Search NASA⌕ Search

SEARCH · Search NASA

Results for “price sensitivity”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6

Modeled Results of Four Residential Energy Efficiency Measure Packages for Deriving Advanced Building Construction Research Targets

The Advanced Building Construction (ABC) Initiative from the U.S. Department of Energy Building Technologies Office is working to accelerate industrialized construction innovations for decarbonizing buildings. To inform performance and cost targets for research under the ABC Initiative, this analysis used the ResStock™ tool to evaluate the energy savings, utility bill impacts, and carbon emissions impacts of four simulated upgrade packages with specific target performance levels on a large sample of residential dwelling units (approximately 550,000) representative of the U.S. housing stock.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Explaining drivers of housing prices with nonlinear hedonic regressions

Housing markets play a critical role in shaping the spatial and demographic evolution of urban areas. Simulating housing price dynamics can enhance projections of future urban development outcomes. However, traditional hedonic regressions for housing prices, which neglect nonlinear interactions among explanatory variables, often exhibit limited predictive performance. While machine learning (ML) methods can provide a more flexible representation of the relationships between predictors, they are often regarded as “black boxes” due to their complexity and lack of transparency. Interpretable ML techniques provide a promising route by combining the flexibility of ML methods with approaches to analyze the relationships between inputs and outputs. In this study, we employ interpretable ML to analyze the patterns driving the housing market in Baltimore, Maryland, USA. We train an Artificial Neural Network (ANN) to predict Baltimore housing prices based on structural characteristics (e.g., home size, number of stories) and locational attributes (e.g., distance to the city center). We then conduct sensitivity and Partial Dependence Plot (PDP) analyses to interpret the fitted ANN model. We find that the ML model achieves higher predictive accuracy and explains 16 % more of housing price variance than a traditional linear regression model. The interpretable ML model also reveals more nuanced and realistic nonlinear relationships between housing sales price and predictors as well as interactive effects underlying Baltimore home price dynamics. For instance, while the linear model indicates a steady housing price increase over time, our interpretable ML model detects a post-2008 decline, with smaller properties experiencing the sharpest drop.

97 MATHEMATICS AND COMPUTING↗

Technoeconomic analysis and life cycle assessment of purification processes for captured CO 2 streams

Captured carbon dioxide (CO 2 ) streams contain impurities that must be removed to meet specifications for safe transport, storage, and utilization. Among these impurities, oxygen poses challenges due to its high reactivity and potential to cause corrosion, motivating stringent purity limits below 10 ppmv. Building on recent experimental demonstrations of catalytic oxygen removal using hydrogen (H 2 ), carbon monoxide (CO), methanol (CH 3 OH), and methane (CH 4 ) as reducing agents, this study presents a technoeconomic (TEA) and life cycle assessment (LCA) of these four catalytic purification pathways. Process flowsheets were developed and simulated in Aspen Plus for CO 2 streams representative of both low-temperature and high-temperature capture processes, with integrated heat recovery and energy optimization. Results showed that total purification costs were dominated by feedstock procurement and electricity consumption. Among the studied reducing agents, the CH 4 -assisted route achieved the lowest purification cost and highest CO 2 recovery. Sensitivity analyses showed that the H 2 route became competitive at H 2 prices below $\$$0.56/kg to $\$$0.84/kg, depending on the CO 2 feed temperature conditions. In conclusion, environmental impacts were primarily driven by indirect CO 2 emissions from raw material production and utility consumption.

CO2 pipeline specifications↗

Impacts of long-term temperature change and variability on electricity investments

Long-term temperature change and variability are expected to have significant impacts on future electric capacity and investments. This study improves upon past studies by accounting for hourly and monthly dynamics of electricity use, long-term socioeconomic drivers, and interactions of the electric sector with rest of the economy for a comprehensive analysis of temperature change impacts on cooling and heating services and their corresponding impact on electric capacity and investments. Using the United States as an example, here we show that under a scenario consistent with a socioeconomic pathway 2 (SSP2) and representative concentration pathway 8.5 (RCP 8.5), mean temperature changes drive increases in annual electricity demands by 0.5-8% across states in 2100. But more importantly, peak temperature changes drive increases in capital investments by 3-22%. Moreover, temperature-induced capital investments are highly sensitive to both long-term socioeconomic assumptions and spatial heterogeneity of fuel prices and capital stock characteristics, which underscores the importance of a comprehensive approach to inform long-term electric sector planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Wood-to-Fuel for California's Transportation Sector using Autothermal Pyrolysis (FRD-17-002 Progress Report)

During the month of January, further research was carried out on understanding and evaluating the availability and potential availability of fire clearing, and other, forestry residue in California. Further investigations into the negative emissions of biomass pyrolysis products and their upgrading for use in other products (such as fuels) by incorporating carbon capture, drying and compression, and sequestration systems were executed. The cost to achieve the maximum amount of negative emissions from these biomass-pyrolysis products with carbon capture and sequestration techniques was calculated. Sensitivity analysis was employed to understand how feedstock collection cost and product selling price affects this cost.

09 BIOMASS FUELS↗

Carbon storage cost modeling for the offshore Gulf of Mexico

Groundbreaking for geologic carbon storage (GCS) projects in the offshore Gulf of Mexico is imminent, and there is great interest in utilizing this region for GCS projects. Offshore saline reservoirs provide a significant and accessible resource for GCS. However, conducting GCS in the offshore environment will pose distinct challenges pertaining to site selection, operations, infrastructure use, and monitoring compared to operating onshore that ultimately affect technoeconomic assessment of offshore GCS projects. Carbon storage and transport costs are critical to project developers looking to deploy carbon storage in the offshore environment. We present CO2_S_COM_Offshore, a model developed by the National Energy Technology Laboratory (NETL) as a screening-level offshore saline GCS cost modeling tool. Based on NETL’s widely used CO2_S_COM cost model for onshore saline CS, CO2_S_COM_Offshore enables technoeconomic analysis of GCS in offshore areas. This model comprehensively incorporates multiple facets of offshore GCS projects, from regional evaluation and site selection to permitting, transport, operations, monitoring, site closure, and decommissioning. In general, the model can explore the cost implications for potential offshore GCS project(s) by enabling the user to change several project operational and financial attribute configurations. Key inputs include offshore storage formation options, CO2 injection rate and duration, infrastructure types, monitoring intensity, project financing, and post-injection site care duration. Supporting cost algorithms within CO2_S_COM_Offshore were compiled utilizing S&P Global’ s QUE$TORTM cost estimation software alongside a variety of open-source scientific literature. In addition to reviewing key model components, we discuss several sensitivity analyses, input variabilities, and results on analysis of break-even CO2 price required by a project based on different regulation/policy and operational scenarios for the offshore Gulf of Mexico. These results indicate the value of modeling offshore GCS specifically, and the potential of offshore GCS within a decarbonization value chain. Presented at the 41st USAEE/IAEE North American Conference, 3-6 November 2024, Baton Rouge, LA, United States.

Mark-Moser, Mackenzie K.↗

Pilot-Scale Testing of an Integrated Circuit for the Extraction of Rare Earth Minerals and Elements from Coal and Coal Byproducts Using Advanced Separation Technologies

The primary objective of this project was to develop and demonstrate an integrated pilot-scale circuitry for recovering high-value rare earth elements (REEs) from coal and coal byproducts. The target performance was to produce a mixed REE product with content of at least two percent by weight on a dry mass basis in a cost-effective and environmentally benign manner. During the first nine months of the project period (Phase 2 Budget Period 2), pilot plant construction was completed including all field site startup activities such as permitting, engineering design, procurement/bidding, unit fabrication, site construction, equipment installation, module assembly, safety training, and circuit shakedown. During the remaining 21 months of project period (Phase 2 Budget Period 3), detailed field-testing activities were performed including feedstock sample collection and preparation, exploratory testing, circuit modification, detailed parametric study, and performance optimization. A detailed techno-economic analysis was performed based on the pilot plant testing findings which provided various scenarios for REE production. The project successfully accomplished the proposed target performance by producing mixed rare earth oxide (REO) with greater than 90% purity by weight in a continuous pilot scale operation from two distinctly different coarse refuse materials (i.e., West Kentucky No. 13 and Fire Clay coal seams), and at least three secondary sources (i.e., heap leach process and naturally formed acid mine drainage system). Project partners included the University of Kentucky, Virginia Tech, West Virginia University, Alliance Coal, Blackhawk Mining, Mineral Refining Company, and Mineral Separation Technologies. The pilot scale test facility was constructed at a former mining complex owned by Alliance Natural Resource Partners (Alliance Coal). The site was rehabilitated to accommodate the equipment installation, construction and fabrication, electrical power requirement, water line management and containment. The process units constructed and installed included X-ray sorting unit, crushing and grinding unit, physical separation unit, acid leaching unit, solvent extraction unit, and wastewater management unit. A rare earth mineral concentration unit was constructed as a standalone unit for flexible operation. A detailed environmental assessment and control plan was carried out to identify and quantify any potential impacts of the pilot-scale processing circuitry on the human and eco-system health and well-being. Corresponding mitigation strategies and control measures were provided. A conceptual flowsheet was developed to effectively remove thorium and uranium from high purity rare earth oxide mix or any potential radionuclide enriched stream. The two distinct feedstock materials were secured from the Blackhawk Mining Complex in eastern Kentucky where the Fire Clay (Hazard No. 4) seam is processed. The West Kentucky No. 13 (Baker) coarse refuse material was collected from an active process stream at an Alliance coal preparation plant located in western Kentucky. Characterization analysis indicated that both of feed materials generated from the two sources contained >300 ppm of TREEs on a dry whole mass basis which met the requirements for a qualified feed stock. The two feedstocks were further upgraded using a dual x-ray sorter to prepare the feed material for hydrometallurgical circuit. Thermal treatment on feed material prior to leaching was found to: 1) improve the leaching recovery of REEs, 2) increase the leaching kinetics, and 3) allow the leaching reaction to occur at lower acidity. Roasting at 600°C was selected as the pre-treatment condition for both West Kentucky No. 13 and Fire Clay coarse refuse material. Over 40% of leaching recovery was achieved by roasting West Kentucky No. 13 material having a top particle size of 3 mm in the pilot scale operation using 1.2M sulfuric acid leaching at 75OC. Initial pilot scale testing involved continuous operation of the pilot plant for 94 hours. The leaching unit was operated at solid-to-liquid ratio of 1 to 10 (w/v) using 0.5M sulfuric acid solution at a temperature of 75°C. The continuous solvent extraction circuit utilized rougher and cleaner units with DEHPA and TBP as the extractants. An innovative stripping circuit was developed to accumulate the REE concentration in the stripping solution to a level above 600 ppm. A bleed stream from the recycled strip solution was treated using oxalic acid precipitation which produced a high grade rare earth oxalate. The oxalate product was roasted to remove the oxalate which produced a rare earth oxide product having a purity greater 90%. Due to high concentrations of contaminant ions in the pregnant leach solution (PLS), a modified flowsheet was developed that involved pre-concentration of the REEs using multiple stages of precipitation and redissolution. The advantage of this process was improved removal of contamination before the downstream purification process and a significant cost reduction relative to the circuit that utilized the solvent extraction process. The modified circuitry included processes involving leaching, multistage precipitation, redissolution, and oxalate precipitation followed by roasting of the oxalate product. The circuit produced a mixed REO that was 92.96% pure from the initial test. A detailed parametric test plan was carried out which involved varying key parameters including solids feed rate, acid flowrate, acid concentration, multistage precipitation pH, redissolution pH, oxalate precipitation dosage and pH. The response variables included REE recovery, contaminant recovery, REO product grade and overall chemical consumption. Test results indicated that the acid-to-solid ratio is the key parameter to leaching efficiency as performance deteriorated with an increase in solids concentration. The optimal pH determined for REE precipitation and redissolution was 6.5 and 2.5, respectively. Additional tests were conducted to further improve the flowsheet. Recirculating a portion of the PLS to the feed of the leach tanks improved the leaching performance by lowering the pH of the leaching system and reducing the contamination recovery by shortening the residence time. Moreover, the removal of Al prior to REE precipitation significantly reduced the oxalic acid consumption in the oxalate precipitation circuit. The modified circuit produced over 90% grade REO by weight from both West Kentucky No. 13 and Fire Clay coarse refuse material in pilot scale continuous test programs. A case analysis model was developed to project the REE and major contaminants concentration in each PLS stream based on the leaching condition, pH cut point, and oxalic acid dosage. A correlation was established using empirical and semi-empirical models. Using the models, chemical consumption required for each stage was predicted based on the projected performance of the hydrometallurgy circuit. After identifying the optimum conditions, validation tests were carried out for the treatment of both West Kentucky No. 13 and Fire Clay coarse refuse materials in the pilot plant. The actual circuit performance and chemical consumptions were very close to the model predictions. Other than the two coarse refuse sources, several secondary feedstocks were also tested in the pilot plant facility. A “heap leach” system was constructed using the coarse refuse material generated from cleaning the West Kentucky No. 13 seam coal. Using the two stage SX rougher and cleaner circuit, a concentrate with a grade >90% REO was produced while recovering >97% of the REEs from the heap leach PLS. Naturally generated acid mine drainage (AMD) from West Kentucky No.13 mine was processed using the multistage precipitation circuit in the pilot plant in a test conducted for a period of 32 hours. The final grade of the mix RE oxide produced from the AMD was 90.84% with an overall circuit recovery of 64%. The primary source of REE was the selective precipitation steps involving iron and aluminum rejection. The hydrophobic-hydrophilic separation (HHS) process was proven to effectively recover coal from fine waste materials. For REM recovery, the HHS process was able to produce concentrates at grades of approximately 1.8% REE on an ash basis; however, recovery values were typically low, <10%, under the optimal conditions determined in the laboratory-scale testing. Staged testing of the pilot-scale HHS process for coal recovery and semi-continuous laboratory testing for REM testing showed that a total concentration ratio of more than 15x was observed for the REM recovery process. A circuit simulation package was developed for REE extraction and purification using a spreadsheet-based platform (Microsoft Excel). The REESim circuit simulation package is configured to track the mass and volume flows of components passing through a series of unit operations specified and configured by the user. The mass rates can then be utilized by the user to determine important performance indicators such as product mass yields, concentrate purity levels, element-by-element recoveries, and so forth. The techno-economic analysis showed that the roasting and leaching operations were the most expensive capital items, each contributing approximately 30% to the total capital cost. One notable contributor to the high production costs was the low REE recovery observed in the pilot scale trials. The product basket price was shown to have a strong influence on the economic viability of the scenarios, with the scandium price being the most significant influencer. Operating cost was shown to be extremely sensitive to REE recovery, REE feed grade, and leaching acid consumption. An analysis of ten different scenarios for a 500 t/h commercial operation revealed that three were economically favorable, producing internal rates of return varying from 27.7% to 33.1% and payback periods of 4 to 5 years. The project successfully developed and demonstrated a process to recover REEs from coal and coal byproducts in a pilot-plant operation which consistently produced over 90% grade REO mix from varies types of feedstocks. Commercialization analysis showed that the technology readiness level successfully achieved TRL 6 at the end of the project and demonstrated the need and the potential for scaling the process to further advance the technologies toward the goal of providing a domestic supply of REEs at a commercial scale.

01 COAL, LIGNITE, AND PEAT↗

Additional Analysis of Carbon Capture at Industrial Facilities

This poster provides summary cost details for a technoeconomic analysis of CO2 capture from flue gas generated by cement plants, conducted by U.S. Department of Energy National Energy Technology Laboratory and presented at the 2022 Carbon Management Project Review Meeting held in Pittsburgh, PA (August 15-19, 2022). A range of modern cement plant configurations was considered, along with different fuel types (coal, coke, and natural gas) and two levels of CO2 capture (95% and 99%). The sensitivity of capture cost to a range of modeling assumptions (such as fuel price, financing assumptions, utilization rate, and plant size) was also conducted, to show possible cost ranges that could be expected for decarbonization of typical cement plants in the U.S.

Hughes, Sydney↗

Data from Biodiesel Production from Engineered Sugarcane Lipids under Uncertain Feedstock Compositions: Process Design and Techno-Economic Analysis

In this study, different process schemes were designed and evaluated for biodiesel production from engineered cane lipids with uncertain fatty acid compositions. Four different process schemes were compared under (i) thermal glycerolysis and (ii) enzymatic glycerolysis approaches. These schemes were based on the biodiesel yield and economic indicators such as the net present value (NPV) and the minimum selling price (MSP) of biodiesel. A scheme with polar lipid separation under thermal glycerolysis resulted in the maximum NPV ($96.5 million) and minimum MSP ($1107/ton biodiesel), respectively. Through local sensitivity analysis, it was concluded that the cane lipid percentage is the most significant factor influencing process economics. A conjoint analysis of the lipid procurement price and cane lipid percent suggested that 15% cane lipids with a low lipid procurement price ($0.536/kg) results in a positive NPV. When the cane lipid price is higher (>$0.80/kg), a 20% lipid content should be considered to achieve a positive NPV. At 20% cane lipids, the worst-case and best-case scenarios were evaluated by analyzing the interplay of the three most important parameters, The best-case scenario revealed that the minimum NPV under any process scheme could yield more than $100 million (or MSP: $0.80/L), and the worst-case analysis showed that losses incurred by the plant could be as high as $80 million (MSP: $1.36/L). A Monte Carlo simulation indicated that there is a 70% chance of the plant being profitable (NPV > 0).

Conversion↗

Biodiesel production from engineered sugarcane lipids under uncertain feedstock compositions: Process design and techno-economic analysis

In this study, different process schemes were designed and evaluated for biodiesel production from engineered cane lipids with uncertain fatty acid compositions. Four different process schemes were compared under (i) thermal glycerolysis and (ii) enzymatic glycerolysis approaches. These schemes were based on the biodiesel yield and economic indicators such as the net present value (NPV) and the minimum selling price (MSP) of biodiesel. A scheme with polar lipid separation under thermal glycerolysis resulted in the maximum NPV ($\$96.5$ million) and minimum MSP ($\$1107$ /ton biodiesel), respectively. Through local sensitivity analysis, it was concluded that the cane lipid percentage is the most significant factor influencing process economics. A conjoint analysis of the lipid procurement price and cane lipid percent suggested that 15% cane lipids with a low lipid procurement price ($\$0.536$ /kg) results in a positive NPV. When the cane lipid price is higher (> $\$0.80$ /kg), a 20% lipid content should be considered to achieve a positive NPV. At 20% cane lipids, the worst-case and best-case scenarios were evaluated by analyzing the interplay of the three most important parameters, Here, the best-case scenario revealed that the minimum NPV under any process scheme could yield more than $\$100$ million (or MSP: $\$0.80$ /L), and the worst-case analysis showed that losses incurred by the plant could be as high as 80 million (MSP: $\$1.36$ /L). A Monte Carlo simulation indicated that there is a 70% chance of the plant being profitable (NPV > 0).

09 BIOMASS FUELS↗

Techno-economic analysis of biomass value-added processing informed by pilot scale de-ashing of paper sludge feedstock

Paper sludge biomass represents an underutilized feedstock rich in pulped and processed cellulose which is currently a waste stream with significant disposal cost to industry for landfilling services. Effective fractionation of the cellulose from paper sludge presents an opportunity to yield cellulose as feedstock for value-added processes. A novel approach to cellulose fractionation is the sidehill screening system, herein studied at the pilot-plant scale. Composition analysis determined ash removal and carbohydrate retention of both sidehill and high-performance benchtop screening systems. Sidehill screening resulted in greater carbohydrates retention relative to benchtop screening (90% vs 66%) and similar ash removal (95% vs 98%). Techno-economic analysis for production of sugar syrup yielded a minimum selling price of $331/metric ton of sugar syrup including disposal savings, significantly less than a commercial sugar syrup without fractionation. Furthermore, sensitivity analysis showed that screening conditions played a significant role in economic feasibility for cellulosic yield and downstream processes.

09 BIOMASS FUELS↗

Trade-offs in land-based carbon removal measures under 1.5 °C and 2 °C futures

Land-based carbon removals, specifically afforestation/reforestation and bioenergy with carbon capture and storage (BECCS), vary widely in 1.5 °C and 2 °C scenarios generated by integrated assessment models. Because underlying drivers are difficult to assess, we use a well-known integrated assessment model, GCAM, to demonstrate that land-based carbon removals are sensitive to the strength and scope of land-based mitigation policies. We find that while cumulative afforestation/reforestation and BECCS deployment are inversely related, they are both typically part of cost-effective mitigation pathways, with forestry options deployed earlier. While the CO 2 removal intensity (removal per unit land) of BECCS is typically higher than afforestation/reforestation over long time horizons, the BECCS removal intensity is sensitive to feedstock and technology choices whereas the afforestation/reforestation removal intensity is sensitive to land policy choices. Finally, we find a generally positive relationship between agricultural prices and removal effectiveness of land-based mitigation, suggesting that some trade-offs may be difficult to avoid.

54 ENVIRONMENTAL SCIENCES↗

Near-Term Reliability and Resilience (NTRR) (Final Report)

The Near-Term Reliability and Resiliency (NTRR) was awarded in December 2020 as an inter-lab project to examine the reliability and resilience of the electricity grid and natural gas transportation availability. The project builds on studies conducted by The North American Electric Reliability Corporation (NERC), the U.S. Department of Energy (DOE), and other non-governmental research and operational focused on reliability and resilience analyses challenges. The research was conceived to address near-term scenarios (within 10 years), when many local and regional policy transitions could begin to impact grid reliability, resilience, and supporting infrastructure availability. To integrate the natural gas interdependency, the team began with the generating capacity and demand projections from the 2020 NERC Long-Term Reliability Assessment and the Bulk Electric System (BES) transmission topologies defined in the Western Electricity Coordinating Council (WECC) Anchor Data Set, Eastern Interconnection Reliability Assessment Group Multi-Regional Modeling Working Group (ERAG/MMWG) Data Set, the team calculated baseline regional power sector gas demands from present electricity delivery year through the end of delivery year 2030/31 by applying security constrained economic dispatch. This demand was compiled along with demand projections for regional residential, commercial, and industrial natural gas demands from the most recent Energy Information Administration (EIA) Annual Energy Outlook Reference Case into Deloitte’s MarketBuilder® North American Gas Model. Through the application of these demands, MarketBuilder® was projected the topology of natural gas flows in the natural gas pipeline network across the interconnected North American system along with regional natural gas prices that may be seen by market participants in future years Additionally, contingencies and sensitivities focused on the built models of the Eastern Interconnection (EI) and Western Interconnection (WI). They address challenges from the following with the outcomes being an identification of performance under the extreme conditions and an identification of potential grid weaknesses that should be addressed to mitigate the reduced performance and improve the resilience and reliability of the specific regions as well as the National Grid: • Weather events including extreme heat, extreme cold, high wind, no wind, wind and solar forecasting errors, and wildfires. • Gas availability, factoring in supply disruption (contractual and physical), seasonal availability constraints, and infrastructure limitations; and • Transmission availability and congestion.

03 NATURAL GAS↗

Comparative Analysis of Model Predictive Control and MPC-Informed Rule-Based Control for Thermal Storage Operation in Ultra-Low Temperature 4th Generation District Heating Networks

The integration of thermal storage and heat pumps in district heating networks (DHNs) can significantly enhance operational flexibility and energy efficiency; however, the practical deployment of advanced control strategies is often hindered by forecasting requirements and computational complexity. This study presents a comparative analysis of thermal storage control strategies in an ultra-low-temperature fourth-generation DHN, focusing on the development of a simplified rule-based control (RBC) explicitly informed by Model Predictive Control (MPC) behavior. The proposed methodology systematically analyzes the charging and discharging decisions of an MPC-controlled system under ideal forecasting conditions and extracts recurrent control patterns as a function of key system variables, including outdoor temperature, thermal demand, and electricity price. These patterns are translated into a set of structured time- and condition-based rules, resulting in an MPC-informed RBC that embeds predictive insights while preserving implementation simplicity and operational transparency. The approach is validated on a realistic mixed-use urban district in Denver, Colorado, USA, equipped with a centralized air-source heat pump, distributed water-to-water heat pumps, and a central thermal storage unit. Results show that the tuned RBC attains approximately 96% of ideal MPC economic performance (-27% of costs), preserves values of technical and environmental indicators (reduction only of 2-3%), and substantially reduces complexity. Sensitivity analyses further demonstrate the robustness of the RBC under varying operational conditions (i.e., ambient temperature, electricity price). Overall, the study demonstrates that MPC-informed rule-based control represents an effective trade-off between control performance and real-world applicability, enabling the integration of additional system components while maintaining simplicity, robustness, and ease of implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Sustainable Recycling of Rare-Earth Elements from NdFeB Magnet Swarf: Techno-Economic and Environmental Perspectives

Rare-earth elements (REEs) are increasingly susceptible to supply risks due to their limited geographical availability and growing demand in clean energy applications such as neodymium-iron-boron (NdFeB) magnets used in electric vehicles and wind turbines. When NdFeB magnets are produced, 6–73% of swarf is generated during the manufacturing steps. This paper presents an innovative technology that utilizes copper nitrate to dissolve REEs in NdFeB magnet swarf and subsequently recovers ~97% of them as mixed rare-earth oxides (REOs) of purity higher than 99.5%. Techno-economic analysis (TEA) and life cycle assessment (LCA) quantified the economic and environmental impacts of adopting the proposed acid-free dissolution technology, projecting a net profit margin of 12–43% and a global warming impact reduction by up to 73% compared to the prevailing REO production routes in China. As copper nitrate is the single largest contributor to the cost and environmental footprint, recycling of copper nitrate was investigated as well as using alternative copper salts (e.g., copper acetate), revealing significant improvements in TEA and LCA results. Dysprosium was a major revenue source, highlighting the importance of targeting electric vehicle magnets that are rich in dysprosium. As the REO market is volatile, sensitivity analysis was employed to evaluate the profitability of the proposed technology under different REO prices over the last 11 years. Overall, our results confirmed the economic and environmental viability of the proposed technology for sustainable recycling of REEs from the NdFeB magnet swarf.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tierra del Fuego Case Study Capacity Expansion Analysis

This case study, developed by Net Zero World Initiative and the Government of Argentina, examines least-cost decarbonization pathways for Tierra del Fuego, Argentina, utilizing renewable energy, energy storage, hydrogen, and other decarbonization technologies. Being the second largest natural gas producing province in Argentina, Tierra del Fuego has historically relied on natural gas for their energy sector needs. As they look at possible decarbonization pathways, they face challenges due to extreme weather conditions, isolation from the mainland, and low population density. The study utilizes the Engage web application for capacity expansion modeling, addressing both business-as-usual (BAU) and accelerated decarbonization scenarios, with varying degrees of electrification and carbon emission constraints. Key findings reveal that an interconnection with the mainland, high contribution of wind energy development on Tierra del Fuego, energy storage, and hydrogen, coupled with energy-efficient electrification technologies (such as heat pumps and electric vehicles), emerge as the most cost-effective solutions to decarbonize, significantly reducing carbon emissions and total system energy costs. The study explores self-generation and interconnection alternatives, demonstrating the economic advantage of an interconnection of Tierra del Fuego with the mainland, as an alternative to 100% local generation. Sensitivity analyses on wind data sources and temporal resolutions, as well as projected natural gas prices, highlight the influence of external factors on the feasibility of decarbonization pathways. Challenges identified include the practicality of phasing out natural gas, economic uncertainty, cost implications of long-term storage technologies as wind energy increases, and geographical limitations for wind generation. The case study concludes that while substantial emissions reductions can be achieved by 2050, and be competitive with conventional pathways, achieving a full 100% decarbonization by 2050 would entail higher costs, particularly due to the significant reliance on storage solutions with higher contribution of wind energy. The analysis offers valuable insights for policymakers and stakeholders in Argentina's energy sector, emphasizing the importance of strategic planning, investment in renewable energy and storage technologies, and careful consideration of local conditions in the transition towards Net Zero targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Uncertainty quantification and reliability assessment for intermodal freight transportation

Intermodal freight optimization models support cost-effective, low-emission, and timely goods movement by coordinating trucks, rail, and barges. These models determine optimal flows, routing, and modal switches while respecting infrastructure and operational constraints. However, their real-world utility is often undermined by pervasive uncertainties-such as fluctuating transportation costs and emissions, variable terminal capacities, and uncertain freight demand-that distort key performance outcomes, including total system cost, carbon footprint, and transit time reliability. This study presents a structured framework for quantifying uncertainty in intermodal freight transportation (IFT) optimization. The framework evaluates how input uncertainty affects system performance and reliability, a critical need for ensuring that model-based decisions remain robust under real-world variability, especially amid volatile fuel prices, shifting demand, and growing disruptions. It integrates three complementary methods: (1) Sobol-based global sensitivity analysis to identify influential parameters affecting cost, emissions, and transit time, (2) Monte Carlo-based capacity perturbation analysis to assess robustness under probabilistic facility disruptions, and (3) Monte Carlo filtering with Bayesian inference to detect threshold-based performance vulnerabilities. The results highlight diesel truck unit cost as the dominant driver of variability. To improve system resilience, planners should prioritize uncertainty in fuel-related parameters when designing intermodal strategies.

Intermodal freight transportation↗

Dispatch Optimization, System Design and Cost Benefit Analysis of a Nuclear Reactor with Molten Salt Thermal Storage

Variable renewable energy availability has increased the volatility in energy prices in most markets. Nuclear power plants, with a large ratio of capital to variable costs, have historically operated as base load energy suppliers but the need for more flexible operation is increasing. We simulate the techno-economic performance of a 950 MWt nuclear power plant, based on the Westinghouse lead-cooled fast reactor, coupled with molten salt thermal storage as a method for flexible energy dispatch. We use the System Advisor Model to model the nuclear reactor thermal power input and power cycle operating modes. We combine this robust engineering model with a mixed-integer linear program model for optimized dispatch scheduling. We then simulate the coupled nuclear and thermal storage system under different market scenarios with varying price volatility. We find that the coupled plant outperforms the base plant under markets where energy price peaks fluctuate by a factor of two or more about the mean price. We show that a calculated power purchase agreement price for the plant improves by up to 10% when operating under California energy market conditions. Sensitivity analysis on the thermal storage cost shows that the optimal design remains unchanged even when doubling costs.

25 ENERGY STORAGE↗