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Results for “Scenario Analysis”

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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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Optimal design and integration of decentralized electrochemical energy storage with renewables and fossil plants

Increasing renewable energy requires improving the electricity grid flexibility. Existing measures include power plant cycling and grid-level energy storage, but they incur high operational and investment costs. Using a systems modeling and optimization framework, we study the integration of electrochemical energy storage with individual power plants at various renewable penetration levels. Furthermore, our techno-economic analysis includes both Li-ion and NaS batteries to encompass different technology maturity levels. A California case-study indicates localized integration to be cost-effective for greater grid flexibility. Li-ion batteries can mitigate the residual demand fluctuations of small to medium-sized plants, while NaS batteries would be best-suited for larger storage with higher renewable penetration. Overall, the battery-enabled renewable integration could reduce the unmet grid demand by 75%, the renewable curtailment by 58%, and the CO 2 emission intensity by 16% while including the life cycle emissions of the battery and the renewable farm. Our scenario-based analysis also indicates that rather than replacing all fossil power plants, it is more economical to combine batteries and renewables with individual fossil plants to achieve a clean energy grid.

25 ENERGY STORAGE↗
DOE OSTI2022

SWP Summary Report for Individual Legacy Well Leakage Risk Analysis at Farnsworth Unit Site: Open Well Scenario

This report summarizes results of the individual legacy well leakage risk analysis of the Farnsworth Unit site (FWU) for Open Well scenario. NRAP tools Integrated Assessment Model for Carbon Storage (NRAP-IAM-CS) and Reservoir Reduced-Order Model Generator (RROMGen) were used (Dilmore et al., 2016; Pawar et al., 2016; King, 2016). This is part one of the additional analysis addressing SWP BP4 Subtask 7.4.1.2: Extend quantitative brine and CO2 leakage calculations (Chu et al., 2020).

58 GEOSCIENCES↗
DOE OSTI2026

Dynamic analysis of fully constrained Cable-Driven Parallel Robots for automated prefabricated component installation

This paper presents a dynamic analysis and validation framework to assess a fully constrained six-anchor Cable-Driven Parallel Robot (CDPR) for automated installation of prefabricated facade components. Compared with conventional eight-anchor systems, the six-anchor configuration simplifies setup and reduces cost, but it also reduces control authority, shrinks the wrench-feasible workspace, and tightens orientation limits. Consequently, it is unclear a priori whether dynamically feasible trajectories exist to move the end effector from pickup to the facade. A constrained trajectory optimization is formulated to enforce the system dynamics, cable-tension bounds, and pose/velocity limits, and the framework is evaluated in simulation at three levels: (i) an idealized reference model, (ii) a lab-scale prototype model incorporating measured anchor misalignments and identified damping, and (iii) a full-scale three-story building model with load decomposition for structural feasibility checks. Across these scenarios, the analysis shows that optimal, constraint-satisfying trajectories exist that move the end effector from pickup to installation while maintaining a near-plumb, level orientation at the final pose. Collectively, this multi-scale dynamic analysis and validation framework supports the deployment readiness of the six-anchor CDPR and provides a prototype-based sensitivity case study of how measured anchor placement deviations affect feasibility.

CDPR↗
DOE OSTI2022

Economic analysis of the benefits to petroleum refiners for low carbon boosted spark ignition biofuels

A refinery modeling framework is developed to estimate the benefits of blending high-quality biofuels directly with refinery gasoline components for attaining a premium grade fuel (also termed as Co-Optima Boosted SI gasoline here). Our results change the paradigm of bio-blendstocks (BBs) being competitors to fossil components, by identifying opportunities for refineries to add value to their product slate, from some favorable BB properties. This potential value can be characterized by calculating the breakeven value (BEV), as defined down below. The proposed modeling framework incorporates extensive data from (1) projected product over the next few decades, (2) crude oil and refinery products pricing, and (3) fuel specifications. The complete refinery models serve as a basis for assessing the value of biofuels, assuming profitability remains the same for representative petroleum refinery configurations. Our assessment showed wide range of variation of biofuels BEV from $\$$20-$\$$120/bbl, within the considered blending level and crude prices. Further, the BEV was correlated with the fuel octane ratings such as octane numbers (research, RON and motor octane numbers, MON) and both antiknock index (AKI, average of RON and MON) and sensitivity (S, difference between RON and MON), with a slightly higher correlation with the sensitivity. However, the expected decrease in gasoline demand for the upcoming years could negatively impact biofuels demand and value, in a business-as-usual scenario. Our analysis also showed a more valuable bio-blendstocks incorporation in smaller refineries since they can enhance the capabilities for producing specialty, high-value fuels/products, and introduce high octane-barrels into otherwise constrained blending operations. Additional implications towards refiners include opportunities to rebalance operations, access to high-value fuel markets, and synchronization with broader transportation industry trends. Furthermore, results indicate the value of Co-Optima boosted spark ignition (BSI) efficiency gains can extend to refiners to incentivize decarbonization and diversified feedstock production.

09 BIOMASS FUELS↗
DOE OSTI2020

Independent Review of Paducah Gaseous Diffusion Plant Freon Release Authorized Limits and Evaluation of Corresponding Radiological Doses

The Portsmouth/Paducah Project Office (PPPO) proposes to use the American National Standard Institute (ANSI)/Health Physics Society (HPS) N13.12 (ANSI 2013) volumetric screening levels as Authorized Limits (ALs) for the release of cryofluorane R-114 (Freon) at the Paducah Gaseous Diffusion Plant (PGDP) in Paducah, Kentucky. A review of the proposed ALs document indicated that potential exposure scenarios from the release of Freon are adequately discussed therein. However, questions arose regarding the assumptions made for the ANSI N13.12 clearance values, and whether or not all pathway doses were adequately considered in the Authorized Limits Request. For example, PPPO used the inverse square rule to estimate dose to the truck driver. A more appropriate evaluation would have considered the material as a cylindrical source for this pathway. In addition, the inverse square rule was inadequately applied to the inhalation and ingestion pathways. Furthermore, while the ANSI N13.12 volumetric clearance values are used in the ALs, questions arose concerning whether the values are appropriate for materials of greater than 1 metric ton, and whether or not the ANSI N13.12 standard could be used for liquids that are sent to an incinerator. For these reasons, dose modeling was conducted to demonstrate that using ANSI/HPS N13.12 screening levels as ALs for release of PGDP Freon meets the dose criteria set in U.S. Department of Energy (DOE) Order 458.1. This report provides a bounding dose analysis using scenarios described in PPPO document. Realistic parameters, such as the incinerator characteristics data, are used when available.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2026

Admissible Powertrain Alternatives for Heavy-Duty Fleets: A Case Study on Resiliency and Efficiency

Heavy-duty vehicles dominate global freight movement and primarily rely on fossil-derived diesel fuel. However, fluctuations in crude oil prices and evolving emissions regulations have prompted interest in alternative powertrains to enhance fleet energy resiliency. This study paired real-world operational data from a large commercial fleet with high-fidelity vehicle models to evaluate the potential for replacing diesel internal combustion engine (ICE) trucks with alternative powertrain architectures. The baseline vehicle for this analysis is a diesel-powered ICE truck. Alternatives include ICE trucks fueled by bio- and renewable diesel, compressed natural gas (CNG) or hydrogen (H 2 ), as well as plug-in hybrid (PHEV), fuel cell electric (FCEV), and battery electric vehicles (BEV). While most alternative powertrains resulted in some payload capacity loss, the overall fleetwide impact was negligible due to underutilized payload capacity for the specific fleet considered in this study. For sleeper cab trucks, CNG-powered trucks achieved the highest replacement potential, covering 85% of the fleet. In contrast, H 2 and BEV architectures could replace fewer than 10% and 1% of trucks, respectively. Day cab trucks, with shorter daily routes, showed higher replacement potential: 98% for CNG, 78% for H 2 , and 34% for BEVs. However, achieving full fleet replacement would still require significant operational changes such as route reassignment and enroute refueling, along with considerable improvements to onboard energy storage capacity. Additionally, the higher total cost of ownership (TCO) for alternative powertrains remains a key challenge. This study also evaluated lifecycle impacts across various fuel sources, both fossil and bio-derived. Bio-derived synthetic diesel fuels emerged as a practical option for diesel displacement without disrupting operations. Conversely, H 2 and electrified powertrains provide limited lifecycle impacts under the current energy scenario. This analysis highlights the complexity of replacing diesel ICE trucks with admissible alternatives while balancing fleet resiliency, operational demands, and emissions goals. These results reflect a US-based fleet’s duty cycles, payloads, GVWR allowances, and an assumption of depot-only refueling/recharging. Applicability to other fleets and regions may differ based on differing routing practices or technical features such as battery swapping.

BEV↗
DOE OSTI2024

The path to 2060: Saudi Arabia's long-term pathway for GHG emission reduction

Saudi Arabia, as part of its Saudi Green Initiative, has announced its goal to achieve net zero green-house gas emissions by 2060. This ambitious target underscores the nation's dedication to address-ing climate change. However, there is a significant gap in comprehensive analysis regarding the long-term effects of Saudi Arabia's climate policies and their collective contribution towards the net-zero objective. This study endeavors to bridge this gap through a detailed examination using the GCAM-KSA, a specialized version of the Global Change Analysis Model tailored for Saudi Arabia, employing a multi-sectoral methodology that integrates economic, energy, and land use systems within a coherent framework to assess the impact of climate policies on GHG emissions. Our anal-ysis reveals that reaching net-zero GHG emissions by 2060 is a complex challenge requiring con-certed efforts across all sectors of the economy. While transitioning to low-carbon electricity and improving energy efficiency offer considerable emission reductions, fully decarbonizing the indus-trial and transportation sectors poses a significant hurdle. Our findings suggest that Saudi Arabia must triple its emission reduction commitments in its next Nationally Determined Contributions (NDCs) update to align with its 2060 net-zero goal. Early action and increased ambition could avoid the chances of getting locked into the high emission assets and give enough time to transform the energy system. Furthermore, the adoption and integration of Carbon Dioxide Removal (CDR) tech-nologies are identified as crucial for offsetting residual emissions, especially in sectors that might continue to rely on fossil fuels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Implications of climate change mitigation strategies on international bioenergy trade

Most climate change mitigation scenarios rely on increased use of bioenergy to decarbonize the energy system. Here we use results from the 33rd Energy Modeling Forum study (EMF-33) to investigate projected international bioenergy trade for different integrated assessment models across several climate change mitigation scenarios. Results show that in scenarios with no climate policy, international bioenergy trade is likely to increase over time, and becomes even more important when climate targets are set. More stringent climate targets, however, do not necessarily imply greater bioenergy trade compared to weaker targets, as final energy demand may be reduced. However, the scaling up of bioenergy trade happens sooner and at a faster rate with increasing climate target stringency. Across models, for a scenario likely to achieve a 2 °C target, 10–45 EJ/year out of a total global bioenergy consumption of 72–214 EJ/year are expected to be traded across nine world regions by 2050. While this projection is greater than the present trade volumes of coal or natural gas, it remains below the present trade of crude oil. This growth in bioenergy trade largely replaces the trade in fossil fuels (especially oil) which is projected to decrease significantly over the twenty-first century. As climate change mitigation scenarios often show diversified energy systems, in which numerous world regions can act as bioenergy suppliers, the projections do not necessarily lead to energy security concerns. Nonetheless, rapid growth in the trade of bioenergy is projected in strict climate mitigation scenarios, raising questions about infrastructure, logistics, financing options, and global standards for bioenergy production and trade.

09 BIOMASS FUELS↗
DOE OSTI2022

Multiscale simulation of integrated energy system and electricity market interactions

Accelerating the deep decarbonization of the world's electric grids requires the coordination of complex energy systems and infrastructures across timescales from seconds to decades. Here, we present a new multiscale simulation framework that integrates process- and grid-centric modeling paradigms to better design, operate, and control integrated energy systems (IESs), which combine multiple technologies, in wholesale energy markets. Traditionally, IESs are analyzed with a process-centric paradigm such as levelized cost of electricity (LCOE) or annualized net revenue, ignoring important interactions with electricity markets. This framework explicitly models the complex interactions between an IES's bidding, scheduling, and control decisions and the energy market's clearing and settlement processes, while incorporating operational uncertainties. Through two case studies, we show the importance of understanding and quantifying complex resource-grid interactions. In case study 1, we demonstrate that optimized bidding from one resource shifts the profit distribution for all energy systems in the market. This result suggests new and more flexible IES technologies can disrupt the economics of all market participants, possibly leading to accelerated retirements of less flexible resources. Interestingly, the optimized bidding has little impact on grid-level aggregate statistics, such as total generation costs and renewable penetration rate. While aggregate modeling strategies may remain valid under some IES adoption scenarios for analysis focused on regional outcomes, direct comparisons of IES technologies at specific locations without considering these interactions may lead to misleading or incorrect conclusions. In case study 2, we consider the design and flexible operation of IESs that hybridize conventional generators with energy storage. Through a sensitivity analysis, we find that as the size of the storage system increases, the total number of start-ups for coal- and natural gas-based IESs reduced by 25% and 33.6%, and the total thermal generator ramping (i.e., mileage) reduced by 86.5% and 62.5%, respectively. This shows the primary benefit of storage may not be reduced operational costs (which do not change significantly) but fewer start-ups and less ramping, which may greatly simplify the design, operation, and control of carbon capture systems. The new modeling and optimization capabilities from this work enable the coupling of rigorous, dynamic process models with grid-level production cost models to quantitatively identify the nuanced interdependencies across these vast timescales that must be addressed to realize clean, safe, and secure energy production. Moreover, the proposed general multiscale simulation framework is applicable to all IES technologies and can be easily extended to consider other energy carriers (e.g., hydrogen, ammonia) and energy infrastructures (e.g., natural gas pipelines).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Climate and air pollution implications of potential energy infrastructure and policy measures in India

India is a rapidly developing economy with interrelated air quality, sustainable development, and climate change mitigation goals. There are unique challenges to achieving each of these goals as well as potential tradeoffs among them. This study examines the implications of possible future energy, climate, and air pollution control policies and measures in India through 2050. We take a scenario approach using the GCAM global energy-climate-land model combined with the Hector simple climate model and the TM5-FASST air quality source-receptor model to examine energy, climate and air quality outcomes. Reducing use of traditional biomass in buildings can reduce primary carbonaceous particulate emissions well below 2015 levels. However, policies that are more ambitious than current plans would likely be required to reduce SO 2 and NO x emissions well below 2015 levels. Among single policy cases considered, pricing of greenhouse gas (GHG) emissions and expansion of natural gas infrastructure have the largest impacts on overall energy system changes relative to the reference scenario. Ambitious air pollution control and GHG policies lead to the largest reductions in air pollution concentrations and radiative forcing, respectively. However, ambitious air pollution control and GHG policies differ in the extent to which they support or impede other policy objectives. Forcing increases due to reduced aerosols from ambitious air pollution policies can be mitigated, at least in part, by applying air pollution control and GHG policies together.

India↗
DOE OSTI2022

An optimization framework for the network design of advanced district thermal energy systems

In this work, a topology optimization framework for district thermal energy systems is presented. The framework seeks to address the questions, for a given district, "What is the best subset of buildings to connect to a district thermal energy system, and by what network should they be connected, to minimize life cycle cost?" A particle swarm optimization approach is validated to address the selection of the subset of buildings, and a graph theory-based heuristic is validated for selection of the network topology for any candidate subset of buildings. The framework is applied to a prototypical urban district for illustrative purposes. Additionally, modeling of prototypical districts revealed reductions in source energy use intensity for heating and cooling of 21-25% through the use of advanced district energy systems relative to code-compliant, building level systems. The framework identifies solutions with life cycle cost values 14% to 72% lower than that of base case scenarios based on conventional design approaches, depending on the base case scenario selected. Analysis of the search space indicates that topology optimization facilitates reductions in life cycle cost, source energy use intensity, and carbon emissions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Evaluating long-term model-based scenarios of the energy system

Energy-economic models are used to provide science-based decision support in a variety of contexts. Analyses using these tools often involve defining a “reference” scenario, which serves as a counterfactual against which alternative scenarios are compared. Evaluating scenarios, including reference scenarios, is critical for establishing the credibility of the analyses these models support. We propose a framework for evaluating energy system scenarios which consists of three parts – a qualitative storyline, quantitative metrics, and evaluation criteria. We apply this framework to the reference scenario for GCAM-USA, a version of the global human-Earth system model GCAM (Global Change Assessment Model) with state-level detail in the United States, focusing on the evolution of the electric power sector. We develop new visual analytic tools to facilitate the evaluation of model outcomes in 51 sub-national regions, and demonstrate how scenario performance can be tracked and compared across four quantifications of the GCAM-USA reference scenario.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Modeling nuclear energy’s future role in decarbonized energy systems

Increased attention has been focused on the potential role of nuclear energy in future electricity markets and energy systems as stakeholders target rapid and deep decarbonization and reductions in fossil fuel use. This paper examines models of electric sector planning and broader energy systems optimization to understand the prospective roles of nuclear energy and other technologies. In this perspective, we survey modeling challenges in this environment, illustrate opportunities to propagate best practices, and highlight insights from the deep decarbonization literature on the range of visions for nuclear energy's role. Nuclear energy deployment is highest with combinations of stringent emissions policies, nuclear cost reductions, and constraints on the deployment of other technologies, which underscores model dimensions related to these areas. New modeling capabilities are needed to adequately address emerging issues, including representing characteristics and applications of nuclear energy in systems models, and to ensure the relevance of models for policy and planning as deeper decarbonization is explored.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Search for a heavy composite Majorana neutrino in events with dilepton signatures from proton-proton collisions at s = 13 TeV

Results are presented of a search for a heavy Majorana neutrino Image 1 decaying into two same-flavor leptons ℓ (electrons or muons) and a quark-pair jet. A model is considered in which the Image 1 is an excited neutrino in a compositeness scenario. The analysis is performed using a sample of proton-proton collisions at s = 13 TeV recorded by the CMS experiment at the CERN LHC, corresponding to an integrated luminosity of 138 fb − 1 . The data are found to be in agreement with the standard model prediction. For the process in which the Image 1 is produced in association with a lepton, followed by the decay of the Image 1 to a same-flavor lepton and a quark pair, an upper limit at 95% confidence level on the product of the cross section and branching fraction is obtained as a function of the Image 1 mass Image 2 and the compositeness scale Λ. For this model the data exclude the existence of Image 3 (Image 4) for Image 2 below 6.0 (6.1) TeV, at the limit where Image 2 is equal to Λ. For Image 5, values of Λ less than 20 (23) TeV are excluded. These results represent a considerable improvement in sensitivity, covering a larger parameter space than previous searches in Image 6 collisions at 13 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Potential impacts of Fukushima nuclear wastewater discharge on nutrient supply and greenhouse gas emissions of food systems

Seafood plays a critical role in promoting a nutritious and climate-friendly food system but faces challenges from marine contamination that pose food safety risks. Here, to address these challenges, we developed a Marine Pollution-induced Food System Risk Assessment and Response (MP-FSRAR) model to assess the impact of consumer perceptions of marine pollution risk events on nutrient supply and greenhouse gas (GHG) emissions. Applying this model to the proposed Fukushima Nuclear Wastewater Discharge (FNWD) into the Pacific Ocean, we identified the potential variation in nutrient supply and GHG emissions resulting from changes in Chinese consumers' willingness to consume seafood under 12 scenarios. Our analysis revealed nutrient supply gaps in daily protein, minerals, vitamins, and fatty acids, ranging from 1.5 to 2.7 g/person, 2.5–4.5 mg/person, 5.6–10.3 mcg/person, and 0.08–0.14 g/person, respectively. Closing the protein gap in China would require an additional 3.2–15.8 billion kg yr -1 protein-rich foods, including aquatic, livestock, dairy, and pulses. Additional food supply would increase extra GHG emissions by 1–79 billion kg CO 2 e yr -1 , resulting in potential GHG emissions being transmitted to other countries through the trade chain. Furthermore, we found that the livestock-based food substitution pathway had 40 times higher GHG emissions than the plant-based one. Our MP-FSRAR model provides global stakeholders with new perspectives on the potential consequences of consumer perceptions of marine pollution risks and offers valuable insights for developing countermeasures to build a more resilient and low-carbon food system.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

First Assessment of Cloud‐Land Coupling in LASSO Large‐Eddy Simulations

Abstract To enhance our understanding of cloud simulations over land, this study provides the first assessment of coupling between cloud and land surface in the Large‐Eddy Simulation (LES) Atmospheric Radiation Measurement Symbiotic Simulation and Observation (LASSO) activity for the shallow convection scenario. The analysis of observation data reveals a diurnal cycle of cloud‐land coupling, which co‐varies with surface fluxes. However, coupled (or decoupled) cumulus clouds are inadequately simulated, manifesting as a too‐high (or low) occurrence frequency during the afternoon. This discrepancy is mirrored by the overestimated cloud liquid water path and cloud‐top height. These overestimations are linked to the overpredicted boundary‐layer development and the easier trigger of shallow convection misrepresented in LES runs. Our study underscores the need to improve the representations of boundary‐layer processes and cloud‐land interactions within LES to better simulate shallow clouds in the future.

58 GEOSCIENCES↗
DOE OSTI2022

Zonal shear layer collapse and the power scaling of the density limit: old L-H wine in new bottles

Edge shear layer collapse causes edge cooling and aggravates radiative effects. This paper details on the microscopic dynamics of the emergence of power (Q) scaling of density limit (DL) from the shear layer collapse transport bifurcation scenario. The analysis is based on a novel 4-field model, which evolves turbulence energy, zonal flow energy, temperature gradient and density, including the neoclassical screening of zonal flow response. Bifurcation analysis yields power scaling of critical density for shear layer collapse as $n_{crit}\sim Q^{1/3}$. The favorable Q scaling of the DL emerges from the fact that the shear layer strength increases with Q, thus preventing shear layer collapse. This in turn reduces particle transport and improves particle confinement. RMP induced ambient stochastic fields degrade the shear layer by inducing decoherence in the Reynolds stress. As a result the particle transport increases and particle confinement degrades. This leads to the emergence of unfavorable stochastic field intensity ($b_{st}^{2}$) scaling of the critical density as $n_{crit}\sim(1+b_{st}^{2})^{-5/3}$. All fields, including zonal flow shear, exhibit hysteresis when the power (Q) is ramped cyclically across the bifurcation point. The hysteresis is due to dynamical delay in bifurcation on account of critical slowing down. Furthermore, the dynamical hysteresis here is fundamentally different from the hysteresis associated with the existence of bi-stable states.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗