Robust Cost-Effective Characterization of Petrophysical Properties in Sedimentary Geothermal Applications Leveraged by Drilling Data and Cuttings
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Cuttings, drilling, porosity↗
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Results for “characterization costs”
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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Pumped Storage Hydropower Operation & Maintenance Cost Estimation
The National Laboratory of the Rockies (NLR) develops and hosts a pumped storage hydropower (PSH) cost model that is the most detailed bottom-up PSH cost model available to the public. It is available both as a spreadsheet and an interactive web tool, enabling users with a variety of PSH interests to transparently characterize costs of alternative PSH sites and designs. The NLR PSH cost model was designed originally to consider only upfront capital costs only. This slide deck describes methodology to expand the cost model to include operations and maintenance (OM) costs. OM costs are characterized as five distinct components with unique sources and methods for cost estimation. By combining methods for each of these components into a cumulative OM cost estimate, these methods allow a more complete estimation of total OM costs that agrees with existing literature values. The methods are scalable and transparent, allowing them to be readily to applied to any prospective PSH facility for a representative preliminary OM cost estimate in advance of detailed site-specific engineering and other studies.
13 HYDRO ENERGY↗
Validation of the NLR Pumped Storage Hydropower Cost Model
The National Laboratory of the Rockies (NLR) first released its pumped storage hydropower (PSH) cost model in 2023 as the most detailed bottom-up PSH cost model available to the public. It is available both as a spreadsheet and an interactive web tool, enabling users with a variety of PSH interests to transparently characterize costs of alternative PSH sites and designs. The PSH cost model cannot replace detailed site-level studies and design, but it is important to validate it against other industry PSH cost estimates. The initial model methodology report validated the cost model for a single proposed site, the Eagle Mountain Project in California. This slide deck documents an expanded validation exercise using cost data from six other sites: Goldendale (Washington), Seminoe (Wyoming), Gordon Butte (Montana), Swan Lake (Oregon), White Pine (Oregon), and Lewis Ridge (Kentucky). It compares itemized costs from Federal Energy Regulatory Commission (FERC) applications and other reported costs with NLR PSH cost model outputs after customizing inputs for each site. The validation exercise finds that the NLR model's conservative indirect cost assumptions often drive overall cost overestimation, with direct cost comparisons typically agreeing more closely. All cost model estimates are well within an Association for the Advancement of Cost Engineering (AACE) Class 5 estimation range (-50% to +100%), with five within the AACE Class 4 range (-30% to +50%) and four being within 15%. This result is considered reasonable performance for a parametric model applied at a preliminary design stage.
13 HYDRO ENERGY↗
Materials for the Photoluminescence-Based Detection of Economically Critical Metals
Critical metals, such as rare earth elements (REEs), cobalt, lithium, aluminum, nickel, and others, are essential to advanced technologies and renewable energy in particular. Widespread global adoption of renewable energy technologies has spurred dramatic demand increases for these metals; however, the global supply of these metals is highly monopolistic and conventional mining poses economic and environmental challenges. As a result, there is increasing interest in domestic production from alternative resources such as coal and its utilization byproducts. Slow and expensive characterization costs remain a significant barrier for domestic production. Here, luminescent sensing materials and platforms are presented that provide an alternative to the current state-of-the-art characterization methods; highly sensitive and selective sensing materials for cobalt, aluminum, and rare earth elements are presented, as well as compact, inexpensive platforms capable of analyzing signal from these materials for rapid characterization of critical metal content.
Crawford, Scott↗
Materials for the Photoluminescence-Based Detection of Economically Critical Metals
Critical metals, such as rare earth elements (REEs), cobalt, lithium, aluminum, nickel, and others, are essential to advanced technologies and renewable energy in particular. Widespread global adoption of renewable energy technologies has spurred dramatic demand increases for these metals; however, the global supply of these metals is highly monopolistic and conventional mining poses economic and environmental challenges. As a result, there is increasing interest in domestic production from alternative resources such as coal and its utilization byproducts. Slow and expensive characterization costs remain a significant barrier for domestic production. Here, luminescent sensing materials and platforms are presented that provide an alternative to the current state-of-the-art characterization methods; highly sensitive and selective sensing materials for cobalt, aluminum, and rare earth elements are presented, as well as compact, inexpensive platforms capable of analyzing signal from these materials for rapid characterization of critical metal content.
Crawford, Scott↗
Integration of Large-Scale Electrical Imaging into Geological Framework Development and Refinement
Geologic framework models (GFMs) are critical to the construction of reliable simulation models of groundwater flow and contaminant transport. To support GFM development, direct information (e.g., core samples, fluid samples, hydraulic testing) tends to be sparse and separated by large distances relative to the spatial scales of aquifer heterogeneity. There are additional challenges associated with highly contaminated legacy waste sites, where drilling is particularly costly, and invasive sampling requires specialized handling and disposal of hazardous materials. At these sites in particular, non-invasive geophysical imaging can play an important role in filling spatial gaps between boreholes and reducing characterization costs by optimizing and minimizing the number of necessary boreholes. Here this paper presents a case study demonstrating the use of large-scale (> 30 km 2 ) electrical mapping to identify hydrostratigraphy and potential paleochannels at the Hanford Site, located in Washington State, USA. In two field campaigns, over 36 line-kilometers of electrical resistivity tomography (ERT) data were collected along 14 transects. ERT surveys were sited and performed to image critical aspects (e.g., paleochannels, stratigraphic contacts) of the subsurface, demonstrating a general workflow for integrating ERT with GFM development. Inconsistencies between the GFM and ERT were catalogued to provide a basis for future site characterization using complementary geophysical methods and (or) direct sampling.
58 GEOSCIENCES↗
An approach for spent nuclear fuel containment integrity verification using gas tagging
Verification of containment integrity is required for spent nuclear fuel (SNF) managed by the commercial nuclear industry and U.S. Department of Energy (DOE), especially after extended storage. Certain SNF storage systems, such as the DOE road-ready dry storage system, hold several packaged containments within a welded over-canister. These packaged containments are called Department of Energy Standard Canisters (DOESCs). DOESC leakage identification is challenging because their containment boundary cannot be accessed for testing and their contents (i.e., SNF and fill gas) are often similar. There are concerns that this could result in costly characterization and repackaging operations of DOE road-ready dry storage systems if compromised DOESCs are suspected. Here, to address these concerns, this paper presents an approach for applying a gas tagging process using xenon to uniquely identify compromised inaccessible containments following extended storage. The containments considered for this application are seven DOESCs, each packaged within a single over-canister. Two different SNF loading configurations from the Advanced Test Reactor and Fort Saint Vrain nuclear power plant are considered. These configurations are used to represent research reactor aluminum-clad spent nuclear fuel (ASNF) and TRi-structural ISOtropic (TRISO) SNF types. Results for this application show that for ASNF and TRISO type fuels for which the selected fuels are representative, the volume of taggant required at loading is determined primarily by the lower detection limit and leak rate of taggant from a compromised DOESC, rather than the amount of fission-generated xenon in the loaded fuel. While the application presented is suited for larger leaks, smaller leaks could be detected by modifying certain design parameters. This gas tagging approach can also be applied to other DOE containments and advanced reactor SNF storage systems.
07 - ISOTOPES AND RADIATION SOURCES↗
Development of Luminescent Materials and Instrumentation for Critical Mineral Discovery and Monitoring
Presentation discussing career paths in chemistry as well as how chemical research is applied to address real-world problems. Here, a variety of different materials (metal-organic frameworks, carbon dots, thin films, etc.) are used as luminescent sensors to detect trace quantities of economically critical metals, which are used in applications ranging from renewable energy to national defense. In an application particularly relevant to Western Pennsylvania, the sensor technologies are deployed in coal utilization byproducts including fly ash leachates and acid mine drainage. Taken together, this research presents an exciting path towards reducing the characterization costs associated with metals prospecting and process monitoring, facilitating domestic production of these metals.
analytical chemistry↗
AlgaSens: An AI-enabled Platform for Cost-effective Automated Characterization of Algae and Other Micro-objects for Optimizing Research and Cultivation in Bioproducts & Biofuels.
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algae bioproducts↗
Autonomous elemental characterization enabled by a low cost robotic platform built upon a generalized software architecture
Despite the rapidly growing applications of robots in industry, the use of robots to automate tasks in scientific laboratories is less prolific due to the lack of generalized methodologies and the high cost of hardware. This paper focuses on the automation of characterization tasks necessary for reducing cost while maintaining generalization and proposes a software architecture for building robotic systems in scientific laboratory environments. A dual-layer (Socket.IO and ROS) action server design is the basic building block, which facilitates the implementation of a web-based front end for user-friendly operation and the use of ROS Behavior Trees for convenient task planning and execution. A robotic platform for automating mineral and material sample characterization is built upon the architecture, with an open-source, low-cost three-axis computer numerical control gantry system serving as the main robot. A handheld laser induced breakdown spectroscopy (LIBS) analyzer is integrated with a 3D printed adapter, enabling (1) automated 2D chemical mapping and (2) autonomous sample measurement (with the support of an RGB-Depth camera). We demonstrate the utility of automated chemical mapping by scanning the surface of a spodumene-bearing pegmatite core sample with a 1071-point dense hyperspectral map acquired at a rate of 1520 bits per second. Furthermore, we showcase the autonomy of the platform in terms of perception, dynamic decision-making, and execution, through a case study of LIBS measurement of multiple mineral samples. The platform enables controlled and autonomous chemical quantification in the laboratory that complements field-based measurements acquired with the same handheld device, linking resource exploration and processing steps in the supply chain for lithium-based battery materials.
Cao, Xuan [Lawrence Berkeley National Laboratory (↗
Low Cost Cloud Based Resource Characterization Tools For Performance Monitoring and Optimization
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13 HYDRO ENERGY↗
Optimal Design Approaches for Cost-Effective Manufacturing & Deployment of Chemical Process Families with Economies of Numbers
This work builds on our optimization formulation for process family design and extends it to explicitly include the benefits of economies of numbers. Economies of numbers (sometimes referred to as economies of learning) is a well-documented cost saving phenomenon. It characterizes the manufacturing cost savings due to standardization; in particular, it is capturing the correlation between cost reduction and the number of times a particular product has been manufactured. Following an approach similar to that in Gazzaneo et al. (2022), we develop a costing expression that captures material costs and manufacturing costs as a function of the number of unit modules produced. If the platform has a small number of unit module designs, we will be manufacturing a large number of each of these designs and gaining increased benefits from economies of numbers. However, increasing the number of unit module designs in the platform gives each process variant more choices to consider (at the cost of reducing economies of numbers). The optimization formulation in Stinchfield et al. (2023) pre-specified the number of unit module designs to be included in the platform. Here, by including the economies of numbers explicitly, we allow the mathematical programming formulation to determine the optimal number of unit module designs to include in the platform. We demonstrate this approach on multiple case studies, including MEA-based carbon capture and water desalination.
Stinchfield, Georgia↗
Methods for Assessing Opportunities for Ring Dam Pumped Storage Hydropower
There is growing interest in new pumped storage hydropower (PSH) deployment to provide a range of grid flexibility, reliability, and resiliency services under an evolving and uncertain future power sector. The National Laboratory of the Rockies develops open PSH resource assessment and cost modeling tools to help evaluate PSH deployment opportunities, and this report describes expansions to those tools to consider an additional PSH system configuration - ring-dam reservoirs built on flat topographical features that are constructed from roller-compacted concrete material. This reservoir type is common among current PSH proposals and requires new methods to identify sites with this reservoir geometry throughout the United States and characterize the associated dam cost. Cost characterization for ring dam reservoirs required collecting historical dam cost data for earthen, rockfill, and roller-compacted concrete dams and regressing equations that relate costs between alternative materials. The ring dam site identification algorithm follows a 5-step procedure to identify circular geometry reservoirs. Once ring dam reservoirs are identified, they are then paired with potential dry-gully reservoirs, and the full set of potential paired reservoirs is cost-optimized to produce a least-cost set of potential PSH sites with no overlapping reservoirs. The resulting analysis found 1,663 ring-dam to dry-gully systems in the contiguous United States that are lower cost than any overlapping dry-gully to dry-gully systems, 29 in Alaska, and none in Hawaii or Puerto Rico. These systems constitute 1.5 TW of capacity in the contiguous United States and nearly 29 GW in Alaska, demonstrating that under suitable topography and head, ring-dam systems can provide cost-effective PSH opportunities. The greatest density of these opportunities are found in the intermountain west where there are mesas and flat land at bases of mountain ranges, but continued work could incorporate additional site characteristics or consider more complex reservoir shapes to find additional PSH deployment opportunities.
13 HYDRO ENERGY↗
A Component-Level Bottom-Up Cost Model for Pumped Storage Hydropower
Pumped Storage Hydropower (PSH) is currently the largest source of utility-scale electricity storage in the U.S. and worldwide. As the accelerating deployment of variable renewable technologies creates opportunity and value for energy storage, it has become increasingly important to characterize PSH costs to understand how it competes. Site-specific considerations and limited cost data in the public domain make it difficult to estimate capital costs for potential new PSH sites. This report documents a spreadsheet-based tool that addresses this challenge and creates a component-level bottom-up cost model for PSH that can be made publicly available for widespread use. It uses detailed site-level physical characteristics and design specifications to calculate key performance and cost parameters for individual components and the project as a whole. The model was developed in consultation with HDR, Inc. and Small Hydro Consulting to ensure it aligns with industry expectations. It enables PSH cost exploration across a wide range of system assumptions and could be customized or extended for the needs of a variety of users.
cost model↗
Optimizing Hydrogen Fueling Infrastructure Plans on Freight Corridors for Heavy-Duty Fuel Cell Electric Vehicles
The development of a future hydrogen energy economy will require the development of several hydrogen market and industry segments including a hydrogen-based commercial freight transportation ecosystem. For a sustainable freight transportation ecosystem, the supporting fueling infrastructure and the associated vehicle powertrains making use of hydrogen fuel will need to be co-established. This article introduces the OR-AGENT (Optimal Regional Architecture Generation for Electrified National Transportation) tool developed at the Oak Ridge National Laboratory, which has been used to optimize the hydrogen refueling infrastructure requirements on the I-75 corridor for heavy-duty (HD) fuel cell electric commercial vehicles (FCEV). This constraint-based optimization model considers existing fueling locations, regional-specific vehicle fuel economy and weight, vehicle origin and destination (O-D), and vehicle volume by class and infrastructure costs to characterize in-mission refueling requirements for a given freight corridor. The authors applied this framework to determine the ideal public access locations for hydrogen refueling (constrained by existing fueling stations), the minimal viable cost to deploy sufficient hydrogen fuel dispensers, and associated equipment, to accommodate a growing population of hydrogen fuel cell trucks. The framework discussed in this article can be expanded and applied to a larger interstate system, expanded regional corridor, or other transportation network. This article is the third in a series of papers that defined the model development to optimize a national hydrogen refueling infrastructure ecosystem for HD commercial vehicles.
33 ADVANCED PROPULSION SYSTEMS↗
Correction: Cost-effective carbon fiber precursor selections of polyacrylonitrile-derived blend polymers: carbonization chemistry and structural characterizations
Correction for ‘Cost-effective carbon fiber precursor selections of polyacrylonitrile-derived blend polymers: carbonization chemistry and structural characterizations’ by Qian Mao et al. , Nanoscale , 2022, 14 , 6357–6372, https://doi.org/10.1039/D2NR00203E.
Mao, Qian [Department of Mechanical Engineering, T↗
Optimizing Long Term Hydrogen Fueling Infrastructure Plans on Freight Corridors for Heavy Duty Fuel Cell Electric Vehicles
The development of a future hydrogen energy economy will require the development of several hydrogen market and industry segments including a hydrogen based commercial freight transportation ecosystem. For a sustainable freight transportation ecosystem, the supporting fueling infrastructure and the associated vehicle powertrains making use of hydrogen fuel will need to be co-established. This paper develops a long-term plan for refueling infrastructure deployment using the OR-AGENT (Optimal Regional Architecture Generation for Electrified National Transportation) tool developed at the Oak Ridge National Laboratory, which has been used to optimize the hydrogen refueling infrastructure requirements on the I-75 corridor for heavy duty (HD) fuel cell electric commercial vehicles (FCEV). This constraint-based optimization model considers existing fueling locations, regional specific vehicle fuel economy and weight, vehicle origin and destination (OD), vehicle volume by class and infrastructure costs to characterize in-mission refueling requirements for a given freight corridor. The authors applied this framework to determine the ideal long term public access locations for hydrogen refueling (constrained by existing fueling stations and dispensing technology), the minimal viable cost to deploy sufficient hydrogen fuel dispensers, and associated equipment, to accommodate a growing population of hydrogen fuel cell trucks. So the framework discussed in this paper can be expanded and applied to additional electrified powertrains as well as a larger interstate system, expanded regional corridor, or other transportation networks.
08 HYDROGEN↗
Feasibility of Passive MOSFET Paralleling for Photovoltaic Current-Voltage Curves
Current-voltage curves are an important method of characterizing Photovoltaic (PV) Modules. NREL has developed several low-cost MOSFET-based devices that can characterize PV cells and modules. The size of PV modules that can be measured is limited by the power limitations of a single MOSFET. By using multiple MOSFET devices, each can operate at a lower current, paralleled on resistance is also decreased allowing for higher power loads. Operating multiple devices in parallel can cause an imbalance in current, thus causing some devices to conduct more, pushing them into a thermal runaway condition. To investigate this, an active feedback circuit was tested with paralleled devices using a PV module load. The efficacy, limitations, and design considerations of using parallel MOSFET loads for PV characterization are explored. This work is not new, but the implementation of a paralleled architecture in a low cost characterization tool is novel.
14 SOLAR ENERGY↗