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DOE OSTI2022

Comparisons of Nodal diffusion and whole-core transport methods for multiple cycles of a small Light water reacto

As part of a cooperative research and development agreement between the US department of Energy's Oak Ridge National Laboratory and Holtec International subsidiary SMR LLC, core simulator models of the SMR-160, a light water-cooled and -moderated, natural circulation, small modular reactor, were developed and compared. The model results indicate pin-by-pin power histories, critical boron concentration, and other key performance indicators useful for developing multi-cycle core loading patterns. One model uses industry standard nodal methods with a simple thermal-hydraulics solution, and the other uses an advanced deterministic neutronics solver with a coupled subchannel calculation. The goals of the comparison are to provide the reactor designer with a detailed and coupled core physics reference solution, inform the reactor designer of nodal model best practices based on the code-to-code comparison, and set up a workflow for performing subsequent detailed core simulator calculations. The results of this work will be used in the development of coupled neutronic, thermal hydraulic, and fuel performance models for advanced analysis of the SMR-160. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRSDate not supplied

Natural Language Processing Analysis of Notices to Airmen for Air Traffic Management Optimization

With new emerging technologies in the field of NLP, we explore their applications to digitize and analyze heritage Air Traffic Management (ATM) documents for planning and optimizing airspace operations. Specifically, this research focuses on harvesting semi-structured or un-structured information contained in Notices to Airmen (NOTAMs). Using NLP and other advanced data analytics, we will construct a data-driven framework which facilitates finding language patterns and the use of pretrained language models for classification and extraction of useful airspace constraints and restrictions. These may lead to tools that assist airspace users in understanding the constraints more efficiently, contributing to better route planning and safer execution. This paper explores three workflows entailing different NLP tasks. First, unsupervised techniques like word embedding and topic modeling are used for pattern finding and document classification. Second, a dataset is created by extracting information from the semi-structured NOTAM format as metadata for categorizing, visualizing, and extracting key entities driving NOTAM content. Third, modern pre-built deep learning based transformer models such as BERT, RoBERTa, and XLNet are evaluated on the question answering task, an even more robust approach to information extraction, as well as their respective fine-tuning tasks. In this work we include various performance metrics for the trained models to evaluate both accuracy and precision and we show that the models can be generalized for their respective tasks. The research work developed shows promise in uncovering trends in digital NOTAMs in the NAS and also offers a new framework for digitizing and inferring insights from free-form legacy NOTAMs, that are yet to be digitized.

Natural Language Processing↗

NASA NTRSDate not supplied

Natural Language Processing (NLP) Analysis of NOTAMs for Air Traffic Management Optimization

Natural Language Processing↗

NASA NTRS2014

Coupled Solid Rocket Motor Ballistics and Trajectory Modeling for Higher Fidelity Launch Vehicle Design

Multi-stage launch vehicles with solid rocket motors (SRMs) face design optimization challenges, especially when the mission scope changes frequently. Significant performance benefits can be realized if the solid rocket motors are optimized to the changing requirements. While SRMs represent a fixed performance at launch, rapid design iterations enable flexibility at design time, yielding significant performance gains. The streamlining and integration of SRM design and analysis can be achieved with improved analysis tools. While powerful and versatile, the Solid Performance Program (SPP) is not conducive to rapid design iteration. Performing a design iteration with SPP and a trajectory solver is a labor intensive process. To enable a better workflow, SPP, the Program to Optimize Simulated Trajectories (POST), and the interfaces between them have been improved and automated, and a graphical user interface (GUI) has been developed. The GUI enables real-time visual feedback of grain and nozzle design inputs, enforces parameter dependencies, removes redundancies, and simplifies manipulation of SPP and POST's numerous options. Automating the analysis also simplifies batch analyses and trade studies. Finally, the GUI provides post-processing, visualization, and comparison of results. Wrapping legacy high-fidelity analysis codes with modern software provides the improved interface necessary to enable rapid coupled SRM ballistics and vehicle trajectory analysis. Low cost trade studies demonstrate the sensitivities of flight performance metrics to propulsion characteristics. Incorporating high fidelity analysis from SPP into vehicle design reduces performance margins and improves reliability. By flying an SRM designed with the same assumptions as the rest of the vehicle, accurate comparisons can be made between competing architectures. In summary, this flexible workflow is a critical component to designing a versatile launch vehicle model that can accommodate a volatile mission scope.

Ables, Brett↗

DOE OSTI2026

Scalable Federated Learning for Scientific Foundation Models on Leadership-Class Systems

Federated learning (FL) at leadership-class HPC systems remains largely unexplored, despite growing interest in deploying federated workflows on modern HPC systems. This paper provides the first system-level empirical characterization of federated fine-tuning of pretrained foundation models on an exascale supercomputer under a multi-node deployment. Using up to 96 concurrent FL clients deployed across Frontier nodes, we study the impact of client scale, model size, data heterogeneity, partial participation, and differential privacy on runtime, communication overhead, and convergence stability. Our results show that pretrained transformer models remain robust to heterogeneity, client dropout, and privacy noise, while system efficiency degrades rapidly with scale as synchronizat and orchestration dominate runtime. We further demonstrate that system-aware execution strategies, including intra-node aggregation and early aggregation, significantly reduce wall-clock time without degrading model quality. These findings establish a practical performance baseline and inform the design of communication-efficient FL systems on leadership-class HPC platforms.

Kotevska, Olivera [ORNL] (ORCID:0000000316772243)↗

DOE OSTI2025

Virtual Engineering: Python framework for engineering process design

Virtual Engineering (VE) is a Python software framework designed to accelerate the research and development of engineering processes that are fundamentally defined by multiple unit operations executed in series. VE supports a wide variety of different multi-physics models and integrates them to simulate a complete end-to-end process. To automate the execution of this model sequence, VE provides (i) a robust method to communicate between models, (ii) a high-level, user-friendly interface to set model parameters and enable optimization, and (iii) an overall model-agnostic approach that allows new computational units to be swapped in and out of workflows. Although the VE framework was developed to support the biochemical conversion of biomass to fuel, we have designed each component to easily accommodate new domains and unit models.

09 BIOMASS FUELS↗

DOE OSTI2023

Nuclear Data Evaluations in the Resolved Resonance Region and Proposed Updates to Rmatrix Modeling in the SAMMY Code [Slides]

This detailed presentation starts off with an evaluation workflow scheme along with observables definition. Provided next are typical cases of explicit experimental effects and the basic quantities for reproducibility. Lastly the presentation mentions the Inverse channel, Complex radius, and the level dependent boundary condition. A visual workflow scheme is provided.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

FY25 Theory and Simulation Performance Target: Development of an integrated modeling framework for fusion reactor design and assessment (Final Report)

This report documents the FY25 Theory and Simulation Performance Target (TSPT) of developing an integrated modeling framework for fusion reactor design and assessment (FREDA). Over Q1-Q4, new capabilities were developed across both plasma and engineering domains and demonstrated on an example representation of a Compact Advanced Tokamak with a Dual Cooled Lead Lithium blanket. This represents a first-of-a-kind demonstration of coupled core-to-wall-to-engineering for a reactor. Self-consistent CESOL workflows were applied to provide core, pedestal, and SOL prediction; new modules were developed for energetic particle stability (FAR3D) and transport (TGLF-EP) analysis; and boundary plasma modeling (SOLPS-ITER, BOUT++/Hermes-3) was expanded to evaluate wall and divertor heat fluxes and interface with engineering thermal analysis. A parameterized CAD tool, TRACER, was expanded to generate medium-fidelity divertor, blanket, and coil geometries; OpenFOAM and Diablo workflows were applied for first-wall and divertor thermal analyses with helium cooling; and reduced-order models were created for high-mass-flux divertor cooling. Magnet multiphysics capabilities were verified between Elmer, Diablo, and a new MFEM-based solver, and workflows enable stress, thermal, and neutron-fluence analysis of TF coils with neutronics-driven heating. Nuclear and blanket analysis workflows were demonstrated, including tritium breeding, transport, and CFD-informed thermo-mechanical assessment. Preliminary multi-fidelity uncertainty quantification workflows were applied to boundary modeling codes and shown to achieve variance reductions with fewer high-fidelity boundary simulations. Key findings highlight the challenges of resolving the ITEP gap to find suitable balance between wall and divertor loads, neutron heating, and practical limits of PFC cooling. Next step priorities are to develop automated workflows to check boundary code convergence and detachment, implement tighter physics-engineering CAD provenance tracking, and inclusion of plasma-material interface models for SLAG and tungsten cracking behavior. Collectively, these developments establish sophisticated capabilities for predictive, multi-fidelity, whole-device modeling that integrates plasma physics, materials, magnets, and nuclear engineering to guide pathways to viable Fusion Pilot Plant design points.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Too Many Materials and Too Many Applications: An Experimental Problem Waiting for a Computational Solution

Finding the best material for a specific application is the ultimate goal of materials discovery. However, there is also the reverse problem: when experimental groups discover a new material, they would like to know all the possible applications this material would be promising for. Computational modeling can aim to fulfill this expectation, thanks to the sustained growth of computing power and the collective engagement of the scientific community in developing more efficient and accurate workflows for predicting materials' performances. We discuss the impact that reproducibility and automation of the modeling protocols have on the field of gas adsorption in nanoporous crystals. We envision a platform that combines these tools and enables effective matching between promising materials and industrial applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2017

A Dose of Reality: Radiation Analysis for Realistic Human Spacecraft

INTRODUCTION As with most computational analyses, a tradeoff exists between problem complexity, resource availability and response accuracy when modeling radiation transport from the source to a detector. The largest amount of analyst time for setting up an analysis is often spent ensuring that any simplifications made have minimal impact on the results. The vehicle shield geometry of interest is typically simplified from the original CAD design in order to reduce computation time, but this simplification requires the analyst to "re-draw" the geometry with a limited set of volumes in order to accommodate a specific radiation transport software package. The resulting low-fidelity geometry model cannot be shared with or compared to other radiation transport software packages, and the process can be error prone with increased model complexity. The work presented here demonstrates the use of the DAGMC (Direct Accelerated Geometry for Monte Carlo) Toolkit from the University of Wisconsin, to model the impacts of several space radiation sources on a CAD drawing of the US Lab module. METHODS The DAGMC toolkit workflow begins with the export of an existing CAD geometry from the native CAD to the ACIS format. The ACIS format file is then cleaned using SpaceClaim to remove small holes and component overlaps. Metadata is then assigned to the cleaned geometry file using CUBIT/Trelis from csimsoft (Registered Trademark). The DAGMC plugin script removes duplicate shared surfaces, facets the geometry to a specified tolerance, and ensures that the faceted geometry is water tight. This step also writes the material and scoring information to a standard input file format that the analyst can alter as desired prior to running the radiation transport program. The scoring results can be transformed, via python script, into a 3D format that is viewable in a standard graphics program. RESULTS The CAD model of the US Lab module of the International Space Station, inclusive of all the racks and components, was simplified to remove holes and volume overlaps. Problematic features within the drawing were also removed or repaired to prevent runtime issues. The cleaned drawing was then run through the DAGMC workflow to prepare for analysis. Pilot tests modeling transport of 1GeV proton and 800MeV/A oxygen sources show that reasonable results are converged upon in an acceptable amount of overall computation time from drawing preparation to data analysis. The FLUKA radiation transport code will next be used to model both a GCR and a trapped radiation source. These results will then be compared with measurements that have been made by the radiation instrumentation deployed inside the US Lab module. DISCUSSION Early analyses have indicated that the DAGMC workflow is a promising toolkit for running vehicle geometries of interest to NASA through multiple radiation transport codes. In addition, recent work has shown that a realistic human phantom, provided via a subcontract with the University of Florida, can be placed inside any vehicle geometry for a combinatorial analysis. This added functionality gives the user the ability to score various parameters at the organ level, and the results can then be used as input for cancer risk models.

Barzilla, J. E.↗

DOE OSTI2023

Proxy-based Bayesian inversion of strain tensor data measured during well tests

Recent instrument developments have made it possible to measure the strain tensor caused by injecting or pumping fluid from aquifers or reservoirs, but the full value of these data is limited because the long runtimes of poroelastic forward models makes it impractical to use many inversion schemes. This limits the interpretation of strain data for managing the recovery of resources or storage of wastes in the subsurface. This paper describes a method of inverting deformation data using a poroelastic numerical simulator so the results can be used to manage reservoirs or aquifers. We developed a workflow designed to reduce the number of simulations sufficiently to make it feasible to use DREAMzs, an advanced Bayesian inversion method that translates the uncertainties from different sources into unbiased posterior parameter distributions and uncertainty envelopes around the field data. Using a KNN proxy model for the poroelastic simulator is key to reducing the overall computations, and the workflow includes a strategy for ensuring the proxy model results converge on the results from the simulator. The workflow is tested using an idealized example that verifies the ability to correctly identify parameters and characterize noise used to perturb the data. Field data from an injection test at an oil reservoir near Tulsa, Oklahoma, are also used to evaluate the efficacy of the workflow with a real dataset. The workflow identified 265 history matching solutions out of 1240 total simulation runs (21% acceptance ratio), where the results were used to characterize posterior parameter distribution and evaluate the prediction uncertainty. Furthermore, this workflow is significant because it enables strain tensor, or other geomechanical measurements to be interpreted to guide decision-making during energy and environmental processes in the subsurface.

42 ENGINEERING↗

DOE OSTI2024

Development of a Sizing and Modeling Platform for District Energy Systems with Geothermal Heat Pumps

Existing tools for community or urban scale energy system modeling and simulation are often limited in their capabilities and require expert-level modeling proficiency to develop system models. To fill this gap, this paper proposes an integrated sizing and modeling platform for district energy systems with geothermal heat pumps. The proposed platform takes in geometric and non-geometric user inputs related to the buildings, borefield, and district energy loop. Then, the platform sizes the geothermal heat exchanger, generates a corresponding district energy system model, and runs an annual simulation automatically. We validated the simulation performance of the borefield in our tool against EnergyPlus. A case study is provided in this paper to demonstrate the workflow and simulation result plausibility of the proposed platform.

decarbonization↗

DOE OSTI2020

TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations

TURBOMOLE is a collaborative, multi-national software development project aiming to provide highly efficient and stable computational tools for quantum chemical simulations of molecules, clusters, periodic systems, and solutions. The TURBOMOLE software suite is optimized for widely available, inexpensive, and resource-efficient hardware such as multi-core workstations and small computer clusters. TURBOMOLE specializes in electronic structure methods with outstanding accuracy–cost ratio, such as density functional theory including local hybrids and the random phase approximation (RPA), GW-Bethe–Salpeter methods, second-order Møller–Plesset theory, and explicitly correlated coupled-cluster methods. TURBOMOLE is based on Gaussian basis sets and has been pivotal for the development of many fast and low-scaling algorithms in the past three decades, such as integral-direct methods, fast multipole methods, the resolution-of-the-identity approximation, imaginary frequency integration, Laplace transform, and pair natural orbital methods. This review focuses on recent additions to TURBOMOLE’s functionality, including excited-state methods, RPA and Green’s function methods, relativistic approaches, high-order molecular properties, solvation effects, and periodic systems. A variety of illustrative applications along with accuracy and timing data are discussed. Moreover, available interfaces to users as well as other software are summarized. TURBOMOLE’s current licensing, distribution, and support model are discussed, and an overview of TURBOMOLE’s development workflow is provided. Challenges such as communication and outreach, software infrastructure, and funding are highlighted.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Rooftop unit comparison calculator: a framework for comparing performance of rooftop units with building energy simulation

The applications of building energy simulation (BES) in designing heating, ventilation, and air conditioning (HVAC) systems are limited by the high costs of developing simulation models and the lack of references for determining the model parameters. This paper presents a software framework for selecting designs for rooftop unit HVAC (RTU) systems with BES. Specifically, this framework reduces the cost of using BES by automating the generation of EnergyPlus models. It also employs a systematic method for determining model parameters based on well-accepted datasets. We applied this framework in a comprehensive assessment of an advanced design of RTU systems in which 478 EnergyPlus models were developed without human involvement. The assessment reveals that replacing a constant-speed fan/coil with a multiple-speed fan/coil may not guarantee better overall performance. In conclusion, it also suggests the benefits of replacing furnace coils with heat pumps are subject to utility cost, weather conditions, and heating load profiles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Data Assimilation for Robust UQ Within Agent-Based Simulation on HPC Systems

Agent-based simulation provides a powerful tool for in silico system modeling. However, these simulations do not provide built-in methods for uncertainty quantification (UQ). Within these types of models a typical approach to UQ is to run multiple realizations of the model then compute aggregate statistics. This approach is limited due to the compute time required for a solution. When faced with an emerging biothreat, public health decisions need to be made quickly and solutions for integrating near real-time data with analytic tools are needed. We propose an integrated Bayesian UQ framework for agent-based models based on sequential Monte Carlo sampling. Given streaming or static data about the evolution of an emerging pathogen this Bayesian framework provides a distribution over the parameters governing the spread of a disease through a population. These estimates of the spread of a disease may be provided to public health agencies seeking to abate the spread. By coupling agent-based simulations with Bayesian modeling in a data assimilation, our proposed framework provides a powerful tool for modeling dynamical systems in silico. We propose a method which reduces model error and provides a range of realistic possible outcomes. Moreover, our method addresses two primary limitations of ABMs: the lack of UQ and an inability to assimilate data. Our proposed framework combines the flexibility of an agent-based model with UQ provided by the Bayesian paradigm in a workflow which scales well to HPC systems. We provide algorithmic details and results on a simulated outbreak with both static and streaming data.

Spannaus, Adam [ORNL] (ORCID:0000000225213657)↗

DOE OSTI2026

A bespoke model of Arctic river basins based on hillslope delineation: Model Archive

This dataset is a model archive of the paper A bespoke model of Arctic river basins based on hillslope delineation (in prep), which introduces a watershed decomposition and parameterization method for large scale permafrost hydrology simulation. With this dataset, this study aims to address the research question: whether a computationally efficient hillslope-based modeling framework can reliably simulate discharge at Arctic river-basin scales. This dataset contains model input and output data for five modeling scenarios at a study site located in the Sagavanirktok River basin. The five modeling scenarios include three modeling cases under temperate conditions using full 3D, decomposed 3D, and decomposed 2D modeling strategies; and two modeling cases under actual Arctic conditions with permafrost using full 3D and decomposed 2D modeling strategies. Simulations were performed using the Advanced Terrestrial Simulator (ATS, v1.6 for three temperate scenarios and v1.5 for two Arctic scenarios), a physics-rich integrated surface–subsurface hydrologic model with cryo-hydrology features. For the three temperate models, simulations were conducted for the period of 10/01/1993 - 09/30/2002; and for the two Arctic models, simulations were conducted for the period of 01/01/1994 - 12/31/2002. To facilitate reproducibility of simulations, all datasets are organized hierarchically. The dataset contains: (1) Mesh files (.exo) for full 3D model, decomposed 3D models, and decomposed 2D models, located in huc/190604020802_gauge15906000/mesh/. Mesh files can be visualized through Paraview or read by Python. (2) Climate forcings (.h5) for full 3D model and decomposed 3D/2D models are located in huc/190604020802_gauge15906000/daymet_onePiece/, and huc/190604020802_gauge15906000/vp_pr_revised_daymet_1980_2006_with_wind/ separately. Accessible by Python. (3) Raw measured gage discharge (.csv) from USGS, located in huc/190604020802_gauge15906000/gaged_basin15906000_discharge_usgs/. Accessible by Python. (4) Delineated subdomain raster (.tif) and shape files (.shp), and the final parameterized results (.npy) for decomposed models, located in huc/190604020802_gauge15906000/data_preprocessed-meshing. Accessible by Python. (5) Temperate models are located in nonpermaf_huc190604020802_gauge15906000/, which includes three cases: decomposed 2D models (inside model_0*-hillslope_*), decomposed 3D models (inside model_1*-subcatchment_*), and full 3D model (inside model_2*-onepiece_*). Two step spin-up results (checkpoint_final.h5) are located in model_*1-*_spinup_steadystate and model_*2-*_spinup_cycle, separately, which are used to initialize real transient models. The input files (.xml) and output results (.dat) of the real transient models are located in model_*3-*_transient/. Especially, for two example hillslope models (ID=-11 and 11), additional h5py files are included in model_03-hillslope_transient/hillslope-11/, model_03-hillslope_transient/hillslope11, model_13-subcatchment_transient/subcatchment-11/, model_13-subcatchment_transient/subcatchment/11, respectively, which are used to plot the saturation figure (Figure 5) in the manuscript. Accessible by Python. (6) Arctic models are located in huc190604020802_gauge15906000/, which includes two cases: decomposed 2D models (inside model_04-hillslope_transient), and full 3D model (inside model_05-onepiece_transient_mannp1_ra). Three step spin-up results (checkpoint_final.h5) are located in model_01-column_freezeup/, model_02-column_spinup/, model_03-hillslope_spinup/, respectively, which are used to initialize real 2D transient hillslope models. The input files (.xml) and output results (.dat) of transient 2D hillslope models are located in model_04-hillslope_transient/. The input files (.xml) and output results (.dat) of the full 3D transient model is located in model_05-onepiece_transient_mannp1_ra/. The full 3D transient model is initialized by model_02-column_spinup/. Accessible by Python. (7) The MOSART routed discharge results (.csv) under Arctic conditions is located in huc190604020802_gauge15906000/MOSART/. Accessible by Python. (8) All Python codes (.py) used to parameterize full 3D model to decomposed 2D models are located in script/. These codes fit with watershed workflow (a watershed delineation tool) v1.4 under the branch gaob/v1.4 from https://github.com/gaobhub/watershed-workflow.git.

EARTH SCIENCE > CRYOSPHERE↗

DOE OSTI2020

Charged Wellbore Casing Controlled Source Electromagnetics (CWC-CSEM) for Reservoir Imaging and Monitoring (Final report)

This project addresses the needs of the U.S. Department of Energy (DOE) to develop advanced monitoring technologies and protocols to track the fate of subsurface carbon dioxide (CO2) plumes for carbon storage. Specifically, the project seeks to develop and test a unique and novel system of technologies consisting of electromagnetic data acquisition, coupled multiphysics imaging, and reservoir model enhancement to understand the migration and long-term distribution of CO2 in the subsurface. The overarching objective is to develop an integrated approach for long term monitoring of carbon storage. The two main components of the project include the methodology development and the test of the method at a field site. The methodology component consists of 1) developing the field procedure and protocol for collecting time-lapse controlled-source electromagnetic (CSEM) data with source electric current injected into the subsurface through wellbore casings; 2) building of background 3D electrical conductivity utilizing multiple sources of data such as supplemental surface transient EM (TEM) surveys, well-logs, and seismic structural information, for enhancing CSEM signal from reservoir depths; and 3) coupled multiphysics simulations and inversion of CSEM data constrained by production data and by structural information from seismic imaging of the reservoir and overlying formations. The testing component used the field site of Bell Creek Oil Field, which served both as a field laboratory for the method development as well as a test site to evaluate the CSEM signal strengths and the methodology developed in this research project. We have accomplished all the proposed tasks and developed the methodology as planned. These include the procedure for time-lapse CSEM data acquisition, data processing techniques, integration with 3D conductivity model building, fast reservoir simulation for history matching using machine learning, and interpreting CSEM data with coupling to the reservoir modeling. Collectively, the outcome of these tasks form a coherent workflow that can be applied to monitor dedicated carbon storage in saline reservoirs. The testing component evaluated the applicability and limitations of the method, and concluded that the method would be ideal for monitoring dedicated carbon storage sites utilizing saline reservoirs.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

R3IT, Rapid Rural Resilient Interconnection Toolkit, Final Technical Report

Utilities nationwide are beginning to experience multiple solar interconnection requests per day. This request volume will soon overwhelm utility engineers, especially at smaller utilities which serve the majority of the landmass of the United States. In this project, we developed open-source software tool that automates the interconnection approval process and removes 80% of the time required to approve an interconnection and hence allow more solar to be quickly and safely integrated with the grid. This software is accompanied by a guidebook detailing interconnection best practices and utility lessons learned. Competing solar interconnection software is extremely expensive at ten times the cost of typical distribution engineering tools, it’s closed source which makes it hard to integrate into utility workflows, and it doesn’t address the hardest power flow modeling challenges of interconnection screening. Our solution was built built with our utility partners who are already experiencing multiple interconnection requests per day and integrates best practices from our past work with DOE and the cooperative community on solar integration. The resulting free and open-source solution has been disseminated through our media channels and conferences that engage over 1,900 utilities nationwide.

14 SOLAR ENERGY↗