Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “system analysis module”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Structure-Informed Graph Learning of Networked Dependencies for Online Prediction of Power System Transient Dynamics

Online transient analysis plays an increasingly important role in dynamic power grids as the renewable generation continues growing. Traditional numerical methods for transient analysis not only are computationally intensive but also require precise contingency information as input, and therefore, are not suitable for online applications. Existing online transient assessment studies focus on the determination of post-contingency system stability or stability margin. Here, this paper develops a novel graph-learning framework, Deep-learning Neural Representation or DNR, for online prediction, of the time-series trajectories of the system states using initial system responses that can be measured by phasor measurement units (PMUs). The proposed DNR framework consists of two sequential modules: a Network Constructor that captures network dependencies among generators, and a Dynamics Predictor that predicts the system trajectories. The key to improved prediction performance is the introduction of the spatio-temporal message-passing operations into graph neural networks with structural knowledge. Its effectiveness and scalability are validated through comparative studies, demonstrating the prediction performance under different contingency scenarios for systems of different sizes. This framework provides a solution to online predicting post-fault system dynamics based on real-time PMU measurements. Additionally, it can also be applied to facilitate the offline transient simulation without simulating the entire trajectories.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Overview of the Langmuir probe system on the Mega Ampere Spherical Tokamak (MAST) Upgrade

A detailed description of the Langmuir probe system on Mega Ampere Spherical Tokamak Upgrade is presented. The system features 850 tile-embedded probes and 40 bespoke electronic modules that each have the capability to drive and acquire data from up to 16 probes in a time-multiplexed manner. The system provides spatiotemporal-resolved measurements (1 cm and ~1 ms, respectively) in the divertor region of ion saturation current, electron temperature, and floating potential. The standard interpretation of current-voltage (IV) characteristics is to apply a four-parameter fit, based on unmagnetized probe theory, which includes a linear model for the ion saturation region. In conclusion, to mitigate the effect of the magnetic field, analysis is restricted to the region of the IV characteristic, which is sensitive to only the tail of the electron energy distribution function.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Electromagnetic Transient Simulation of Photovoltaic Inverter Using Implicit-Explicit Solver

This paper introduces the implementation of electromagnetic transient (EMT) simulations of a photovoltaic (PV) inverter module using the Implicit-Explicit (ImEx) solver in the Suite of Nonlinear and Differential/Algebraic Equation Solvers (SUNDIALS). This study demonstrates the effectiveness of the ImEx solver in overcoming the challenges inherent in simulating the complex dynamics of PV inverter modules. Furthermore, using SUNDIALS’ ImEx solver module ARKODE for EMT simulation automates key aspects of the process, such as numerical integration, providing substantial benefits including enhanced consistency, faster implementation, reduced human error, and the capability to handle the complexities of advanced numerical integration. By conducting comparative simulations with an implicit method used in commercial software, the research showcases the ImEx solver’s capability in achieving high accuracy and reliability. Results indicate that leveraging the ImEx approach significantly enhances modeling fidelity and reduces simulation setup times, offering a promising tool for the EMT analysis of PV inverter systems in power electronics-dominated power grids.

Choi, Jongchan [ORNL] (ORCID:000000025952455X)↗
DOE OSTI2025

Pervaporative Dehydration of 2,3-Butanediol by Dense Poly(vinylidene fluoride) Hollow Fiber Membranes: Parameter Estimation, Process Design, and Technoeconomic Evaluation under Uncertainty

Pervaporation, combined with other separation processes, can effectively remove water from fermentation product streams, making it highly suitable for purifying alcohols like 2,3-butanediol (BDO). In this study, a dense poly(vinylidene fluoride) (PVDF) hollow fiber membrane module prototype was fabricated for BDO dehydration, achieving >0.2 LMH total flux and >95% BDO rejection. With a Markov chain Monte Carlo (MCMC) approach, Bayesian inference was used to quantify the uncertainty of the permeance parameters. A membrane cascade model was developed to scale up a process that purifies a preconcentrated BDO feed (70 wt %) to high purity (90 wt %). Through propagation of the uncertainty of the parameters and sensitivity analyses of the process variables, a cascade design was recommended. Despite data and model limitations, the framework enabled a reliable system analysis and economic evaluation, validated through tight confidence intervals in key process metrics, establishing the foundation for future applications of Bayesian methods in membrane-based processes.

Animal feed↗
DOE OSTI2021

Comparison of human poly-N-acetyl-lactosamine synthase structure with GT-A fold glycosyltransferases supports a modular assembly of catalytic subsites

Poly-N-acetyl-lactosamine (poly-LacNAc) structures are composed of repeating [-Galβ(1,4)-GlcNAcβ(1,3)-]n glycan extensions. They are found on both N- and O-glycoproteins and glycolipids and play an important role in development, immune function, and human disease. The majority of mammalian poly-LacNAc is synthesized by the alternating iterative action of β1,3-N-acetylglucosaminyltransferase 2 (B3GNT2) and β1,4-galactosyltransferases. B3GNT2 is in the largest mammalian glycosyltransferase family, GT31, but little is known about the structure, substrate recognition, or catalysis by family members. Here we report the structures of human B3GNT2 in complex with UDP:Mg 2+ and in complex with both UDP:Mg 2+ and a glycan acceptor, lacto-N-neotetraose. The B3GNT2 structure conserves the GT-A fold and the DxD motif that coordinates a Mg 2+ ion for binding the UDP-GlcNAc sugar donor. The acceptor complex shows interactions with only the terminal Galβ(1,4)-GlcNAcβ(1,3)- disaccharide unit, which likely explains the specificity for both N- and O-glycan acceptors. Modeling of the UDP-GlcNAc donor supports a direct displacement inverting catalytic mechanism. Comparative structural analysis indicates that nucleotide sugar donors for GT-A fold glycosyltransferases bind in similar positions and conformations without conserving interacting residues, even for enzymes that use the same donor substrate. In contrast, the B3GNT2 acceptor binding site is consistent with prior models suggesting that the evolution of acceptor specificity involves loops inserted into the stable GT-A fold. These observations support the hypothesis that GT-A fold glycosyltransferases employ coevolving donor, acceptor, and catalytic subsite modules as templates to achieve the complex diversity of glycan linkages in biological systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Creating a Simulation Platform for Research and Development of Advanced Control Methods

Advanced nuclear reactors are essential to meet the changing energy requirements throughout both the United States and the rest of world. In addition to other features, they are designed to enable deployment in remote locations and operate in a fully (or near-fully) autonomous manner, which will require a new control paradigm. To realize autonomously operating reactors, the U.S. Department of Energy’s Nuclear Energy Enabling Technologies Advanced Sensors and Instrumentation (NEET ASI) program conducts research and development into the enabling technologies and methods needed, including digital twins, machine learning, and risk modeling, in addition to various types of control methods. These technologies and methods are the key foundations needed to achieve fully autonomous systems. To develop and evaluate the technologies and methods necessary for achieving autonomous operations, it is critical to identify a software tool capable of integrating all the required elements. In surveying the available solutions, no software platforms were identified that could accomplish what was needed without introducing drawbacks. This challenge was the motivation for the current effort: to develop a software platform that can seamlessly integrate autonomouscontrol-enabling technologies and methods, allowing for accelerated research and development and transfer of ideas. The resulting platform, known as the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND), is Python-based, and leverages open-source tools to provide flexibility and facilitate building upon prior research. It is designed to enable advanced reactor developers to deploy and test advanced control technologies and methods coupled with their own models, solutions, and hardware. Given the substantial undertaking of developing such a platform, the current effort focused on laying down scalable, flexible software foundations and infrastructure, then demonstrating the platform via a use case. These foundations included developing generic modules, which contain the base variable and system blocks (the information and functional building blocks, respectively, that can be used to design a simulation) and the data handling and storage blocks needed to exchange information between the various blocks; as well as enablingtechnology-specific modules. This platform was evaluated via a use case, which was to simulate and control a process for the Microreactor Automated Control System (MACS) test bed. While MACS is not currently directly coupled to any specific microreactor physics, it was initially developed in concert with the Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and so the MARVEL physics are used here. As part of this use case, several enabling-technology-specific blocks within COMMAND were integrated, including a proportional integral derivative (PID) control block, a Reactor Excursion and Leak Analysis Program (RELAP5-3D) block, and an anomaly detection block. The COMMAND software platform was successfully demonstrated to achieve the scalability and flexibility objectives of this effort and will be leveraged by the program’s research efforts to advance state of the art control methodologies towards autonomous operations of advanced reactors. As new use cases are created and implemented, it is anticipated that COMMAND will continue to grow and evolve to meet new requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Highly Efficient Regeneration Module for Carbon Capture Systems in NGCC Applications

The objective of this project is to design, fabricate, and test a highly efficient regeneration module capable of providing an ultra-lean absorption solution that is required for capturing CO 2 from dilute sources at 95% or better efficiency. By integrating this advanced regenerator module with SRI International’s Mixed Salt Process (MSP) absorption modules, SRI expects to demonstrate significant progress toward a reduction in cost of capture versus the DOE reference natural gas combined cycle (NGCC) plant with carbon capture. SRI designed, built, and tested an advanced stripper to enhance the performance of SRI’s MSP for CO 2 capture – a transformational ammonia-based solvent technology – for natural gas (NG) power sources. The testing of the advanced stripper for MSP was conducted at an SRI site using a simulated flue gas stream equivalent to about 10 kWe. The research work included modeling of the advanced stripper and integrating it with the MSP absorbers; studying the strategies for producing very highly alkaline lean solvent with minimized emissions; operating the stripper with advanced heat integration to improve process efficiencies; and collecting critically important data for a detailed techno-economic analysis (TEA). The project tasks were designed to address concerns relating to scale-up and integration of the technology to NG power plants—more specifically, to maximize the carbon capture efficiency achievable with MSP and identify pathways to achieve higher capture efficiencies and ultimately zero net carbon emissions. SRI teamed up with a process modeling company (OLI Systems), a process and chemical engineering company (Trimeric Corporation), and a cost-sharing commercial partner (Baker-Hughes – a leading multinational company that designs, manufactures, and services transformative energy technologies) to execute the project. The research findings will accelerate the MSP development and pave the way for the technology to reach the DOE’s goal, and ultimately commercialization of the MSP technology for low-cost CO 2 capture from NGCC flue gas and other dilute CO 2 sources.

03 NATURAL GAS↗
DOE OSTI2020

Deconstructing the Soil Microbiome into Reduced-Complexity Functional Modules

The soil microbiome is an invaluable component of the biosphere and critical for ecosystem functions, including biogeochemical cycling, soil-atmosphere gas exchange, degradation of toxic compounds, and promotion of plant growth and stress resistance/resilience. An improved understanding of the soil microbiome will help with predicting how these processes respond to external perturbations, and with harnessing beneficial aspects of the soil microbiome for agronomic applications such as crop amendments. However, the extensive taxonomic and functional diversity inherent within the soil microbiome hinders efficient analysis of this system. Microbial biodiversity in soils is orders of magnitude greater than other commonly studied systems such as the human gut microbiome (Blum, Zechmeister-Boltenstern, and Keiblinger 2019; Berendsen, Pieterse, and Bakker 2012). Thousands of microbial taxa may be found in a single gram of soil (Roesch et al. 2007), and high rates of gene flow and mutation further promote microbial diversification (Sergaki et al. 2018). Concomitantly, functional diversity in soil is similarly extensive. Soil is a heterogeneous mixture of microenvironments with defined physical and chemical attributes (Bach et al. 2018), within which numerous microbial guilds of distinct life-strategies and metabolic capacities can be found (Perez-Garcia, Lear, and Singhal 2016; H.-S. Song et al. 2014). Furthermore, the soil microbiome harbors a significant fraction of rare and/or quiescent members (Blagodatskaya and Kuzyakov 2013) that exist below the threshold of detection of current technologies. Such rare taxa may make significant contributions to process rates (Shade and Gilbert 2015; Dawson et al. 2017), but their scarcity complicates their identification and analysis. Finally, the vast amounts of information generated through holistic analyses of soil communities represent an intense computational burden (Scholz, Lo, and Chain 2012; Prosser 2015) that precludes assessment of the complete functional and taxonomic diversity contained in this ecosystem.

Naylor, Dan T.↗
DOE OSTI2025

SOHIP Abel Transform and Onion Peeling Model Module

This software provides tools for analyzing and modeling physical systems using mathematical transforms and layered models. It includes (1) functions for performing the Abel transform, which is used to relate measurements of bending angles to properties such as refractive index and radius in a medium. The code can compute bending angles from input profiles and also reconstruct these profiles from observed data; (2) the functions for modeling systems with multiple layers using an onion-peeling approach, allowing users to simulate and analyze the behavior of layered materials or structures. These capabilities are useful for researchers and engineers working in fields such as optics, atmospheric science, and materials analysis, enabling them to interpret and model data from experiments or simulations relates to refraction in spherical symmetric medium.

Xu, Shuang [Lawrence Livermore National Laboratory↗
DOE OSTI2020

reV (The Renewable Energy Potential Model - Open Source) [SWR-21-59, SWR-20-20 and SWR-17-34]

The Renewable Energy Potential (reV) model is a platform for the detailed assessment of renewable energy resources and their geospatial intersection with grid infrastructure and land use characteristics. The reV model currently supports photovoltaic (PV), concentrating solar power (CSP), and land-based wind turbine technologies. Modules in the reV framework function at different spatial and temporal resolutions, allowing for the assessment of resource potential, technical potential, and supply curves at varying levels of detail. The platform runs on the National Renewable Energy Laboratory’s (NREL’s) high-performance computing system, providing scalable and efficient performance from a single location up to a continent, for a single year or decades of time-series resource data. Coupled with NREL’s System Advisor Model (SAM), reV supports resource assessments from 5-minute to hourly temporal resolutions and supports the analysis of long-term (i.e., year-on-year) variability of renewable generation (e.g., interannual variability and exceedance probabilities).

Maclaurin, Galen↗
DOE OSTI2022

A System Engineering Approach in the Analysis of Ionic Liquids Properties [Thesis]

Room temperature ionic liquids (RTIL) are ionic compounds, comprised of a cation and anion, in the liquid state at temperatures below 100 ⁰C. There are estimated 10 18 anion and cation combinations, which can create RTILs with unique properties. While the ionic character of RTILs made them attractive in a wide variety of electrochemical applications, their behaviors under electrochemical conditions are not well understood. In this research, we developed a RTIL testbed to investigate how RTILs differ from molecular solvents and electrolytes in electrochemical systems through the study of the effects of their morphology and chemical properties on the electron transfer processes. The test bed is composed of three modules: Electrochemistry, Material characterization, Computational. All modules have been completely developed, verified, and integrated and two of them, i.e., Electrochemistry and Material characterization have been validated in this dissertation. To evaluate the proposed system, experiments were performed on solutions of a redox active species in RTILs. It was found that it is possible to investigate the RTIL's morphology and chemical properties' impact on the electron transfer processes of the solute based on the outcomes and evaluations of tests performed by the RTIL testbed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Onymous early‐life performance degradation analysis of recent photovoltaic module technologies

Abstract The cost of photovoltaic (PV) modules has declined by 85% since 2010. To achieve this reduction, manufacturers altered module designs and bill of materials; changes that could affect module durability and reliability. To determine if these changes have affected module durability, we measured the performance degradation of 834 fielded PV modules representing 13 module types from 7 manufacturers in 3 climates over 5 years. Degradation rates ( Rd ) are highly nonlinear over time, and seasonal variations are present in some module types. Mean and median degradation rate values of −0.62%/year and −0.58%/year, respectively, are consistent with rates measured for older modules. Of the 23 systems studied, 6 have degradation rates that will exceed the warranty limits in the future, whereas 13 systems demonstrate the potential of achieving lifetimes beyond 30 years, assuming Rd trends have stabilized.

14 SOLAR ENERGY↗
DOE OSTI2026

Performance and Stability Characterization of the ICARUS Light Detection System

The ICARUS detector, a key component of the Short Baseline Neutrino (SBN) Program at Fermilab, consists of two identical T300 modules filled with liquid argon. It is equipped with a Light Detection System (LDS) based on 360 8-inch Hamamatsu R5912-MOD photomultiplier tubes (PMTs) arranged behind the wire planes to collect Vacuum Ultraviolet (VUV, $\sim$ 128 nm) scintillation light. Operating under cryogenic conditions ( $\sim$ 87 K), the LDS is essential for determining the event start time (t0) with nanosecond precision for beam spill synchronization, improving longitudinal spatial resolution, and contributing to the event trigger and cosmic-ray mitigation. The performance of the LDS was investigated addressing both hardware and data analysis aspects. Following a progressive degradation in PMT gain observed during operations at FNAL, systematic gain measurements were first carried out from room temperature down to low temperatures. The results show stable performance at room temperature but a significant, irreversible reduction in gain at low temperatures. Based on these findings, a series of mitigation strategies were implemented in the ICARUS detector to preserve PMT performance and ensure reliable cryogenic operation. Currently, ongoing waveform analysis of the PMT signals is being performed to characterize signal shape, charge integration, and timing properties, aiming to refine and improve the agreement between experimental data and Monte Carlo simulations.

Saia, Clara [U. Catania (main); INAF, Catania; Cat↗
DOE OSTI2025

Quasi-optical beam tracing module development for millimeter-wave high-wavenumber collective scattering on the NSTX-U and EAST tokamaks

A Python3-based beam tracing code utilizing Quasi-Optics has been developed to track both incident and receiving beams in high-k collective millimeter wave scattering systems within magnetic fusion plasmas. In contrast to existing ray tracing codes that solely consider refraction, this beam tracing code incorporates diffraction phenomena, providing a more comprehensive calculation. Here, this enhanced capability allows for a more accurate calculation of the scattering volume and spatial resolution in high-k collective scattering systems, crucial for evaluating system performance and facilitating data analysis. Unlike Geometrical Optics, Quasi-Optics employs the complex eikonal method, representing a Gaussian beam as a collection of coupled rays to accurately preserve diffraction characteristics. The developed code is intended for application in NSTX-Upgrade and EAST high-k beam tracing analyses, targeting frequencies of 693 GHz and 270 GHz, respectively. The high-k system's primary objective is the observation of electron-scale instabilities. Employing a symplectic integrator, the code ensures numerical accuracy, assessed through the conservation of the Hamiltonian. With its precision and efficiency, the code facilitates rapid inter-shot analyses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

SCALE modeling of foil irradiations at WSU’s TRIGA with sensitivity/uncertainty analysis

We report the Washington State University TRIGA reactor was modeled in the SCALE system’s KENO neutron transport code. The model includes 119 fuel rods, a central boral control rod, 4 control blades, 5 irradiation ports, and 20 graphite reflector blocks within a rectangular aluminum grid box. The model accurately simulated the irradiation of depleted uranium and highly enriched uranium foils and predicted reaction rate ratios for 238 U(n,2n) 237 U / 238 U(n,γ) 239 U and 99 Mo / fission, which compared favorably to empirical values previously measured at Los Alamos. Finally, a sensitivity/uncertainty analysis was performed using the continuous-energy TSUNAMI-3D module of SCALE.

237Np↗
DOE OSTI2025

Web-Based Tools for Data-Informed Remedy Optimization: Software Theory and User Guide

This report documents the development and application of two web-based decision-support tools for pump-and-treat (P&T) groundwater remediation systems: PTOLEMY (Pump-and-Treat Optimized Location Evaluation to Maximize Yields) and OPTIMA (Optimization for Pump-and-Treat Implementation, Management, & Assessment). These tools enhance remedy design and management by leveraging advanced computational methods – specifically deep learning and multi-objective optimization – within a user-friendly platform. By integrating data-driven models with established hydrogeological knowledge, PTOLEMY and OPTIMA enable more efficient evaluation of well placement and operational strategies, helping site managers balance multiple remediation objectives under complex conditions. Both tools are implemented as modules within the SOCRATES (Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites) web platform, which provides data access, visualization, and analytics to support remedy optimization across sites in the U.S. Department of Energy Office of Environmental Management complex. PTOLEMY is a rapid screening module designed to identify promising locations for new extraction wells. It employs a multi-channel three-dimensional convolutional neural network (MC3D-CNN) trained on high-fidelity simulation data to predict the relative performance (in terms of contaminant mass recovery) of potential well sites. Through an interactive web interface, PTOLEMY visualizes the probability of high performance across a site, highlighting areas where an extraction well is likely to yield above-threshold contaminant removal over a multi-year period. PTOLEMY’s map-based displays and exportable results support transparent communication of screening analyses. By focusing attention on the most favorable candidate locations, the tool augments traditional engineering judgment and physics-based modeling, providing a data informed basis for subsequent detailed evaluations. OPTIMA is a multi objective optimization module designed to find wellfield layouts and operating schedules that meet various cleanup goals. It quickly evaluates thousands of candidate setups – combinations of well locations, timing, and rates – and returns a small set of best trade-off options for comparison. At its core, OPTIMA uses a U-Net-based surrogate model – a deep-learning emulator of a groundwater flow and transport simulator – to dramatically accelerate scenario evaluations. Coupling this fast surrogate with the NSGA-II (Non-dominated Sorting Genetic Algorithm II) evolutionary algorithm, OPTIMA explores a wide decision space of well locations and schedules to identify Pareto-optimal solutions that trade off key objectives (e.g., minimizing cleanup time, maximizing contaminant mass removal, and minimizing plume extent). The tool outputs a family of optimal configurations and visualizes their trade-offs (Pareto frontiers of cleanup metrics and maps of optimized well placements). Site managers can use these results to understand the range of viable strategies and to select candidate designs for more detailed verification. OPTIMA is currently under active development and not yet fully released; this guide provides early documentation to support planning and gather user feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Spatially resolved charge-transfer kinetics at the quantum dot–microbe interface using fluorescence lifetime imaging microscopy

Integrating the optoelectronic properties of quantum dots (QDs) with biological enzymatic systems to form microbe-semiconductor biohybrids offers promising prospects for both solar-to-chemical conversion and light-modulated biochemical processes. Developing these nano–bio hybrid systems necessitates a deep understanding of charge-transfer dynamics at the nano–bio interface. Photoexcited carrier transfer from QDs to microbes is driven by complex interactions, with emerging insights into the relevant thermodynamic and kinetic factors. The heterogeneities of both microbes and QD ensembles pose significant challenges in mechanistic understanding, which is critical for designing advanced nano–bio hybrids. We used fluorescence lifetime imaging microscopy to analyze charge transfer between a CdSe QD film andShewanella oneidensismicrobes. We correlated the spatiotemporal fluorescence data with an analytical model. Our analysis revealed two distinct distributions of QD de-excitation pathways. The characteristics of these distributions: 1) a faster transfer rate ( k ¯ E T 1 = 1.5 10 9 s - 1 ), with a lower acceptor number ( N ¯ a 1 = 0.03 ) and 2) a slower transfer rate ( k ¯ E T 2 = 4.1 10 8 s - 1 ) with a higher acceptor number ( N ¯ a 2 = 0.18 ). We assign these distributions to the indirect and direct electron transfer mechanisms, respectively. Our findings demonstrate how spectroscopic imaging can uncover fundamental electron transfer mechanisms at complex interfaces, offering valuable design principles for future nano–bio hybrids.

Science & Technology - Other Topics↗
DOE OSTI2024

Bifacial Photovoltaic Module Degradation Dynamics

In a comprehensive study conducted at NREL's 75 kW bifacial single-axis-tracked field, accelerated degradation was observed in four out of five bifacial silicon photovoltaic (PV) module technologies when compared to their monofacial counterparts. Root cause analysis of accelerated bifacial degradation involved various analytical tools and techniques. This included employing RdTools to identify rates of power loss, conducting measurements on fielded and control modules using infrared imaging, electroluminescence (EL) and photoluminescence (PL), quantum efficiency (QE) analysis, IV-curves assessment, as well as utilizing handheld Raman and reflectance measurement targeted at anti-reflective coating. Most cases pointed to carrier lifetime degradation causing Voc loss and simultaneous Isc loss. In some cases, Isc further decreases likely due to optical effects from encapsulant degradation. The outcomes and methodologies employed in this investigation are documented in this publication. This study's significance is further emphasized by placing the findings within the broader context of the performance and degradation of various bifacial systems, as identified in the PV Fleets data.

bifacial↗