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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 361 records · Page 20

Integrated Framework of Multisource Data Fusion for Outage Location in Looped Distribution Systems

Accurate outage location is essential for expediting post-outage power restoration, minimizing outage duration, and enhancing the resilience of distribution networks. With the advent of advanced metering infrastructure, data-driven outage location methods have significantly advanced beyond traditional approaches that rely on manual inspections. However, existing methods still face critical challenges, like reliance on single-source data, limited ability to handle partially observable systems or difficulties with loop networks. To the best of our knowledge, no single approach has comprehensively addressed all of these challenges at once. To this end, this paper proposes a comprehensive multisource data fusion framework for outage locations via probabilistic graph networks. The framework consists of three key phases. First, a novel method for reconstituting distribution networks with loops is developed, transforming looped networks into multiple radial subnetworks that retain all outage causalities of the original network. Second, Bayesian network (BN) models are established for each subnetwork, integrating multiple data sources and network structures. Finally, a joint Gibbs sampling mechanism, featuring forward and backward information flow, is designed to merge data from separate BN models and maximize the utilization of limited evidence, ensuring accurate outage location identification. In conclusion, the framework was validated on two modified public test systems, and comparative studies confirmed its effectiveness.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The DESI Survey Validation: Results from Visual Inspection of the Quasar Survey Spectra

Abstract A key component of the Dark Energy Spectroscopic Instrument (DESI) survey validation (SV) is a detailed visual inspection (VI) of the optical spectroscopic data to quantify key survey metrics. In this paper we present results from VI of the quasar survey using deep coadded SV spectra. We show that the majority (≈70%) of the main-survey targets are spectroscopically confirmed as quasars, with ≈16% galaxies, ≈6% stars, and ≈8% low-quality spectra lacking reliable features. A nonnegligible fraction of the quasars are misidentified by the standard spectroscopic pipeline, but we show that the majority can be recovered using post-pipeline “afterburner” quasar-identification approaches. We combine these “afterburners” with our standard pipeline to create a modified pipeline to increase the overall quasar yield. At the depth of the main DESI survey, both pipelines achieve a good-redshift purity (reliable redshifts measured within 3000 km s −1 ) of ≈99%; however, the modified pipeline recovers ≈94% of the visually inspected quasars, as compared to ≈86% from the standard pipeline. We demonstrate that both pipelines achieve a median redshift precision and accuracy of ≈100 km s −1 and ≈70 km s −1 , respectively. We constructed composite spectra to investigate why some quasars are missed by the standard pipeline and find that they are more host-galaxy dominated (i.e., distant analogs of “Seyfert galaxies”) and/or more dust reddened than the standard-pipeline quasars. We also show example spectra to demonstrate the overall diversity of the DESI quasar sample and provide strong-lensing candidates where two targets contribute to a single spectrum.

79 ASTRONOMY AND ASTROPHYSICS↗

SuperCam Calibration Targets: Design and Development

Abstract SuperCam is a highly integrated remote-sensing instrumental suite for NASA’s Mars 2020 mission. It consists of a co-aligned combination of Laser-Induced Breakdown Spectroscopy (LIBS), Time-Resolved Raman and Luminescence (TRR/L), Visible and Infrared Spectroscopy (VISIR), together with sound recording (MIC) and high-magnification imaging techniques (RMI). They provide information on the mineralogy, geochemistry and mineral context around the Perseverance Rover. The calibration of this complex suite is a major challenge. Not only does each technique require its own standards or references, their combination also introduces new requirements to obtain optimal scientific output. Elemental composition, molecular vibrational features, fluorescence, morphology and texture provide a full picture of the sample with spectral information that needs to be co-aligned, correlated, and individually calibrated. The resulting hardware includes different kinds of targets, each one covering different needs of the instrument. Standards for imaging calibration, geological samples for mineral identification and chemometric calculations or spectral references to calibrate and evaluate the health of the instrument, are all included in the SuperCam Calibration Target (SCCT). The system also includes a specifically designed assembly in which the samples are mounted. This hardware allows the targets to survive the harsh environmental conditions of the launch, cruise, landing and operation on Mars during the whole mission. Here we summarize the design, development, integration, verification and functional testing of the SCCT. This work includes some key results obtained to verify the scientific outcome of the SuperCam system.

Manrique, J. A. (ORCID:0000000220532819)↗

Topological Surface and Bulk States in Dirac Semimetal Alpha-Sn Thin Films

Supported by this DOE grant, we made significant advancements in the study and application of topological surface states (TSS) in topological Dirac semimetal (TDS) α-Sn thin films. Our key findings include: (1) the successful growth of TDS α-Sn thin films via sputtering, an industry-friendly technique, on Si and InSb substrates, marking a breakthrough over previous molecular beam epitaxy methods, (2) the demonstration of enhanced damping in adjacent NiFe thin films due to the TSS of α-Sn, (3) the first observation of a strong bilinear magneto-electric resistance (BMER) effect in TDS materials at room temperature, with responses surpassing previous results, (4) the identification of quantum oscillations in α-Sn thin films associated with the TSS, revealing critical quantum transport characteristics such as Berry phase and quantum mobility, (5) the first experimental observation of negative magnetoresistance in α-Sn, and (6) the demonstration of spinorbit torque-driven, field-free magnetization switching in an α-Sn/Ag/CoFeB trilayer, achieving efficiency levels higher than conventional heavy-metal-based structures, highlighting the essential role of TSS in enabling the switching process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

ClimateNet: an expert-labeled open dataset and deep learning architecture for enabling high-precision analyses of extreme weather

Abstract. Identifying, detecting, and localizing extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Pattern recognition tasks such as classification, object detection, and segmentation (i.e., pixel-level classification) have remained challenging problems in the weather and climate sciences. While there exist many empirical heuristics for detecting extreme events, the disparities between the output of these different methods even for a single event are large and often difficult to reconcile. Given the success of deep learning (DL) in tackling similar problems in computer vision, we advocate a DL-based approach. DL, however, works best in the context of supervised learning – when labeled datasets are readily available. Reliable labeled training data for extreme weather and climate events is scarce. We create “ClimateNet” – an open, community-sourced human-expert-labeled curated dataset that captures tropical cyclones (TCs) and atmospheric rivers (ARs) in high-resolution climate model output from a simulation of a recent historical period. We use the curated ClimateNet dataset to train a state-of-the-art DL model for pixel-level identification – i.e., segmentation – of TCs and ARs. We then apply the trained DL model to historical and climate change scenarios simulated by the Community Atmospheric Model (CAM5.1) and show that the DL model accurately segments the data into TCs, ARs, or “the background” at a pixel level. Further, we show how the segmentation results can be used to conduct spatially and temporally precise analytics by quantifying distributions of extreme precipitation conditioned on event types (TC or AR) at regional scales. The key contribution of this work is that it paves the way for DL-based automated, high-fidelity, and highly precise analytics of climate data using a curated expert-labeled dataset – ClimateNet. ClimateNet and the DL-based segmentation method provide several unique capabilities: (i) they can be used to calculate a variety of TC and AR statistics at a fine-grained level; (ii) they can be applied to different climate scenarios and different datasets without tuning as they do not rely on threshold conditions; and (iii) the proposed DL method is suitable for rapidly analyzing large amounts of climate model output. While our study has been conducted for two important extreme weather patterns (TCs and ARs) in simulation datasets, we believe that this methodology can be applied to a much broader class of patterns and applied to observational and reanalysis data products via transfer learning.

54 ENVIRONMENTAL SCIENCES↗

A Novel Fiber-Bragg-Grating-Based Unique Identifier for Use in Tags and Seals

Tags and seals are important tools used in safeguards regimes for the control of nuclear materials. Vital to a successful tag or seal is the ability to securely, uniquely, and positively distinguish it from others of the same kind. This allows one to validate that items entered into an inspection regime to which the tag or seal is affixed are as claimed. We are developing a new type of unique identifier (UID) for such applications that is based on fiber-Bragg grating (FBG) technology. The index of refraction of the core glass of a fiber optic can be locally and permanently altered if sensitized fibers are exposed to intense ultraviolet light. This can be used to create index modulations with a regular periodicity comparable to the wavelengths of light with which the fiber is used. If broadband illumination is sent down the fiber, any light that is in resonance with the modulations will be reflected back to the input end of the fiber where it can be detected. The shape of the returned spectrum can be set by the modulation pattern written into the fiber’s core. We take advantage of these properties to create a compact UID that contains several FBGs potted into a monolithic body. By connecting the UID to an optical interrogator, the complex spectral return can be uniquely identified with a short measurement, providing a robust identification. As a device based on narrowband spectral returns, FBGs are inherently radiation tolerant, making them ideal for use with nuclear materials. Further, they can be read out remotely via a long fiber optic or locally via brief connection to a portable optical interrogator. Because the spectral signature of FBGs is sensitive to external mechanical perturbations, we are exploring the ability to reversibly alter the signature obtained from the UID by applying controlled mechanical forces with a simple device. Such a “key” will allow different stakeholders to obtain their own unique signature from the device, providing a new level of surety to safeguards inspections.

Ziock, Klaus-Peter↗

Refinery Integration Analysis: Pathways, Challenges, and Opportunities

Integrating biomass-derived intermediates into traditional petroleum refineries presents unique challenges and opportunities, requiring innovative analysis approaches that account for biofuel producers and refiners. Consequently, teams within the National Renewable Energy Laboratory (NREL) have developed a comprehensive refinery integration analysis framework that combines experimental data, detailed techno-economic analyses of bio-conversion pathways, and economic projections within refinery linear programming (LP) optimization models. These models enable the identification of promising bio-integration strategies tailored to specific refinery configurations, economic conditions, and production goals. They also capture upstream and downstream impacts, highlighting critical bottlenecks and research opportunities for increasing the share of biogenic feedstocks in traditional refining operations. Refinery models are also packaged into a broader bio-economy optimization framework which enables biofuel supply chain optimization with standalone biofuel production and refinery co-processing/repurposing options. This presentation discusses promising refinery bio-integration strategies along with key challenges and opportunities identified using NREL's refinery and bio-economy optimization frameworks.

09 BIOMASS FUELS↗

Decarbonization Scenarios in the United States: Comparing Biofuels Growth in Two Models - GCAM and BSM

Scenarios for deep decarbonization rely on biomass for biofuels, biopower, and bioproducts, often including negative emissions via carbon capture and storage or utilization. Despite the prominence of biomass in many deep decarbonization pathways, critical questions remain about biomass allocation, effects of transportation electrification, the pace of growth, and implications for agriculture and land use. We address these questions through a unique comparison of carbon pricing effects on the growth of biomass utilization and its effects on land use in the United States by comparing results from a multisectoral integrated assessment model, the Global Change Analysis Model [GCAM], with results from a biomass-to-biofuels system dynamics model, the Biomass Scenario Model [BSM]. We contribute to model comparison efforts by analyzing the biomass deployment needed for a scenario consistent with a "Middle of the Road" Shared Socioeconomic Pathway [SSP2] and a representative concentration pathway of 2.6 W/m2. The GCAM scenarios solve for global equilibrium conditions that are consistent with this pathway, including demands for biomass across all economic sectors and representing bioenergy with carbon capture and storage as a technology option. The BSM scenarios assess those biomass and biofuel results for the United States and identify challenges associated with that pace and amount of expansion. In the scenario analysis, we harmonize key factors such as carbon price trajectory, domestic ethanol fuel demand, ethanol blending, and arable land availability, and vary them in both models. In GCAM, we vary the carbon price, transportation electrification, ethanol blending constraints, and arable land availability inputs and the value of the carbon in land; in BSM, in addition to directly inputting certain GCAM results, we vary the maximum rate of biorefinery construction, flexibility of feedstock types across conversion processes, and policy incentives such as tax credits and renewable identification number payments. The selected carbon price trajectory results in a rapid increase in biofuel production in the United States, reaching about 9.4 EJ/year in 2060 in the highest scenario analyzed in GCAM. Results differ between the two models in timing and ultimate quantity of biomass and biofuel production. GCAM biofuel quantities generally exceed BSM amounts because CCS is applied to biofuel pathways in GCAM, and because of differences in capacity expansion and related dynamics of land allocation, biomass production, and price dynamics. These dynamics include rapid biorefinery capacity expansion in high demand cases. To satisfy this biomass demand, GCAM rapidly equilibrates land allocation, but the BSM limits the rate at which this re-allocation can occur. A further contrast with the equilibrium approach in GCAM is that the BSM represents a delay between planting and harvesting woody biomass resources. As a result of these model contrasts, feedstock costs in BSM increase more than in GCAM, and the absence of CCS in the BSM also reduces the relative economic attractiveness of biofuels production. The bottlenecks, lags, and price increases also lead to potential for volatility in feedstock price and land allocation to biomass in the BSM. GCAM has more biomass production than BSM in all scenarios, partly because of the broader, economy-wide coverage of GCAM, in contrast to BSM's exclusive focus on biofuels. In both models, trends like those of biofuels production were observed for biomass production: minimal growth without a carbon price and policy incentives, and increases with a carbon price, particularly with carbon capture and storage, because the inputs assume that biopower and biofuels decrease greenhouse gas emissions. In high policy scenarios, biomass demand is high, and the consequent high biomass prices due to the land re-allocation bottleneck in the BSM limit biofuel production even if the biorefinery capacity is expanded. However, because biomass prices do not increase as much in the low policy scenario, growth is slower and the land-reallocation bottleneck no longer dominates, such that the effect of increased capacity can be seen. Across both the models, a change in assumptions from less to more land availability increases biofuel production in both GCAM and BSM, as the upward pressure on feedstock price and volatility are both reduced.

biofuels↗

Spent Nuclear Fuel Exploratory Roadmaps - 20054

The U.S. Department of Energy manages nearly 2,500 metric tons of heavy metal (MTHM) of spent nuclear fuel (SNF) resulting from several decades of research, testing, and production reactors [DOE 1995]. This SNF is managed at the DOE Hanford Site in Washington State (Hanford), Idaho National Laboratory (INL), and Savannah River Site in South Carolina (SRS). From 1995 to 2004, the Department of Energy (DOE) made several key programmatic decisions, supported by appropriate documentation in accordance with the National Environmental Policy Act (NEPA) for the management of SNF [DOE 1995]. These decisions have provided an overarching framework for SNF management, as well as site-specific and SNF-related management decisions for the past two decades. In the years since these decisions were made, with the notable exception of the successful drying and packaging of the production reactor fuel at Hanford, a majority of the decisions have been largely unimplemented. Also, since these decisions were made, a number of changes that bear on considerations relative to the path forward have occurred. A SNF Exploratory Road map activity, identified reasonable alternate pathways for DoE's inventory of SNF. Three fundamental pathways were identified in this activity for the long-term management and disposition of DOE SNF: Direct Disposal Pathway, Existing Processing Pathway and Alternate Processing Pathway. Further actions would be required (e.g., evaluation of NEPA analysis, technology maturity evaluations, refinement of cost and risks, benefits and advantages relative to other alternate paths) to define and inform many key decisions that will result in the selection of the disposition pathways that are most beneficial to the US Government in dispositioning DoE's SNF inventory. DOE is currently managing all SNF safely; however, the age of DOE-owned SNF and facilities for storing and processing SNF, coupled with the uncertainty of the storage duration, necessitates decisions and actions to ensure that the infrastructure will be in place to ensure continued safe and effective long-term management and eventual disposal. The identification of reasonable alternate pathways took these considerations into account in an effort to proactively manage conditions that could challenge the safety of storing and managing DOE SNF over the time periods now contemplated and also to ensure that flexibility is preserved to ensure that the DOE SNF remains compatible with final disposition pathways when they become available. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Counterintuitive Catalytic Reactivity of the Aluminum Oxide “Passivation” Shell of Aluminum Nanoparticles Facilitating the Thermal Decomposition of exo -Tetrahydrodicyclopentadiene (JP-10)

High energy density aluminum nanoparticles (AlNP) have been at the center of attention as additives to hydrocarbon jet fuels like exo-tetrahydrodicyclopentadiene (JP-10, C 10 H 16 ) aiming at a superior performance of volume-limited air-breathing propulsion systems. However, a fundamental understanding of the ignition and combustion chemistry of JP-10 in presence of AlNPs has been elusive. Exploiting an isomer-selective comprehensive identification of the decomposition products in a newly designed high temperature chemical microreactor coupled to vacuum ultraviolet photoionization, we reveal an active low temperature heterogeneous surface chemistry commencing at 650 K involving the alumina (Al 2 O 3 ) shell. Contrary to textbook knowledge of an “inactive alumina surface”, this unconventional reactivity, where oxygen is transferred from alumina to JP-10, leads to generating cyclic, oxygenated organics like phenol (C 6 H 5 OH) and 2,4-cyclopentadiene-1-one (C 5 H 4 O) - key tracers of an alumina-mediated interfacial chemistry. Furthermore, this counterintuitive reactivity transforms our knowledge on the (catalytic) processes of alumina-coated AlNPs on the molecular level.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

General Failure Modes and Effects Analysis for Accelerator and Detector Magnet Design at JLab

The aim of this article is to develop a risk management procedure, which could be applied to the magnet design process, for both superconducting and normal magnets at the Jefferson Laboratory (JLab). This procedure allowed us to identify the key risks at each of the critical phases of design and propose procedures, tests, and checks to mitigate each risk. In this article, we present a qualitative and quantitative risk management procedure commonly referred to a “failure modes and effects analysis.” As part of this procedure, we calculated a risk priority number (RPN) for each activity of the process, identified the most critical activities and proposed mitigation activities, which in turn resulted in a revised RPN. Additionally, another benefit of this procedure was the identification of appropriate “control and hold” points within the design process, which allowed one to review and approve a particular outcome before proceeding to the next sequential activity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Enhancing phase identification in waste-to-energy fly ashes: Role of Raman spectroscopy, background fluorescence, and photobleaching

Waste-to-Energy (WTE) facilities incinerate ~11% (~ 222 Mt) of global solid waste, generating bottom and fly ashes. Landfilling these ashes is costly, and risks releasing contaminants into the environment. Instead, using WTE ashes in secondary industrial applications can circumvent such environmental risks. However, their secondary use is restricted by their inconsistent mineralogy, which may vary due to fluctuating waste composition and combustion conditions. Therefore, there is a need for rapid and reliable monitoring of WTE fly ash mineralogy. Here, we evaluate the employment of Raman spectroscopy for that purpose. Our initial investigation of 12 unique WTE fly ashes resulted in excessive fluorescence, rendering key Raman peaks obscure. To address this issue, we report that a mere 2 minutes of photobleaching can significantly reduce this fluorescence, facilitating the detection of calcite, calcium sulfate, zincite, and carbon – phases previously undetectable in original spectra. Furthermore, these results show the potential of Raman spectroscopy for rapid monitoring of WTE fly ash mineralogy, which could be beneficial in diverting these ashes from landfill.

36 MATERIALS SCIENCE↗

Defect and satellite characteristics of additive manufacturing metal powders

Metal additive manufacturing (AM) requires high-quality metal powders to three-dimensionally (3D) print metallic components with complex and customizable geometries. The lack of quantification of AM metal powders creates quality control challenges for 3D printed components, increases the uncertainty of printing reliability and net cost of inspected and certified printed components, and reduces the recyclability of used powders. However, critical characteristics of AM metal powders that are decisive factors for the 3D printing process, such as internal porosity, contamination, and satellite feature, remain ambiguous. In this work, we developed a novel approach to 3D quantify key characteristics of AM metal powders down to individual particles by using high-resolution synchrotron x-ray computed tomography. Empowered by the penetrative capability of high-energy x-ray, internal porosity and contamination within as-atomized metal powders from high-entropy alloys to nickel-based superalloys were evaluated. Additionally, the newly-developed dispersion method enables the homogeneous separation of individual particles, and consequently, results in the implementation of 3D particle shape analysis. To resolve a major challenge of identification and quantification of satellite-feature particles in as-atomized AM metal powders, the satellite features were quantitated by modeling and analyzing the shape parameter of local thickness variance. Furthermore, the 3D analytical methods of particle assessment in this study can be applied to other materials systems like rock, food, and pharmaceutical particles, and provide insights for process optimization across powder metallurgy, concrete, food and pharmaceutical manufacturing, and AM industries.

36 MATERIALS SCIENCE↗

Pre-Commercial Scale-Up of a Gas-Fired Absorption Heat Pump

The project sought to advance the maturity of SMTI’s 80 kBTU/hr residential space and water heating GAHP from the engineering prototype stage (TRL-7) to pre-production readiness by addressing manufacturing, balance of system design and installation, cost, reliability, and field application questions. As part of this project, the project team has: (1) Matured the design package for a commercially ready product (2) Demonstrated compliance with relevant ANSI standards (3) Completed manufacturing and assembly process specifications (4) Completed total production cost estimates and capital equipment requirements (5) Initiated component and system level reliability assessments (6) Completed a small field demonstration including measured performance, installation requirements and expected costs, and customer/key stakeholder feedback. (7) Completed a Techno-economic analysis for representative applications and climate zones, including justification for utility incentive programs. (8) Completed a market intelligence report. Scope of Work: A multi-faceted project was completed that included: (a) design for manufacturing tasks for both the sealed system and balance of system, (b) development and trial of key manufacturing processes and techniques, (c) evaluation of component and system level reliability, (d) exploration of make/buy decisions including impact on cost and required capital. Additionally, (e) installation and monitoring of a small number of field test units was completed to demonstrate energy savings and collect customer/installer feedback, and (f) a focused market research task was completed to explore potential barriers and improve market introduction plans. These tasks addressed many of the remaining technical risks regarding long-term reliability, verification of manufacturing cost estimates and identification of cost concerns, identify installation and balance of system design criteria necessary to achieve energy savings and installed cost goals, and identify market barriers and strategies prior to product market introduction.

03 NATURAL GAS↗

Identification of a specific exporter that enables high production of aconitic acid in Aspergillus pseudoterreus

Aconitic acid is an unsaturated tricarboxylic acid that is attractive for its potential use in the manufacture of biodegradable and biocompatible polymers, plasticizers, and surfactants. Previously Aspergillus pseudoterreus was engineered as a platform to produce aconitic acid by deleting the cadA (cis-aconitic acid decarboxylase) gene in the itaconic acid biosynthetic pathway. In this study aconitic acid transporter gene (aexA) was identified using comparative global discovery proteomics analysis between the wild-type and cadA deletion strains. Deletion of aexA almost eliminated aconitic acid secretion, while its overexpression led to a significant increase in aconitic acid production. Transportation of aconitic acid across the plasma membrane is a key limiting step. In vitro proteoliposome transport assay further validated AexA’s function and its substrate specificity. This research provides new approaches to efficiently pinpoint and characterize exporters of fungal organic acids and accelerate the metabolic engineering to improve secretion capability and lower cost for bioproduction.

59 BASIC BIOLOGICAL SCIENCES↗

Identification of potent and selective N -myristoyltransferase inhibitors of Plasmodium vivax liver stage hypnozoites and schizonts

Drugs targeting multiple stages of the Plasmodium vivax life cycle are needed to reduce the health and economic burdens caused by malaria worldwide. N-myristoyltransferase (NMT) is an essential eukaryotic enzyme and a validated drug target for combating malaria. However, previous PvNMT inhibitors have failed due to their low selectivity over human NMTs. Herein, we apply a structure-guided hybridization approach combining chemical moieties of previously reported NMT inhibitors to develop the next generation of PvNMT inhibitors. A high-resolution crystal structure of PvNMT bound to a representative selective hybrid compound reveals a unique binding site architecture that includes a selective conformation of a key tyrosine residue. The hybridized compounds significantly decrease P. falciparum blood-stage parasite load and consistently exhibit dose-dependent inhibition of P. vivax liver stage schizonts and hypnozoites. Our data demonstrate that hybridized NMT inhibitors can be multistage antimalarials, targeting dormant and developing forms of liver and blood stage.

60 APPLIED LIFE SCIENCES↗

A framework and tool for designing cost-effective, resilient, and circular net-zero supply chains under uncertainty with an application to multilayer plastic films

While 55% of Fortune 500 companies have committed to achieving net-zero emissions and/or zero-waste operations by 2035, only 2% are currently on track, revealing a critical gap between ambition and action. Designing supply chains that reduce both emissions and waste is a complex non-intuitive, multi-objective challenge, compounded by the high costs of new technologies and the need for resilient, profitable solutions. This paper aims to address this challenge by presenting a generic framework and multi-objective optimization formulation for designing cost-effective, circular, and resilient supply chains under uncertainty, implemented through a user-friendly decision-support tool with intuitive data visualization capabilities, enabling communication of results to both technical and non-technical stakeholders. We demonstrate the application of this framework in the context of multilayer plastic films (barrier films), which are widely used in food packaging and composite materials. The model quantifies trade-offs across three objectives: minimizing global warming potential, maximizing circularity, and minimizing cost. A key contribution of this work is the explicit modeling of technological resilience, the ability of supply chains to maintain function under disruption. In the cost-minimization case, the resilience constraint makes the design approximately three times more expensive in the short-term metric, but shifts the system from relying on a single recovery pathway to a portfolio of four recovery pathways, improving the robustness of the optimization solution under uncertainty. Lastly, we introduce TranZero, a decision-support tool that integrates material flow analysis, hotspot identification, and optimization-based scenario planning to support net-zero and circularity decisions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Medium- and Heavy-Duty Vehicle Electrification: An Assessment of Technology and Knowledge Gaps

The objective of this assessment was to leverage current medium- and heavy-duty vehicle (MHDV) data and information to evaluate the state of commercial vehicle electrification technologies, including the following: 1. Assessment and inventory of current MHDV electrification architectures; 2. Identification and assessment of MHDV component technologies; 3. Assessment of potential performance and cost drivers; and, 4. Identification of R&D gaps where appropriate R&D and technology would accelerate commercial vehicle electrification. These gaps include shortfalls in technology, gaps in data, and inadequate knowledge and understanding. To inform this study, the National Renewable Energy Laboratory–Oak Ridge National Laboratory team examined the open literature; conducted workshops; assessed and analyzed data on more than 175 electrified MHDVs, including vehicle and powertrain specifications; and conducted one-on-one meetings with industry representatives. This systems-level information was concatenated and parsed with respect to key characteristics such as battery energy, power, and range compared across vehicle classes. Operational data of many conventional vehicles were also examined to help determine the requirements on electrified vehicle attributes such as range. Previous studies on the total cost of ownership of electrified MHDVs were reviewed to determine where improvements in technologies (efficiency, cost, maintenance) were needed to accelerate adoption. The team also assessed the state of the art in electric drivetrains for component specifications and challenges for the commercial vehicle sector, including electric machines, power electronics, and off-board high-power charging systems (extreme fast charging and beyond). The goal of this analysis was to identify the barriers to widespread adoption of commercial vehicle electrification technologies and prioritize the research and development gaps that need to be overcome to accelerate significant market penetration of these technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗