model is comprised of several interacting modules that represent specific portions of the LIB supply chain. The model tracks the buildout of the domestic LIB industry over time (2020 - 2050) and in the context of competing demands for raw materials, recycling, and markets for LIBs. The LIBRA model represents major systemic feedback loops and delays across the supply chain. This report provides a complete documentation for the LIBRA model, including model assumptions, data, scenario analysis results, and sensitivity analysis of the model's input space.

25 ENERGY STORAGE↗
DOE OSTI2021

Numerical and experimental evaluation of mechanical performance of the multifunctional energy storage composites

This work presents numerical simulation methods to model the mechanical behavior of the multifunctional energy storage composites (MESCs), which consist of a stack of multiple thin battery layers reinforced with through-the-hole polymer rivets and embedded inside carbon fiber composite laminates. MESC has been demonstrated through earlier experiments on its exceptional behavior as a structural element as well as a battery. However, the inherent complex infrastructure of the MESC design has created significant challenges in simulation and modeling. A novel homogenization technique was adopted to characterize the multi-layer properties of battery material using physics-based constitutive equations combined with nonlinear deformation theories to handle the interface between the battery layers. Second, mechanical damage and failure modes among battery materials, polymer reinforcements, and carbon fiber-polymer interfaces were characterized through appropriate models and experiments. The model of MESCs has been implemented in a commercial finite element code in ABAQUS. A comparison of structural response and failure modes from numerical simulations and experimental tests are presented. The results of the study showed that the predictions of elastic and damage responses of MESCs at various loading conditions agreed well with the experimental data. © 2021

Materials Science↗
DOE OSTI2023

A Task Based Approach for Co-Scheduling Ensemble Workloads on Heterogeneous Nodes

Scientific workflows consist of multiple, connected applications, with data and results flowing from one to another in a pipeline. Traditionally, such workflows are executed in sequential order, storing intermediate data in storage disks. Co-scheduling application workflows concurrently on the same compute nodes would greatly reduce the cost of moving data to/from storage and allow real-time analysis of intermediate results. Nevertheless, most parallel programming runtimes do not allow seamless integration of various applications in a scientific workflow, in part due to the complexity of managing data and resources. The situation is even more complicated for heterogeneous systems. In this work we extend the Minos Computing Library (MCL) runtime to accelerate pipe-lined and parallel workloads where multiple applications are running in the same system. MCL’s asynchronous task library and runtime dynamically manages resources to allow co-scheduling of multiple processes sharing heterogeneous resources. In addition, we design a custom ex- tension of the Open Compute Language (OpenCL) to enable multiple processes to share device memory. We enable MCL to coordinate these shared buffers to allow for easy, fast data sharing between applications. Using malleable micro-benchmarks and two application workflows that combine scientific simulation and AI-based analysis, we show that our method outperforms traditional approaches.

Index Terms—Parallel systems, Scheduling and Task ↗
DOE OSTI2024

Online MCMC Thinning with Kernelized Stein Discrepancy

A fundamental challenge in Bayesian inference is efficient representation of a target distribution. Many nonparametric approaches do so by sampling a large number of points using variants of Markov chain Monte Carlo (MCMC). Here, we propose an MCMC variant that retains only those posterior samples which exceed a kernelized Stein discrepancy (KSD) threshold, which we call KSD thinning. We establish the convergence and complexity trade-offs for several settings of KSD thinning as a function of the KSD threshold parameter, sample size, and other problem parameters. We provide experimental comparisons against other online nonparametric Bayesian methods that generate low-complexity posterior representations. We observe superior consistency/complexity trade-offs across a range of settings including MCMC sampling on two Bayesian inference problems from the biological sciences, and 10 × inference speedup and storage reduction for Bayesian neural networks with no loss of accuracy and no increase in training time. Our code is available at https://github.com/colehawkins/KSD-Thinning.

Bayesian inference↗
DOE OSTI2025

Adsorptive Capture of Iodide by Metal-Organic Framework from Off-Gas Condensate Simulate

Millions of gallons of liquid nuclear wastes generated due to nuclear weapon development during the Cold War are in tank storage at several Department of Energy (DOE) sites across the country. DOE is responsible for disposal of the tank nuclear waste and clean-up of the contaminated sites. These efforts are complex and challenging technically and are costly financially, with the predicted overall cost reaching $377 billion over the next few decades [1]. The current practice of nuclear waste treatment and tank closure is to separate high-level waste (HLW) and low-level waste (LLW) [2]. The HLW is then vitrified into a borosilicate-based glass waste form [3], while the LLW is immobilized into cementitious grout or vitrified into glass [4]. However, these treatment processes have met unsolved technical problems

Jiang, Junhua [Savannah River National Laboratory ↗
DOE OSTI2023

2023 FORCE Development Status Update

Technical and economic analysis of integrated energy systems (IES) using software models is a complex process requiring multiple commodity market decision analysis, optimal control, process modeling, and stochastic analysis. Many assumptions used in traditional energy analysis tools do not hold in future energy markets with significant storage and variable renewable energy sources (VRE), let alone with multiple commodity markets. Capturing these intricate elements for accurate techno-economic analysis of IES led to the development of the Framework for Optimization of ResourCes and Economics (FORCE) tool suite under the U.S. Department of Energy’s Integrated Energy Systems crosscutting technology program. With the aim of a full framework release in 2025, many improvements to the FORCE tool suite were developed in fiscal year 2023 (FY23). These improvements broadly fit into three focuses for development of FORCE: capability, accessibility, and reliability. Capability refers to the ability of FORCE to accurately model the technical and economic viability of various IES. Accessibility refers to ease-of-use for new and existing IES analysts to efficiently set up, analyze, and produce results using FORCE. Reliability refers to the consistency of the software, allowing consistency to analysis regardless of erstwhile changes to the software. In addition to many smaller changes, there are three major capability improvements in FORCE in FY23. In summary, FORCE developments in FY23 have moved us close to all the capability requirements for FORCE 1.0 to be delivered in FY25. Inclusion of Bayesian optimization, resilience metrics, and levelized cost analysis expand the capability, accessibility, and reliability of FORCE.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Savings in Action: Lessons from Observed and Modeled Residential Solar Plus Storage Systems

The electric grid is rapidly evolving as small-scale, demand-side resources play increasingly important roles in grid operations and decarbonization. Maximizing the potential of demand-side resources involves incentivizing electricity customers to use those resources in ways that benefit the broader electrical grid. These incentives depend largely on the electricity cost savings that customers can realize from demand-side resource adoption. Determining these potential cost savings is a complex task. Cost savings depend on numerous factors, including the characteristics of different technologies, the algorithms that control these devices, system performance, customer behavior, electricity rate structures, and climatic factors. Another challenge is that estimated cost savings are frequently based on modeled rather than observed system performance, particularly in the academic literature. In this study, we begin to fill the gap in empirical research of demand-side resources using data from a new construction residential community equipped with rooftop solar and storage (S+S) in Arizona. We use these data to analyze the factors that determine customer electricity cost savings and emissions impacts of S+S in the real world. We then compare these data to modeled system performance to understand how models deviate from real-world outcomes. Based on these findings, we explore ways to improve such models and, conversely, use modeled results to suggest improvements to actual S+S deployment. The results of these analyses can be summarized in four key findings: 1) rate structures play a central role in the grid and customer value of demand-side resources; 2) certain customers can benefit more from demand-side resource adoption than others; 3) modeled battery dispatch and sizing reveals opportunities for additional cost savings; and 4) optimal dispatches can reduce grid emissions while maximizing bill savings.

14 SOLAR ENERGY↗
DOE OSTI2023

Stacked Greenfield and Brownfield ROZ Fairways in the Illinois Basin Geo-Laboratory: Co-Optimization of EOR and Associated CO 2 Storage

Residual oil zones (ROZs) are economically viable targets for carbon dioxide enhanced oil recovery (CO 2 -EOR); thick, carbonate ROZs in the San Andres Formation in the Wasson Field of the Permian Basin are an example. Incremental oil produced from CO 2 -EOR can be carbon negative via associated storage of injected CO 2 . Given the regional extent of ROZ fairways and generally higher net utilization of CO 2 (compared to conventional CO 2 -EOR), ROZs provide the opportunity for significant carbon neutral to carbon negative oil production with associated CO 2 storage, and therefore should be a priority target for exploration. However, ROZs have not been widely recognized or identified due to poor or no conventional oil production. Hence, in places like the Illinois Basin (ILB), exploratory analyses are required to recognize the existence of an ROZ. As part of this study, four formations were selected for detailed regional characterization and analysis: Carper Sandstone (part of the Borden Siltstone), Tar Springs Sandstone, Cypress Sandstone, and Middle Devonian (Geneva Dolomite and associated Dutch Creek Sandstone). The four formations underwent regional geological characterization to develop a regional geologic framework for the ROZs and their overlying seals. Findings of this study are supported by data from two field laboratory sites, one with stacked greenfield ROZs and the other with a stacked complex that includes a brownfield ROZ and depleted conventional reservoirs. The field laboratory sites were used to collect data and conduct tests to validate ROZ detection methodologies and identify economic field-deployable strategies to co-optimize CO 2 -EOR and associated storage in stacked ROZs. Findings from these field sites were extrapolated to characterize the basin-wide stacked ROZ fairway resource.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Evaluating large scale aqueous organic redox flow battery performance with a hybrid numerical and machine learning framework

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low-capacity degradation in 10 cm$^2$ cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier to commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm$^2$ DHP-based AORFB by combining a physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. Such combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗
DOE OSTI2023

Impacts of Lanthanide Ion Complexation on the Radiation Robustness of Diglycolamide Extractants

Nuclear power reactors represent a clean and reliable source of baseload energy. However, nuclear reactors produce used nuclear fuel (UNF), which, if not recycled/reprocessed, must be disposed of as high-level radioactive waste, necessitating long-term storage options. UNF contains approximately a third of the periodic table, including the radioactive minor actinides (MA) americium and curium. Removal of these MA from UNF would greatly reduce the radiotoxic burden, volume, and cost of a storage facility or geological repository. Thus, a significant global effort has been devoted to the design of reprocessing strategies for the clean separation of the MA from UNF. As MA separations are difficult, due to the presence of lanthanide elements in UNF and their remarkably similar chemical properties, many extractants have been studied. The diglycolamide (DGA) class of extractants are promising for this separation as they exhibit high distribution coefficients for the MAs, high metal loading capacities, and are robust in highly acidic radiation environments.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2024

Parts-Per-Million Carbonate Mineral Quantification with Thermogravimetric Analysis–Mass Spectrometry

Mitigating the deleterious effects of climate change requires the development and implementation of carbon capture and storage technologies. To expand the monitoring, verification, and reporting (MRV) capabilities of geologic carbon mineralization projects, we developed a thermogravimetric analysis–mass spectrometry (TGA–MS) methodology to enable quantification of <100 ppm calcite (CaCO 3 ) in complex samples. We extended TGA–MS calcite calibration curves to enable a higher measurement resolution and lower limits of quantification for evolved CO 2 from a calcite–corundum mixture. We demonstrated <100 ppm carbonate mineral quantification with TGA–MS for the first time, an outcome applicable across earth, environmental, and materials science fields. We applied this carbonate quantification method to a suite of Columbia River Basalt Group (CRBG) well cuttings recovered in 2009 from Pacific Northwest National Laboratory’s Wallula #1 Well. Our execution of this new combined calcite and calcite–corundum calibration curve TGA–MS method on our CRBG sample suite indicated average carbonate contents of 0.050 wt % in flow interiors (caprocks) and 0.400 wt % in interflow zones (reservoirs) in the upper 1250 m of the Wallula #1 Well. Finally, by advancing our knowledge of continental flood basalt-hosted carbonates in the mafic subsurface and reaching new TGA–MS quantification limits for carbonate minerals, we expand MRV capabilities and support the commercial-scale deployment of carbon mineralization projects in the Pacific Northwest United States and beyond.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

An Architectural Survey of the U12G Tunnel Historic District, Nevada National Security Site, Nye County, Nevada

The U.S. Department of Energy (DOE), in conjunction with the National Nuclear Security Administration Nevada Field Office (NNSA/NFO), proposes to demolish six buildings and three storage areas located at the U12g Tunnel portal area in Area 12 of the Nevada National Security Site (NNSS). The buildings are 12-358 (Signal Vault); 12-201800 (Storage Quonset Hut); 12-202555 (Walker Shack); 12-868 (Pipe Assembly); 12-B100933 (Electrical Shop); 12-B100944 (Conference Room); and Storage Area 1; Storage Area 2; and Storage Area 3. The buildings and storage areas were selected for demolition as part of the DOE’s Real Property Efficiency Plan to reduce the footprint of unused and non-operational facilities on the NNSS. They are all vacant and have no proposed uses for current or upcoming NNSS missions. Demolition activities constitute an undertaking subject to review under Section 106 of the National Historic Preservation Act (NHPA) (54 United States Code [USC] § 306101) and its implementing regulations, 36 Code of Federal Regulations (CFR) Part 800. Identification efforts began with resources proposed for demolition in federal Fiscal Year (FY) 23. Four buildings were proposed to be demolished in FY23 (12-358, 12-868, 12-201800, and 12-202555). These buildings and the U12g Tunnel Historic District (SHPO No. D444) were recorded in Identification, Evaluation, and Finding of Adverse Effect for the Proposed Demolition of Five Buildings in Area 12, Nevada National Security Site, Nye County, Nevada (Menocal et al. 2023). Identification efforts indicated three buildings (12-358, 12-201800, and 12-868) supported nuclear testing in the U12g Tunnel. The fourth building post-dated the use of U12g Tunnel for nuclear testing activities. The report recommended that three of the four buildings (12-358, 12-201800, 12-868) and the U12g Tunnel Historic District may be eligible for the National Register of Historic Places (NRHP). The report also found that the undertaking would have an adverse effect on the three buildings and on the historic district. The Nevada State Historic Preservation Office (SHPO) concurred with the report’s findings (Reed 2023). The U12g Tunnel was determined eligible as a historic district under the Secretary of the Interior’s (SOI) Significance Criterion A, at the local level, in the context of the Cold War as an underground testing environment for the development of nuclear weapons and to assess the effects of a nuclear explosion on materials and equipment with a period of significance from 1959 to 1971. It was also determined eligible under Significance Criterion C for embodying the distinctive characters of a horizontal tunnel complex used for nuclear testing and as a significant and distinguishable entity. The three buildings were determined to be contributing elements of the district. The undertaking was expanded with the addition of two buildings and three storage areas proposed to be demolished and located within U12g Tunnel Historic District in FY24. These five resources (12-B100933, 12-B100944, and Storage Areas 1, 2, and 3) were recorded in Supplemental Identification, Evaluation, and Finding of Effect for Additional Proposed Demolition at U12g Tunnel, Area 12, Nevada national Security Site, Nye County, Nevada (Brannan et al. 2024). Identification efforts indicated that the two buildings and Storage Area 1 supported nuclear testing in the U12g Tunnel. Storage Area 1 and Storage Area 2 post-dated the nuclear testing activities at U12g Tunnel and were not recommended as contributing elements to the district. The report also found that the undertaking would have an adverse effect on the newly identified buildings and one storage area and on the historic district. The SHPO concurred that the expanded undertaking would result in adverse effects to historic properties (Reed 2025). To resolve these adverse effects, NNSA/NFO, in consultation with the SHPO, is following standard mitigation as stipulated in the 2024 Programmatic Agreement DE-GM58-22NA25554 Among the U.S. Department of Energy and the Nevada State Historic Preservation Officer and the Advisory Council on Historic Preservation Concerning the Protection of Historic Properties on the Nevada National Security Site, Nye County, Nevada (hereafter referred to as the NNSS PA). The standard mitigation measures are outlined in Appendix D of the NNSS PA. As such, this architectural survey has been prepared in accordance with Appendix D of the NNSS PA and follows the report format outlined in Appendix F. It includes a historic context that describes the district’s origin, history, and support functions, its significance in the context of nuclear testing on the NNSS, and identifies contributing and non-contributing elements within the district. The report is accompanied by Architectural Resource Assessment (ARA) forms for individual resources and a Historic District Resource Assessment (HDRA) for the U12g Tunnel Historic District. In total, this architectural report identified 32 primary resources within the district boundary. Six of the primary resources were previously identified as contributing elements. An additional 17 resources are recommended as contributing elements to the district for a total of 23 contributing elements. The other nine resources identified are recommended as non-contributing elements to the district.

12-201800↗