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At least 703 records · Page 39

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DOE OSTI2022

Generative Design for Resilience of Interdependent Network Systems

Abstract Interconnected complex systems usually undergo disruptions due to internal uncertainties and external negative impacts such as those caused by harsh operating environments or regional natural disaster events. To maintain the operation of interconnected network systems under both internal and external challenges, design for resilience research has been conducted from both enhancing the reliability of the system through better designs and improving the failure recovery capabilities. As for enhancing the designs, challenges have arisen for designing a robust system due to the increasing scale of modern systems and the complicated underlying physical constraints. To tackle these challenges and design a resilient system efficiently, this study presents a generative design method that utilizes graph learning algorithms. The generative design framework contains a performance estimator and a candidate design generator. The generator can intelligently mine good properties from existing systems and output new designs that meet predefined performance criteria while the estimator can efficiently predict the performance of the generated design for a fast iterative learning process. Case studies results based on synthetic supply chain networks and power systems from the IEEE dataset have illustrated the applicability of the developed method for designing resilient interdependent network systems.

Engineering↗

DOE OSTI2024

Status Quo and Gap Analysis of Heliostat Field Deployment Processes for Concentrating Solar Tower Plants

In this study, deployment of the solar field of a concentrating solar power plant is one of many factors that are integral to the success of a project. Knowledge transfer from outside the industry is limited due to the unique nature of heliostats, which redirect sunlight to a receiver with high precision while maintaining a high level of reflectivity. Moreover, learning from project to project can be limited due to the site-specific nature of projects, as the market includes several developers, each with their own unique design. In this paper, we discuss the state of the art in heliostat field deployment. We cover all the key aspects of deployment from project assessment to a fully functioning system, which include site selection, layout development, supply chain, assembly, site preparation and construction, calibration, and operations and maintenance. We then perform a gap analysis on field deployment and recommend priorities for future research.

14 SOLAR ENERGY↗

DOE OSTI2024

A Simulated Evaluation of Powder Flowability Through a Partially Obstructed Consumable in Blown Powder Directed Energy Deposition Systems

Abstract In the interest of continued industrialization of metal additive manufacturing in modern production environments, cost is often referenced as a primary deterrent to new adopters. Conventional economic models for additive systems, processes, and supply chains often focus on specific process applications with little generalizability, or they neglect significant costs associated with production such as machine maintenance and consumable part replacement. Compounding the latter issue are substantial knowledge gaps in consumable part wear characterization for additive and other convergent manufacturing systems. In coaxial blown powder directed energy deposition systems, gas atomized metal powder is wasted during material deposition at a rate that is partly dependent on present wear phenomena in a consumable nozzle housed in the cladding head assembly. The price and lead time required to replace the nozzle incentivizes its reuse even when visibly worn. Often this initiates a process quality decline in the form of underbuilt geometry and internal defects due to losses in powder catchment efficiency. While depositing H13 steel using a hybrid manufacturing machine tool equipped with such a deposition system, a unique partial clog with a bridge-like structure formed at the consumable nozzle exit when supporting argon gas flows failed mid-process. To further understand coaxial multi-phase powder flow in the event of support gas failure, a computational fluid dynamics simulation is tailored to relevant process parameters, H13 powder material profile, and machine operator observations collected after the incident. The resulting differences in powder flow compared to control gas flow parameters is presented and discussed. The powder flowability and performance of the clogged nozzle is then assessed by using an optical profilometer to extract the profile of the clog and recreate the clog geometry within the simulation environment. In past work this simulation has been experimentally validated for a 316L steel powder material profile and used specifically for analyzing powder stream geometry and catchment efficiency. After the initial powder flow characterization, the clog is removed, and the nozzle is reprofiled. After removing the obstructing clog, the newly unobstructed nozzle geometry, the original off the shelf nozzle geometry, and additional nozzle profiles exploring different consumable refurbishment strategies are reevaluated in the simulation. Powder catchment efficiency for all variant nozzle geometries and relevant flow variables are compared and discussed, along with potential mitigation strategies for optimizing powder flowability with worn consumables. This work expands on the known morphology of blown powder obstructions and wear defects present in consumable coaxial nozzles while discussing pragmatic simulation driven responses to unanticipated subsystem failure in hybrid manufacturing machining platforms.

DeWitte, Lisa↗

DOE OSTI2023

Cobalt mineralogy at the Iron Creek deposit, Idaho cobalt belt, USA: Implications for domestic critical mineral production

Current U.S. policies aim to establish domestic supply chains of critical minerals for the energy transition. The Iron Creek deposit in the Idaho cobalt belt (ICB) is one of the most promising cobalt (Co) targets. Our case study illustrates the importance of mineralogy in strategic evaluations of critical mineral potential. Most of the Co at Iron Creek occurs as Fe substitution in pyrite, with lattice-bound and inclusion-hosted Ag, As, Bi, Ni, Pb, Se, Te ± trace Au and Sb. Cobalt also occurs in minor cattierite-vaesite. The Co minerals are intergrown with Co-poor chalcopyrite hosting Cu ± minor In and Zn. Worldwide, most Co is recovered from deposits mineralogically distinct from the ICB, and the United States currently lacks infrastructure to recover this Co and its associated metals. ICB ore minerals could be processed by autoclave, roaster, smelter, bioleach, or heap leach. Recovery of the Ag, As, Au, Bi, In, Pb, Se, Te, and Zn would be costly by autoclave, and construction of a custom smelter for ICB ores is likely uneconomic, so these elements would become waste irrespective of criticality. The Co-Fe and Co-As sulfide minerals are most suitable for Co and Ni recovery by a hydrometallurgical autoclave process, with potential pretreatment of cobaltiferous pyrite/arsenopyrite in an inert-atmosphere roaster, in new domestic or anticipated international facilities. The ICB is the second largest known Co resource in the United States. Consideration of ore mineralogy in the ICB is essential in strategies for domestic production.

58 GEOSCIENCES↗

DOE OSTI2023

Review—Earth-Abundant, Mn-Rich Cathodes for Vehicle Applications and Beyond: Overview of Critical Barriers

Broadening the portfolio of cathode active materials for Li-ion battery applications is now more important than ever. Recent focus on enabling diversity and security in supply chains, as well as concerns over sustainability of a massively growing energy storage market, have put emphasis on enabling more Earth-abundant cathode materials as an attractive strategy. With respect to relatively near-term options, manganese-based cathodes are particularly interesting. In this work, we discuss some of the challenges associated with advancing the development of manganese-based oxides and, in particular, those that take advantage of complex local structures and/or over-lithiated compositions. Discussion centers on the representative, lithium- and manganese-rich class of cathodes and considerations to future development are given that range from the atomic-scale to the electrode level.

25 ENERGY STORAGE↗

DOE OSTI2024

Application of the Multi-Species, Multi-Reaction Model to Coal-Derived Graphite for Lithium-Ion Batteries

Graphite is a critical material used as the negative electrode in lithium-ion batteries. Both natural and synthetic graphites are utilized, with the latter obtained from a range of carbon raw materials. In this paper, efforts to synthesize graphite from coal as a domestic feedstock for synthetic graphite are reported. Domestic coal-derived graphite could address national security and energy issues by standing up domestic supply chains for battery critical materials. The performance in lithium-ion coin cells of this coal derived graphite is compared to a commercial battery-grade graphite. For the first time, a multi-species, multi-reaction (MSMR) modeling technique is applied to synthetic graphite derived from coal. Key thermodynamic, transport, and kinetic parameters are obtained for the coal derived graphite and compared to the same parameters for commercial battery-grade graphite. Modeling of synthetic graphites will allow for virtual evaluation of these materials toward production of domestically sourced graphite.

Paul, Abigail (ORCID:0000000172892069)↗

DOE OSTI2023

Water Network Tool for Resilience (WNTR)

The Water Network Tool for Resilience (WNTR) is an open source Python package designed to simulate and analyze resilience of water distribution networks. The United States Environmental Protection Agency, in partnership with Sandia National Laboratories, developed WNTR to integrate critical aspects of resilience modeling for water distribution networks into a single software framework. The software includes capability to: • Generate water network models • Modify network structure and operations • Assign fragility and survival curves to network components • Model disruptive events such as power outages, earthquakes, fires, pipe breaks, and contamination incidents • Model response and repair strategies • Simulate hydraulics and water quality • Evaluate resilience using a wide range of metrics • Integrate dependency with other critical infrastructure and supply chains • Analyze results and generate graphics SAND2019-450 M

Villa, Daniel↗

DOE OSTI2020

RELOG

RELOG is a supply chain optimization package focusing on reverse logistics and reverse manufacturing. For example,the package can be used to determine where to build recycling plants, what sizes should they have and which customers should be served by which plants. The package supports customized reverse logistics pipelines, with multiple types of plants, multiple types of product and multiple time periods.

ILOEJE, CHUKWUNWIKE↗

DOE OSTI2022

PV DMFA [SWR-21-105]

The Photovoltaic Dynamic Material Flow Assessment (PV DMFA) model (also referred to here as “The model”) is a computational framework written in Python based on utility-scale PV electricity generation to quantify time-series stocks and flows of PV materials primarily in crystalline silicon PV technologies. The model evaluates cradle-to-cradle life cycle of utility-scale solar PV systems in the United States in the period 2000-2100. PV DMFA serves as a sustainability analysis tool to assess the impacts of different material circularity practices (i.e., reduce, reuse/refurbish, remanufacture, and recycle), PV module design shifts and sensitivity of material processing and technology related parameters to material installations, waste creation and raw material depletion in PV material supply chains. This tool enables advanced planning for future material needs and informs sustainable pathways for PV material management in the circular economy. This tool could be helpful to a wide range of stakeholders; Particularly, researchers and manufacturers looking for technoeconomic and/or environmental life cycle analysis (LCA) feedback for renewable energy (RE) systems.

Khalifa, SherifA.↗

DOE OSTI2022

Storm DEPART(Damage Estimate Prediction And Recovery Tool)

Damage prediction, materials needed, and resource allocation modeling capability in order to support pre-incident planning and preparation by predicting damage to the power generation capacity, transmission grids, distribution networks, and communications assets. The capabilities will be developed by multiple factors to include wind bands, storm surge, and flooding forecasts to participant’s assets which will result in a report of predicted damages. Additional factors to include available participants infrastructure data to include class, age, construction, location, wind rating, and additional information not in the public domain. Based on predicted damages, the output will be a bill of materials (BOM) to support short-term recovery operations. The extensiveness and level of detail for this BOM will depend on the replacement configuration specifications provided for each individual participant asset. Any limiting factors for the model will be applied related supply chain and resource constraints.

Klett, Mary↗

DOE OSTI2025

OPTICHEM (OPTimizer for Industrial CHEMical pathways) [SWR-25-70]

Using alternative feedstocks such as biomass and waste could help the chemical sector address growing challenges from supply chain disruptions. This project aims to identify optimal combinations of chemical production pathways that achieve user-defined priorities within set resource constraints. This project contains two main Python modules that work together to perform multi-objective optimization of feedstock usage and post-optimization analysis. The outputs from both modules (e.g., CSV files, PDF diagrams, HTML reports, and pickle files) are automatically saved in dedicated output folders. The folder names include key parameters such as the optimization metric, target year, and whether 2030 results are fixed.

Ghosh, Tapajyoti [National Renewable Energy Labora↗

DOE OSTI2026

Dynamic Disruption Resilience in Intermodal Transport Networks: Integrating Flow Weighting and Centrality Measures

Resilient intermodal freight networks are vital for sustaining supply chains amid increasing threats from natural hazards and cyberattacks. Transportation resilience has been widely studied; understanding how random and targeted disruptions affect structural connectivity and functional performance remains a key challenge. To address this, this study evaluates the robustness of the US intermodal freight network, which consists of rail and water modes, using a simulation-based framework that integrates graph-theoretic metrics with flow-weighted centrality measures. Disruption scenarios are examined, including random failures as well as targeted node and edge removals based on static and dynamically updated degree and betweenness centrality. To reflect more realistic conditions, flow-weighted degree centralities (WDC) and partial node degradation are considered. Two resilience indicators are used: (1) the size of the giant connected component to measure structural connectivity; and (2) flow-weighted network efficiency (NE) to assess freight mobility under disruption. The results show that progressively degrading nodes ranked by WDC to 60% of their original functionality causes a sharper decline in normalized NE, for up to approximately 45 affected nodes, than complete failure (100% loss of functionality) applied to nodes targeted by weighted betweenness centrality or selected at random. This highlights how partial degradation of high-tonnage hubs can produce disproportionately large functional losses. The findings emphasize the need for resilience strategies that go beyond network topology to incorporate freight flow dynamics.

42 ENGINEERING↗

DOE OSTI2026

Modeling and Calibration of Supplier Selection Problem in Freight Agent-Based Simulations

Freight transportation modeling often struggles with data limitations, especially in accurately representing complex supplier selection processes and their impact on network flows. This research addresses this critical gap by developing a large-scale, calibrated agent-based model for supplier selection, complemented by a probabilistic heuristic for international shipments. Our approach integrates trade relationships between industry sectors, transportation costs, and a supplier-rating model adapted from existing literature. The model’s core objective is to minimize the discrepancy between modeled and observed commodity flows while ensuring a close match to regional shipping distance distributions. Implemented and tested across four major U.S. metropolitan areas—Atlanta, Chicago, Dallas–Fort Worth, and Los Angeles—the model demonstrates high fidelity in replicating observed freight patterns. Key findings reveal consistent alignment with national shipping distance trends and highlight significant spatial variations in commodity trade assignments and demand across the study regions. This behaviorally informed and transport-sensitive framework is designed to approximate real-world decision making, providing a robust tool for policymakers and planners to evaluate targeted interventions, assess infrastructure investments, and enhance supply chain resilience in the face of disruptions.

Ismael, Abdelrahman (ORCID:0000000303712110)↗

DOE OSTI2020

Research note: LED lighting – A global enterprise

There is considerable focus on technology manufacturing locations and the value in funding innovation when upstream products are not manufactured within a domestic economy. Light-emitting diodes (LEDs) are such an upstream product. Here, we evaluate the value added along the supply chain of luminaires, a product that utilizes LEDs, using bottom-up cost modelling. Coupling the results with analysis of shipping cost and time, this analysis examines how advances in LEDs can incentivize LED luminaire adoption leading to the potential for significant domestic manufacturing effects even if the upstream products are produced in other economies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Dynamic life-cycle carbon analysis for fast pyrolysis biofuel produced from pine residues: implications of carbon temporal effects

Abstract Background Woody biomass has been considered as a promising feedstock for biofuel production via thermochemical conversion technologies such as fast pyrolysis. Extensive Life Cycle Assessment studies have been completed to evaluate the carbon intensity of woody biomass-derived biofuels via fast pyrolysis. However, most studies assumed that woody biomass such as forest residues is a carbon–neutral feedstock like annual crops, despite a distinctive timeframe it takes to grow woody biomass. Besides, few studies have investigated the impacts of forest dynamics and the temporal effects of carbon on the overall carbon intensity of woody-derived biofuels. This study addressed such gaps by developing a life-cycle carbon analysis framework integrating dynamic modeling for forest and biorefinery systems with a time-based discounted Global Warming Potential (GWP) method developed in this work. The framework analyzed dynamic carbon and energy flows of a supply chain for biofuel production from pine residues via fast pyrolysis. Results The mean carbon intensity of biofuel given by Monte Carlo simulation across three pine growth cases ranges from 40.8–41.2 g CO 2 e MJ −1 (static method) to 51.0–65.2 g CO 2 e MJ −1 (using the time-based discounted GWP method) when combusting biochar for energy recovery. If biochar is utilized as soil amendment, the carbon intensity reduces to 19.0–19.7 g CO 2 e MJ −1 (static method) and 29.6–43.4 g CO 2 e MJ −1 in the time-based method. Forest growth and yields (controlled by forest management strategies) show more significant impacts on biofuel carbon intensity when the temporal effect of carbon is taken into consideration. Variation in forest operations and management (e.g., energy consumption of thinning and harvesting), on the other hand, has little impact on the biofuel carbon intensity. Conclusions The carbon temporal effect, particularly the time lag of carbon sequestration during pine growth, has direct impacts on the carbon intensity of biofuels produced from pine residues from a stand-level pine growth and management point of view. The carbon implications are also significantly impacted by the assumptions of biochar end-of-life cases and forest management strategies.

09 BIOMASS FUELS↗

DOE OSTI2024

The circular bioeconomy: a driver for system integration

Background: Human and earth system modeling, traditionally centered on the interplay between the energy system and the atmosphere, are facing a paradigm shift. The Intergovernmental Panel on Climate Change’s mandate for comprehensive, cross-sectoral climate action emphasizes avoiding the vulnerabilities of narrow sectoral approaches. Our study explores the circular bioeconomy, highlighting the intricate interconnections among agriculture, forestry, aquaculture, technological advancements, and ecological recycling. Collectively, these sectors play a pivotal role in supplying essential resources to meet the food, material, and energy needs of a growing global population. We pose the pertinent question of what it takes to integrate these multifaceted sectors into a new era of holistic systems thinking and planning. Results: The foundation for discussion is provided by a novel graphical representation encompassing statistical data on food, materials, energy flows, and circularity. This representation aids in constructing an inventory of technological advancements and climate actions that have the potential to significantly reshape the structure and scale of the economic metabolism in the coming decades. In this context, the three dominant mega-trends—population dynamics, economic developments, and the climate crisis—compel us to address the potential consequences of the identified actions, all of which fall under the four categories of substitution, efficiency, sufficiency, and reliability measures. Substitution and efficiency measures currently dominate systems modeling. Including novel bio-based processes and circularity aspects might require only expanded system boundaries. Conversely, paradigm shifts in systems engineering are expected to center on sufficiency and reliability actions. Effectively assessing the impact of sufficiency measures will necessitate substantial progress in inter- and transdisciplinary collaboration, primarily due to their non-technological nature. In addition, placing emphasis on modeling the reliability and resilience of transformation pathways represents a distinct and emerging frontier that highlights the significance of an integrated network of networks. Conclusions: Existing and emerging circular bioeconomy practices can serve as prime examples of system integration. These practices facilitate the interconnection of complex biomass supply chain networks with other networks encompassing feedstock-independent renewable power, hydrogen, CO 2 , water, and other biotic, abiotic, and intangible resources. Elevating the prominence of these connectors will empower policymakers to steer the amplification of synergies and mitigation of tradeoffs among systems, sectors, and goals.

09 BIOMASS FUELS↗

DOE OSTI2024

Data for Spatially Varying Costs of GHG Abatement with Alternative Cellulosic Feedstocks for Sustainable Aviation Fuels

Cellulosic biomass-based sustainable aviation fuels (SAFs) can be produced from various feedstocks. The breakeven price and carbon intensity of these feedstock-to-SAF pathways are likely to differ across feedstocks and across spatial locations due to differences in feedstock attributes, productivity, opportunity costs of land for feedstock production, soil carbon effects, and feedstock composition. We integrate feedstock to fuel supply chain economics and life-cycle carbon accounting using the same system boundary to quantify and compare the spatially varying greenhouse gas (GHG) intensities and costs of GHG abatement with SAFs derived from four feedstocks (switchgrass, miscanthus, energy sorghum, and corn stover) at 4 km resolution across the U.S. rainfed region. We show that the optimal feedstock for each location differs depending on whether the incentive is to lower breakeven price, carbon intensity, or cost of carbon abatement with biomass or to have high biomass production per unit land. The cost of abating GHG emissions with SAF ranges from $181 Mg−1 CO2e to more than $444 Mg−1 CO2e and is lowest with miscanthus in the Midwest, switchgrass in the south, and energy sorghum in a relatively small region in the Great Plains. While corn stover-based SAF has the lowest breakeven price per gallon, it has the highest cost of abatement due to its relatively high GHG intensity. Our findings imply that different types of policies, such as volumetric targets, tax credits, and low carbon fuel standards, will differ in the mix of feedstocks they incentivize and locations where they are produced in the U.S. rainfed region. Note: Column V in TableS7_DayCentSimulatedYield.csv should be labelled Corn Stover CoSo-NT-50% Max.

Geospatial↗

DOE OSTI2022

Deployment of the HFIRCON transport and depletion tool for plutonium-238 production studies

Irradiation of {sup 237}Np-bearing targets in Oak Ridge National Laboratory's (ORNL) High Flux Isotope Reactor (HFIR) results in the efficient production of {sup 238}Pu, which, in the form of heat source PuO{sub 2}, is used as a reliable power source for deep-space and planetary NASA missions. A technology demonstration subproject was initiated at ORNL in 2011 to develop and implement the technology required to establish a {sup 238}Pu supply chain. A systematic progression of NpO{sub 2}/Al cermet (20 vol.% NpO{sub 2}) activities to date has successfully demonstrated target fabrication, irradiation, and chemical recovery processes. Recent program tasks have included the development of the HFIRCON transport and depletion tool for efficient reactor physics analyses and the evaluation of increased NpO{sub 2} loadings (i.e., beyond 20 vol.%) and NpN-based targets. This paper documents the deployment of the HFIRCON code to assess various Np concentrations in NpO{sub 2}- and NpN-based targets in HFIR's inner small vertical experiment facilities. Results indicate that {sup 238}Pu production and quality can be enhanced with increased Np loadings; however, target conversion rates are reduced. The results recorded in this paper, thermal and material balance evaluations, and testing requirement planning will be used to determine whether increased NpO{sub 2} loadings or NpN-based targets will be further considered. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗