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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 OSTI2023

BEopt™ (Building Energy Optimization Tool) version 3.0.1 3/16/2023 [SWR-05-41]

The BEopt™ (Building Energy Optimization Tool) software provides capabilities to evaluate residential building designs and identify cost-optimal efficiency packages at various levels of whole-house energy savings along the path to zero net energy. The BEopt software can be used to analyze both new construction and existing home retrofits, as well as single-family detached and multi-family buildings, through evaluation of single building designs, parametric sweeps, and cost-based optimizations. The BEopt software provides detailed simulation-based analysis based on specific house characteristics, such as size, architecture, occupancy, vintage, location, and utility rates. Discrete envelope and equipment options, reflecting realistic construction materials and practices, are evaluated. The BEopt software uses EnergyPlus®, the Department of Energy's flagship simulation engine. Simulation assumptions are based on ANSI/RESNET/ICC Standards and the Building America Housing Simulation Protocols. The sequential search optimization technique used by the BEopt software: Finds minimum-cost building designs at different target energy-savings levels Identifies multiple near-optimal designs along the path, allowing for equivalent solutions based on builder or contractor preference. Download A BEopt™ Version 3.0.1 Beta release (Mar. 16, 2023) is now available. Download the BEopt 3.0.1 Beta setup file.

Christensen, Craig↗
DOE OSTI2023

Influence of NaCl concentration on the optical scattering properties of water-based aerosols

We present the characterization of several atmospheric aerosol analogs in a tabletop chamber and an analysis of how the concentration of NaCl present in these aerosols influences their bulk optical properties. Atmospheric aerosols (e.g., fog and haze) degrade optical signal via light–aerosol interactions causing scattering and absorption, which can be described by Mie theory. This attenuation is a function of the size distribution and number concentration of droplets in the light path. These properties are influenced by ambient conditions and the droplet’s composition, as described by Köhler theory. It is therefore possible to tune the wavelength-dependent bulk optical properties of an aerosol by controlling droplet composition. We present experimentation wherein we generated multiple microphysically and optically distinct atmospheric aerosol analogs using salt water solutions with varying concentrations of NaCl. The results demonstrate that changing the NaCl concentration has a clear and predictable impact on the microphysical and optical properties of the aerosol.

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

Imaging extended single crystal lattice distortion fields with multi-peak Bragg ptychography

Recent advances in phase-retrieval-based x-ray imaging methods have demonstrated the ability to reconstruct 3D distortion vector fields within a nanocrystal by using coherent diffraction information from multiple crystal Bragg reflections. However, these works do not provide a solution to the challenges encountered in imaging lattice distortions in crystals with significant defect content that result in phase wrapping. Moreover, these methods only apply to isolated crystals smaller than the x-ray illumination, and therefore cannot be used for imaging of distortions in extended crystals. We introduce multi-peak Bragg ptychography which addresses both challenges via an optimization framework that combines stochastic gradient descent and phase unwrapping methods for robust image reconstruction of lattice distortions and defects in extended crystals. Our work uses modern automatic differentiation toolsets so that the method is easy to extend to other settings and easy to implement in high-performance computers. This work is particularly timely given the broad interest in using the increased coherent flux in fourth-generation synchrotrons for innovative material research.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Robust Distributed State Estimator for Interconnected Transmission and Distribution Networks (Final Report RPPR-1)

This project’s objective is to develop a combined transmission and distribution state estimator which accounts for very large system size and model complexity (by way of distributing the computations) and large number of solar PV units connected to the distribution system on multiple feeders. The project not only provides a robust formulation and solution to this problem but also tests the solution by implementing it on a well-established large utility system. It introduces several improvements with respect to the state of the art in existing state estimation software: (a) The developed state estimator (SE) allows robust and accurate monitoring of bidirectional flows in distribution systems which result due to the distributed energy sources which are not observable and thus not incorporated in generation dispatch; (b) Large utility systems with tens of thousands of transmission buses and hundreds of thousands of distribution nodes are difficult to model as a single integrated system. This shortcoming is addressed by developing a “scalable distributed computational framework” which allows splitting the ultra large system models into several small subsystems and coordinating their solution by a robust and practical state estimation formulation; (c) Measurement errors irrespective of their locations are detected and removed by the developed state estimator. Historically, transmission and distribution systems were analyzed and operated as two independent systems. Given the non-transposed short feeder sections, unevenly loaded phases, strictly radial configuration and unidirectional power flows in the absence of remote generation, distribution system analysis was customized to account for these characteristics. However, some of these assumptions are no longer valid (non-radial configuration, bidirectional power flows) and thus distribution system analysis should be revisited. Furthermore, in the past, the interaction between the transmission and distribution systems was quite passive, where distribution substations were modeled as lumped loads in the transmission system model. With substantial generation injected by renewable generation located in the distribution systems, such modeling will no longer be accurate. The developed state estimator facilitates proper monitoring of the interactions between the transmission and distribution systems and enables smart dispatch of these units which are made observable by the state estimator.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Learning to Branch with Interpretable Machine Learning Models

This presentation describes an algorithm for applying machine learning to branching to speed up the solution of integer optimization problems. These problems are challenging and solved multiple times a day by power systems operators. We show that our approach speeds up a widely used open-source optimization solver.

Bayramoglu, Selin↗
DOE OSTI2025

Geospatial Data Workflow Orchestration and Architecture

In an era characterized by explosive growth in geospatial data, the selection of appropriate technologies for data storage, processing, and orchestration is critical for organizations aiming to maintain competitive advantages. This white paper provides a comprehensive analysis of how Oak Ridge National Laboratory (ORNL) has effectively employed various cloud technologies, including containerized applications, container orchestrators, and workflow orchestrators, to develop robust geospatial data processing solutions. We explore the fundamental concepts behind these technologies and compare multiple deployment models tailored to diverse use cases. Our findings conclude that while Kubernetes has emerged as the preferred platform for truly scalable and fault-tolerant production workflows, the choice of workflow orchestration tool requires careful consideration of team needs, pipeline complexity, and deployment environments. This paper aims to serve as a strategic guide for organizations leveraging geospatial data, articulating the balance between technology choices and practical implementation to enhance workflow efficacy and scalability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

End-to-end deep learning pipeline for real-time Bragg peak segmentation: from training to large-scale deployment

X-ray crystallography reconstruction, which transforms discrete X-ray diffraction patterns into three-dimensional molecular structures, relies critically on accurate Bragg peak finding for structure determination. As X-ray free electron laser (XFEL) facilities advance toward MHz data rates (1 million images per second), traditional peak finding algorithms that require manual parameter tuning or exhaustive grid searches across multiple experiments become increasingly impractical. While deep learning approaches offer promising solutions, their deployment in high-throughput environments presents significant challenges in automated dataset labeling, model scalability, edge deployment efficiency, and distributed inference capabilities. We present an end-to-end deep learning pipeline with three key components: (1) a data engine that combines traditional algorithms with our peak matching algorithm to generate high-quality training data at scale, (2) a modular architecture that scales from a few million to hundreds of million parameters, enabling us to train large expert-level models offline while deploying smaller, distilled models at the edge, and (3) a decoupled producer-consumer architecture that separates specialized data source layer from model inference, enabling flexible deployment across diverse computing environments. Using this integrated approach, our pipeline achieves accuracy comparable to traditional methods tuned by human experts while eliminating the need for experiment-specific parameter tuning. Although current throughput requires optimization for MHz facilities, our system's scalable architecture and demonstrated model compression capabilities provide a foundation for future high-throughput XFEL deployments.

Wang, Cong↗
DOE OSTI2024

Catalytic, Spectroscopic, and Theoretical Studies of Fe 4 S 4 -Based Coordination Polymers as Heterogenous Coupled Proton–Electron Transfer Mediators for Electrocatalysis

Iron–sulfur clusters play essential roles in biological systems, and thus synthetic [Fe 4 S 4 ] clusters have been an area of active research. Recent studies have demonstrated that soluble [Fe 4 S 4 ] clusters can serve as net H atom transfer mediators, improving the activity and selectivity of a homogeneous Mn CO 2 reduction catalyst. Here, in this work, we demonstrate that incorporating these [Fe 4 S 4 ] clusters into a coordination polymer enables heterogeneous H atom transfer from an electrode surface to a Mn complex dissolved in solution. A previously reported solution-processable Fe 4 S 4 -based coordination polymer was successfully deposited on the surfaces of different electrodes. The coated electrodes serve as H atom transfer mediators to a soluble Mn CO 2 reduction catalyst displaying good product selectivity for formic acid. Furthermore, these electrodes are recyclable with a minimal decrease in activity after multiple catalytic cycles. The heterogenization of the mediator also enables the characterization of solution-phase and electrode surface species separately. Surface enhanced infrared absorption spectroscopy (SEIRAS) reveals spectroscopic signatures for an in situ generated active Mn–H species, providing a more complete mechanistic picture for this system. The active species, reaction mechanism, and the protonation sites on the [Fe 4 S 4 ] clusters were further confirmed by density functional theory calculations. The observed H atom transfer reactivity of these coordination polymer-coated electrodes motivates additional applications of this composite material in reductive H atom transfer electrocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

From Modular ADMS to Plug-and-Play Ops: Distribution Grid Operations with Platform-Level Orchestration to Enable Ambitious App Hosting

The core function of the distribution grid is to provide electricity to consumers affordably, reliably, and securely. In pursuing these core objectives, distribution utilities are accountable to customers, regulators, and in some cases, shareholders. Other third parties such as aggregators and microgrids can also have a stake in the smooth operation of the grid. Each of these stakeholders has economic, business, and/or governance objectives that inform their expectations of the distribution grid. This multi-objective, multi-stakeholder environment creates tension that must be reconciled to successfully design and operate the distribution grid. Innovative companies are competing to bring high-tech solutions to electric utilities and their customers that address each of these objectives. Many developers of advanced distribution management systems (ADMS) and distributed energy resource management systems (DERMS) have adopted a modular architecture that allows grid operators to select functions and features according to their individual system needs. A modular platform also allows the solution provider to develop and integrate specific new product modules; however, the need to pursue multiple objectives with a fixed set of controllable devices makes integration expensive whether it is done at the product development stage or the deployment stage. This cost creates a significant barrier to adoption and can lengthen the product to market time of new solutions. To fundamentally address the complexity of system integration for distribution grid operations, the U.S. Department of Energy Office of Electricity has funded the GridAPPS-D project at PNNL, which streamlines integration by contributing to standards development, defining system architecture, applying advanced mathematics, and developing open-source software to demonstrate the concept of an open data-integration platform for distribution operations. The open data-integration platform concept enables system operators and solution providers to deploy ambitious, best-of-breed applications (or apps) without continually reengineering for integration. Ambitious apps developed by different solution providers will inevitably attempt to achieve different control objectives with the same set of controllable devices. If the open platform itself can resolve these conflicts in a way that achieves the best available outcomes for all apps, doesn’t restrict the ambitious design of apps, and ensures safe and secure operations, apps will be able to plug-and-play with the platform at the same time as other ambitious apps. In this paper, we describe a framework called App Deconfliction that empowers a platform to assign setpoints to controllable devices based on the values preferred by different apps (and even external stakeholder entities like customers or aggregators). The App Deconfliction framework is compatible with several methods for determining setpoint values. We present two methods based on game theory that provide a subtle built-in incentive structure for developers to adapt their apps to the fact that they will be operating in a moderated multi-app environment and to favor device setpoints that have the most effect on their objectives over those that have the least effect. Our simulation-based demonstrations have shown that game-theory-based deconfliction can lead to a 7% improvement in control space utilization compared to design-based methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Non-Diffusive Volume Advection with A High Order Interface Reconstruction Method

We show that non-diffusive volume advection in two-dimensions is achieved with several benchmark problems using a newly developed high-order volume of fluids (VOF) interface reconstruction method. (1) A new VOF interface reconstruction method using circular/corner facets (linear facets are a degenerate case of arcs). We create a circular interface facet in each mixed zone by matching neighbor volume with a hybrid Newton’s-bisection method and the local solution is final. In the general case, the new VOF interface reconstruction has 3rd order accuracy and can be easily made seamless. The new method addresses intrinsic issues with Young’s method such as gaps between interface facets in the case of a curved interface, and inability to define curvature nor identify corners. (2) A non-diffusive volume advection scheme. In an ALE advection step, a well-defined interface can be carried over through a Lagrange step and used to compute volume distribution into a relaxed mesh. Then, an interface reconstruction step is performed to redefine the interface in the relaxed mesh. We must point out that the interface carried over is also a solution of interface reconstruction because all the volume fractions in the relaxed mesh are naturally matched. We provide an interface tracking method compatible with our reconstruction scheme, where it is granted to use the prior info as an initial guess to capture sub-mesh resolution features. As a result, we are able to treat multiple facets inside a single mixed cell and obtain highly accurate, non-diffusive solution for advection problems with rather coarse meshes. We show our solutions for two-dimensional incompressible flows with two materials with a) the X + O diagonal translation; b) the Zalesak rotational test; and c) the single vortex spiral test.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Pairing a Global Optimization Algorithm with EXAFS to Characterize Lanthanide Structure in Solution

Ensemble-average sampling of structures from ab initio molecular dynamics (AIMD) simulations can be used to predict theoretical extended X-ray absorption fine structure (EXAFS) signals that closely match experimental spectra. However, AIMD simulations are time-consuming and resource-intensive, particularly for solvated lanthanide ions, which often form multiple nonrigid geometries with high coordination numbers. Here, to accelerate the characterization of lanthanide structures in solution, we employed the Northwest Potential Energy Surface Search Engine (NWPEsSe), an adaptive-learning global optimization algorithm, to efficiently screen first-shell structures. As case studies, we examine two systems: Eu(NO 3 ) 3 dissolved in acetonitrile with a terpyridine ligand (terpyNO 2 ), and Nd(NO 3 ) 3 dissolved in acetonitrile. The theoretical spectra for structures identified by NWPEsSe were compared to both experimental and AIMD-derived EXAFS spectra. The NWPEsSe algorithm successfully identified the proper solvation structure for both Eu(NO 3 ) 3 (terpyNO 2 ) and Nd(NO 3 )(acetonitrile) 3 , with the calculated EXAFS signals closely matching the experimental spectra for the Eu-ligand complex and showing good similarity for the Nd salt; the better agreement with the ligand-containing structure is attributed to a less dynamic coordination environment due to the rigid ligand. The key advantage of the global optimization algorithm lies in its ability to sample the coordination environment across the potential energy surface and reduce the time required to identify structures from generally a month to within a week. Additionally, this approach is versatile and can be adapted to characterize main-group metal complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

An error-in-constitutive equations strategy for topology optimization for frequency-domain dynamics

This paper presents a topology optimization formulation for frequency-domain dynamics to reduce solution dependence upon initial guess and considered loading conditions. Due to resonance phenomena in undamped steady-state dynamics, objectives measuring dynamic response possess many local minima that may represent poor solutions to a design problem, an issue exacerbated for design with respect to multiple frequencies. In this work, we propose an extension of the modified error-in-constitutive-equations (MECE) method, used previously in material identification inverse problems, as a new approach for frequency-domain dynamics topology optimization to mitigate these issues. The main idea of the proposed framework is to incorporate an additional penalty-like term in the objective function that measures the discrepancy in the constitutive relations between stresses and strains and between inertial forces and displacements. Then, the design problem is cast within a PDE-constrained optimization formulation in which we seek displacements, stresses, inertial forces, and a density-field solution that minimize our new objective subject to conservation of linear momentum plus some additional constraints. We show that this approach yields superior designs to conventional gradient-based optimization approaches that solely use a functional of displacements as the objective, while strictly enforcing the constitutive equations. The MECE strategy integrates into a density-based topology optimization scheme for void–solid or two-phase material structural design. We highlight the merits of our approach in a variety of scenarios for direct frequency response design, considering multiple frequency load cases and structural objectives.

42 ENGINEERING↗
DOE OSTI2025

Resilient Operation of Networked Community Microgrids with High Solar Penetration

This project, funded by the US Department of Energy’s Solar Energy Technologies Office (SETO), focused on the operation of microgrids as a coordinated network. The primary objective, which was successfully achieved, was to develop both control strategies and hardware solutions to support the resilient and efficient operation of networked microgrids with high solar penetration. The work was structured around the following four main tasks: • Development of distributed and scalable optimization algorithms for AC-coupled networked microgrids. • Design and implementation of a novel DC interconnection hardware to enable precise power exchange between microgrids. • Laboratory operational validation of the developed technologies using 480 V testbeds and commercially available hardware. • Field operational validation of the complete solution in Adjuntas, Puerto Rico, interconnecting two kW-scale, split-phase microgrids of Casa Pueblo’s microgrids. This project addressed multiple technical challenges across the domains of optimization, control, hardware interconnection, and protection. One of its key contributions was delivering tangible, real-world solutions for networking microgrids. In contrast to purely theoretical or simulation-based work, this project included full-scale hardware operational validation both in the lab and in the field. The work conducted as part of this project—in collaboration with the University of Puerto Rico; the University of Tennessee, Knoxville; the University of Central Florida; and Casa Pueblo—has advanced the state of the art in networked microgrids. Key contributions include the development of distributed control strategies, practical solutions for real-world implementation challenges, and the introduction of a novel DC interlink approach for microgrid interconnection. The project featured both laboratory and field validation using commercial off-the-shelf components. The field deployment successfully validated that a group of microgrids can operate in a coordinated manner, enabling precise power flow between systems and mutual support during extreme events. This project resulted in 15 journal publications and 15 conference papers; 5 graduate students and 15 undergraduate students were supported. The codes of distributed optimization and forecasting were made open-source through OSTI.gov for distributed optimization and forecasting. All the publications are available in the ORNL-hosted project landing page. The DC interlink with state-of-charge balancing control was operationally validated in Adjuntas by interconnecting two real-world, 240 V split-phase microgrids. To the best knowledge of the team, this represents the first operational validation of AC microgrids interconnected via DC-interlinks. As a culmination of this project, a follow-on grant was awarded to support the technology transfer of the distributed optimization framework to a commercial microgrid controller, Stellar Edge, developed by the California-based company New Sun Road.

14 SOLAR ENERGY↗
DOE OSTI2026

Low-stress creep behavior of multiple salt caverns under cyclic operations

Here, the use of multiple salt caverns for large-scale underground hydrogen storage offers a strategic solution to the growing demand for efficient and flexible energy storage, due to the inherent low permeability, high mechanical strength, and self-healing properties of the salt formation. Despite these advantages, the long-term geomechanical response of salt caverns under cyclic injection and withdrawal remains a significant challenge for ensuring operational stability. This mechanistic study highlights the critical role of low-stress creep, also known as pressure solution creep, in governing deformation of salt caverns during cyclic operations. Unlike conventional creep mechanisms that dominate under high-stress conditions, low-stress creep becomes particularly relevant under the moderate stress changes induced by repeated injection and withdrawal, which provides a previously underexplored control on cavern closure. Our three-dimensional computational model integrates the low-stress creep mechanism into the Munson–Dawson creep equation across a spectrum of operational scenarios including variations in cavern pressure cycles, injection-withdrawal frequencies, and caprock mechanical property. The low-stress creep components accelerate the cavern creep closure, which is amplified with shorter cycle frequency and larger pressure difference. Sensitivity analyses capture the complex interactions between multiple caverns and surround formations at the field scale that allows for a quantitative assessment of deformation patterns and closure rates over time and thereby informs the design and operation of sustainable underground hydrogen storage system.

Cyclic operation↗
DOE OSTI2022

Development and performance of INCONEL® alloy 740H® seam-welded piping

INCONEL® alloy 740H® is an age-hardenable nickel-based alloy approved for pressure vessels and piping within ASME Section I, VIII, and B31.1. Currently, the code applies a weld strength reduction factor (WSRF) of 0.7 to the allowable stresses for longitudinal seam welds in the time dependent creep regime. In this work, a full-scale seam weld was successfully produced using typical industrial practices. The component was solution heat-treated and aged after fabrication to improve the performance of the weldment. Tensile, bend, impact, and low-cycle fatigue tests showed the component met all the specification requirements and elevated temperature properties were within base metal expectations with failures predominately in the weld metal. Long-term creep tests, including large samples more representative of the entire weldment, were fabricated and tested to times in excess of 10,000 h at multiple temperatures. Analysis of the creep data supports a WSRF of 0.9 for the solution annealed + aged weldments in contrast to the WSRF of 0.7 currently applied to welded + aged weldments. Metallurgical analysis shows that the solution annealing causes recrystallization of the weld metal and reduces the chemical compositional and microstructural gradients in the weldments resulting in acceptable short-term performance. In long-term creep, evidence for coarsened zones in the weldments due to discontinuous coarsening reactions were identified as the mechanism leading to accelerated creep damage formation in the weld metal and sample failure.

14 SOLAR ENERGY↗
DOE OSTI2024

Noise robust detection of quantum phase transitions

Quantum computing allows for the manipulation of highly correlated states whose properties quickly go beyond the capacity of any classical method to calculate. Thus one natural problem which could lend itself to quantum advantage is the study of ground-states of condensed matter models, and the transitions between them. However, current levels of hardware noise can require extensive application of error-mitigation techniques to achieve reliable computations. In this work, we use several IBM devices to explore a finite-size spin model with multiple “phaselike” regions characterized by distinct ground-state configurations. Using preoptimized Variational Quantum Eigensolver (VQE) solutions, we demonstrate that in contrast to calculating the energy, where zero-noise extrapolation is required in order to obtain qualitatively accurate yet still unreliable results, calculations of the energy derivative, two-site spin correlation functions, and the fidelity susceptibility yield accurate behavior across multiple regions, even with minimal or no application of error-mitigation approaches. Taken together, these sets of observables could be used to identify level crossings in a simple, noise-robust manner which is agnostic to the method of ground state preparation. This work shows promising potential for near-term application to identifying quantum phase transitions, including avoided crossings and nonadiabatic conical intersections in electronic structure calculations. Published by the American Physical Society 2024

Lively, Kevin (ORCID:0000000320981494)↗
DOE OSTI2020

Submodular optimization problems and greedy strategies: A survey

The greedy strategy is an approximation algorithm to solve optimization problems arising in decision making with multiple actions. How effective is the greedy strategy compared to the optimal solution? In this survey, we mainly consider two classes of optimization problems where the objective function is submodular. The first is set submodular optimization, which is to choose a set of actions to optimize a set submodular objective function, and the second is string submodular optimization, which is to choose an ordered set of actions to optimize a string submodular function. Our emphasis here is on performance bounds for the greedy strategy in submodular optimization problems. Specifically, we review performance bounds for the greedy strategy, more general and improved bounds in terms of curvature, performance bounds for the batched greedy strategy, and performance bounds for Nash equilibria.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A nodal transport method for coupled fast-thermal reactor analysis

We report that for efficient core analyses of coupled fast-thermal reactors, a new deterministic method has been developed based on the variational nodal transport method of VARIANT. A new multigroup cross section generation procedure was devised by combining Monte Carlo lattice calculations for thermal assemblies and the two-step procedure of the MC 2 -3 code for fast assemblies. To reduce assembly homogenization errors in nodal transport calculations, a new nodal equivalence method was developed based on the partial current discontinuity factor (PCDF) and incorporated in VARIANT. A practical procedure to calculate PCDFs with fixed source supercell calculations was also devised. The performance of the proposed method was investigated using a test problem derived from the versatile coupled test reactor (VCTR) design. The new procedure produced multigroup cross sections accurately for all assemblies. VARIANT transport calculations with PCDFs produced accurate multiplication factor and power distribution compared to reference Serpent-2 Monte Carlo solutions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗