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DOE OSTI2025

Closing the Loop between In Situ Stress Complexity and EGS Fracture Complexity

We present an agent-guided approach to CAD geometry decomposition that automates hex/hybrid meshing with graph neural networks (GNNs) to accelerate next-generation ModSim workflows. Our end-to-end pipeline (i) reduces 3D boundary-representation (B-Rep) models to a 2D chordal axis skeleton (CAT) and then to a 1D bipartite graph of surface and curve nodes, (ii) assigns per node labels as Cubit® WebCut actions, (iii) trains a multi-action GNN under supervised learning, and (iv) predicts five surface-node and three curve-node actions on out-of-distribution test geometries. Each graph node carries geometric, topological, and meshing attributes drawn from the B-Rep “skin” and CAT “skeleton,” with two-way mappings across 3D↔2D↔1D representations to maintain traceability back to 3D CAD. The supervised learning model exhibits stable convergence of the binary cross-entropy loss and achieves 98.7% accuracy on unseen lattice models. To operationalize decision-making, we rank predicted commands by geometric significance and prototyped the agent-guided workflow through the Cubit® Meshing PowerTool GUI. As a stretch goal, we explore reinforcement learning (RL) to reduce or remove label requirements and to learn policies for action sequences that maximize total reward (e.g., size of hex-meshable regions and resulting hex mesh quality). When all-hex meshing is not feasible, the agent assists in producing hybrid meshes—prioritizing hex in critical regions and transitioning to tetrahedral elements (tets) elsewhere—maintaining fidelity while ensuring robustness. The overarching objective is to replace manual, heuristics-based decomposition with data-driven, reproducible automation, cutting meshing turnaround time by orders of magnitude. We anticipate direct impact on simulation workflows through intelligent, scalable decomposition of complex CAD models into hex-meshable subdomains.

42 ENGINEERING↗

DOE OSTI2020

Asset Management: Beyond 2020

This Asset Management Beyond 2020 document provides: (1) an introduction to asset management (AM) and an asset management system (AMS), along with insights to next steps, (2) an overview of the International Standards Organization (ISO) 55000 series documents, (3) an overview of the ISO 55001 gap analysis of Center 4700/4800 ("Facilities") organizations at Sandia National Laboratories, hereafter referred to as Sandia, with observations, gaps, and gap closure recommendations, and (4) an asset management architecture (AMA) recommendation aligned with the ISO 55001. The AMS and the AM are different but related. ISO 55000 cites AMS as "a management system for AM" to "direct, coordinate, and control AM activities." ISO 55000 cites AM as translating "the organizational objectives into technical and financial decisions, plans and activities."1 Essentially, the AMS begins with all levels of leadership to enable a structured and consistent approach to AM culminating in lifecycle asset management excellence.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Marginal Damage of Methane Emissions: Ozone Impacts on Agriculture

Methane directly contributes to air pollution, as an ozone precursor, and to climate change, generating physical and economic damages to different systems, namely agriculture, vegetation, energy, human health, or biodiversity. The methane-related damages to climate, measured as the Social Cost of Methane, and to human health have been analyzed by different studies and considered by government rulemaking in the last decades, but the ozone-related damages to crop revenues associated to methane emissions have not been incorporated to policy agenda. Using a combination of the Global Change Analysis Model and the TM5-FASST Scenario Screening Tool, we estimate that global marginal agricultural damages range from ~ 423 to 556 $2010/t-CH 4 , of which 98 $2010/t-CH 4 occur in the USA, which is the most affected region due to its role as a major crop producer, followed by China, EU-15, and India. These damages would represent 39–59% of the climate damages and 28–64% of the human health damages associated with methane emissions by previous studies. The marginal damages to crop revenues calculated in this study complement the damages from methane to climate and human health, and provides valuable information to be considered in future cost-benefits analyses.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Halfway to Zero: Progress towards a Carbon-Free Power Sector

Sharply reducing carbon emissions is imperative to prevent the worst effects of climate change. Yet even in the power sector—often viewed as the lynchpin to economy-wide decarbonization, and where low-carbon solutions are increasingly plentiful and cost-effective—the pace and scale of the required transformation can be daunting. A review of historical trends, however, shows the progress the power sector has already made in reducing emissions. Fifteen years ago, many business-as-usual projections anticipated that annual carbon dioxide (CO 2 ) emissions from power supply in the United States would reach 3,000 million metric tons (MMT) in 2020. In fact, direct power-sector CO 2 emissions in 2020 were 1,450 MMT—roughly 50% below the earlier projections. By this metric, in only 15 years the country’s power sector has gone halfway to zero emissions. Other metrics also evolved differently than projected: total consumer electricity costs (i.e., bills) were 18% lower; costs to human health and the climate were 92% and 52% lower, respectively; and the number of jobs in electricity generation was 29% higher. Economic, technical, and policy factors contributed to this success, including sectoral changes, energy efficiency, wind and solar, continued operations of the nuclear fleet, and coal-to-gas fuel switching. This historical record demonstrates the ability of technological and policy changes to set the power sector on a dramatically different emissions trajectory. Past success, however, does not trivialize the challenges that remain for further decarbonization in the power sector and beyond. Nor does it offer a specific roadmap for how best to achieve additional power-sector emissions reductions. Numerous challenges confront a zero-emissions pathway, and future strategies will likely differ from those of the past. Many recent studies have assessed how to make further progress in decarbonizing the power sector on the pathway to decarbonizing the economy as a whole. We summarize the core results of those studies, but the primary goal of this report is to highlight the progress that has already been made in reducing power-sector emissions. As the country maps out a plan for further decarbonization, experience from the past 15 years offers two central lessons. First, policy and technology advancement are imperative to achieving significant emissions reductions. Second, our ability to predict the future is limited, and so it will be crucial to adapt as we gain policy experience and as technologies advance in unexpected ways.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Enabling Principles for Dual Participation by Energy Storage as a Transmission and Market Asset

Because the electric transmission system is sized to meet the highest levels of customer demand, much of its designed capacity goes unused during average operating conditions. As a uniquely flexible and scalable asset capable of providing multiple grid services, energy storage can be deployed to support the transmission system and then also provide services to energy markets when not needed for transmission. This paper reviews the technical barriers in transmission planning practices and energy market design that prevent the realization of dual-use energy storage projects that provide both regulated transmission and competitive market services. Current practices create barriers against the identification of energy storage in the transmission planning process and against the participation of a regulated transmission asset in competitive energy markets. A review of regional transmission plans identifies best practices for including energy storage in the planning process by directing planners to proactively identify such projects or by providing clear mechanisms for stakeholders to propose them. Creating a market participation model for dual-use energy storage assets requires establishing when an asset will be allowed to participate in the market, how it will participate in the market, and where it will recover its costs. In answering these questions, key principles must be satisfied, such as prioritizing reliability, incrementally building on existing market design, and balancing competing objectives. Several policy options exist for satisfying those principles, giving grid operators and stakeholders significant flexibility in developing a dual-use participation model in accordance with regional policies and conditions. By objectively framing the issue and identifying policy options, this paper may inform subsequent proceedings on dual-use energy storage and be a resource to regional market operators, utilities, developers, regulators, policymakers, and other stakeholders as they collectively work on this complex issue.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Reducing Economy-Wide Greenhouse Gas Emissions with Electrofuels and Biofuels as the Grid Decarbonizes

Biofuels and electrofuels have the potential to complement electrification in speeding greenhouse gas emissions reductions, especially in hard-to-decarbonize sectors. Concentrated waste CO 2 streams that can be used as a feedstock for electrofuels, however, may become less available as the share of renewable electricity increases and industries undergo decarbonization. Here, we conduct an analysis with detailed treatment of biofuels and electrofuels to probe their role in decarbonizing multiple industrial sectors and transportation. We examine how the changing availability of CO 2 could affect electrofuel production and the potential role of direct air capture in stabilizing the supply of CO 2 . The results indicate that biofuels could fulfill 12% of the total final energy demand across all U.S. sectors in 2050. Using seven industrial source points of CO 2 available in 2050, 15,388 PJ of electrofuels could be produced, which amounts to 25% of the total final energy demand. This result holds even upon decarbonization that requires direct air capture to boost the CO 2 supply. Biofuels and e-fuels have the potential to reduce economy-wide GHG emissions by 7 and 21% beyond electrification alone. However, electricity consumption and land use grow markedly with decarbonization at scale.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Examining Rail Transportation Route of Crude Oil in the United States Using Crowdsourced Social Media Data

Safety issues associated with transporting crude oil by rail have been a concern since the boom of the U.S. domestic shale oil production in 2012. During the last decade, over 300 crude-oil-by-rail incidents have occurred in the United States. Some of them have caused adverse consequences including fire and hazardous materials leakage. However, only limited information on crude-on-rail routes and their associated risks is available to the public. To this end, this study proposed an unconventional way to reconstruct crude-on-rail routes using geotagged photos harvested from the Flickr website. The proposed method linked the geotagged photos of crude oil trains posted online with national railway networks to identify potential railway segments that those crude oil trains were traveling on. Here, a shortest path-based method was applied to infer the complete crude-on-rail routes, by utilizing the confirmed railway segments as well as their directional information. Validation of the inferred routes was performed using a public map and official crude oil incident data. The results suggested that the inferred routes based on geotagged photos had high coverage, with approximately 96% of the documented crude oil incidents aligned with the reconstructed crude-on-rail network. The inferred crude oil train routes were found to pass through several metropolitan areas of high population density, who were exposed to potential risk. These findings could improve situational awareness for policy makers and transportation planners. In addition, with the inferred routes, this study has established a good foundation for future crude oil train risk-analyses along the rail route.

42 ENGINEERING↗

DOE OSTI2026

The Baltimore Community Weather Station Network: Filling the Urban Measurement Desert

Quantification and understanding of how heat, rainfall, and air quality vary within cities are needed to identify the area with the worst conditions, develop solutions to extreme weather, and assess the impact of proposed policies. However, neighborhood-level variability is not well quantified because there are few environmental measurement stations within cities. In Baltimore City, a community-based network of weather stations to address this issue has been developed through a partnership between universities, state agencies, and Baltimore residents. The weather stations are hosted by community partners, and the data collected are enabling the mapping of urban weather across the city and the testing of models and proposed mitigation strategies. In addition, the network provides direct community involvement, with resulting benefits of increased community engagement, education, and empowerment. Researchers have an opportunity to democratize the scientific process and ensure that local knowledge and lived experiences of city residents inform future decision-making. The approach could be used as a model for other cities that apply similar monitoring instruments for other environmental exposures.

community↗

DOE OSTI2021

Effect of specific non-pharmaceutical intervention policies on SARS-CoV-2 transmission in the counties of the United States

Non-pharmaceutical interventions (NPIs) remain the only widely available tool for controlling the ongoing SARS-CoV-2 pandemic. We estimated weekly values of the effective basic reproductive number (R eff ) using a mechanistic metapopulation model and associated these with county-level characteristics and NPIs in the United States (US). Interventions that included school and leisure activities closure and nursing home visiting bans were all associated with a median R eff below 1 when combined with either stay at home orders (median R eff 0.97, 95% confidence interval (CI) 0.58–1.39) or face masks (median R eff 0.97, 95% CI 0.58–1.39). While direct causal effects of interventions remain unclear, our results suggest that relaxation of some NPIs will need to be counterbalanced by continuation and/or implementation of others.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Disruptive Photovoltaic Technologies Can Accelerate Global Decarbonization

This contribution explores PV manufacturing capacity expansion trajectories needed to achieve the goal of global decarbonization assuming that investors make financially rational decisions avoiding stranded production assets while still effectively exploiting experience curve benefits in both manufacturing process and product design. Substantial production cost savings and timely decarbonization risk mitigation could accrue by adoption and scaling of high efficiency multijunction device architectures and thin film direct bandgap semiconductor technologies that provide lower manufacturing capital intensity. We demonstrate that there is a $1-2 trillion market opportunity for such disruptive technologies while also providing hundreds of billions of dollars of cost savings to reach total decarbonization.

decarbonization↗

DOE OSTI2020

Improving PCM Waste Management Through New Approaches to Screening for LLW Treatment and Disposal - 20145

A major step forward in the management of Plutonium Contaminated Material (PCM) Waste has been taken at the Sellafield site with the introduction of new capabilities to enable wastes previously conservatively designated as PCM Intermediate Level Waste (ILW) to be re-classified for treatment as Low Level Waste (LLW). The Sellafield site, located in the North West of England, within the United Kingdom (UK), has operated plutonium processing plants and waste facilities for almost 70 years. During this time management of the raw PCM waste produced has presented a variety of challenges. The waste is currently processed by high force waste compaction in the Waste Treatment Complex (WTC). The WTC converts 200 litre drums of raw PCM waste into a compacted, grout encapsulated monolith form within stainless steel containment, ready for emplacement within the UK's Geological Disposal Facility (GDF) when it becomes available. To help progress some of the wastes waiting for treatment, recent improvements have been made with the introduction of new waste assay instrumentation which enables the identification of a 'candidate' waste potentially suitable for disposal via the LLW treatment route. Opening a new LLW route for previously designated PCM has been a major advance in PCM waste management policy. It has required a range of technical assessment arrangements to be developed, tested and commissioned and involved the engagement of a wide range of stakeholders. In particular, very detailed technical analysis methods have been developed to ensure that there is a robust and conservative approach to the final sentencing of waste. Following completion of commissioning tests, the first 86 m{sup 3} of previously designated PCM waste was successfully treated through the LLW route and consigned to LLW disposal in June 2019. The direct benefit of sentencing waste to the correct waste route (LLW) is the significant cost savings across the complete range of waste management activities. This work is also strategically important for demonstrating to a range of stakeholders including workforce and regulators, that waste previously designated as PCM can be re-classified in a systematic and justifiable way without increasing risk to personnel or the wider environment. By ensuring that waste is being managed appropriately it will be possible to carry out more remediation work safely, in less time, and at a lower cost. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Sampling Size Optimization for Bioburden Density Estimation in Planetary Protection

Planetary protection (PP) is a discipline that focuses on minimizing the biological contamination of spacecraft to ensure compliance with international policy. Precise estimation of bioburden - the total number of microbes in or on spacecraft hardware – and the bioburden density are of utmost importance for PP. Such estimation is the way concordance with requirements is demonstrated, and it is critical for quantifying the potential risk of inadvertently contaminating other planetary bodies. Although a suite of molecular techniques have been used to thoroughly characterize and profile the microbiome of various cleanroom environments and spacecraft, the gold standard remains the physical enumeration of microbes via culturing of samples directly taken from spacecraft and associated surfaces. However, due to technical, budgetary, and programmatic constraints, only a manageable portion (around 10%) of the entire spacecraft surface is directly sampled with cotton swabs or wipes. To generate the bioburden current best estimate (CBE) for components not directly verifiable, the accepted approach is to apply a NASA-defined bioburden estimate based on the components’ manufacturing or assembly environment. This approach utilizes a prespecified bioburden density estimation that applies a maximum value across the total surface area of the specified component. For hardware components that underwent similar assembly processes, an implied bioburden is adopted for all components, based on a direct verification of a representative component within the same lot. Once all components have a CBE, the bioburden estimates are generated. In previous publication [ 1], we have shown that statistical risks quantifying the accuracy of the estimates for sampled, prespecified, and implied components can be derived and ranked. For mean squared error (MSE) function, the risks are available analytically and hence a cost function can be obtained to optimize the risks with respect to the sampling area and sampling cost. Since the sampling area and sampling cost are two complimentary variables, their sum will have a well-defined minimum. This paper presents the multivariate optimization of the integrated risk of an empirical Bayes estimator to determine the optimal sampling schedule for a given number of components. It is assumed that given a number of components, N, the bioburden density for each component can either be sampled, implied, or prespecified. The multivariate optimization searches through different options to sample, imply or prespecify the bioburden density for a component, and account for the component’s surface area and cost of sampling. The idea of the optimization is based on the observation that the statistical risk of using an estimator is a monotonically decreasing function of the sampled area. The larger the sampled area, the lower the risk of using the estimator as the estimator becomes more and more accurate as the sampling area increases. On the other hand, the cost of sampling is monotonically increasing as the sampled surface grows. This makes the risk and total cost of sampling complimentary variables which can be counterbalanced to achieve an optimal overall value with respect to the sampled surface. In this paper, the integrated risk has been used to quantify the accuracy of the estimator. This risk has been selected because it depends on neither the true value of the parameter nor on the collected data. The cost of each sample was also available to obtain the total cost of sampling of N components. The paper will present the results based on computer-simulated data as well as the data collected during the InSight mission. The computer-simulated data have N components with randomly generated total areas and each component assigned to one of the three categories according to the method of estimating of bioburden density: sampled, implied, or prespecified. The cost of sampling is also available. The cost of sampling is estimated based on a cost model provided by the planetary protection group at JPL. For this paper, the overall cost was assumed to be a linear function of exposure. The optimization process finds the allocation of the components to the three categories that minimizes the tradeoff between integrated risk and total cost. For the InSight data, a set of components is selected representing all three categories, and optimization is performed to determine if the performed allocation was optimal or if a better allocation could have been obtained. To the best of our knowledge, this work is the first attempt not only perform an accurate estimation of bioburden density but also do it in an optimal way.

97 - MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Market Pricing and Settlements Analysis Considering Capacity Sharing and Reserve Substitutions of Operating Reserve Products

Electricity market pricing and settlement are the key signals for real-time dispatch and long-term investment decisions. Regional transmission operators (RTOs) in the U.S. adopt uniform pricing scheme, which is based on the marginal costs of supplying an incremental MW of electric services. The marginal cost of an electric service is highly dependent on the constraints in the pricing models of RTOs. A slight difference in constraint modeling of pricing model on energy and ancillary services could result in drastically different market clearing prices (MCPs), cleared reserve quantities, and associated revenue. RTOs in the U.S. have various market designs and assumptions in ancillary services modeling in capacity sharing and reserve substitutes. This paper examines four combination models of capacity sharing and reserve substitutes and analyzes the associated market implications. The numerical results present that 1) cascading reserve requirements have direct impact on reserve pricing schemes 2) both cascading reserve requirements and sharing capacity have significant impact on reserve MCPs and locational marginal prices, and thus result in drastically different reserve revenue, energy revenue, generation cost, and generation profit.

ancillary services↗

DOE OSTI2020

Cross-Border Electricity Trading and Renewable Energy Zones

India's national renewable energy zones for wind power and solar photovoltaics (PV) could become regional green power resources if South Asian countries liberalize their rules for cross-border energy trading (CBET). Similarly, Nepal's wealth of hydropower could be more valuable to Nepal and its neighbors with greater market integration. These are the findings of a study by the U.S. National Renewable Energy Laboratory (NREL) that tested trading scenarios for wind power, solar power, and hydropower among Bangladesh, India, Nepal, and Sri Lanka. The NREL study found that wheeling power through India's interstate transmission system (ISTS) could be just as efficient operationally as building new high-voltage direct current (HVDC) lines from the renewable energy zones directly to the importing country. This means that CBET integration could substitute for new long-distance HVDC transmission - which could cost billions of dollars - while delivering to all participating countries the same benefits for renewable energy development and decarbonization.

14 SOLAR ENERGY↗

DOE OSTI2021

Integrating Cambium Marginal Costs into Electric Sector Decisions: Opportunities to Integrate Cambium Marginal Cost Data into Berkeley Lab Analysis and Technical Assistance

NREL’s Cambium tool generates forward-looking simulations of marginal wholesale electricity costs associated with NREL’s Standard Scenarios. The scenarios include growing shares of variable renewable energy (VRE, i.e. wind and solar), among other power sector assumptions, between 2018 and 2050. The tool’s primary output—hourly costs at more than 130 balancing areas—could serve as public and transparent data source that supports electric-sector decision-making processes across the U.S. Berkeley Lab conducts a large range of analyses that use historical and forward-looking wholesale electricity prices to inform electric-sector decisions. In this report, Berkeley Lab uses its expertise to evaluate the Cambium cost data. We compare Cambium data with historical wholesale prices for the year 2018 and other modeled prices for the year 2030. We then present eight case studies in which Berkeley Lab researchers use Cambium data to replicate previous analyses based on other price datasets. We describe where primary findings and underlying key price dynamics align or differ, and highlight possible novel insights from the Cambium data. Finally, we qualitatively evaluate the suitability of Cambium costs in ten additional Berkeley Lab studies, though a direct comparison with alternative price data was not feasible at this time. The goal is to inform how electric-sector decision-makers and DOE program offices may be able to use this cohesive dataset, and to highlight what improvements to Cambium may make it even more useful.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Distributed clean energy opportunities for US oil refinery operations

The oil and gas industry is increasingly seeking operational improvements to reduce costs and emissions while improving resilience. This study describes techno-economic analysis of opportunities for distributed energy resources that could be integrated to support oil and gas companies’ economic, environmental, and energy resiliency goals. Specifically, the analysis evaluates solar photovoltaics, wind turbines, battery energy storage, landfill gas, biomass, municipal solid waste-to-energy, solar steam for process heat, combined heat and power, and electrolyzers for hydrogen production at two hypothetical refineries, one located in Louisiana and the other in southern California. These technologies could reduce the sites’ consumption of grid electricity and/or natural gas and thus can help reduce emissions. This study employs the ReOPT tool and System Advisor Model to evaluate the techno-economic potential for clean energy technologies to support refineries in achieving energy goals, including energy cost savings, resiliency, and emissions reductions. Results indicate that the associated costs of emissions reductions via several distributed clean energy technologies are competitive with other emissions reduction strategies such as energy efficiency, reducing flaring, direct carbon capture and sequestration, and markets under certain conditions. There are also cost beneficial opportunities for the use of renewable energy for refining, especially for resilience, depending on local conditions such as resources and utility costs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Towards Prospective LCA Using Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) Framework for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM(Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

emissions↗

DOE OSTI2020

Simulation of Cross-Border Renewable Energy Trading in South Asia [Slides]

13 HYDRO ENERGY↗