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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

BETO 2021 Peer Review - Analytical Development and Standardization for Biomass-Derived Thermochemical Liquids

This project began in FY14 to address the lack of standard chemical characterization analytical methods for bio-oils. Bio-oils are very complex and present numerous analytical challenges; yet reliable chemical information (quantification of both individual compounds and chemical functional groups) is needed to inform upgrading research and refinery co-processing. In this project, analysis needs are first determined from engaging the bioenergy community. Next, standard methods are developed to meet these needs, and then subsequently validated via inter-laboratory studies. Methods that are successfully validated (< 10% variability) are then shared as Laboratory Analytical Procedures (LAPs), which are free and publicly available. We have been tracking LAP use and have seen sustained usage as evidenced by an average of 500 pages views and 100 downloads per quarter, demonstrating the value of these methods to the bioenergy community. LAP methods that are particularly useful and reliable will be chosen for the next-level of standardization through ASTM. We have recently achieved approval by ASTM for our carbonyl titration method. This method (ASTM E3146) is the first example of an ASTM standard solely focused on the chemical characterization of bio-oils. Work in this project is meeting the analysis needs of the bioenergy community and will ultimately help enable the commoditization of bio-oils.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Real-Time Model-Adaptive Relaying Applied to Microgrid Protection

In microgrids, the short-circuit current magnitude is significantly limited by more than an order of magnitude due to the relatively small inverter-based resources. Commercially available protective devices for distribution cannot reliably protect a microgrid due to their dependence on the magnitude of the fault current. Moreover, overcurrent relays typically cannot function properly for a microgrid because they are incapable of detecting faults and/or performing the coordination between the relays in inverter-based microgrids operated in the islanded mode. This paper proposes a model-adaptive relay designed to adjust the relay curves based on the available generation and the network topology. The proposed method runs a real-time model of the microgrid, which gathers information from the network to calculate the available short-circuit current in the specified node. The fault current from the model is then used for the adaptive algorithm to calculate the relay settings, considering coordination with the downstream fuses and upstream reclosers. This work presents the validation of the proposed method in Hardware-in-the-Loop, in a hardware testbed as well as field deployed in a real microgrid in East-Tennessee.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Comparative Analysis of Radial and Random Microstructures of Mesophase Pitch Carbon Fibers

Carbon fibers (CF) with radial and random microstructures are produced. Here, these fibers are subjected to identical treatment before being mechanically tested and analyzed with Weibull analysis, with the results revealing a statistically significant difference in tensile strengths of 2.23 GPa for random CF and 1.69 GPa for radial CF. Raman mapping probed the crystalline structure perpendicular to the fiber axis and found a uniform structure, while wide‐angle X‐ray diffraction showed a significant difference of 7.5 Å in the crystallites’ basal lengths parallel to the fiber. Small‐angle X‐ray scattering is completed parallel to the fiber for the first time. A cross‐section Guinier plot of the 1D azimuthal integration is generated assuming symmetric scattering, and the parallel scatterers are found to have a similar length scale to the crystallite's length, validating the testing method. Finally, transmission electron microscopy is completed on the longitudinal cross‐section of each fiber. The radial carbon fiber is found to have a core–shell structure, as evidenced further by fast Fourier transform images. Through all studies, it is shown that the structure developed during mesophase pitch spinning altered the microstructure, thus impacting the mechanical properties, confirming a direct relationship between processing, structure, and properties.

Scherschel, Alexander [Univ. of Virginia, Charlott↗
DOE OSTI2021

Chemometric optimisation of pressurised liquid extraction for the determination of alliin and S‐allyl‐cysteine in giant garlic ( Allium ampeloprasum L.) by liquid chromatography tandem mass spectrometry

Abstract Introduction Giant garlic is a functional food that contains different kinds of bioactive molecules with beneficial effects on chronic noncommunicable diseases like diabetes and cardiovascular conditions. Considering biosynthesis pathways, abundance, and biological activity, alliin and S‐allyl‐cysteine were used as chemical markers of organosulphur compounds present in giant garlic. Objective To establish a chemometric optimisation of pressurised liquid extraction for the determination of alliin and S‐allyl‐cysteine in giant garlic by liquid chromatography tandem mass spectrometry (LC–MS/MS). Methodology Samples were blanched (ca. 90°C for 10 min) to inactivate alliinase and γ‐glutamyl transpeptidase enzymes and then freeze‐dried. Chemometric optimisation was performed via response surface methodology based on central composite design (CCD). Organosulphur compound yields were determined applying a validated LC–MS/MS method in multiple reaction monitoring (MRM) mode using the following transitions: for alliin m/z 178 → 74 and for S‐allyl‐cysteine m/z 162 → 41. Results According to CCD results, under constant conditions of pressure (1500 psi) and time (20 min), the optimal conditions for pressurised liquid extraction of alliin and S‐allyl‐cysteine were 70.75 and 68.97% v/v of ethanol in extraction solvent and 76.45 and 98.88°C as extraction temperature, respectively. Multiple response optimisation for the simultaneous extraction of both organosulphur compounds was established via desirability function. Under these conditions, 2.70 ± 0.27 mg g −1 dry weight (DW) of alliin and 2.79 ± 0.22 mg g −1 DW of S‐allyl‐cysteine were extracted. Conclusions These results clearly demonstrated that pressurised liquid extraction is an efficient green technique to extract bioactive organosulphur compounds from giant garlic. Extraction yields were significantly ( p < 0.05) higher than those obtained with conventional ultra‐turrax extraction.

Peterssen‐Fonseca, Darlene↗
DOE OSTI2022

Collaborative Study for Certification of Trace Elements in Uranium Ore Concentrate CRMs UCLO-1, UCHI-1, and UPER-1

Trace impurity patterns are important nuclear forensic signatures in uranium ore concentrates (UOCs) and Certified Reference Materials (CRMs) are used to validate the analysis methods employed by end users. Herein, we discuss the certification campaign for three new UOC CRMs from the National Research Council Canada: UCLO-1 (https://doi.org/10.4224/crm.2020.uclo-1), UCHI-1 (https://doi.org/10.4224/crm.2020.uchi-1), and UPER-1 (https://doi.org/10.4224/crm.2020.uper-1). This study involved 15 laboratories from 10 countries, using sector-field and (triple) quadrupole inductively-coupled plasma mass spectrometry to analyze 64 trace element impurities. We discuss the importance of the acids used for sample digestion, difficulties analyzing in a high uranium matrix, and data combination and uncertainty evaluation for this large dataset.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

Predicting System Response at Unmeasured Locations

Traditional techniques to derive dynamic specification for components have a great deal of uncertainty. One of the major sources of uncertainty is that the number of response measurements in the operational system environment is insufficient to determine the component motion. This inadequacy is due to logistical limitations for data recording in field testing and space limitations for accelerometers, strain gages and associated wiring. Available measurements are often some distance from the component and therefore do not represent component motion. Typical straight-line envelopes of these unrepresentative measurements guarantee an increase in the uncertainty. In this paper multiple methods are attempted to expand a sparse set of field test measurements on a system to responses of interest that cannot be measured in the field due to the limitations. Proof of concept is demonstrated on the Modal Analysis Test Vehicle (MATV). The responses of interest, known as “truth responses”, are measured in a system vibration environment along with an optimized sparse set of 30 field responses. Methods to expand the field responses to the truth responses are demonstrated by comparing the acceleration spectral density of the expanded response to the measured response. Two methods utilize a validated finite element model of the MATV. One is developed from purely experiment based frequency response functions of a laboratory pre-test. Finally, these approaches are designed to drastically reduce the uncertainty of the component in-service motion as a basis for developing specifications that are guaranteed to be conservative with a known (instead of unknown) conservatism.

42 ENGINEERING↗
DOE OSTI2025

Harnessing on-machine metrology data for prints with a surrogate model for laser powder directed energy deposition

In this study, we leverage the massive amount of multi-modal on-machine metrology data generated from Laser Powder Directed Energy Deposition (LP-DED) to construct a comprehensive surrogate model of the 3D printing process. By employing Dynamic Mode Decomposition with Control (DMDc), a data-driven technique, we capture the complex physics inherent in this extensive dataset. This physics-based surrogate model emphasizes thermodynamically significant quantities, enabling us to accurately predict key process outcomes. The model ingests 21 process parameters, including laser power, scan rate, and position, while providing outputs such as melt pool temperature, melt pool size, and other essential observables. Furthermore, it incorporates uncertainty quantification to provide bounds on these predictions, enhancing reliability and confidence in the results. We then deploy the surrogate model on a new, unseen part and monitor the printing process as validation of the method. Our experimental results demonstrate that the predictions align with actual measurements with high accuracy, confirming the effectiveness of our approach. Furthermore, this methodology not only facilitates real-time predictions but also operates at process-relevant speeds, establishing a basis for implementing feedback control in LP-DED.

Digital twins↗
DOE OSTI2026

Extending SLUSCHI for Automated Diffusion Calculations

We present an extension of the SLUSCHI package (Solid and Liquid in Ultra Small Coexistence with Hovering Interfaces) to enable automated diffusion calculations from first-principles molecular dynamics. While the original SLUSCHI workflow was designed for melting temperature estimation via solid-liquid coexistence, we adapt its input and output handling to isolate the volume search stage and generate one production trajectory suitable for diffusion analysis. Post-processing tools parse VASP outputs, compute mean-square displacements (MSD), and extract tracer diffusivities using the Einstein relation with robust error estimates through block averaging. Diagnostic plots, including MSD curves, running slopes, and velocity autocorrelations, are produced automatically to help identify diffusive regimes. The method has been validated through representative case studies: self-diffusion in Al-Cu liquid alloys, sublattice melting in Li7La3Zr2O12 and Er2O3, interstitial oxygen transport in bcc and fcc Fe, and oxygen diffusivity in Fe-O liquids with variable Si and Al contents. Viscosity and diffusivity are linked through the Stokes-Einstein relation, with composition dependence assessed via simple linear mixing. This capability broadens SLUSCHI from melting-point predictions to transport property evaluation, enabling high-throughput, fully first-principles datasets of diffusion coefficients and viscosities across metals and oxides.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Determination of transition metal ions in fossil fuel associated wastewaters using chelation ion chromatography

Here, this study outlines the development and subsequent validation of a method using chelation ion chromatography (CIC) pretreatment followed by traditional ion chromatography (IC) and post column UV/vis detection to measure transition metals in fossil fuel wastewaters, such as oil &amp; gas (O&G) brines and coal mine drainage (CMD) waters. Measurement of transition metals is often an important characterization step in the research of environmental and energy systems. IC represents one way to measure these metals with the advantages of being versatile, simple and relatively low cost compared to other analytical methods. However, high concentrations of alkali and alkaline earth metals present in fossil fuel wastewaters will decrease IC detectability of transition metals in these waters. In this study, a CIC method was developed for the analysis of transition metal ions (Fe 3+ , Cu 2+ , Ni 2+ , Zn 2+ , Co 2+ , Mn 2+ , and Fe 2+ ) in fossil fuel associated wastewaters such as Appalachian CMD and O&G wastewaters from the Permian and Bakken shale basins in the United States. CIC system incorporated an on-line chelator column (e.g., the MetPac CC-1) with high selectivity for transition metals over alkali and alkaline earth metals for salt matrix removal prior to transition metal separation and detection. Additional method developments also included acidifying all samples to 2% v/v HCl and using gradient elution rather than isocratic. The recoverability of transition metals in simple salt solutions commonly found in CMD and brine samples (e.g. NaCl, Na 2 SO 4 , CaCl 2 ) using CIC was evaluated and compared to that using traditional IC. Our results found that the CIC system significantly improved transition metal recoveries for samples in 10,000 mg/L CaCl 2 matrix, reaching 87%-108% recovery for all analytes, as opposed to 2-323% recovery in traditional IC. The limits of detection in this study achieved 10.09 – 161.2 μg/L, comparable to reported values in similar IC studies. The developed method was also verified with certified water samples, resulting in 89% - 111% recoveries in samples with higher analyte concentrations (i.e. >4x the LoDs). The developed method achieved 87% -112% recoveries for most analytes in CMD samples and 72%-138% recoveries for Bakken shale samples, relative to ICP-MS values. Overall, the current IC method can be a very good screening tool for fast and cheap analysis for transition metals at mg/L level, to facilitate selection of samples for more detailed ICP-MS analysis.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Parallel diffusion operator for magnetized plasmas with improved spectral fidelity

Diffusive transport processes in magnetized plasmas are highly anisotropic, with fast parallel transport along the magnetic field lines sometimes faster than perpendicular transport by orders of magnitude. This constitutes a major challenge for describing non-grid-aligned magnetic structures in Eulerian (grid-based) simulations. Here, the present paper describes and validates a new method for parallel diffusion in magnetized plasmas based on the anti-symmetry representation [Halpern and Waltz, Phys. Plasmas 25, 060703 (2018)]. In the anti-symmetry formalism, diffusion manifests as a flow operator involving the logarithmic derivative of the transported quantity. Qualitative plane wave analysis shows that the new operator naturally yields better discrete spectral resolution compared to its conventional counterpart. Numerical simulations comparing the new method against existing finite difference methods are carried out, showing significant improvement. In particular, we find that combining anti-symmetry with finite differences in diagonally staggered grids essentially eliminates the so-called “artificial numerical diffusion” that affects conventional finite difference and finite volume methods.

Anisotropic diffusion↗
DOE OSTI2020

Generating realistic building electrical load profiles through the Generative Adversarial Network (GAN)

Building electrical load profiles can improve understanding of building energy efficiency, demand flexibility, and building-grid interactions. Current approaches to generating load profiles are time-consuming and not capable of reflecting the dynamic and stochastic behaviors of real buildings; some approaches also trigger data privacy concerns. In this study, we proposed a novel approach for generating realistic electrical load profiles of buildings through the Generative Adversarial Network (GAN), a machine learning technique that is capable of revealing an unknown probability distribution purely from data. The proposed approach has three main steps: (1) normalizing the daily 24-hour load profiles, (2) clustering the daily load profiles with the k-means algorithm, and (3) using GAN to generate daily load profiles for each cluster. The approach was tested with an open-source database – the Building Data Genome Project. We validated the proposed method by comparing the mean, standard deviation, and distribution of key parameters of the generated load profiles with those of the real ones. The KL divergence of the generated and real load profiles are within 0.3 for majority of parameters and clusters. Additionally, results showed the load profiles generated by GAN can capture not only the general trend but also the random variations of the actual electrical loads in buildings. We report the proposed GAN approach can be used to generate building electrical load profiles, verify other load profile generation models, detect changes to load profiles, and more importantly, anonymize smart meter data for sharing, to support research and applications of grid-interactive efficient buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

A Decomposition-Based Learn-To-Optimize Approach with Feasibility Layer Assistance for Sub-Hourly Unit Commitment

Sub-hourly unit commitment (UC) with 15-min intervals is gaining significant attention as a way to respond rapidly to the fluctuations in electricity supply and demand introduced by renewable resources. However, the increased temporal resolution and complex inter-temporal dependencies pose substantial computational challenges for traditional optimization methods. To this end, this paper explores a decomposition-based learn-to-optimize approach. Building on recent advances in machine learning, our method revisits the long- overlooked Lagrangian relaxation framework, which is a classical decomposition technique that enables tractable subproblem solving. These smaller subproblems are inherently well-suited for machine learning, as their reduced dimensionality and structural regularity allow predictive models to efficiently learn and generalize solution patterns. We thus propose a generic predictive model, which embeds Gated Recurrent Units (GRUs) and Attention in the encoder-decoder structure, and integrate a rule-based feasibility layer to capture temporal dependencies, reduce training effort, and improve feasibility w.r.t. unit-level constraints. Our method has been validated on the IEEE 118-bus system, demonstrating promising performance in solving sub-hourly UC problems efficiently and feasibly.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Rapid prediction of fuel research octane number and octane sensitivity using the AFIDA constant-volume combustion chamber

Current research octane number (RON) and motor octane number (MON) gasoline performance characterization techniques use dated, complex engine testing methodology and limit researchers’ ability to easily characterize small volumes of experimental fuels. A novel methodology is presented that correlates measured ignition delay (ID) time to RON in an Advanced Fuel Ignition Delay Analyzer (AFIDA) constant-volume combustion chamber device at a single pressure/temperature condition, with an r2 of 0.99 and standard error (SE) of 1.0. The correlation of the slope of the ID time between two additional temperature points to octane sensitivity (S) produces an r2 of 0.97 and SE of 0.69; however, fuels with S>12 are indistinguishable. These results are based on methodology calibration using 31 primary and toluene reference fuels containing 0%-40% ethanol with RON values ranging from 85 to 113. Validation of these methods using a 102-sample fuel matrix spanning an array of base fuels and additive chemistry designed to test the robust applicability of the method, along with pump gasoline and high-octane surrogate blend samples, demonstrates an r2 of 0.94 and SE of 1.3 for the RON correlation over all samples, whereas the equivalent S correlation produces an r2 of 0.78 and SE of 1.2 by excluding two additives, 3-pentanone and diisobutylene, which displayed poor S correlation results. This novel AFIDA analysis method can be performed in 1 h and with 40 mL of fuel, offering significant improvements in time and volume requirements over traditional techniques.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Periodic boundary conditions for arbitrary deformations in molecular dynamics simulations

A generalization of the Lees-Edwards periodic boundary conditions (gLE-PBC) for molecular dynamics (MD) simulations is developed to allow for arbitrary deformations to be applied to the domain. The gLE-PBC domain remains a rectangular cuboid regardless of the applied deformation in contrast with the Lagrangian-rhomboid periodic boundary conditions (LR-PBC) where the domain deforms according to the applied deformation. Furthermore, the kinematics of gLE-PBC are validated against pure shear. The gLE-PBC method for interacting systems is then validated against the LR-PBC method and analytical solutions for a solid under isotropic compression, one-dimensional shearing, three-dimensional extension and shearing and for a liquid under Couette flow. Bulk physical properties extracted from the gLE-PBC simulations agree well with values calculated from equilibrium MD simulations. Three dimensional shearing and a deformation with a full velocity gradient matrix are also simulated, showing the range of problems gLE-PBC can explore.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Using SIMS to decode noisy stratigraphic δ 13 C variations in Ediacaran carbonates

Carbonate carbon isotope (δ 13 C carb ) chemostratigraphy is a valuable tool in Precambrian stratigraphic correlation. The effectiveness of this tool rests on the assumption that δ 13 C carb data record global seawater signals. However, in some cases δ 13 C carb data exhibit rapid and noisy stratigraphic variations that may have been influenced by authigenic or diagenetic carbonate minerals. To assess the contribution of non-primary minerals towards bulk carbonate carbon isotope values, we acquired SIMS (secondary ion mass spectrometry) δ 13 C carb data, electron microscopic data, and CL (cathodoluminescence) microscopic data from two Ediacaran successions—the lower Member II of the Doushantuo Formation in South China and the Mooifontein Member of the Zaris Formation in southern Namibia. The Doushantuo samples came from a stratigraphic interval with noisy meter-scale δ 13 C carb variations of up to 10‰, whereas the Mooifontein Member is characterized by consistent δ13Ccarb values with limited meter-scale variations of less than ~4‰. Our data show that the meter-scale stratigraphic variations in δ 13 C carb are also mirrored in the SIMS data at μm-mm scales in both Doushantuo and Mooifontein samples. In the Doushantuo samples, SIMS δ 13 C carb values of authigenic calcite vary by up to 10‰ over μm-mm scales and can be either higher or lower than those of the co-existing dolomite matrix, which also appears to be affected by authigenic carbonate on the basis of petrographic observation. Bulk-sample δ 13 C carb values measured on powders microdrilled from the same SIMS specimens are within the range of SIMS δ 13 C carb values. Thus, we infer that bulk-sample δ 13 C carb values of Doushantuo samples represent mixtures of different carbonate components. The Doushantuo and Mooifontein SIMS δ 13 C carb data validate the traditional method of using chemostratigraphic consistency to evaluate authigenic/diagenetic alteration, but given that secondary phases may be 13 C-enriched relative to matrix carbonate, caution is warranted when taking maximum values to approximate primary chemostratigraphic trends.

58 GEOSCIENCES↗
DOE OSTI2025

Comments on “Failure analysis of corroded hydrogen-blended natural gas pipelines based on finite element analysis and genetic algorithm-back propagation neural network” [262 (2025) 111174]

This is a brief commentary paper to highlight and discuss the determination of hydrogen concentration in pipeline steel, effect of hydrogen embrittlement (HE) on the mechanical properties of the material, burst strength of corroded pipelines using finite element analysis (FEA) simulations, and curve-fit models for assessing remaining strength of X80 corroded pipelines for transporting hydrogen blended natural gas. Recently, Xie et al. [1] proposed a methodology to quantify the impact of HE on material properties and numerically determined burst pressure of X80 corroded pipelines. However, their HE quantification overestimated the degradation of tensile strength for hydrogen blending ratios beyond the original data range, and their FEA results of burst pressure are nonconservative. This work thus recharacterized the hydrogen concentration in the steel pipeline and the effect of HE on tensile strength, and then redetermined burst pressures for a set of typical corrosion defect cases considered by Xie et al. [1] based on an experimentally validated FEA modelling method. With the new FEA results, two empirical corrosion models were proposed for X80 corroded pipelines for hydrogen service. At zero hydrogen blending ratio, the novel empirical models predict burst pressures to be consistent with the industry-accepted corrosion models. Furthermore, both the numerical simulation method and the novel corrosion models are significant contributions to the pipeline industry and the hydrogen community. Application of these results will enhance the safety, reliability, and integrity of natural gas pipelines when used to transport hydrogen.

Burst pressure prediction↗
DOE OSTI2021

Rapid and automated separation of uranium ore concentrates for trace element analysis by inductively coupled plasma – optical emission spectroscopy/triple quadrupole mass spectrometry

The present study documents an automated approach to performing elemental analysis on a large group uranium ore concentrate (UOC) samples. In this work, 17 UOC samples, 2 quality control samples, and 26 process blanks were purified sequentially through a single 500 μL Uranium and TEtra Valent Actinides (UTEVA®) column. For each sample, the trace elemental impurities were separated from its dissolved uranium matrix on the UTEVA column and collected for analysis by inductively coupled plasma – optical emission spectroscopy / triple quadrupole mass spectrometry (ICP-OES/TQMS). The UTEVA column was subsequently regenerated prior to separation of the following sample. The column was efficiently regenerated, for each UOC, even after processing ~50 mg of uranium, cumulatively. The validity of the method was established by determining the trace impurities of two quality control uranium reference samples (CRM 124–1 and CUP-2). The current trace element measurements from the 17 UOC samples were compared to previously reported values from an interlaboratory comparison exercise, when available. The methodology employed here produces trace elemental analysis with excellent correlation to the previously reported data for many of the elements / samples, particularly when viewed through the context of existing geochemical comparisons tools (e.g. chondrite normalized variation plots).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Feature review of photovoltaic modeling software utilizing blind performance assessment

While confidence in photovoltaic (PV) modeling software has always been essential, the rapid pace of new PV plant developments makes accuracy and credibility more critical than ever. Independent assessments, particularly through blind modeling comparisons, are therefore necessary to ensure unbiased benchmarking across PV modeling software. Previous studies have been limited by a narrow range of models compared, anonymized results, or system size. This study presents results from the first-ever onymous blind modeling comparison, evaluated using both lab- and utility-scale fixed-tilt, monofacial, south-facing systems at sub-hourly time intervals. Seven commercially used PV software tools were compared: 3E SynaptiQ, PlantPredict, PVsyst, RatedPower, SAM, SolarFarmer, and Solargis Evaluate. Predictions were submitted directly by software representatives, providing unique insights into each software’s implementation and resulting prediction behavior. Notable features, including plane-of-array (POA) transposition model, module temperature model, shading model, and performance model were analyzed and compared. Four summary tables compile these features of the software, serving as a resource to help users understand the methodological differences and select the most suitable software for their applications. The software tools show deviations from mean error in annual yield up to 2.5 % in the lab-scale system, increasing to 6.0 % for the utility-scale system. These differences arise from a combination of user decisions and the inherent behavior of the software, indicating the need for continuous and rigorous validation of modeling methods using these software tools against complex, real-world systems.

14 SOLAR ENERGY↗