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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Theoretical Open Architecture Framework and Technology Stack for Digital Twins in Energy Sector Applications

Digital twin is often viewed as a technology that can assist engineers and researchers make data-driven system and network-level decisions. Across the scientific literature, digital twins have been consistently theorized as a strong solution to facilitate proactive discovery of system failures, system and network efficiency improvement, system and network operation optimization, among others. With their strong affinity to the industrial metaverse concept, digital twins have the potential to offer high-value propositions that are unique to the energy sector stakeholders to realize the true potential of physical and digital convergence and pertinent sustainability goals. Although the technology has been known for a long time in theory, its practical real-world applications have been so far limited, nevertheless with tremendous growth projections. In the energy sector, there have been theoretical and lab-level experimental analysis of digital twins but few of those experiments resulted in real-world deployments. There may be many contributing factors to any friction associated with real-world scalable deployment in the energy sector such as cost, regulatory, and compliance requirements, and measurable and comparable methods to evaluate performance and return on investment. Those factors can be potentially addressed if the digital twin applications are built on the foundations of a scalable and interoperable framework that can drive a digital twin application across the project lifecycle: from ideation to theoretical deep dive to proof of concept to large-scale experiment to real-world deployment at scale. This paper is an attempt to define a digital twin open architecture framework that comprises a digital twin technology stack (D-Arc) coupled with information flow, sequence, and object diagrams. Those artifacts can be used by energy sector engineers and researchers to use any digital twin platform to drive research and engineering. This paper also provides critical details related to cybersecurity aspects, data management processes, and relevant energy sector use cases.

Gourisetti, Sri, Nikhil Gupta (ORCID:0000000188778↗
DOE OSTI2025

Impact of a dynamic grid mix and climate on operational carbon emissions modeling for different building typologies and climate zones

Calculating operational carbon emissions through a building’s lifecycle is complex due to the dynamic nature of influencing factors such as climate and energy grid mix. This paper introduces a novel methodology for modeling 30-year operational carbon impacts of buildings and applies this method to mid-rise office and residential typologies across various US climate zones. The method accounts for these temporal variabilities using new and scarcely cited data sources. Key findings indicate that future changes in the climate, while impactful, play a relatively modest role in operational carbon emissions compared to significant reductions with modeling scenarios using the projected decarbonization of the electricity grid. Here, the study also finds that using annual, month-hourly, or hourly grid emission factors have a minimal impact on carbon accounting, except in certain climates and program types where emission patterns do not align with a building’s energy consumption. Warmer climates like Miami, Florida and Tucson, Arizona, which rely heavily on cooling, demonstrate larger variations in carbon emissions when using higher temporal resolution emission factors. Ultimately, this study underscores the critical role of grid decarbonization in reducing long-term emissions and the importance of incorporating this variable in life cycle assessment (LCA) modeling.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Wabash Valley Integrated Gasification Combined Cycle, Coal to Fischer Tropsch Jet Fuel Conversion Study

This reports examines the feasibility of converting the existing Wabash Integrated Gasification Combined Cycle (IGCC) plant into a liquid fuel facility, with the goal of maximizing jet fuel production. The fuels produced are required to be in compliance with Section 526 of the Energy Independence and Security Act of 2007 (EISA 2007 §526) lifecycle greenhouse gas (GHG) emissions requirements, so lifecycle GHG emissions from the fuel must be equal to or better than conventional fuels. Retrofitting an existing gasification facility reduces the technical risk and capital costs associated with a coal to liquids project, leading to a higher probability of implementation and more competitive liquid fuel prices. The existing combustion turbine will continue to operate on low cost natural gas and low carbon fuel gas from the gasification facility. The gasification technology utilized at Wabash is the E-Gas™ Technology and has been in commercial operation since 1995. In order to minimize capital costs, the study maximizes reuse of existing equipment with minimal modifications. Plant data and process models were used to develop process data for downstream units. Process modeling was utilized for the syngas conditioning, acid gas removal, CO 2 compression and utility units. Syngas conversion to Fischer Tropsch (FT) liquids and upgrading of the liquids was modeled and designed by Johnson Matthey Davy Technologies (JM Davy). In order to maintain the GHG emission profile below that of conventional fuels, the CO 2 from the process must be captured and exported for sequestration or enhanced oil recovery. In addition the power utilized for the plant’s auxiliary loads had to be supplied by a low carbon fuel source. Since the process produces a fuel gas with sufficient energy content to power the plant’s loads, this fuel gas was converted to hydrogen and exported to the existing gas turbine for low carbon power production. Utilizing low carbon fuel gas and process steam in the existing combined cycle power plant provides sufficient power for all plant loads. The lifecycle GHG profile of the produced jet fuel is 95% of conventional jet fuel. Without converting the fuel gas to a low carbon fuel gas, the emissions would be 108% of conventional jet fuel and without any GHG mitigation, the profile would be 206%. Oil prices greater than $120 per barrel are required to reach a targeted internal rate of return on equity (IRROE) of 12%. Although capital expenditure is much less than if a greenfield facility was built, the relatively small size of the plant, assumed coal price, and the CTL risk profile used in the economic assumptions lead to a high cost of production. Assuming more favorable factors, the economic oil price could be reduced to $78 per barrel with GHG mitigation and $55 per barrel with no GHG mitigation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2013

Optimised management of orphan wastes in the UK

Orphan wastes have properties preventing them from being managed according to existing or currently planned management routes, or lack characterisation so that their management is uncertain. The identification of new management opportunities for orphan wastes could realise significant benefits by reducing the number of processing facilities required, reducing waste volumes, reducing hazard or leading to the development of centres of excellence for the processing of certain types of orphan wastes. Information on the characteristics of orphan waste existing at nuclear licensed sites across the UK has been collated and a database developed to act as a repository for the information gathered. The database provides a capability to analyse the data and to explore possible treatment technologies for each orphan waste type. Thirty five distinct orphan waste types have been defined and possible treatment options considered. Treatment technologies (including chemical, high temperature, immobilisation and physical technologies) that could be applied to one or more of the generic orphan waste streams have been identified. Wiring diagrams have been used to highlight the waste treatment / lifecycle management options that are available for each of the generic orphan groups as well as identifying areas for further research and development. This work has identified the potential for optimising the management of orphan wastes in a number of areas, and many potential opportunities were identified. Such opportunities could be investigated by waste managers at waste producing nuclear sites, to facilitate the development of new management routes for orphan wastes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Securing Your ICS Software with the AttackSurface Host Analyzer (AHA)

Implementing a secure development lifecycle (SDL) presents increasing challenges to software developers as they must ensure software correctly integrates both underlying operating system security features while also managing dependencies on third-party libraries or executables. There are a growing number of security functions that require a close integration between the OS security features and software builds to ensure strong protection. Furthermore, as software platforms grow in complexity, they present many opportunities for misconfigurations and inadequate defenses. This challenge is especially prevalent for industrial control systems (ICS), which oten depend on both legacy sotware platforms, or out of date operating systems. This paper presents the AttackSurface Host Analyzer (AHA) tool, which is used to assess the security of a software platform through its integration with a host operating system. The tool collects data from the various platforms running on an OS, evaluates an array of security properties, and then introduces metrics and visualizations to provide feedback on the system's attack surface based on the external interconnections and the completeness of the available security protections. The paper then explores the attack surface of a variety of industry-standard ICS platforms to provide insight into the current degree of protection enabled by them.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

JGI Archive and Metadata Organizer (JAMO) v2.0.0

JAMO (JGI Archive and Metadata Organizer) helps researchers keep large collections of scientific files organized, findable, and safe. It lets you submit files with consistent, template-driven metadata, bundle related files into sets, and track them as a group instead of one by one. As data ages, JAMO automatically moves it from fast disk to cost-saving tape and can bring it back when needed, keeping storage lean without losing access. A simple web/CLI workflow supports submitting, checking status, retrying, and updating metadata. Compared with generic storage, JAMO's strengths are: clear, searchable metadata tuned for science; set-level organization that mirrors real projects; and built-in lifecycle care (archive, purge, restore) so you don't have to manage those steps yourself.

Cassol, Daniela [Lawrence Berkeley National Labora↗
DOE OSTI2021

Thermophysical Properties of Mixtures of Thorium and Uranium Nitride

Abstract The miscibility, lattice parameter, and thermophysical properties of (Th 0.2 U 0.8 )N and (Th 0.5 U 0.5 )N have been investigated. It is shown that additions of thorium nitride (ThN) to uranium nitride (UN) increases the thermophysical performance of the mixed nitride fuel form in comparison to reference UN. In the more dilute limit, additions of ThN serve as a burnable neutronic poison and reduces the change in k eff over the lifecycle of the fuel. At higher concentrations, additions of ThN serve as a significant fertile source of 233 U. Where appropriate, comparisons to previous work on UN + PuN mixtures are made, as this is a comparable fuel form for potential fast reactor concepts, and a suitable point of contrast in the possible design space afforded by mixed (Th x U 1 − x )N fuel forms. The data from this work are the input parameters for finite element modeling of the temperature distribution in a compact reactor. The results of modeling and simulation of this core design are shown for the case of steady-state operation and during double, adjacent heat pipe failure.

Parker, S. S. (ORCID:000000018597440X)↗
DOE OSTI2026

A Reverse Logistics Tool For Ev Battery Recycling And Repurposing,

The demand for electric vehicles (EVs) in the United States is projected to rise significantly, with sales expected to reach approximately 4.1 million units by 2030. However, the U.S. remains heavily reliant on imports for the batteries and critical raw materials—such as lithium, cobalt, and nickel—that power these vehicles. As of 2024, around 70% of these imports originate from China. This dependency has become even more precarious following China’s imposition of export restrictions in April 2025, a retaliatory move against U.S. tariffs. These developments highlight the strategic vulnerabilities posed by China’s dominant position in the critical materials market. Compounding the issue, decades of intensive extraction have severely depleted global reserves of critical materials, widening the gap between supply and growing demand. This situation underscores the urgent need for the U.S. and other nations to diversify their sources of critical materials and enhance domestic capabilities to secure these resources—an essential step toward ensuring long-term energy security. At the end of their lifecycle—whether due to the battery’s degradation or the retirement of the vehicle—EV batteries are often improperly disposed of or sent to landfills. However, many of these batteries still retain usable capacity and can follow one of three alternative pathways: (a) Re-used: deployed in another vehicle with a shorter driving range, (b) Re-purposed: utilized act as a backup storage/power for data centers, solar panels, and e-scotters or (c) Recycled: broken down to recover the critical materials. To that end, the proposed tool (REBORN) is designed to optimize the reverse logistics network for battery repurposing and recycling. Its goal is to minimize associated costs while identifying optimal locations for battery collection and processing. Ultimately, REBORN ensures that each battery is used to its fullest potential.

Srinivas, SrikarV. [Idaho National Laboratory (INL↗
DOE OSTI2024

Measuring Sustainability of Solar Modules for Energy Transition: Mass, Energy, and Circularity

Transition to a carbon-free energy system is crucial for global decarbonization and underpins Circular Economy (CE) goals. Photovoltaic (PV) technology is required for Energy Transition, but manufacturing and circular pathways can be material, energy, and carbon-intensive. Therefore, we need a prioritization of sustainability strategies for PV evolution and lifecycle management in the context of Energy Transition. This study employs a suite of quantitative metrics to compare different proposed sustainability strategies for PV modules on their ability to achieve Energy Transition. Proposals for sustainable PV range from high-yield, high-efficiency paradigms, to short-lived and fully recyclable, to long-lasting, indestructible modules. We leverage a global decarbonization deployment schedule through 2100 with the open-source PV in Circular Economy (PV ICE) tool to quantify the impacts of different evolving module design scenarios covering the range of proposed sustainability strategies. First, modules are compared on effective capacity and required replacements to meet and maintain decarbonization capacity targets through 2100. We demonstrate the effects of lifetime, degradation, and reliability on effective capacity. Next, we quantify and compare virgin material demands and lifecycle wastes, examining the impacts of lifetime and recycling rates. Finally, and critically for renewable energy technologies, we quantify the energy demands required to achieve the decarbonization capacity targets and calculate energy balance metrics (net energy, energy return on investment). These results are then summarized into a metric matrix, demonstrating tradeoffs and the importance of longevity. Our suite of mass and energy metrics provides stakeholders and decision-makers with quantitative data on circular economy choices for PV in the energy transition, enabling informed evaluation of tradeoffs of different PV module designs and CE pathways.

circular economy↗
DOE OSTI2016

Atmospheric Radiation Measurement Madden-Julian Oscillation Investigation Experiment Field Campaign Report

Every 30–90 days during the Northern Hemisphere winter, the equatorial tropical atmosphere experiences pulses of extraordinarily strong deep convection and rainfall. This phenomenon is referred to as the Madden–Julian Oscillation, or MJO, named after the scientists who identified this cycle. The MJO significantly affects weather and rainfall patterns around the world (Zhang 2013). To improve predictions of the MJO—especially about how it forms and evolves throughout its lifecycle—an international group of scientists collected an unprecedented set of observations from the Indian Ocean and western Pacific region from October 2011 through March 2012 through several coordinated efforts. The coordinated field campaigns captured six distinct MJO cycles in the Indian Ocean. The rich set of observations capturing several MJO events from these efforts will be used for many years to study the physics of the MJO. Here we highlight early research results using data from the Atmospheric Radiation Measurement (ARM) Madden-Julian Oscillation Investigation Experiment (AMIE), sponsored by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Mesoscale convective systems over the Amazon basin. Part I: climatological aspects

ABSTRACT Mesoscale convective systems ( MCSs ) over the Amazon basin provide a large contribution to regional precipitation, which strongly influences the maintenance of unique ecosystems. Despite the importance of these MCSs , their characteristics are not well described in the literature. The present study uses a 14‐year long (2000–2013) data set of high‐resolution (4 km; 30 min) infrared satellite images to compile a climatology of MCSs that during the period of analysis were within the borders of the Amazon basin at some point in their lifespan. MCSs that originated over the continent and the ocean are considered separately. It is found that on average about 7200 continental and 50 oceanic MCSs occurred per year in the Amazon basin. The majority (minority) of continental (oceanic) MCSs completed their lifecycles between 3 and 5.5 h. These MCSs are studied separately from those with lifespan longer than 6 h. Continental and oceanic MCSs over the Amazon occurred primarily during austral summer and autumn–winter, respectively. The preferred regions and time for genesis of continental and oceanic MCSs are identified. The average area, propagation speed and direction of displacement for MCSs in the different stages of their lifecycle are also examined.

Rehbein, Amanda↗
DOE OSTI2025

WorkflowHub: a registry for computational workflows

The rising popularity of computational workflows is driven by the need for repetitive and scalable data processing, sharing of processing know-how, and transparent methods. As both combined records of analysis and descriptions of processing steps, workflows should be reproducible, reusable, adaptable, and available. Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity. In reality, workflows are scattered and difficult to find, in part due to the diversity of available workflow engines and ecosystems, and because workflow sharing is not yet part of research practice. WorkflowHub provides a unified registry for all computational workflows that links to community repositories, and supports both the workflow lifecycle and making workflows findable, accessible, interoperable, and reusable (FAIR). By interoperating with diverse platforms, services, and external registries, WorkflowHub adds value by supporting workflow sharing, explicitly assigning credit, enhancing FAIRness, and promoting workflows as scholarly artefacts. The registry has a global reach, with hundreds of research organisations involved, and more than 800 workflows registered.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

TRMM Latent Heating Retrieval: Applications and Comparisons with Field Campaigns and Large-Scale Analyses

Yanai et al. (1973) utilized the meteorological data collected from a sounding network to present a pioneering work on thermodynamic budgets, which are referred to as the apparent heat source (Q1) and apparent moisture sink (Q2). Latent heating (LH) is one of the most dominant terms in Q1. Yanai’s paper motivated the development of satellite-based LH algorithms and provided a theoretical background for imposing large-scale advective forcing into cloud-resolving models (CRMs). These CRM-simulated LH and Q1 data have been used to generate the look-up tables in Tropical Rainfall Measuring Mission (TRMM) LH algorithms. A set of algorithms developed for retrieving LH profiles from TRMM-based rainfall profiles are described and evaluated, including details concerning their intrinsic space-time resolutions. Included in the paper are results from a variety of validation analyses that define the uncertainty of the LH profile estimates. Also, examples of how TRMM-retrieved LH profiles have been used to understand the lifecycle of the MJO and improve the predictions of global weather and climate models as well as comparisons with large-scale analyses are provided. Areas for further improvement of the TRMM products are discussed.

field campaigns↗
DOE OSTI2025

Securing the Modern Grid: Federal Investments, Digitization, and Supply Chain Strategy

Across the United States (U.S.) grid expansion and modernization is underway, paving the way for accelerated load growth and intelligent resource management. Digitization of the grid is supported by several state and federal programs, providing support for utilities installing advanced metering infrastructure (AMI), AI-powered analytics systems, battery energy storage systems (BESS), and distributed energy resource management systems (DERMS) to transform the grid from a one-way power delivery system into an intelligent, responsive network that will enable faster load growth and power expansion of data centers for advanced artificial intelligence (AI) applications. The digital transformation of America's grid presents opportunity for increased efficiency and resiliency but also introduces new digital risks that require careful management. Digital equipment often contains several vulnerabilities such as unencrypted communication protocols, and persistent remote access capabilities that could be exploited to manipulate device settings, coordinate service disruptions, or inject false data into grid operations. These digital risks become particularly important as the grid must rapidly scale to support AI-driven data centers, which the administration has identified as essential for maintaining U.S. technological leadership and economic competitiveness. These vulnerabilities are compounded by supply chain realities: Chinese manufacturers currently produce 70-90% of essential grid components including inverters, batteries, and control systems, with the U.S. lacking domestic manufacturing capacity for critical assets like extra-high voltage transformers. Recent federal legislation has established Foreign Entity of Concern (FEOC) restrictions to address these risks, requiring projects to achieve escalating thresholds of non-FEOC content to receive tax credits while utilities work to expand sourcing channels for their supply chains and strengthen security measures. These restrictions arrive precisely when utilities face unprecedented electricity demand growth driven by the rapid growth in data centers, creating a considerable challenge: rapidly expanding infrastructure while navigating complex compliance requirements while lacking viable alternatives for many critical components. Idaho National Laboratory (INL) and its partners have developed practical approaches to help utilities navigate these intersecting challenges as they leverage federal investment to strengthen and grow the grid. These solutions include Cyber-Informed Engineering (CIE) principles that build resilience directly into systems, the Cirrus tool for secure cloud migration, and enhanced procurement guidance that embeds security requirements throughout equipment lifecycles. Federal initiatives, such as the Technical Assistance for Digital Assurance (TADA) project, provide direct support to utilities implementing these approaches while facilitating knowledge sharing across the industry. While these tools and frameworks cannot eliminate all risks inherent in foreign supply chain dependencies, they offer pragmatic pathways for strengthening security posture without sacrificing the deployment momentum essential to meeting surging electricity demand. Ultimately, securing America's digital energy infrastructure demands dedicated coordination across multiple fronts: building domestic supply chains, implementing robust digital assurance practices, and maintaining the aggressive modernization timeline necessary for reliability, resilience, and energy independence.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Lifecycle assessment of microalgae to biofuel: Comparison of thermochemical processing pathways

Microalgae are currently being investigated as a renewable transportation fuel feedstock based on various advantages that include high annual yields, utilization of poor quality land, does not compete with food, and can be integrated with various waste streams. This study focuses on directly assessing the impact of two different thermochemical conversion technologies on the microalgae to biofuel process through life cycle assessment. A system boundary of a “well to pump” (WTP) is defined and includes sub-process models of the growth, dewatering, thermochemical bio-oil recovery, bio-oil stabilization, conversion to renewable diesel, and transport to the pump. Models were validated with experimental and literature data and are representative of an industrial-scale microalgae to biofuel process. Two different thermochemical bio-oil conversion systems are modeled and compared on a systems level, hydrothermal liquefaction (HTL) and pyrolysis. The environmental impact of the two pathways were quantified on the metrics of net energy ratio (NER), defined here as energy consumed over energy produced, and greenhouse gas (GHG) emissions. Results for WTP biofuel production through the HTL pathway were determined to be 1.23 for the NER and GHG emissions of -11.4 g CO 2-eq (MJ renewable diesel) -1 . WTP biofuel production through the pyrolysis pathway results in a NER of 2.27 and GHG emissions of 210 g CO2 eq (MJ renewable diesel)-1. The large environmental impact associated with the pyrolysis pathway is attributed to feedstock drying requirements and combustion of co-products to improve system energetics. Discussion focuses on a detailed breakdown of the overall process energetics and GHGs, impact of modeling at laboratory- scale compared to industrial-scale, environmental impact sensitivity to engineering systems input parameters for future focused research and development and a comparison of results to literature.

09 BIOMASS FUELS↗
DOE OSTI2020

Co-op at Sandia National Laboratories (July - December 2019, Final Report)

This co-op was performed at Sandia National Laboratories (SNL) within the Weapon Surety Engineering 11 Department (9435), which is a customer-focused organization that provides engineering and system analysis expertise to ensure a safe deterrent throughout the entire weapon lifecycle. Engineers in 9435 develop a deep knowledge in both component and system function to support rigorous evaluation and mitigation of potential failure modes. They operate across multiple engineering disciplines (mechanical, electrical, computer, materials and systems engineering) with opportunities to develop crossdisciplinary capability. The team supports a variety of stockpile systems and is part of the product teams during development, design and production, as well as advanced concept and exploratory efforts. 9435 engineers use their extensive component and system knowledge, as well as experimental data and modeling, to ensure products function as intended with assured safety. Members of the department learn the function of multiple components, how those components integrate within the system and apply surety principles and processes to ensure a safe, secure, reliable, and effective U.S. nuclear deterrent.

42 ENGINEERING↗
DOE OSTI2020

Activity Time-Use Patterns and Experienced Satisfaction: Travel Behavioral Dynamics from the 2010–2013 American Time-Use Survey Data

Central to the theory of activity-based approaches is the role of time-use and its impacts on various decision processes related to individual activity-travel patterns, thereby determining ones’ daily well-being. This research aims at quantifying and investigating the underlying correlation of time-use and happiness using the repeated cross-section data from the 2010-2013 American Time Use Survey Well-Being module. The survey specifically records reported levels of activity satisfaction as measured through – happiness, meaningfulness, tiredness, sadness and stress experienced from activity participation. Using these scores, we first construct a composite degree of activity satisfaction that a person experiences using latent class cluster analysis. A series of regression models are then estimated to jointly analyze episodic duration and satisfaction separately for each of years from 2010-2013, by controlling for socioeconomics, household lifecycle stages (29-groups based on age, gender, marital status and presence of children), activity characteristics and global life and health assessment measures. Overall, model estimation results reveal a strong negative correlation between episodic duration and happiness from individual activity engagement patterns. This correlation pattern is temporally stable for the years 2010-2013, with minor variations. Results also suggest that household lifecycle stage has a major impact on activity time-use and satisfaction behavior. Further, single parent and younger couples (25 years to 45 years) with children are more likely to engage in longer and less happy episodes due to family commitments. The model findings also show a strong correlation between health conditions and activity happiness.

Ravulaparthy, Srinath↗
DOE OSTI2021

A machine learning degradation model for electrochemical capacitors operated at high temperature

Electrochemical capacitors (ECs) have only recently been considered as an alternative power source for telemetry sensors of drilling equipment for geothermal or oil and gas exploration. The lifecycle analysis and modelling of ECs is underrepresented in literature in comparison to other storage devices e.g. Li-ion batteries. This paper investigates the degradation of ECs when cycled outside the manufacturer-specified operating temperature envelope and proposes a machine learning-based approach for modelling the degradation. Experimental results show that end of life, defined as a 30% decrease in capacitance, occurs at 1,000 cycles when the environmental temperature exceeds the maximum operating temperature by 30%. The life-cycle test data is then used as an input to a Gaussian process regression (GPR) algorithm to predict the capacitance fade trend. The GPR is validated on a total of nine commercial cells from two different manufacturers, achieving an average root mean squared percent error of less than 2% and a mean calibration score of 93% when referenced to a 95% confidence interval. The model can be utilized to determine the EC degradation rate at a range of operating temperature values.

42 ENGINEERING↗