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DOE OSTI2024

WELLBASE - An Interactive Platform for Wellbore Material Assessment

This project seeks to build an open-source wellbore material data repository with adequate material performance and contextual data to support Geological Carbon Storage (GCS). By appropriately evaluating the data types as mentioned earlier made available by the WELLBASE tool, stakeholders can make more informed decisions regarding well selections, risk assessment, and economic analysis for geologic carbon storage projects. Advanced Natural Language Processing models and other custom python scripts will be deployed in an automated process to extract unstructured data from documents, reports, and web applications and subsequently parse to more usable formats. The processed data will then be integrated into a robust and comprehensive database architecture, optimizing data accessibility, and usability for analytical purposes. The final data products will be accessible through a user-friendly visualization platform that will allow users to query and visualize the data, as well as download data in usable formats.

Tetteh, Daniel A.↗

DOE OSTI2026

Elevating SolTrace's Capabilities for the Next Generation of Concentrating Solar Analysis

SolTrace is an open-source Monte Carlo ray tracing software developed at NREL. SolTrace can characterize concentrating solar thermal (CST) collector optical performance and is CST technology agnostic. Shown in Fig. 1, SolTrace is a foundational tool in NREL's CST system and component modeling suite. SolTrace's generic surface elements can flexibly model novel collector and receiver designs to predict spatial and temporal flux distributions - critical to understand for CST component design, performance prediction, and system integration. Since its initial development, SolTrace has over 1,650 references on Google Scholar, over 9,800 downloads since 2017, and has served the CST research and development community as a benchmark of 3rd party verification. SolTrace provides users with many options for defining surface shape and boundaries. However, SolTrace provides limited documentation which can result in a steep learning curve for new users. Additionally, SolTrace lacks the computational performance required to evaluate optical performance of a CST system over the course of a year and/or iteratively over design parameters in a timely manner. To address this, we are working towards a new release of SolTrace that enables increased computational throughput by implementing ray tracing acceleration structures and enabling GPU parallelization. Additionally, we are working to improve SolTrace's usability, accessibility, and maintainability by (1) automating solar position time-dependent simulation processes, (2) creating general CST collector templates of grouped elements, (3) updating the user interface to better visualize model inputs and outputs, and (4) creating a user support network through forums, "how to" videos, and documentation.

14 SOLAR ENERGY↗

NASA NTRSDate not supplied

Recent Advancements in the PATO Material Response Code

Introduction: Predicting the complicated multiphysics phenomena during atmospheric entry requires high-fidelity modeling tools to refine estimates of mission risks during entry. To this end, new capabilities are being added to the Porous-material Analysis Toolbox based on OpenFOAM (PATO). PATO is an open-source software for Computational Material Response (CMR) of reactive porous materials submitted to high-temperature environments. The objective of this work is to highlight current efforts to add to and improve upon the modeling capabilities of PATO. These include efforts to loosely couple PATO with other discipline specialized codes including hypersonic Computational Fluid Dynamics (CFD), to assess the interaction effects between pyrolysis gas blowing and the boundary layer, and Computational Solid Mechanics (CSM), to address modeling of mechanical erosion. Other refinements include surface phenomena modeling capabilities to address the effects of silicone-based coatings applied to the TPS during flight preparation, and a unified multiphase solver for a mixed porous-material and plain-fluid domain. Coupling CMR with CFD (CMR/CFD): A loose coupling between PATO and the Data Parallel Line Relaxation (DPLR) CFD code has been achieved by making use of a blowing boundary condition at the heatshield surface available in DPLR. Starting with heat flux estimates with no pyrolysis gas blowing at the surface, blowing gases are computed by the CMR and passed to the CFD such that aerothermal properties of the environment can be recomputed for a new CMR computation. This leads to an iterative process which is supplemented with an estimate of the radiative heat flux using the Nonequilibrium air radiation (NEQAIR) program. The entire iterative process is illustrated in Figure 1. This coupling strategy has been utilized in computing the MSL material response. The goal is to compare the coupled CMR/CFD results with material response results obtained using traditional blowing corrections. Coupling CMS with CMR: A mechanical erosion model is currently being implemented in PATO to account for the additional mass removal induced by high shear conditions. The modeling process at each timestep consists of updating the mechanical properties as a function of temperature and computing the stress tensor and displacement fields of the material. Then, a failure criteria model determines the regions in which the stress exceeds the ultimate strength values resulting in mesh movement to account for mass removal. This model allows the material response simulation to compute the recession due to both oxidation and shear-induced erosion. The model is demonstrated by computing material response of sphere-cone arc jet samples. Surface Modeling Capabilities: NuSil, a silicone-based coating, was sprayed onto the MSL and Mars 2020 heatshields to mitigate shedding of phenolic dust. To better understand the effects of the NuSil coating on the material response, a novel model has been implemented in PATO. In this model, the equilibrium of the charred NuSil surface is modeled as pure silica, and a constant offset, inspired by the classical spallation model, is added to the the char blowing rate and wall enthalpy to reproduce HyMETS experimental results. The model has also been used to estimate the 3D material response of the MSL heatshield. Unified Solver: In addition to the iterative loose coupling approach mentioned above, a multiphase unified solver is being developed to couple the environment (plain-fluid phase) and the porous-material phase. The solver is based on the volume averaged conservation of mass, momentum, and energy for the macroscale with closure models which include microscale effects through effective physicochemical properties. The unified solver has been used to compute flow through a porous plug and solve the Beavers and Joseph problem. Since the strong coupling between phases is inherent to this solver, modeling assumptions present in other coupling methods of material response are mitigated. This strategy also makes it feasible to capture the competition between surface and volume ablation in the same computational domain, which is usually not possible with other coupling approaches.

Material Response↗

DOE OSTI2025

The Fluid Dynamics Uncertainty Quantification Challenge Problem: XFOIL vs. MFOIL

Uncertainty quantification (UQ) has become more critical in aerospace engineering due to the growing dependence on computational tools for design optimization and performance analyses of aerospace vehicles. Even though the significance of UQ in assessing the credibility of computational analyses is well recognized, its costs and complexity impede its integration into standard practices, particularly in computational fluid dynamics (CFD) and other fluid analyses. This paper presents a UQ study for low-fidelity computational aerodynamics analyses with XFOIL and mfoil (i.e., the MATLAB version of XFOIL with several implementation modifications); these tools are utilized widely in both research and education. The main contributions of this paper are as follows: 1) improved precision in quantifying the uncertainty of the baseline Monte Carlo results used to benchmark surrogate modeling techniques for UQ, 2) quantification of the effect of the implementation differences between XFOIL and mfoil on solution quantities of interest (QoIs), such as lift and pitching moment coefficients, and 3) development of an open-source UQ library for use with XFOIL and mfoil, which has educational values and helps promote UQ for fluid analyses with aerospace applications. Results and discussions revolve around cases 1-4 of the challenge problem posed by the AIAA Fluid Dynamics Technical Committee’s Uncertainty Quantification Discussion Group (UQDG). In case 3, this work employs CFDverify, an open-source solution verification software, to quantify the discretization error and evaluate the extrapolated QoIs based on the grid convergence index (GCI). This UQ study differentiates itself from previous studies in the rigor of handling baseline Monte Carlo uncertainty and in including mfoil, which is a more accessible alternative to XFOIL. Finally, despite the growing computing power, low-fidelity computational tools remain valuable, such as for aerodynamic shape optimization at Mach numbers below 0.65 and low-to-mid Reynolds numbers.

Lay, Aidan S [University of Tennessee, Knoxville (↗

DOE OSTI2025

Hardware acceleration for HPS algorithms in two and three dimensions

We provide a flexible, open-source framework for hardware acceleration, namely massively-parallel execution on general-purpose graphics processing units (GPUs), applied to the hierarchical Poincaré–Steklov (HPS) family of algorithms for building fast direct solvers for linear elliptic partial differential equations. To take full advantage of the power of hardware acceleration, we propose two variants of HPS algorithms to improve performance on two- and three-dimensional problems. In the two-dimensional setting, we introduce a novel recomputation strategy that minimizes costly data transfers to and from the GPU; in three dimensions, we modify and extend the adaptive discretization technique of Geldermans and Gillman [1] to greatly reduce peak memory usage. We provide an open-source implementation of these methods written in JAX, a high-level accelerated linear algebra package, which allows for the first integration of a high-order fast direct solver with automatic differentiation tools. We conclude with extensive numerical examples showing our methods are fast and accurate on two- and three-dimensional problems.

Fast direct solvers↗

DOE OSTI2024

Dimensionally Aligned Signal Projection Algorithms Library

Dimensionally aligned signal projection (DASP) algorithms are used to analyze fast Fourier transforms (FFTs) and generate visualizations that help focus on the harmonics for specific signals. At a high level, these algorithms extract the FFT segments around each harmonic frequency center, and then align them in equally sized arrays ordered by increasing distance from the base frequency. This allows for a focused view of the harmonic frequencies, which, among other use cases, can enable machine learning algorithms to more easily identify salient patterns. This work seeks to provide an effective open-source implementation of the DASP algorithms proposed by Vann et al. (2018) as well as functionality to help explore and test how these algorithms work with an interactive dashboard and signal-generation tool. The DASP library is implemented in Python and contains four types of algorithms for implementing these feature engineering techniques: fixed harmonically aligned signal projection (HASP), decimating HASP, interpolating HASP, and frequency aligned signal projection (FASP). Each algorithm returns a numerical array, which can be visualized as an image. The HASP algorithms are variations of the algorithms originally presented by Vann et al. (2018). For consistency, FASP, which is the terminology used for the short-time Fourier transform (STFT), has been implemented as part of the library to provide a similar interface to the STFT of the raw signal. Additionally, the library contains an algorithm to generate artificial signals with basic customizations such as the base frequency, sample rate, duration, number of harmonics, noise, and number of signals. Finally, the library provides multiple interactive visualizations, each of which is implemented using IPyWidgets and works in a Jupyter environment. A dashboard-style visualization is provided, which contains some common signal-processing visual components (signal, FFT, spectogram) updating in unison with the HASP functions (see Figure 1 below). Separate from the dashboard, an independent visualization is provided for each of the DASP algorithms as well as for the artifical signal generator. These visualizations are included in the library to aid in developing an intuitive understanding how the algorithms are affected by different input signals and parameter selections.

harmonics↗

NASA NTRS2014

Prediction of the Aero-Acoustic Performance of Open Rotors

The rising cost of jet fuel has renewed interest in contrarotating open rotor propulsion systems. Contemporary design methods offer the potential to maintain the inherently high aerodynamic efficiency of open rotors while greatly reducing their noise output, something that was not feasible in the 1980's designs. The primary source mechanisms of open rotor noise generation are thought to be the front rotor wake and tip vortex interacting with the aft rotor. In this paper, advanced measurement techniques and high-fidelity prediction tools are used to gain insight into the relative importance of the contributions to the open rotor noise signature of the front rotor wake and rotor tip vortex. The measurements include three-dimensional particle image velocimetry of the intra-rotor flowfield and the acoustic field of a model-scale open rotor. The predictions provide the unsteady flowfield and the associated acoustic field. The results suggest that while the front rotor tip vortex can have a significant influence on the blade passing tone noise produced by the aft rotor, the front rotor wake plays the decisive role in the generation of the interaction noise produced as a result of the unsteady aerodynamic interaction of the two rotors. At operating conditions typical of takeoff and landing operations, the interaction noise level is easily on par with that generated by the individual rotors, and in some cases is even higher. This suggests that a comprehensive approach to reducing open rotor noise should include techniques for mitigating the wake of the front rotor as well as eliminating the interaction of the front rotor tip vortex with the aft rotor blade tip.

VanZante, Dale↗

NASA NTRS2014

Prediction of the Aero-Acoustic Performance of Open Rotors

Van Zante, Dale E.↗

NASA NTRS2022

VESIcal: An Open-source Thermodynamic Model Engine for Mixed Volatile (H2O-CO2) Solubility in Silicate Melts

Modeling the solubility of volatiles in silicate melts is fundamental to the interpretation of volcanic systems and has implications for magma dynamics, eruption style, and material transport between the mantle, crust, and atmosphere. Recent advancements in computational capabilities and access to computing tools has outpaced the functionality and extensibility of previously available modeling platforms. Here we present VESIcal (Volatile Equilibria and Saturation Index calculator), the first comprehensive modeling tool for H2O, CO2, and mixed (H2O-CO2) solubility in silicate melts that: a) allows users access to seven popular models, with easy inter-comparison between models; b) provides universal functionality for all models (e.g., functions for calculating saturation pressures, degassing paths, etc.); c) can process large datasets (1,000’s of samples) automatically; d) can output computed data into an Excel spreadsheet or CSV file for post-modeling analysis; e) integrates plotting capabilities directly within the tool; and f) provides all of this within the framework of a python library, making the tool extensible by the user and allowing any of the model functions to be incorporated into any other code capable of calling python.Here we will provide a demonstration of VESIcal and its capabilities with applications to various volcanic processes affected by volatiles. VESIcal represents the first tool capable of directly comparing multiple solubility models and equations of state. We find that commonly used models predict surprisingly different volatile solubilities, particularly for pure CO2 or mixed CO2-H2O fluids. Even for melt compositions that are well represented in the calibration datasets of multiple models (e.g., MORBs), calculated solubilities for pure CO2 and pure H2O can deviate from one another by factors of >2 leading to 2x deviations in calculated saturation pressures (e.g., 5 to 10 kbar). The solubility of CO2 predicted by different rhyolitic models also differs substantially, overwhelming other sources of uncertainty such as analytical errors on measurements of volatile contents or uncertainties in crustal density profiles. This highlights the importance of model choice when drawing geological conclusions based on volatiles in magmas.

Kayla Iacovino↗

DOE OSTI2025

Fine-Grained Application Energy and Power Measurements on the Frontier Exascale System

The increasing complexity and power/energy demands of heterogeneous exascale systems, such as the Frontier supercomputer, present significant challenges for measuring and optimizing power consumption in applications. Current tools either lack the resolution to capture fine-grained power and energy measurements, fail to validate in-band measurements against out-of-band power sensors, or cannot integrate this information with application performance events in a scalable manner. This paper introduces a novel open-source performance toolkit that integrates extended PAPI components with Score-P plugins to enable in-band, fine-grained power and energy measurements, while also supporting validation using power meter measurements for both CPUs and GPUs. One key contribution is the ability to perform millisecond-level power and energy measurements for AMD MI250X GPUs, mapping them to application performance events within a single trace and measurement system that scales. Our toolkit combines coarse-grained measurements from cray_pm counters with high-resolution metrics from rocm_smi and RAPL, converting GPU instantaneous accumulated energy into power to capture both transient and steady-state power behavior, a capability often missed by out-of-band and monitoring tools. By mapping these metrics to specific application regions, developers can identify energy hotspots, address inefficiencies in GPU kernel execution, and validate in-band measurements against external measurements. We demonstrate the effectiveness of this approach through case studies using benchmarks such as GPU rocblas_sgemm, BLIS c_blas_dgemm, and rocHPL, highlighting the variability of the measurements and the impact of transient power spikes on kernel-level efficiency.

Hernandez Mendoza, Oscar [ORNL] (ORCID:00000002538↗

DOE OSTI2025

EnergyPlus-MCP: A model-context-protocol server for ai-driven building energy modeling

Traditional building energy modeling with the EnergyPlus building performance simulation engine requires domain expertise, programming skills, and intensive manual efforts limiting its effective adoption. This paper introduces EnergyPlus-MCP, the first open-source Model Context Protocol (MCP) server specifically designed for EnergyPlus simulation workflows, establishing a new foundational infrastructure for AI-driven building energy modeling. The MCP server implements a layered architecture with 35 specialized tools spanning model management, editing and analysis, HVAC and other systems configuration inspection, and simulation execution, enabling Large Language Models to interact with EnergyPlus through conversational interfaces. The server addresses critical workflow barriers by automating model validation, streamlining energy efficiency measures modification, and providing intelligent output management with interactive visualization. Through practical demonstrations using a multi-zone building retrofit analysis, we show how the EnergyPlus-MCP server significantly reduces manual efforts while maintaining full simulation rigor. By providing accessible natural language interfaces to sophisticated building energy analysis, this approach enables scalable deployment of simulation expertise across public and private organizations, educational institutions, and research teams, fundamentally transforming traditional building energy modeling practices.

AI↗

DOE OSTI2025

TOFHunter—unlocking rapid untargeted screening of inductively coupled plasma–time-of-flight–mass spectrometry data

This study provides an overview of a newly developed open source program written in Python, TOFHunter, which permits the rapid and untargeted screening of inductively coupled plasma (ICP)-time-of-flight (TOF)-mass spectrometry (MS) datasets. ICP-TOF-MS is an analytical tool capable of providing quasi simultaneous detection of all nuclides from Li to Pu. This capability has triggered an increase in studies investigating single-particle analysis in which the TOF-MS provides correlated elemental/isotopic signatures on a particle basis in time. Similarly, laser ablation mapping has seen rapid growth owing to ICP-TOF-MS's capacity to handle fast washout times (<10 ms) while providing a broad nuclide coverage. The caveat to this broad mass coverage and high time resolution comes in the form of large, overwhelming datasets. With datasets typically on the scale of gigabytes, it is easy for a user to only focus on very targeted analytes; however, this focus diminishes the opportunity offered by the TOF-MS detector. TOFHunter applies chemometric methods, principal component analysis (PCA), and interesting features finder (IFF) on ICP-TOF-MS data, allowing for investigation of correlations, major and minor variance sources, and sample screening. The unique spectra identified by the (IFF) are used to generate a list of mass peaks, which are then matched with both nuclides and potential interferences before being exported for the user to investigate. Several case studies are discussed herein, demonstrating TOFHunter's ability to screen aqueous injections, single-particle/single-cell analysis, and probe laser ablation mapping files for unique regions of interest.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

ChemEnv : a fast and robust coordination environment identification tool

Coordination or local environments have been used to describe, analyze and understand crystal structures for more than a century. Here, a new tool called ChemEnv, which can identify coordination environments in a fast and robust manner, is presented. In contrast to previous tools, the assessment of the coordination environments is not biased by small distortions of the crystal structure. Its robust and fast implementation enables the analysis of large databases of structures. The code is available open source within the pymatgen package and the software can also be used through a web app available on http://crystaltoolkit.org through the Materials Project.

42 ENGINEERING↗

DOE OSTI2025

AdditiveFOAM: A Continuum Multiphysics Code for Additive Manufacturing

AdditiveFOAM is a computational framework that simulates transport phenomena in Additive Manufacturing (AM) processes. It is built on OpenFOAM (Weller et al., 1998), the leading free, open-source software package for computational fluid dynamics (CFD). OpenFOAM offers an extensible platform for solving complex multiphysics problems using state-of-the-art finite volume methods. AdditiveFOAM leverages these capabilities to develop specialized tools aimed at addressing challenges in AM processing. Metal additive manufacturing, also known as metal 3D printing, is an advanced manufacturing technique that creates physical parts from a three-dimensional (3D) digital model by melting metal powder or wire feedstock. A significant area of research in metal AM focuses on process planning to mitigate anomalous features during printing that are deleterious to part performance (e.g., porosity and cracking), as well as controlling localized microstructure and material properties. Given the high costs and substantial time requirements associated with experimental methods for qualifying new materials and processes, there is a compelling incentive for researchers to utilize advanced computational simulations. In this context, AdditiveFOAM offers a simulation framework to better understand undesirable features in printing, thereby enhancing process planning and reducing the reliance on labor-intensive experimental campaigns.

Coleman, John [Oak Ridge National Laboratory (ORNL↗

DOE OSTI2022

SplitML

SplitML (Signal Processing Library for Interference rejecTion by Machine Learning) is a code repository for a set of tools for interference rejection in complex time-domain signals. The goal of the tools is to provide machine learning modeling capabilities for rejecting interference. Recent related machine learning algorithms for signal processing have focused mostly on speech enhancement or multi-speaker speech separation; the tools in SplitML will extend these innovations to generic time-domain signals of interest. SplitML includes tools for generating synthetic noisy signals, code for customized machine learning models applicable to interference rejection, and tools for evaluating such algorithms against standard signal processing techniques. These components are written in Python, a high-level programming language that takes advantage of the Python ecosystem of high-quality open-source packages for machine learning and signal processing.

Klein, Natalie↗

NASA NTRS2004

Using the GeoFEST Faulted Region Simulation System

GeoFEST (the Geophysical Finite Element Simulation Tool) simulates stress evolution, fault slip and plastic/elastic processes in realistic materials, and so is suitable for earthquake cycle studies in regions such as Southern California. Many new capabilities and means of access for GeoFEST are now supported. New abilities include MPI-based cluster parallel computing using automatic PYRAMID/Parmetis-based mesh partitioning, automatic mesh generation for layered media with rectangular faults, and results visualization that is integrated with remote sensing data. The parallel GeoFEST application has been successfully run on over a half-dozen computers, including Intel Xeon clusters, Itanium II and Altix machines, and the Apple G5 cluster. It is not separately optimized for different machines, but relies on good domain partitioning for load-balance and low communication, and careful writing of the parallel diagonally preconditioned conjugate gradient solver to keep communication overhead low. Demonstrated thousand-step solutions for over a million finite elements on 64 processors require under three hours, and scaling tests show high efficiency when using more than (order of) 4000 elements per processor. The source code and documentation for GeoFEST is available at no cost from Open Channel Foundation. In addition GeoFEST may be used through a browser-based portal environment available to approved users. That environment includes semi-automated geometry creation and mesh generation tools, GeoFEST, and RIVA-based visualization tools that include the ability to generate a flyover animation showing deformations and topography. Work is in progress to support simulation of a region with several faults using 16 million elements, using a strain energy metric to adapt the mesh to faithfully represent the solution in a region of widely varying strain.

Geophyical Finite Element Simulation Tool (GeoFEST↗

DOE OSTI2024

Ground Source Heat Pump Screening Tool and Related Resources

This archive contains both a link to Oak Ridge National Laboratory's Ground Source Heat Pump (GSHP) Screening Tool and related resources documenting its development, technical features, and applications. The web-based screening tool is a techno-economic analysis resource designed to evaluate the feasibility, costs, and benefits of implementing GSHP systems in buildings across various U.S. climate zones. It is intended for use by building owners, HVAC system designers, and installers to support decision-making in residential and commercial applications, incorporating advanced modeling capabilities such as ground heat exchanger design. The included resources detail the tool's creation and use, covering topics such as innovative ground heat exchanger design methodologies, the development of an open library of g-functions for borehole configurations, and studies on GSHP performance and economic viability in retrofitting single-family homes.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Hybrid Tandem Photovoltaics

Tandem solar cell structures are the only strategy demonstrated to surpass the detailed balance efficiency limit of high-quality single-junction solar cells. To continue to improve the efficiencies of cost-effective terrestrial solar power, hybrid tandems of dissimilar subcells are being considered by many around the world, especially designs that incorporate silicon solar cells as a bottom subcell. In this project, we studied a wide variety of tandem design possibilities including those with three-terminal (3T) and four-terminal (4T) configurations. The use of 3T and 4T designs could be useful for efficient and economical hybrid tandem designs that utilize the best available subcell materials such as emerging perovskite materials. Three-terminal configurations, in particular, have not been sufficiently studied previously. We have laid the foundational groundwork in this project for understanding the operation of 3T tandems: developing a taxonomy for naming, a methodology for measuring and interconnecting, and models for simply characterizing 3T tandems. Electrical and optical subcell coupling between the subcells was also measured and modeled. An important part of this work was the fabrication of novel example tandem structures, including 4T GaAs/Si, 3T GaInP/Si, 3T GaAs/Si, and 3T GaInP/GaAs devices. Using these high-quality tandem cells, we have been able to clearly demonstrate the achievability of high-efficiencies, and subtle physical effects such as photon recycling and luminescent coupling. We have developed and demonstrated essential building-block tools such as transparent conductive adhesives (TCA) and 3T silicon bottom cells with interdigitated back contacts (IBC) that can also be used in many other tandem designs. We have tested the reliability of these tools and devices under standardized testing and outdoor measurements. We have found 4T GaAs/Si tandems to be relatively straightforward to fabricate and robust in real-world outdoor conditions. While we have demonstrated working hybrid 3T III-V/TCA/Si IBC tandems, we experienced low yields even with our best process flows yet. Further work is still needed to improve the processing yield of these devices. We therefore also created tandem cells using an all-III-V 3T tandem process which was very robust with high yields, allowing for the creation of voltage-matched strings in many different configurations using 8 nearly identical 3T tandems. Using these robust 3T tandem examples, we were able measure and precisely characterize 3T tandem behaviors to predict their operation under changing spectrum and temperature. The optoelectronic equivalent-circuit model was shown to be very general and applicable to hybrid tandems, and encompassed the operation 3T Si IBC cells. This general model has been distributed to the public in as open-source Python-based software called PVcircuit. We have calculated the implications of these new tandem device designs on the real-world energy production and shown how the relative performance of different tandem configurations is situational and can be engineered using the tools developed here.

14 SOLAR ENERGY↗