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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Model Data Archive Associated with Manuscript "Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon"

This data package supports the publication “Fire-altered Carbon Pools Create Disturbance Memory in Stream Dissolved Organic Carbon” by Li et al. (2026). The package contains processed model inputs, configuration files, restart files, simulation outputs, scripts, and visualization products used to evaluate post-fire dissolved organic carbon (DOC) dynamics in the Naches River Watershed, Washington, USA, following the 2021 Schneider Springs Fire. The modeling workflow couples ELM-BGC, the biogeochemistry-enabled Energy Exascale Earth System Model Land Model; ATS, the Advanced Terrestrial Simulator for integrated surface-subsurface hydrology; and PFLOTRAN, a reactive transport model for multicomponent aqueous geochemistry. Together, these models simulate how wildfire-induced changes in vegetation, litter, coarse woody debris, and soil organic matter influence DOC production, transport, and reaction from burned hillslopes to stream networks. The archive includes preprocessed meteorological, geospatial, hydrologic, and biogeochemical forcing data; ELM-BGC-derived DOC source terms; ATS mesh files; PFLOTRAN reactive-transport inputs; model configuration files; spin-up and transient restart files; watershed-scale diagnostic outputs; stream concentration time series; and figures or visualization files used to inspect and reproduce key results. File types include Hierarchical Data Format 5 (HDF5) files for gridded forcing and model-coupling data, model input and configuration files for ELM-BGC, ATS, and PFLOTRAN, restart and simulation-output files generated by the modeling workflow, tabular or time-series diagnostic outputs, scripts for post-processing and figure generation, and image or visualization products associated with the manuscript. Use of the package depends on the intended task. Re-running the simulations requires the relevant modeling software, including ELM-BGC, ATS, and PFLOTRAN as ATS's geochemical engine. Inspecting outputs and reproducing figures requires Python with scientific plotting libraries such as Matplotlib, and three-dimensional model outputs may be viewed with ParaView. Geographic information system files or maps may be inspected with ArcGIS Pro or comparable GIS software. The data package is intended to enable traceability, reuse, and partial reproduction of the coupled land-to-watershed hydro-biogeochemical modeling workflow used to test how wildfire disturbance affects terrestrial carbon pools and downstream DOC dynamics.

ATS↗
NASA NTRSDate not supplied

Cloud Computing Option for Modeling the Debris Environment

NASA’s Digital Transformation Initiative aims to promote the agency’s adoption of current and evolving digital technologies. Through agency-wide collaboration with other NASA teams, the Office of Safety and Mission Assurance (OSMA) has directed the Orbital Debris Program Office and the Meteoroid Environment Office to integrate cloud computing technologies in their publicly released software models: the Orbital Debris Engineering Model (ORDEM) and the Meteoroid Engineering Model (MEM). Decoupling the user interface from the backend processor was key for the software packages to run on a cloud computing framework. Benefits to this design include horizontal scaling of computing resources, user authentication and authorization, and automated deployment. Both models are hosted on a cloud computing platform supported by the NASA authorized IT security and compliance framework. This paper focuses on the new ORDEM web application, which includes the current features of the publicly released ORDEM software with an upgraded frontend design. The underlying ORDEM processor is run on a cloud container, allowing the user to run multiple spacecraft and telescope/radar mode simulations. Featuresexclusive to the ORDEM web application, such as importing multiple TLEs, auto-generated plotting, and the ability to check runtime progress are discussed. Comparisons between the current ORDEM software and the web application are summarized.

Andrew Vavrin↗
NASA NTRS2023

Cloud Computing Option for Modeling the Debris Environment

NASA’s Digital Transformation Initiative aims to promote the agency’s adoption of current and evolving digital technologies. Through agency-wide collaboration with other NASA teams, the Office of Safety and Mission Assurance (OSMA) has directed the Orbital Debris Program Office and the Meteoroid Environment Office to integrate cloud computing technologies into their publicly released software models: the Orbital Debris Engineering Model (ORDEM) and the Meteoroid Engineering Model (MEM). Decoupling the user interface from the backend processor was key for the software packages to run on a cloud computing framework. Benefits to this design include horizontal scaling of computing resources, user authentication and authorization, and automated deployment. Both models are hosted on a cloud computing platform supported by the NASA authorized IT security and compliance framework. This paper focuses on the new ORDEM web application, which includes the current features of the publicly released ORDEM software with an upgraded frontend design, although parallels between ORDEM and MEM are also discussed. The underlying ORDEM processor is run on a cloud container, allowing the user to run multiple spacecraft and telescope/radar mode simulations. Features exclusive to the ORDEM web application, such as importing multiple TLEs, auto-generated plotting, and the ability to check runtime progress are discussed. Comparisons between the current ORDEM software and the web application are summarized.

Andrew Vavrin↗
DOE OSTI2020

Off-design performance of molten salt-driven Rankine cycles and its impact on the optimal dispatch of concentrating solar power systems

This paper presents a model for improving off-design performance predictions for molten salt-driven Rankine power cycles, such as in concentrating solar power tower applications. The model predicts cycle off-design performance under various boundary conditions, including molten salt inlet temperature, mass flow rate, and ambient temperature. The model is validated using industry performance data and benchmarked with results from the literature. A complete concentrating solar power plant, inclusive of solar heliostat field and receiver, is then considered, by implementing the Rankine cycle off-design performance results into the National Renewable Energy Laboratory’s System Advisor Model software, which includes a tool that determines optimal power production schedules. The work improves upon the current System Advisor Model by updating off-design performance characteristics. A case study demonstrates the impact of cycle off-design behavior on annual performance for a stand-alone concentrating solar power system and a concentrating solar power-photovoltaic hybrid system. In addition, we demonstrate how cycle off-design performance influences optimal operator dispatch decisions and, thereby, overall system design and economics. We conclude that off-design cycle performance impacts “optimal” sub-system sizing, especially for a concentrating solar power-photovoltaic hybrid configuration in which concentrating solar power must dispatch in conjunction with photovoltaic generation.

14 SOLAR ENERGY↗
DOE OSTI2024

QUIC-DEPDOSE: Software tools to prepare for and respond to nuclear emergencies

QUIC-DEPDOSE is a software application that calculates radiation doses from inhalation of radionuclides downstream from an atmospheric radiological release. Unlike other radiological modeling software, QUIC-DEPDOSE can provide accurate dose information in as little as an hour running on a regular laptop, allowing for use by emergency responders after an accident.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS2007

High-Performance, Radiation-Hardened Electronics for Space Environments

The Radiation Hardened Electronics for Space Environments (RHESE) project endeavors to advance the current state-of-the-art in high-performance, radiation-hardened electronics and processors, ensuring successful performance of space systems required to operate within extreme radiation and temperature environments. Because RHESE is a project within the Exploration Technology Development Program (ETDP), RHESE's primary customers will be the human and robotic missions being developed by NASA's Exploration Systems Mission Directorate (ESMD) in partial fulfillment of the Vision for Space Exploration. Benefits are also anticipated for NASA's science missions to planetary and deep-space destinations. As a technology development effort, RHESE provides a broad-scoped, full spectrum of approaches to environmentally harden space electronics, including new materials, advanced design processes, reconfigurable hardware techniques, and software modeling of the radiation environment. The RHESE sub-project tasks are: SelfReconfigurable Electronics for Extreme Environments, Radiation Effects Predictive Modeling, Radiation Hardened Memory, Single Event Effects (SEE) Immune Reconfigurable Field Programmable Gate Array (FPGA) (SIRF), Radiation Hardening by Software, Radiation Hardened High Performance Processors (HPP), Reconfigurable Computing, Low Temperature Tolerant MEMS by Design, and Silicon-Germanium (SiGe) Integrated Electronics for Extreme Environments. These nine sub-project tasks are managed by technical leads as located across five different NASA field centers, including Ames Research Center, Goddard Space Flight Center, the Jet Propulsion Laboratory, Langley Research Center, and Marshall Space Flight Center. The overall RHESE integrated project management responsibility resides with NASA's Marshall Space Flight Center (MSFC). Initial technology development emphasis within RHESE focuses on the hardening of Field Programmable Gate Arrays (FPGA)s and Field Programmable Analog Arrays (FPAA)s for use in reconfigurable architectures. As these component/chip level technologies mature, the RHESE project emphasis shifts to focus on efforts encompassing total processor hardening techniques and board-level electronic reconfiguration techniques featuring spare and interface modularity. This phased approach to distributing emphasis between technology developments provides hardened FPGA/FPAAs for early mission infusion, then migrates to hardened, board-level, high speed processors with associated memory elements and high density storage for the longer duration missions encountered for Lunar Outpost and Mars Exploration occurring later in the Constellation schedule.

Keys, Andrew S.↗
DOE OSTI2020

Behind the Meter Storage for Electric Vehicle Charging, Electrochemical and Thermal Energy Storage, and Solar Photovoltaic

In response to the potentially large and irregular demand from EVs, along with changing load profiles from buildings with on-site generation, utilities are evaluating multiple options for managing dynamic loads, including time-of-use pricing, demand charges, battery storage, and curtailment of variable generation. Buildings, as well as commercial, public, and workplace EV charging operations, can use a combination of electrochemical battery storage and thermal energy storage coupled with on-site generation to manage energy costs as well as provide resiliency and reliability for EV charging and building energy loads. We are completing a behind the meter storage analysis that focuses on determining the optimal system designs and energy flows for thermal and electrochemical behind the meter storage with on-site solar photovoltaic (PV) generation enabling electric vehicle charging in various climates, building types, and utility rate structures. In completing this analysis, we have developed a tool that combines existing battery models via the System Advisor Model (SAM) and building modeling software via EnergyPlus into a single interface. This tool allows us to simulate a building with a detailed battery model to properly size the battery, thermal energy storage, and solar PV systems to maximize profit for the system owner. This also allows us to assess how the battery degrades under various supervisory control dispatch algorithms to control charging/discharging; we can also see how thermal energy storage is created and used to complement the battery to reduce thermal loads in the building. With this project, we can analyze new batteries that are designed specifically for energy storage, rather than designed to be extremely energy dense for electric vehicle applications, using battery lifetime models from other national labs and the existing SAM battery model, which has detailed lifetime and degradation parameters. We can also assess novel thermal storage technologies by integrating them into the whole building energy simulation program EnergyPlus. Because the model calls both SAM and EnergyPlus, required inputs need to be compatible for both models. These inputs include, on a high-level, the following: weather files, building and electric vehicle load profiles, electricity rate tariff information, and system cost information for the stationary battery, solar PV, and thermal storage system. The various buildings we are studying for this analysis are retail big-box grocery store, commercial office building, fleet vehicle depot and operations facility, multi-family residential, and electric vehicle charging station. For these different applications, the battery and thermal storage will be dispatched differently, and the various technologies are sized differently to optimize cost.

30 DIRECT ENERGY CONVERSION↗
NASA NTRS1994

Design for dependability: A simulation-based approach

This research addresses issues in simulation-based system level dependability analysis of fault-tolerant computer systems. The issues and difficulties of providing a general simulation-based approach for system level analysis are discussed and a methodology that address and tackle these issues is presented. The proposed methodology is designed to permit the study of a wide variety of architectures under various fault conditions. It permits detailed functional modeling of architectural features such as sparing policies, repair schemes, routing algorithms as well as other fault-tolerant mechanisms, and it allows the execution of actual application software. One key benefit of this approach is that the behavior of a system under faults does not have to be pre-defined as it is normally done. Instead, a system can be simulated in detail and injected with faults to determine its failure modes. The thesis describes how object-oriented design is used to incorporate this methodology into a general purpose design and fault injection package called DEPEND. A software model is presented that uses abstractions of application programs to study the behavior and effect of software on hardware faults in the early design stage when actual code is not available. Finally, an acceleration technique that combines hierarchical simulation, time acceleration algorithms and hybrid simulation to reduce simulation time is introduced.

Goswami, Kumar K.↗
NASA NTRS2008

Robustness Analysis and Reliable Flight Regime Estimation of an Integrated Resilent Control System for a Transport Aircraft

Formal robustness analysis of aircraft control upset prevention and recovery systems could play an important role in their validation and ultimate certification. As a part of the validation process, this paper describes an analysis method for determining a reliable flight regime in the flight envelope within which an integrated resilent control system can achieve the desired performance of tracking command signals and detecting additive faults in the presence of parameter uncertainty and unmodeled dynamics. To calculate a reliable flight regime, a structured singular value analysis method is applied to analyze the closed-loop system over the entire flight envelope. To use the structured singular value analysis method, a linear fractional transform (LFT) model of a transport aircraft longitudinal dynamics is developed over the flight envelope by using a preliminary LFT modeling software tool developed at the NASA Langley Research Center, which utilizes a matrix-based computational approach. The developed LFT model can capture original nonlinear dynamics over the flight envelope with the ! block which contains key varying parameters: angle of attack and velocity, and real parameter uncertainty: aerodynamic coefficient uncertainty and moment of inertia uncertainty. Using the developed LFT model and a formal robustness analysis method, a reliable flight regime is calculated for a transport aircraft closed-loop system.

Shin, Jong-Yeob↗
NASA NTRS2013

Kennedy Space Center: Swamp Works

When I began my internship with the Granular Mechanics and Regolith Operations laboratory (GMRO), also known as Swamp Works, I was given the unique opportunity to shadow many teams working on various projects, and decide what projects I wanted to take part in. Before I go into details of my experiences at Swamp Works, I would like to take a moment to explain what I discovered Swamp Works to be. Swamp Works is a family of hardworking, dedicated, and driven people from various backgrounds and skill sets. These people all work to advance technologies and make science fiction science fact through means of rapid prototyping. They support and encourage failure as an option when learning new things, as long as lesson learned from said failure. In fact, their motto states "Fail, Fast, Forward." What this means is, not if but when one fails he or she must do so quickly and spring forward from the failure so that his or her progress is not delayed. With this acceptance, it provided me the confidence to dive into a multitude of projects working in various fields and with a wide range of skill sets. The first project I joined was Badger. My motivation for taking on this project was the opportunity I would have to obtain valuable experience working with 3D modeling and 3D printing technologies. Badger was a digging apparatus to be used in a highly dusty environment in a material known as Regolith. Regolith is a scientific term for the dirt or top soil found on planetary bodies. Regolith contains a large quantity of sediments less than lOppm and as a result poses a challenge of keeping it out of any cracks and crevices. Furthermore, regolith can create high levels of electrostatic energy, which can prove damaging to sensitive electrical hardware. With these characteristics in mind, I decided to take on the task of designing and manufacturing a dust proof cover for the sensitive electrical hardware. When I began this project, I did not have the slightest idea as to how to use 3D modeling software or a means of manufacturing a viable product. As I went along with variants of the design, I became very proficient with a 3D modeling program known as CREO 2.0. Upon completion of my 3D design, I then had the task of manufacturing and having, in my hands, a usable model. To do this I had to work with additive printing technologies also known as 3D printing. Through my experiences working with Badger, I realized that 3D modeling is the focal point in much of engineering. With this in mind, I have embraced this fact and decided to further my experience with this software so that I may become a more valuable asset to any firm later in my career. Mid-way through work with Badger, I picked up another project in which I found much interest. I ha~ the opportunity to work side by side with a materials and composites guru in manufacturing carbon composite coupons (test strips) for performing stress, strain, and sheer analysis on. Being from a surfing, kiteboarding, and other water sport background I have always been interested in board design. With this in mind, it is no wonder why I found interest in such a project. I had the opportunity to refine Mold preparatory, composite layup, and composite curing techniques. Following manufacturing of these composite strips, I then performed various stress tests and logged my results. With these results, future teams could create lighter, stronger, and more cost effective composite structures for use in varieties of applications. After my experiences with materials and composites testing, I have obtained crucial appreciation for detailed documentation and analysis that material sciences involve. However, as interesting as composite materials testing has been, I do not feel this is where my future career lies. Another, more on the side, project I have been involved in is building a 626 cubic foot regolith containment chamber for doing full scale testing of robotic systems. This chamber is built of high strength aluminum scaffold materials, 80/20, and massive panels of Lexan. Once the chamber is completed, it is be filled with 120 tons of regolith and dubbed the largest regolith test chamber in the world. Through my experiences with building "Big Bin" as we called it, I discovered my demand for engaging and hands on activities. Through all of my incredible experiences working with the Swamp Works at Kennedy Space Center; I have obtained crucial knowledge, insights, and experiences that have fuelled, shaped, and will continue to drive me toward my ultimate goal of obtaining not only a degree in Engineering, but obtaining a job that I can call a career. I want to give much thanks to all of those who mentored me along my journey, and to all who made this opportunity a reality.

DeFilippo, Anthony Robert↗
DOE OSTI2024

Development and Experimental Optimization of High-Temperature Modeling Tools and Methods for Concentrated Solar Power Particle - Systems

A novel, open-source radiative modeling toolset was developed to extend the functionality of particle-based modeling software (e.g. discrete element method (DEM)) to environmental conditions relevant to concentrated solar power applications. This toolset was optimized for deployment on desktop workstations instead of high-performance computing systems, to render such tools more accessible to the research community. Both particle-based modeling and radiative exchange modeling are computationally expensive and often require specialized programming expertise, making these methods cumbersome to use. Recent developments in DEM software by DCS Computing have greatly reduced these challenges, providing a graphical-user-interface based platform and modeling optimization for desktop workstations, HPCs, and cloud computing. The University of Dayton leveraged the experience of DCS Computing in developing a user-friendly, open-source radiative heat transfer expansion for DEM modeling. The University of Dayton DEM+ radiative modeling toolset was developed using a combination of fundamental experimental measurements, modeling, and simplified flow experiments over a range of temperatures and flow conditions. The toolset provides researchers with access to multiple radiative models including an accelerated Monte-Carlo Ray Tracing (application agnostic, highly computationally expensive), an expanded database of distance-based approximations (application limited, computationally light), and a weighted blending of the two methods capable of achieving over 90% reduction in computation time with equivalent accuracy compared to Monte-Carlo Ray Tracing. Through a graphical user interface, users can customize the radiative models to match their desired accuracy and available computational resources, improving access to particle based modeling for the research community. Ceramic sintered bauxite proppants were used in modeling and experimentally as a baseline. Both the radiative heat transfer and flow properties for particulate systems were investigated at elevated temperatures up to 800 °C. The major accomplishments for this work include a verified, open-source radiative modeling toolset to be distributed amongst the research community and the fabrication of three small-scale test facilities to investigate particle behavior and tune DEM flow properties for operation up to 800 °C. The findings have been shared with the research community via conference modeling workshops, deployment of the tools in DCS Computing Aspherix®, and open-source access to the developed radiative modeling tool. The development of next-generation CSP facilities and thermal energy storage systems based on ceramic particles requires providing access to computationally efficient and accurate modeling tools. Particles will experience a wide range of environments (20-800 °C) and handling conditions (dilute curtains or dense packing), requiring specially designed and optimized equipment. Optimizing solid particle physics models and establishing best-practices for particle modeling in CSP environments will assist researchers with designing optimized equipment, accelerating the deployment of more economically-competitive CSP facilities.

14 SOLAR ENERGY↗
NASA NTRS1986

C.A.D. representation of ternary and quaternary phase diagrams

This work is concerned with the utilization of C.A.D. solid-modeling software for the computer representation of three-dimensional phase diagrams. The work was undertaken in two parts. First, the C.A.D. software (I-DEAS, by Structural Dynamics Research Corp.) was integrated with a variety of auxiliary Fortran 77 and I-DEAS language programs which were written specifically for the purpose of phase diagram representation. The capabilities of the resulting suite of software for three-dimensional phase diagram representation were developed and illustrated by the construction, display and manipulation of solid-model phase diagrams for a hypothetical quaternary eutectic system. The results of this work are discussed in some detail in the attached publication ('Solid-modeling: a C.A.D. Alternative for Three-dimensional Phase Diagram Representation'). Such a technique is of general applicability, having utility in both research and education. Secondly, using the C.A.D. technique, data from the literature (gleaned from some 70 separate publications), which represent experimentally determined phase boundaries, were combined to form solid-model representations of the CMS2-M2S-S ternary space diagram and the CMS2-CAS2-M2S-S quaternary liquidus projection (where C=CaO, M=MgO, A=Al2O3, and S=SiO2). These diagrams were utilized in a concurrent study of solidification in the CMAS system.

Delao, James D.↗
NASA NTRS2006

Modeling and Correcting the Time-Dependent ACS PSF

The ability to accurately measure the shapes of faint objects in images taken with the Advanced Camera for Surveys (ACS) on the Hubble Space Telescope (HST) depends upon detailed knowledge of the Point Spread Function (PSF). We show that thermal fluctuations cause the PSF of the ACS Wide Field Camera (WFC) to vary over time. We describe a modified version of the TinyTim PSF modeling software to create artificial grids of stars across the ACS field of view at a range of telescope focus values. These models closely resemble the stars in real ACS images. Using 10 bright stars in a real image, we have been able to measure HST s apparent focus at the time of the exposure. TinyTim can then be used to model the PSF at any position on the ACS field of view. This obviates the need for images of dense stellar fields at different focus values, or interpolation between the few observed stars. We show that residual differences between our TinyTim models and real data are likely due to the effects of Charge Transfer Efficiency (CTE) degradation. Furthermore, we discuss stochastic noise that is added to the shape of point sources when distortion is removed, and we present MultiDrizzle parameters that are optimal for weak lensing science. Specifically, we find that reducing the MultiDrizzle output pixel scale and choosing a Gaussian kernel significantly stabilizes the resulting PSF after image combination, while still eliminating cosmic rays/bad pixels, and correcting the large geometric distortion in the ACS. We discuss future plans, which include more detailed study of the effects of CTE degradation on object shapes and releasing our TinyTim models to the astronomical community.

Rhodes, Jason↗
NASA NTRS2015

The Safe Removal of Frozen Air from the Annulus of an LH2 Storage Tank

Large Liquid Hydrogen (LH2) storage tanks are vital infrastructure for NASA. Eventually, air may leak into the evacuated and perlite filled annular region of these tanks. Although the vacuum level is monitored in this region, the extremely cold temperature causes all but the helium and neon constituents of air to freeze. A small, often unnoticeable pressure rise is the result. As the leak persists, the quantity of frozen air increases, as does the thermal conductivity of the insulation system. Consequently, a notable increase in commodity boil-off is often the first indicator of an air leak. Severe damage can result from normal draining of the tank. The warming air will sublimate which will cause a pressure rise in the annulus. When the pressure increases above the triple point, the frozen air will begin to melt and migrate downward. Collection of liquid air on the carbon steel outer shell may chill it below its ductility range, resulting in fracture. In order to avoid a structural failure, as described above, a method for the safe removal of frozen air is needed. A thermal model of the storage tank has been created using SINDA/FLUINT modeling software. Experimental work is progressing in an attempt to characterize the thermal conductivity of a perlite/frozen nitrogen mixture. A statistical mechanics model is being developed in parallel for comparison to experimental work. The thermal model will be updated using the experimental/statistical mechanical data, and used to simulate potential removal scenarios. This paper will address methodologies and analysis techniques for evaluation of two proposed air removal methods.

cryogenic insulation↗
DOE OSTI2022

GOOML - Finding Optimization Opportunities for Geothermal Operations: Preprint

Geothermal Operational Optimization with Machine Learning (GOOML) is a transferable and extensible component-based geothermal asset modeling framework that considers complex steamfield relationships and identifies optimization prospects using a data-driven approach. We have used this framework to develop digital twins that provide steamfield operators with an operational environment to analyze and understand historical and forecasted power production, explore new steamfield configuration possibilities, and seek optimal asset management for real world applications. The GOOML modeling software is built on a generic component-based systems framework that allows for both historical and forecast analysis. A GOOML model can perform historical data-assimilation using first-principal thermodynamics to create a meaningful data model. Historical production data can then be coupled with a forecast framework to train machine-learning models of steamfield components to predict future outputs. This modeling environment enables digital exploration of steamfield design configurations and operational scenarios. GOOML digital twins have been developed for steamfields in New Zealand and the United States representing differing power generation and field conditions. These digital twins have been validated by comparing hindcast predictions against historical production data. Reinforcement learning experiments were conducted to demonstrate the ability to programmatically explore the operations space using machine learning agents. Our initial results are compelling; two to five percent increases in annual energy production were demonstrated by the GOOML models with no additional infrastructure build required. GOOML offers a new approach to geothermal operations by applying state-of-the-art machine learning algorithms, comprehensive data analytics, and interaction with digital twins. Through application of these tools, operators will realize greater availability and higher net generation which will increase the cost effectiveness of geothermal energy projects.

access↗
DOE OSTI2025

Multi-Entity Simulation with CoSim Toolbox

Co-simulation is an analysis technique for linking multiple software models during runtime by facilitating data exchange and simulation time synchronization. There are numerous challenges when constructing an effective co-simulation including simulation tool installation, data management, and writing new models in a manner compatible with the co-simulation framework of choice. CoSim Toolbox is an integration of multiple pieces of software designed to make assembling such a co-simulation in HELICS easier. This report summarizes the existing capabilities of CoSim Toolbox and outlines future development plans.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Modeling of a Four-Stage Linear Ionization Cooling Channel for a Muon Collider in g4Beamline

A previous study of an eight-stage rectilinear ionization cooling channel in the ICOOL software demonstrated a five-order-of-magnitude reduction in a muon beam’s 6D emittance. In this study, we look to compare the ways ICOOL and Muons, Inc.’s g4Beamline software model ionization cooling by comparing their modeling of the first four stages of this optimized cooling channel constructed in ICOOL. We begin by identifying the parameters used to construct the optimized ionization cooling channel in ICOOL. We then reconstruct this beam in g4Beamline with identical parameter specifications and simulate the cooling of an identical input beam. Finally, we compare the two simulations based on their beam transmission, longitudinal emittance, and transverse emittance along the channel length. Through this process, we demonstrate that G4Beamline accurately reproduces transverse cooling results but predicts systematically different longitudinal emittance evolution while maintaining similar overall cooling performance, reproducing a 97.9% reduction in 6D emittance over four stages.

Keeler, Dominic [Purdue U., West Lafayette] (ORCID↗
DOE OSTI2026

Modeling of a Four-Stage Linear Ionization Cooling Channel for a Muon Collider in G4Beamline

A previous study of an eight-stage rectilinear ionization cooling channel in the ICOOL software demonstrated a five-order-of-magnitude reduction in a muon beam’s 6D emittance. In this study, we look to compare the ways ICOOL and Muons, Inc.’s g4Beamline software model ionization cooling by comparing their modeling of the first four stages to this optimized cooling channel constructed in ICOOL. We begin by identifying the parameters used to construct the optimized ionization cooling channel in ICOOL. We then reconstruct this beam in g4Beamline with identical parameter specifications and simulate the cooling of an identical input beam. Finally, we compare the two simulations based on their beam transmission, longitudinal emittance, and transverse emittance along the channel length. Through this process, we demonstrate that G4Beamline accurately reproduces transverse cooling results but predicts systematically different longitudinal emittance evolution while maintaining similar overall cooling performance, reproducing a 97.9% reduction in 6D emittance over four stages.

Keeler, Dominic [Purdue U., West Lafayette] (ORCID↗