Results for “System Engineering and Integrations” — Page 4

DOE OSTI2025

A Recipe for ABC Multifamily Retrofits: Technologies, Financing, and Project Delivery

This report documents the final technical accomplishments and outcomes of Rocky Mountain Institute’s project under the U.S. Department of Energy (DOE) Award DE-EE0009064. The project aimed to develop, validate, and scale whole building retrofit solutions for multifamily buildings, including two configurations of Integrated Mechanical System Pods (IMSP-C and IMSP-U), in alignment with DOE Advanced Building Construction (ABC) initiative's decarbonization and energy efficiency goals. While the project made significant progress in Budget Period 1 (Phase 1) and throughout Budget Period 2 (Phase 2), activities were discontinued as of March 26, 2025, following a Stop Work Order issued by DOE. As such, this report reflects all completed work through that date. The project did not enter Budget Periods 3 and 4 (Phase 2), and demonstration site implementation, field M&V, and final commercialization execution were not conducted.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

From Data to Knowledge: A Graph-Based Reliability Approach to Assess System Health

With the goal of maximizing plant reliability and availability, complex systems such as nuclear power plants continuously monitor and record the performance and the health status of many components, assets, and systems. Such data may take the form of online monitoring data, condition reports, and maintenance reports and it carries the potential to provide system engineers with insights into anomalous behaviors or degradation trends as well as the possible causes behind them and to predict their direct consequences. The analysis of such data poses however few challenges. While some of these challenges are technical in nature (i.e., data are often distributed over several physical servers or databases), others are conceptual in nature (i.e., data elements come in different formats, numeric or textual), and measured values have different scales (e.g., vibration spectra and oil temperature). This paper directly tackles these challenges, and it focuses on the integration of all these data elements in order to assist plant system engineers in analyzing component, assets, and systems performances and optimize maintenance activities. This is performed by 1) extracting knowledge from textual data via technical language processing methods, and 2) quantifying system, asset, and component health from numeric condition-based data. We rely on model-based system engineering (MBSE) models of systems and assets to identify their architecture and functional (i.e., cause and effect) relations. Numeric and textual data elements are then associated with an MBSE graph element, based on their nature. This bonding of MBSE models and data elements constitutes a first-of-its-kind knowledge graph of a nuclear power plants system, with data elements being organized in a structured manner that enables system engineers to identify cause-effect trends in data elements and carry out appropriate actions in response.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Engineering Against Digital Risk in CIP Applications: Cyber-Informed Engineering Use Cases

Cyber-Informed Engineering (CIE) addresses the reality that cyber attacks on engineered systems can have consequences far beyond data loss or disruption of digital networks. When control systems are compromised, safety, reliability, and performance of the physical process itself may be threatened. This presentation discusses engineered controls of 7 categories and the CIE database of controls that provides clear examples and guidance for defining and applying engineered controls in CIE. It explains what engineered controls are, how they differ from information security measures, and how they are integrated into system design.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

Improving the Cost-Effectiveness of Algal CO2 Utilization by Synergistic Integration With Power Plant and Wastewater Treatment Operations

Creating an economic demand for carbon utilization products will require lowering the overall cost of the products to compete within the current market. Photosynthetic uptake of carbon dioxide is an emerging pathway for product development in the animal feed market that globally amounts to over 400 Billion USD and is expected to continue growing. This project aims to continue the development of a process that utilizes carbon dioxide while increasing the cost competitiveness of algae as an animal feed product. The overall goal of the project is to demonstrate an engineering-scale open raceway pond algae cultivation system (180 m2) including integration of technologies that utilize coal-fired power plant CO2 and wastewater nutrient inputs. The system is designed to maximize the cost-effectiveness and environmental benefits of algal biomass production for commodity animal feed.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2024

Review and Modeling of Integrated Energy Systems with Nuclear Reactor Coupled Desalination and District Heating

Detailed reviews of a past advanced nuclear reactor based integrated energy system, as well as other nuclear reactor and fossil fuel based integrated energy systems have been performed for this work. Review of the utilization of heat from nuclear reactors for various applications and cogeneration has been done. The heat can be utilized by extraction of the steam from the turbine while the steam is still at a desired temperature. While use of nuclear process heat for district heating in countries like Finland, France, China, Poland, and elsewhere is discussed, more focus of the review has been given on nuclear desalination processes. Integrated energy systems (IES) where distinct types of reactors like PWR, BWR, sodium cooled fast reactor, heavy water reactor and other advanced reactors are coupled with various nuclear desalination processes like multi-effect distillation (MED), multi-stage flashing (MSF) and reverse osmosis (RO) methods have been discussed. The nuclear desalination plant at Aktau has been discussed in more detail due to its decades of successful operation. The IES of the Aktau plant coupled with 5-effect MED desalination plant has been taken as a reference for modeling the Open Modelica (OM) based IES of this work. Here, the OM IES model shows good agreement with the MED plant output of Aktau and can be extended for future applications of IES.

42 ENGINEERING↗

DOE OSTI2025

Software For Advanced Large-scale Analysis Of Magnetic Confinement For Numerical Design, Engineering & Research (salamander)

As magnetic confinement fusion energy gains traction internationally to enable abundant energy production, designing components for fusion systems is a pressing challenge. During the planned lifetime of a fusion device, components evolve in extreme environments and must withstand large, repeated thermal loads and bombardment by 14 MeV neutrons, plasma ions, and neutral particles (deuterium, tritium, and helium), corrosive conditions, etc. All these physical processes take place simultaneously, interact in intricate ways, and impose important constraints that can affect performance. Experimental data is rare and costly to obtain, making design particularly challenging. Predictive computational frameworks must be an integral part of an accelerated and cost-effective design process by modeling fusion system performance in simulated environments. To better understand component degradation and operational impacts on their performance, the Software for Advanced Large-scale Analysis of MAgnetic confinement for Numerical Design, Engineering & Research (SALAMANDER) is designed as an open-source, fully integrated, multiphysics, multiscale, NQA-1 compliant framework facilitating 3D, high-fidelity fusion system modeling. To that end, SALAMANDER is a MOOSE-based framework, and therefore leverages MOOSE upstream libraries such as PETSc and libMesh to deliver sophisticated finite element, finite volume, and nonlinear solver technology for fusion energy simulations. SALAMANDER couples MOOSE physics module capabilities—such as thermal hydraulics, heat conduction, Navier-Stokes, and thermomechanics—with tritium transport via TMAP8, neutronics via Cardinal, and nascent particle-in-cell capabilities. Direct simulation Monte Carlo methods will be used to address neutral transport near the walls. By coupling all these physics in an integrated application, SALAMANDER will enable high-fidelity modeling of irradiation levels and plasma exposure conditions of plasma facing components and their impact on heat and tritium distributions, as well as the resulting mechanical constraints experienced by the plasma facing components and performance of blanket systems. Furthermore, SALAMANDER will be particularly suited for engineering studies thanks to the stochastic tool module readily available in MOOSE, allowing for extended uncertainty quantification and risk analysis studies. It is also able to use computer-aided design (CAD) meshes to model complex geometries, which is indispensable for fusion systems. SALAMANDER therefore supports design, safety, engineering, and research projects for magnetic confinement fusion systems

Simon, Pierre-Clement [Idaho National Laboratory (↗

DOE OSTI2026

Uncertainty-Driven Rapid Thermodynamic Assessment of Nb-Ta-Zr System and Effects of C impurities (L25GF9298S): Annual Progress Report

An integrated computational materials engineering (ICME) method is in development for rapid thermodynamic experimental investigation and high-fidelity computational modeling of refractory multi-principal element alloys (RMPEAs). These ultra-high-temperature (UHT) alloys are of interest for structural applications in extreme environments, but deficiency of reliable data, especially melting temperatures, impedes the prediction of alloys with favorable properties. The method leverages UHT capabilities and computational expertise of LLNL’s Materials Science Division and the McCormack Lab’s UHT conical nozzle levitation (CNL) system to iteratively map the Nb-Ta-Zr phase space, with focus on the liquidus surface, through targeted experiments selected by quantifying uncertainty in the thermodynamic model fitting parameters. This method will reduce the time to map uncharted RMPEA phase space and thereby accelerate discovery and development of advanced materials for applications in extreme environments.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Dependable classical-quantum computing systems engineering

Increasing evidence suggests quantum computing (QC) complements traditional High-Performance Computing (HPC) by leveraging its unique capabilities, leading to the emergence of a new, hybrid paradigm, QHPC. However, this integration introduces new challenges, with dependability–defined by reproducibility, resiliency, and security and privacy–emerging as a central concern for building trustworthy systems that provide an advantage to the users. This paper proposes a framework for dependable QHPC system design, organized around these three pillars. We identify integration challenges, anticipate roadblocks, and highlight productive synergies across QC, HPC, cloud platforms, and network security. Drawing from both classical computing principles and quantum-specific insights, we present a roadmap for co-design that supports robust hybrid architectures. Our approach offers concrete metrics for assessing dependability, provides design guidance for engineers working at the QC-HPC interface, and surfaces new engineering questions around complexity, scale, and fault tolerance. Ultimately, designing for dependability is key to realizing practical, scalable QHPC systems and accelerating the broader quantum ecosystem capable of translating quantum promises into actual application delivery.

HPC↗

DOE OSTI2024

IDAES-PSE 2.6.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.6.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New Intersphinx extension automatically linking Jupyter notebook examples to project documentation New end-to-end diagnostics example demonstrated on a real problem New complementarity formulation for VLE with cubic equations of state, backward compatibility for old formulation New solver interface with presolve (ipopt_v2) in support of upcoming changes to the initialization and APIs methods, with default set to ipopt to maintain backwards compatibility; this will deprecate once all examples have been updated New forecaster and parameterized bidder methods within grid integration library Updated surrogates API and examples to support Keras 3, with backwards compatibility for older formats such as TensorFlow SavedModel (TFSM) Updated costing base dictionary to include the 2023 cost year index value Updated ProcessBlock to include information on the constructing block class Updated Flowsheet Visualizer to allow visualize() method to return value and functions Bug Fixes Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Fixed typos flagged by June update to crate-ci/typos and removed DMF-related exceptions Minor corrections of units of measurement handling in power plant waste/transport costing expressions, control volume material holdup expressions, and BTX property package parameters Fixed throwing >7500 numpy deprecation warnings by replacing scalar value assignment with element extraction and item iteration calls Testing and Robustness Migrated slow tests (>10s) to integration, impacting test coverage but also yielding a nearly 30% decrease in local test runtime Pinned pint to avoid issues with older supported Python versions Pinned codecov versions to avoid tokenless upload behavior with latest version Bumped extensions to version 3.4.2 to allow pointing to non-standard install location Deprecations and Removals Python 3.8 is no longer supported. The supported Python versions are 3.9 through 3.12 The Data Management Framework (DMF) is no longer supported. Importing idaes.core.dmf will cause a deprecation warning to be displayed until the next release The SOFC Keras surrogates have been removed. The current version of the SOFC surrogate model in the examples repository is a PySMO Kriging model.

AS↗

DOE OSTI2025

Hydrologic response of artificially drained agricultural watersheds: insights from high-resolution integrated surface/subsurface simulations

Artificial drainage systems comprising subsurface networks of perforated pipes (tile drains) and engineered surface ditches are widely used to remove excess water from poorly drained agricultural regions. Artificial drainage lowers the water table by design but also has inadvertent effects on the watershed-scale hydrologic response with important implications for flood risk and nutrient exports. We investigated the effects of tile drains on watershed-scale hydrologic response in the Portage River, OH, Watershed using a high-resolution physically based integrated surface/subsurface hydrology model with recently developed capabilities to represent artificial drainage. Tile drains were found to enhance streamflow during times of low flow, generally consistent with previous studies. Streamflow flashiness was found to have a non-monotonic dependence on tile spacing with a minimum at intermediate spacings (∼50 m). Flashiness and the event hydrographs for small tile spacing were similar to the situation with no tiles, but flow paths from farm to stream were very different for those two end member cases, emphasizing the limitations of the stream hydrograph in characterizing hydrologic response. For typical tile spacings, peak flow can either be enhanced or attenuated by the presence of tiles, depending on the size of the event and the antecedent meteorological conditions. Tiles enhance peak flow when the event is below a threshold of ∼25 mm or when events arrive in dry conditions. Peak flow is reduced by tiles when events are large and arrive in conditions that are not overly dry. The dependence on event size and antecedent conditions is explained by differences in available storage and flow paths to the streams. These results provide additional insights into how tile drainage modulates event-scale hydrologic response, an important control on flood generation mechanisms and nutrient exports.

agricultural watershed↗

DOE OSTI2025

Advanced nuclear reactor integration opportunities for the pulp and paper industry in the U.S. context: Technical perspectives, gap analysis, and preliminary technoeconomic assessment

Pulp and paper (P&P) manufacturing requires a large amount of low-pressure (LP) steam to digest, wash wood fibers and dry pulp into paper. Most of the LP steam is extracted from backpressure turbines that produce power from high-pressure (HP) steam. This HP steam is generated from burning wood waste material; bark is burned in hog boilers, and lignin is boiled in a black liquor recovery boiler. In a typical integrated P&P mill, 50–100% of the steam is produced from these sources, while additional steam is produced in natural gas (NG), fuel oil, or coal boilers. The other energy-intensive process in the plant is the chemical-recovery section (e.g., lime kiln), which requires high-temperature processing from NG combustion to retrieve and recirculate spent chemicals. This paper assesses the energy and heat demand and material balances of a typical generic kraft pulp mill, along with the nuclear heat, steam, and power integration opportunities to replace conventional combustion systems. The paper also addresses steam and electricity generation through a comprehensive technical and engineering gap analysis of five different nuclear-integration opportunities and their process economics, thus enabling the lignin and bark to be further processed into biobased chemicals or fuels, as well as the potential to reduce overall emissions from kraft pulping. Preliminary findings have shown that the P&P industry could achieve technological benefits by integrating their current manufacturing process with small modular nuclear reactors (SMNRs) on a national level. This research aims to set the path forward for a cleaner and more resilient P&P industry.

Advanced nuclear reactor↗

DOE OSTI2024

Probabilistic Grid Reliability Analysis with Energy Storage Systems

SAND2025-12025O The Probabilistic Grid Reliability Analysis with Energy Storage Systems (ProGRESS) software tool is an open-source tool for assessing the resource adequacy of the evolving electric power grid integrated with energy storage systems (ESS). This tool uses a simulation engine to create diverse scenarios that test the limits of the modern power grid consisting of a high-volume ESS and variable energy resources (VER). Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Nguyen, Tu↗

DOE OSTI2024

IDAES-PSE 2.5.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost, most environmentally sustainable solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.5.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New diagnostics check for near-parallel variables and constraints. New diagnostics tools for identifying causes of infeasibility in models. New example for creating a custom model of a liquid-liquid extractor unit operation. Bug Fixes Fixed bug in Gibbs reactor that caused it to appear to have additional spurious degrees of freedom. Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Testing and Robustness Deployed the IDAES Diagnostics Toolbox to confirm that there are no structural or numerical issues in the core model libraries. Additional robustness tests for core model, and some associated improvements in the converge tester class. Fixed a number of issues that were causing unexpected warnings to be emitted during testing. Deprecations and Removals Removed examples for RIPE tool which has not been supported for a number of releases.

AS↗

DOE OSTI2024

IDAES-PSE 2.7.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.7.0 Release Highlights New features: AutoScaler and CustomScalerBase classes: Such tools are the core of the new scaling framework being implemented in IDAES. Wider adoption of scaling tools among users will result in quicker and more robust model solutions. Scaler for equilibrium reactor and saponification properties: These scaler models are examples to follow for how to use the new scaling tools. ONNX Surrogate support from Optimization & Machine Learning Toolkit (OMLT): ONNX is an open standard format to save and load ML/AI models that is widely supported by all major frameworks. This capability makes it easier for IDAES users to create surrogate models and use them without having to support each framework individually. 1D Membrane Model for CO2 Capture and Utilization: Supports ongoing efforts for modeling and optimizing polymer membrane processes for CO2 capture and conversion into formic acid. StreamScaler unit model: Unrelated to the CustomScalerBase, this unit model allows a stream’s extensive variables to be scaled by a fixed factor. This allows streams being processed by multiple units in parallel to be scaled down to unit scale and scaled back up to process scale. Bug fixes or improvements: Scaling, EoS, Diagnostics tool, Modular Properties, tests & documentation Deprecations: Old Cubic EoS

AS↗

DOE OSTI2025

IDAES-PSE 2.8.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications.

AS↗

DOE OSTI2025

HyRAM+ (Hydrogen Plus Other Alternative Fuels Risk Assessment Models) v.6.1

SAND2025-11565O HyRAM+ (Hydrogen Plus Other Alternative Fuels Risk Assessment Models) is a tool for conducting quantitative risk assessment (QRA) in transportation systems. HyRAM+ contains validated, simplified release behavior models, engineering models, and generic data relevant to hydrogen installations. HyRAM+’s platform integrates models and data to conduct QRA on user-defined hydrogen or other alternative fuel systems. The software will enable the international safety research community to add validated models to the HyRAM+ platform for use in QRAs. HyRAM (hydrogen-only) versions 1.0 to 3.1 were developed by Sandia for the Department of Energy (DOE) Hydrogen and Fuel Cell Technologies Office. The following agencies contributed to the development of HyRAM+ version 4.0 regarding the addition of methane (natural gas) and propane models: the DOE Vehicle Technologies Office and the Department of Transportation Pipeline and Hazardous Material Safety Administration. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Groth, Katrina [Sandia National Lab. (SNL-NM), Alb↗

DOE OSTI2024

Digital Assurance for High Consequence Systems: 2024 Mission Campaign White Paper

This Sandia National Laboratories Mission Campaign (MC) seeks to create the technical basis that allows national leaders to efficiently assess and manage the digital assurance of high consequence systems. We will call for transformative research that enables efficient (1) development of provably secure systems and secure integration of untrusted products, (2) intelligent threat mitigation, and (3) digital risk-informed engineering trade-offs. Ultimately, this MC will impact multiple national security missions; it will develop an informed Digital Assurance for High Consequence Systems (DAHCS) community and expand Sandia partnerships to build this national capability.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Sierra Space Technology Collaboration-Advanced Manufacturing of Thermal Protection System Tiles for Space Plane Atmospheric Reentry

Thermal protection systems (TPS) constitute a major material, engineering, and manufacturing challenge for space access. Atmospheric re-entry generates very high heats and requires advanced materials to withstand such conditions. Combining the required materials and integrating them into the vehicle is a major engineering undertaking that often must use creative designs to accommodate the selected materials and systems. Likewise, the manufacture of TPS is costly and challenging; it requires a combination of materials in a range of complex and unique shapes with specialized process conditions. Compounding these challenges, for harsh re-entry profiles or on high heat flux regions of the vehicle, even state of the art TPS is effectively single use and thereby creating a strong economic incentive to improve the TPS materials, integration, and manufacture. This work focuses on the use of ceramic modifications to TPS materials thereby allowing multi flight capability.

99 GENERAL AND MISCELLANEOUS↗