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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A Review of Software for Designing and Operating Quantum Networks

Quantum networks development is crucial to realizing a production-grade network that can support distributed sensing, secure communication, and utility-scale quantum computation. However, the transition from laboratory demonstration to deployable networks requires software implementations of architectures and protocols tailored to the unique constraints of quantum systems. This paper reviews the current state of software implementations for quantum networks, organized around a three-plane abstraction of infrastructure, logical, and control/service planes. We cover software for both designing quantum network protocols (e.g., SeQUeNCe, QuISP, and NetSquid) and operating testbeds, with a focus on essential control/service plane functions such as entanglement, topology, and resource management, in a proposed taxonomy. Our review highlights a persistent gap between theoretical architecture and protocol proposals and their realization in simulators or testbeds, particularly in dynamic topology and network management. We conclude by outlining open challenges and proposing a roadmap for developing scalable software architectures to enable hybrid, large-scale quantum networks.

Network Design↗
DOE OSTI2025

Progress Towards NQA-1 for Cardinal in FY25

Cardinal is a wrapping of the GPU-oriented spectral element Computational Fluid Dynamics (CFD) code NekRS and the Monte Carlo particle transport code OpenMC within the Multiphysics Object-Oriented Simulation Environment (MOOSE). Cardinal provides high-resolution thermal-hydraulics and/or radiation transport feedback to MOOSE multiphysics simulations. Multiphysics feedback is implemented in a geometry-agnostic manner which eliminates the need for rigid one-to-one mappings. A generic data transfer implementation also allows NekRS and OpenMC to couple to any MOOSE application, enabling a broad set of multiphysics capabilities. Cardinal simulations can also leverage combinations of MPI, OpenMP, and GPU resources. Cardinal continuous development and improvement efforts have led to the software being considered as a high-fidelity design and licensing tool for key areas of nuclear reactor relevant physics, including neutron transport, fluid flow, heat transfer, and mechanical processes. The fast development and expansion of the software from a pure R&D framework towards its application in the nuclear industry and regulation require a focus on developing, enhancing,and maintaining Cardinal’s software quality through strict adherence to a Software Quality Assurance (SQA) framework and SQA program. To facilitate compliance with SQA standards, the Cardinal SQA Program was initiated during Fiscal Year 2023 (FY23). During the development of the Cardinal SQA Program, multiple gaps have been identified. These gaps are primarily related to model verification and code pedigree as they relate to the use of Cardinal as an analysis tool. These gaps were captured in a report published in 2023. A second report highlighted the progress made during Fiscal Year 2024 (FY24) and described Argonne’s effort to document and integrate software verification within Cardinal’s software development process. This report documents the progress made towards NQA-1 for Cardinal in the Fiscal Year 2025 (FY25). All cases in the expanded Continuous Integration (CI) suite of NekRS are included in this report which test the solvers and modules available in NekRS exhaustively. The NekRS tests are integrated with the Cardinal CI suite and made available in publicly accessible Github documentation. Following the CI practice permits integrating of source code changes frequently and ensuring that the integrated codebase clears the verification testing for the software. Also in this report is a brief overview of the development of the Cardinal Software Quality Assurance Plan (SQAP) that was done in FY25, though it should be noted that the rest of the documentation for the SQA program needs to be developed in a future step of this task.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Modeling receiver flux of commercial power tower concentrating solar power plants using ray tracing: a round-robin comparison of SolTrace, Solstice, and TieSOL

This study presents a multi-stage, cross-validation comparison of three software packages for Monte Carlo ray tracing (MCRT) applied to central tower concentrating solar power (CSP) systems. The three packages evaluated are: (1) SolTrace, an open-source tool developed by the National Renewable Energy Laboratory (NREL); (2) Solstice, an open-source program created by CNRS-PROMES and Meso-Star, with enhancements for CSP applications (called solsticepy) from the Australian National University; and (3) TieSOL, a commercial software developed by Tietronix. This investigation extends previous ray tracing comparisons by incorporating models of multi-facet heliostats within a commercial-scale solar field, taking into account zoned focal lengths and canting configurations. Receiver flux distributions were compared across the tools using a series of case studies, including single-heliostat scenarios, isolated blocking situations, and comprehensive full-field simulations. The case studies were designed to diagnose differences across the models at varying levels of complexity, and to identify and resolve discrepancies as additional parameters were introduced. Key factors examined in the analysis include sun positions, heliostat location, facet and canting focus, and aimpoint strategies. The comparison aims to improve the accuracy and reliability of these tools while providing benchmark cases for validating future optical modeling tools.

14 SOLAR ENERGY↗
DOE OSTI2024

MolSym : A Python package for handling symmetry in molecular quantum chemistry

A consideration of the point group symmetry of molecules is often advantageous from a computational efficiency standpoint and sometimes necessary for the correct treatment of chemical physics problems. Many modern electronic structure software packages include a treatment of symmetry, but these are sometimes incomplete or unusable outside of that program’s environment. Therefore, we have developed the MolSym package for handling molecular symmetry and its associated functionalities to provide a platform for including symmetry in the implementation and development of other methods. Features include point group detection, molecule symmetrization, arbitrary generation of symmetry element sets and character tables, and symmetry adapted linear combinations of real spherical harmonic basis functions, Cartesian displacement coordinates, and internal coordinates. We present some of the advantages of using molecular symmetry as achieved by MolSym, particularly with respect to Hartree–Fock theory, and the reduction of finite difference displacements in gradient/Hessian computations. Furthermore, this package is designed to be easily integrated into other software development efforts and may be extended to further symmetry applications.

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

Abbreviated Report for 25-FS-011: Switch and Stitch Similar Subgraph Synthesizer

Government institutions utilize software from a wide array of development sources, including those written by large software companies, government contractors, and open-source repositories. Avoiding installation of malicious software components is an important national security endeavor. Automated analysis of previously unseen software is an active research area, and there is much research in the design of systems that compare new software artifacts to a large set of previously seen software records organized by various behaviors they contain. One attractive approach is to turn each compiled software binary into a graph representation and apply a graph similarity model that scores pairs of binaries by their relative similarity. When a pair is deemed similar, it is useful to know why, in the sense of providing explanations to security analysts regarding which portions of the software they should look into further.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2024

Dashboard for Marine Energy Site Assessment and Monitoring

The marine energy (ME) industry presently relies upon fragmented site assessment solutions that require high resource expenditure for deployment at each site and do not leverage the wealth of readily available tools and information. A wave energy resource assessment dashboard, currently in development, will substantially improve siting, permitting, operations, and maintenance of ME projects by providing an integrated solution that is a one-stop-shop for a developer’s needs. The Site Energy Assessment and MOnitoring Dashboard (SEAMOD) will be of commercial interest to anyone seeking to deploy an ME project and is easily expandable to include tidal and wind energy site assessments. The integrated dashboard is being developed using state-of-the-art database and cloud computing methods and data-assimilative modeling tools that can be coupled with low-cost, rapidly deployable wave buoys and environmental sensing hardware. The combined software and hardware dashboard will reduce wave energy site characterization and wave climate monitoring costs by more than 60 percent and provide assessments that meet international industry standards. To realize a thriving global ME industry, the physical environment at a potential deployment site must be understood, not only for resource characterization, but also for optimization of device and power conversion performance. SEAMOD directly addresses these needs with a commercially marketable product. SEAMOD is a low-cost solution that provides comprehensive ME resource assessments, baseline environmental monitoring, and offshore characterizations required for successful ME development. The key technical objectives for Phase I were a series of software development goals, which when implemented with monitoring solutions, produced an initial proof-of-concept low-cost wave energy resources dashboard. In Phase II, the development of the prototype SEAMOD continued. The basic framework employed was the development of a revised dashboard and monitoring tool customized for ME applications by focusing on IEC site assessment and method requirements. Development was focused on the integration of full hindcast metocean products to provide hindcast resource characterization and environmental information. The final integrated dashboard provides a low-cost solution that delivers comprehensive, scalable, industry-standard energy resource assessments and offshore characterizations required for successful ME development. The integrated dashboard offers visibility of the most recent site modeling, measurements, and historical data. The application and integration of consensus-based standards for wave energy resource assessment, as determined by the International Electrotechnical Commission (IEC), are crucial for the impact and value of SEAMOD. SEAMOD includes monthly, seasonal, and yearly statistics, as well as the total 30-year record, offering temporal resolution of the IEC parameters to aid potential developers in determining the available wave energy resources in their area of interest.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Evaluating a Commercial Dynamic Line Rating Software with the National PMU Dataset

To accelerate the development of data-driven applications for power systems, the Department of Energy (DOE) supported the collection and curation of a synchrophasor dataset spanning two years of observations from transmission utilities across the US. This National PMU Dataset (NPDS) was anonymized and distributed to awardees of a DOE research grant under nondisclosure agreements (NDAs) but has also been retained at PNNL to enable further research. Agreements with data contributors prevent the data from being shared outside the organization. However, establishing a blind research validation methodology is envisioned to maximize the value proposition of the NPDS. In this validation strategy, researchers may share algorithms/software (potentially as executables to protect intellectual property) with PNNL, and PNNL will share feedback about the software’s performance on subsets of the NPDS. Such a blind methodology ensures that sensitive information about critical infrastructure remains protected, but the value of the NPDS can be extended to research beyond PNNL. Through iterative feedback, the algorithms may be tweaked to address real-world artifacts. As the NPDS data is temporally and geographically diverse, it may capture features absent in smaller datasets used during the development of the algorithm under test. This report presents lessons learned from applying the blind validation methodology to LineID™, a synchrophasor-based dynamic line rating software developed by Topolonet Corporation. Improvements made to the software through iterative feedback, limitations of the validation methodology, as well as how the limitations of the NPDS affected the evaluation process are discussed. Observations indicate that the proposed validation methodology can be valuable for evaluating other tools in the future.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Fiscal Year 2024 Software Quality Assurance Activities for the ARC Software

The continued goal of the ARC SQA project in the Advanced Reactor Technologies program of DOE is to resolve the QA gaps for the ARC software that limit, or prevent, commercialization of the software for industry users. This project started in earnest in fiscal year 2023 which saw the entire code system moved from a SVN repository to a GitLab repository and an associated software quality assurance plan (SQAP) developed and ratified. Most of the QA gaps in the ARC software were identified in collaboration with industry partners and work begin in fiscal year 2023 and continued in 2024. The primary documentation that is missing includes user manuals, user guides, software verification reports, and code coverage assessments. The SUMMAR manual was completed this fiscal year and work was started on creating manuals for SE2ANL, SE2RCT, and DASSH. Software verification work was carried out for DIF3D and REBUS in a previous program and the current fiscal year saw the completion of software verification reports for GAMSOR, GAMSRC, VARPOW, EvaluateFlux, and SUMMAR. The goal for the next fiscal year is to complete the PERSENT software verification work and begin planning the software verification work for DASSH, SE2ANL, and SE2RCT. The code coverage reports for DIF3D and MC2-3 were completed in the previous fiscal year and the goal is to generate code coverage reports for REBUS, GAMSOR, PERSENT, and DASSH in the coming fiscal year. A considerable amount of effort was spent in the current fiscal year working on the continuous integration capability for automated regression testing in GitLab. The first version of the testing was created in the previous fiscal year and applied to DIF3D and its utility programs. That testing was extended this year to cover GAMSOR, REBUS, and PERSENT. To accomplish this, the first version of the new testing methodology had to be updated to make a single output checking methodology viable for all of the ARC software. This will result in a single document to detail the automated regression testing methodology and minor documents to detail the tolerance settings that have been applied to the output for each ARC code. The previous methodology put into place with SVN would have required a separate document for each ARC code to detail the output checking methodology and the tolerance settings for the output from each code. Because some of our industry partners are providing funds to add new capabilities to the ARC software to meet their needs, all of which must be reviewed and approved by the SQA program funded by this project, a summary of that development work is detailed in this report. Overall progress on resolving the QA gaps has been good this year with the most impactful improvement for our industry partners in capability being the creation of a threaded version of DIF3D-VARIANT that allows the DIF3D, REBUS, and GAMSOR run times to be reduced by a factor of 4-6. The most impactful QA gap that was resolved was the software verification of GAMSRC and VARPOW.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Automation of Nanoparticle Synthesis Processes in a Plasma Environment Using LabVIEW

This work presents an automated control system for the synthesis of nanomaterials by plasma-enhanced chemical vapor deposition (PECVD), implemented using the LabVIEW software environment. The main objective of the study is to develop an integrated hardware-software platform that enables sequential control of the key stages of the PECVD process, including vacuum chamber preparation, pressure monitoring, working gas supply, plasma ignition, power matching, cyclic nanomaterial growth, and optical monitoring of nanoparticles in the plasma environment. The use of LabVIEW made it possible to integrate actuator control, experimental parameter acquisition, and realtime process visualization within a single automated system. The automated cycle begins with evacuation of the reaction chamber to a predefined base pressure. Transition to the next stage is permitted only after the specified pressure threshold has been reached, ensuring reproducible initial conditions for each experiment. The program then controls the supply of the working gas through mass flow controllers (MFCs). In this work, two gas-flow control modes were considered: analog control using a 0-5 V voltage signal and digital communication via RS-232 interface. It was shown that the analog approach requires accurate scaling of the control voltage, since applying 5 V corresponds to full-scale opening of the controller and results in the maximum gas flow. In contrast, the RS232 interface enables the gas flow rate to be specified directly in sccm, improving the accuracy, flexibility, and convenience of gas-environment control. After pressure stabilization, LabVIEW initiates RF plasma ignition and executes the RF matching algorithm aimed at minimizing reflected power and improving the stability of the plasma process. A separate software module implements the cyclic nanomaterial growth mode, in which the plasma-on time, plasma duration, and total number of synthesis cycles are predefined. This approach makes it possible to control material accumulation on the substrate and to correlate the process parameters with the morphological characteristics of the resulting nanostructures. The final module of the system is designed for optical monitoring of the nanoparticle cloud density in dusty plasma. For this purpose, the change in the intensity of laser radiation passing through the plasma region is recorded using a photodetector and a Keithley 2401 measuring unit connected to LabVIEW via RS-232 interface. The difference between the initial and modified optical signal intensity is used as a diagnostic parameter characterizing the formation and temporal evolution of nanoparticles. The developed system demonstrates that LabVIEW can be effectively applied not only for the automation of individual instruments, but also for the implementation of a complete digital control cycle for PECVD-based nanomaterial synthesis.

PECVD↗
DOE OSTI2024

Deep Learning for Fish Identification from Sonar Data (CRADA 481 Final Report)

In eastern regions of the United States, the American eel is a species of management and regulatory concern because of significant population declines, despite the species’ previous abundance in all tributaries of rivers flowing into the Atlantic Ocean. The American eel is also a candidate for listing under the U.S. Endangered Species Act. While hydropower construction and operation are only one of several factors contributing to this population decline, such a listing could impose additional regulatory challenges for a large number of hydropower projects. In this CRADA project, we improved technologies for identifying migrating eels with the goal of reducing the cost and time required for future American eel hydropower impact assessment and mitigation studies, while maintaining accuracy. We built on results from a previous FOA project (FOA# DE-FOA-0001662), led by the Electric Power Research Institute (EPRI), which developed a highly accurate, deep-learning method for identifying migrating eels from imaging sonar data. The current study aimed to further optimize this deep-learning model, originally designed for image classification, and to develop an object detection software capable of identifying fish from sonar videos in real time, enabling the detection of events like fish migrations and specific species, such as the American eel, at hydropower dams. The data conversion algorithms were packaged as software with a graphical user interface, and the software is evaluated by external collaborators. We focused on the American eel in this project and explored the transferability of the developed deep learning models to the sea lamprey, given the similar body shape and swimming behavior between the two species.

13 HYDRO ENERGY↗
DOE OSTI2025

Autonomous Flow Electrochemistry for Accelerated Catalyst Discovery

Our objective is to develop an Autonomous Chemical Experimentation (ACE) platform that accelerates discovery of new catalytic transformations and other energy-relevant chemical reactions and processes. We intentionally designed ACE to be highly modular, both with respect to its rapid deployment to different chemistries and experimental workflows as well as incorporation of a wide range of different AI algorithms. In addition to the development of the core software architecture, initial efforts were made to incorporate Large Language Models to provide human-interpretable reasoning of the optimizer’s actions, and to develop a user-friendly graphical interface for experimental researchers. ACE was demonstrated using a flow electrocatalysis platform containing an inline FTIR spectrometer for real-time analysis and quantification of the reaction outcome. Human-in-the-loop experiments were performed in which a human researcher conducted an experiment using electrode potentials suggested by ACE, then fed the spectral data back to ACE for decision making. After confirming the successful function of the optimizer, efforts were next directed to automation of the hardware and performed full autonomy tests using three reactions: catalytic oxidation of formate, catalytic oxidation of cyclohexanol, and oxidation of hydroquinone. These studies confirm that ACE can close the loop between reaction execution, analysis, and optimization. They also reveal that more improved product detection methods will be essential for ACE to make well-informed decisions for reactions with low conversions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

300_underground robot (final research report)

Recent advancements in mobile robotics have displayed impressive capabilities in traversing and accessing areas that are inaccessible to humans either due to the characteristics of the environment or potential hazards. Furthermore, these advancements within the field of mobile robotics, more specifically uncrewed ground vehicles (UGVs), give the ability to potentially survey, observe, and map these inaccessible areas for humans. However, one of the most challenging areas to implement this technology is underground environments. The main challenge with implementing this technology in underground environments is the dependence on either GPS or RF communication for UGVs to navigate properly. Therefore, in order to properly demonstrate the mapping capabilities of the UGV this challenge must be resolved. The overall goal of this study is to demonstrate the mapping capabilities of a UGV while addressing this challenge and documenting the implementation and testing phase of the robot. The proposed solution to this challenge is to implement a SLAM algorithm onto the main computational device of the UGV utilizing the Robot Operating System (ROS). The algorithm is the open-source software package Slam Toolbox developed by Steve Macenski. Furthermore, the sllidar_ros2 package from Slamtec will be used to gather the lidar data from an A3M1 2D lidar. A separate program will be created to gather odometry information for our UGV robot. All of these software packages will run together in a Docker environment. Through working on this project I have developed a better understanding of the world of robotics/autonomous systems, especially with applications such as navigation and mapping. Furthermore, through this project, I have been given exposure to how research is conducted within a DOE lab setting. As robotics/autonomous systems become more advanced it's important to pursue more avenues of research such as this project as it will ensure the development of our capabilities.

42 ENGINEERING↗
DOE OSTI2026

Multi-Artifact Analysis of Self-Admitted Technical Debt in Scientific Software

Context: Self-admitted technical debt (SATD) occurs when developers acknowledge shortcuts in code. In scientific software (SSW), such debt poses unique risks to the validity and reproducibility of results. Objective: This study aims to identify, categorize, and evaluate scientific debt, a specialized form of SATD in SSW, and assess the extent to which traditional SATD categories capture these domain-specific issues. Method: We conduct a multi-artifact analysis across code comments, commit messages, pull requests, and issue trackers from 23 open-source SSW projects. We construct and validate a curated dataset of scientific debt, develop a multi-source SATD classifier to guide SATD management, and conduct a practitioner validation to assess the practical relevance of scientific debt. Results: Our classifier performs strongly across 900,358 artifacts from 23 SSW projects. SATD is most prevalent in pull requests and issue trackers, underscoring the value of multi-artifact analysis. Models trained on traditional SATD often miss scientific debt, emphasizing the need for its explicit detection in SSW. Practitioner validation confirmed that scientific debt is both recognizable and useful in practice. Conclusions: Scientific debt represents a unique form of SATD in SSW that that is not adequately captured by traditional categories and requires specialized identification and management. Our dataset, classification analysis, and practitioner validation results provide the first formal multi-artifact perspective on scientific debt, highlighting the need for tailored SATD detection approaches in SSW.

Melin, Eric [Boise State University]↗
DOE OSTI2025

Towards exact finite temperature electronic structure in solids and molecules (Final Technical Report)

This report describes the University of Iowa portion of a project that is now continuing at Michigan State University. We are developing novel methods, algorithms, and software to enable simulations of molecules and materials at high temperature. This is a key challenge in chemistry and materials science. By refining an approach called Density Matrix Quantum Monte Carlo (DMQMC), we developed faster and more accurate ways to conduct these simulations. These advances will help us understand how temperature affects the behavior of electrons, chemical bonds, and phase transitions in solids and molecules. These breakthroughs are especially important for applications where light and heat drive chemical reactions, superconductivity, and materials used in energy and sensing. In addition, this project involved the development of the open-source HANDE-QMC software package, supporting the broader community in benchmarking and developing finite-temperature electronic structure methods.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The 200 Gbps Challenge: Imagining HL-LHC analysis facilities

The IRIS-HEP software institute, as a contributor to the broader HEP Python ecosystem, is developing scalable analysis infrastructure and software tools to address the upcoming HL-LHC computing challenges with new approaches and paradigms, driven by our vision of what HL-LHC analysis will require. The institute uses a "Grand Challenge" format, constructing a series of increasingly large, complex, and realistic exercises to show the vision of HL-LHC analysis. Recently, the focus has been demonstrating the IRIS-HEP analysis infrastructure at scale and evaluating technology readiness for production. As a part of the Analysis Grand Challenge activities, the institute executed a "200 Gbps Challenge", aiming to show sustained data rates into the event processing of multiple analysis pipelines. The challenge integrated teams internal and external to the institute, including operations and facilities, analysis software tools, innovative data delivery and management services, and scalable analysis infrastructure. The challenge showcases the prototypes - including software, services, and facilities - built to process around 200 TB of data in both the CMS NanoAOD and ATLAS PHYSLITE data formats with test pipelines. The teams were able to sustain the 200 Gbps target across multiple pipelines. The pipelines focusing on event rate were able to process at over 30 MHz. These target rates are demanding; the activity revealed considerations for future testing at this scale and changes necessary for physicists to work at this scale in the future. The 200 Gbps Challenge has established a baseline on today's facilities, setting the stage for the next exercise at twice the scale.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Real time heat load calculation software based on EPICS for Fermilab PIP-II CM tests

Fermilab has a project to improve the proton beam energy which is called PIP-II (the 2nd Proton Improvement Plan). There is a superconducting linear accelerator, LINAC, to improve the proton beam power and the LINAC consists of 5 types of cryomodules (CM), 1 HWR CM, 2 SSR1 CM, 4 SSR2 CM, LB650 CM, and HB650 CM. The prototypes of these cryomodules are being tested at Fermilab’s CryoModule Test Facility (CMTF). Heat load measurements are an important part of the prototype CM testing. The CMTF cryogenic control system was developed based on the ACNET (Accelerator Control NETwork) for CM testing for other projects, but the PIP-II cryogenic control system will be implemented using the Experimental Physics and Industrial Control System (EPICS). As part of the prototype CM testing campaign an EPICS based control system has been implemented at CMTF. This EPICS cryogenic control system includes real time heat load calculation software utilizing the Fortran implementation of Hepak. This paper details the real time heat load calculation software developed for the prototype CM testing including the first results from the HB 650 CM.

Yoon, S. [Fermilab]↗
DOE OSTI2026

Real time heat load calculation software based on EPICS for Fermilab PIP-II CM tests

Fermilab has a project to improve the proton beam energy which is called PIP-II (the 2nd Proton Improvement Plan). There is a superconducting linear accelerator, LINAC, to improve the proton beam power and the LINAC consists of 5 types of cryomodules (CM), 1 HWR CM, 2 SSR1 CM, 4 SSR2 CM, LB650 CM, and HB650 CM. The prototypes of these cryomodules are being tested at Fermilab’s CryoModule Test Facility (CMTF). Heat load measurements are an important part of the prototype CM testing. The CMTF cryogenic control system was developed based on the ACNET (Accelerator Control NETwork) for CM testing for other projects, but the PIP-II cryogenic control system will be implemented using the Experimental Physics and Industrial Control System (EPICS). As part of the prototype CM testing campaign, an EPICS based control system has been implemented at CMTF. This EPICS cryogenic control system includes real-time heat load calculation software utilizing the Fortran implementation of Hepak. This paper details the real time heat load calculation software developed for the prototype CM testing including the first results from the HB650 CM.

Yoon, S. [Fermilab]↗