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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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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Design of a supervisory control system for autonomous operation of advanced reactors

Advanced reactors to be deployed in the coming decades will face deregulated energy markets, and may adopt flexible operation to boost profitability. To aid in the transition from baseload to flexible operation paradigm, autonomous operation is sought. This work focuses on the control aspect of autonomous operation. Specifically, a hierarchical control system is designed to support constraint enforcement during routine operational transients. Within the system, data-driven modeling, physics-based state observation, and classical control algorithms are integrated to provide an adaptable and robust solution. A 320 MW Fluoride-cooled High-temperature Pebble-bed Reactor is the design basis for demonstrating the proposed control system. The hierarchical control system consists of a supervisory layer and low-level layer. The supervisory layer receives requests to change the system's operating conditions (e.g., the current reactor power to meet a load -follow), and accepts or rejects them based on constraints that have been assigned. Constraints are issued to keep the plant within an optimal operating region. The low-level layer interfaces with the actuators of the system to fulfill requested changes, while maintaining tracking and regulation duties. Further, to accept requests at the supervisory layer, the Reference Governor algorithm was adopted. To model the dynamics of the reactor, a system identification algorithm, Dynamic Mode Decomposition, was utilized. To estimate the evolution of process variables that cannot be directly measured (e.g., the propagation of delayed neutron precursors), the Unscented Kalman Filter, incorporating a nonlinear model of nuclear dynamics, was adopted. The composition of these algorithms led to a numerical demonstration of constraint enforcement during a 40% power drop transient (at a rate of 5 %/min). Uncontrolled secondary-side temperatures were successfully constrained. Adaptability of the proposed system was demonstrated by modifying the constraint values, and enforcing them during the transient. Robustness was also demonstrated by enforcing constraints under noisy environments.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Towards Improving luminosity using optics tuning and data-driven methods

The results of Run 24 experiments at Relativistic Heavy Ion Collider (RHIC) for improving luminosity using optics tuning are presented in this study. In the first experiment, MADx matching was used to output magnet strengths corresponding to specific s star movements around Interaction Region 8 (IR8). The corresponding Zero Degree Calorimeter (ZDC) signal was measured in place of luminosity, and Bayesian Optimization aids search of optimal movements. It was found that values retrieved from matching were inaccurate, resulting in negative feedback loops. The second experiment focused on calculating accurate s star movements. The matching method was replaced with a linear sensitivity matrix, directly relating optics to power supply, and its null space was used to fit constraints such as hysteresis effects. At the experiment, beam losses were observed at collimators around boundary of IR8, which were fixed for the third experiment. Dynamic mode decomposition was also introduced to improve quality of turn-by-turn (TBT) data as well as accuracy and consistency of optics measurements at IR8. These improvements will be tested in the experiment of next RHIC run for luminosity optimization.

Accelerator Physics↗
DOE OSTI2024

Jacobian-based Model Diagnostics and Application to Equation Oriented Modeling of a Carbon Capture System

Equation-oriented (EO) modeling has the potential to enable the effective design and optimization of the operation of advanced energy systems. However, advanced modeling of energy systems results in a large number of variables and non-linear equations, and it can be difficult to search through these to identify the culprit(s) responsible for convergence issues. The Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES-IP) contains a tool to identify poorly scaled constraints and variables by searching for rows and columns of the Jacobian matrix with small L2-norms so they can be rescaled. A further singular value decomposition can be per-formed to identify degenerate sets of equations and remaining scaling issues. This work presents an EO model of a flowsheet developed for post-combustion carbon capture using a monoethanolamine (MEA) solvent system as a case study. The IDAES diagnostics tools were successfully applied to this flowsheet to identify problems to improve model robustness and enable the optimization of process design and operating conditions of a carbon capture system.

Allan, Douglas↗
DOE OSTI2024

Quantum-classical tradeoffs and multi-controlled quantum gate decompositions in variational algorithms

The computational capabilities of near-term quantum computers are limited by the noisy execution of gate operations and a limited number of physical qubits. Hybrid variational algorithms are well-suited to near-term quantum devices because they allow for a wide range of tradeoffs between the amount of quantum and classical resources used to solve a problem. This paper investigates tradeoffs available at both the algorithmic and hardware levels by studying a specific case – applying the Quantum Approximate Optimization Algorithm (QAOA) to instances of the Maximum Independent Set (MIS) problem. We consider three variants of the QAOA which offer different tradeoffs at the algorithmic level in terms of their required number of classical parameters, quantum gates, and iterations of classical optimization needed. Since MIS is a constrained combinatorial optimization problem, the QAOA must respect the problem constraints. This can be accomplished by using many multi-controlled gate operations which must be decomposed into gates executable by the target hardware. We study the tradeoffs available at this hardware level, combining the gate fidelities and decomposition efficiencies of different native gate sets into a single metric called the gate decomposition cost .

Tomesh, Teague↗
DOE OSTI2026

Temporal Convolutional Network Using Empirical Mode Decomposition to Detect Faults in Grid Connected Systems

Grid-connected power electronic systems require timely and reliable fault detection to prevent equipment damage and reduce downtime. This paper presents a forecasting-based anomaly detection pipeline that decomposes voltage and current measurements into intrinsic mode functions (IMFs) using empirical mode decomposition (EMD), then trains a causal temporal convolutional network (TCN) on normal-operation IMF data to predict short-horizon future dynamics. Deviations between forecasts and observations are summarized as reliability-weighted residual scores and thresholded per sensor using robust statistics with temporal persistence constraints to suppress false positives. To reduce runtime, EMD is performed on downsampled signals for detection, while raw-rate EMD is applied only within a short region of interest for high-frequency interpretability near detected events. Results on a simulated grid-connected converter system demonstrate that IMF-domain forecasting improves anomaly separability relative to raw-signal forecasting and provides interpretable evidence of faults across decomposition channels.

Sutton, Elizabeth [ORNL] (ORCID:0009000078885935)↗
DOE OSTI2026

Interregional Transmission Operational Coordination (IRTOC)

This report presents a modeling and evaluation framework developed through the Inter-Regional Transmission Operational Coordination (IRTOC) project to study market-to-market (M2M) congestion management across day-ahead and real-time markets. The framework extends the Sienna platform through Sienna Decomposition, a multi-stage evaluation architecture that enables flexible representation of multiple regions and systematic assessment of alternative market coordination designs. Additional modeling capabilities include reserve deliverability constraints, High-Voltage Direct Current (HVDC) optimization for Alternating Current (AC) congestion management, and several real-time distributed coordination algorithms. Case studies using the RTS-GMLC test system and a large-scale Eastern Interconnection model demonstrate that the framework can evaluate alternative coordination structures and quantify their economic and operational impacts. The proposed framework provides a scalable platform for analyzing inter-regional coordination strategies in large-scale electricity markets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Decomposing a renewable energy design and dispatch model

We address a mixed-integer linear programming model which selects a cost-minimizing set of available technologies with which to design a renewable energy system and prescribe their associated dispatch decisions. Realistically sized instances of such models pose computational challenges. To this end, we develop a Lagrangian heuristic based on a decomposition methodology which partitions the model into blocks and optimizes these more manageable, smaller subproblems. It also provides a lower bound to assess solution quality. In conclusion, we apply this methodology to the National Renewable Energy Laboratory's Renewable Energy Integration and Optimization (REopt TM ) model to generate near-optimal solutions to realistic instances containing, on average, approximately 300,000 variables and at least as many constraints, with a mean 30% optimality gap improvement using a five-minute solution time limit, compared to directly solving the original monolith.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Extreme-scale EV charging infrastructure planning for last-mile delivery using high-performance parallel computing

Here, this paper addresses stochastic charger location and allocation problems under queue congestion for last-mile delivery using electric vehicles (EVs). The objective is to decide where to open charging stations and how many chargers of each type to install, subject to budgetary and waiting-time constraints. We formulate the problem as a mixed-integer non-linear program, where each station-charger pair is modeled as a multiserver queue with stochastic arrivals and service times to capture the notion of waiting in fleet operations. The model is extremely large, with billions of variables and constraints for a typical metropolitan area; even loading the model in solver memory is difficult, let alone solving it. To address this challenge, we develop a Lagrangian-based dual decomposition framework that decomposes the problem by station and leverages parallelization on high-performance computing systems, where the subproblems are solved by using a cutting plane method and their solutions are collected at the master level. We also develop a three-step rounding heuristic to transform the fractional subproblem solutions into feasible integral solutions. Computational experiments on data from the Chicago metropolitan area with hundreds of thousands of households and thousands of candidate stations show that our approach produces high-quality solutions in cases where existing exact methods cannot even load the model in memory. We also analyze various policy scenarios, demonstrating that combining existing depots with newly built stations under multiagency collaboration substantially reduces costs and congestion. These findings offer a scalable and efficient framework for developing sustainable large-scale EV charging networks.

Capacity allocation↗
DOE OSTI2025

A Review of Tank 48H Treatment of Tetraphenylborate with Permanganate

Tank 48H contains roughly 270,000 gallons of radioactive waste material. The waste stored in this tank was to be processed in multiple stages utilizing facilities at the Savannah River Site (SRS) almost 30 years ago. The In-Tank Precipitation Process (ITP) was initiated in Tank 48H, which precipitated highly radioactive cesium-137 using sodium tetraphenylborate (NaTPB). While the process succeeded in precipitating the Cs, Sr, and other actinides, it also generated an unexpectedly large amount of benzene. The evolved benzene created a safety concern and made the waste incompatible with further downstream processing. This halted the ITP, and a new method of treatment was required to continue processing the legacy waste contained in Tank 48H. A myriad of treatment options have been proposed with multiple teams of researchers assembled to work on this highly complex issue over the last few decades. This review investigated one potentially viable treatment option, in-tank oxidation with sodium permanganate. Permanganate has been well known in literature as a strong oxidizing agent for organic compounds, as well as being utilized at the Savannah River Site (SRS) in other processes. A small number of studies have been conducted utilizing waste simulants to evaluate the use of permanganate as an oxidant for tetraphenylborate (TPB). A search of the literature and data from these studies indicates that permanganate could be a viable treatment for destruction of TPB in Tank 48H. While the scoping studies had a small number of individual experiments and nonideal conditions, the permanganate decomposed up to 90% of the TPB. A free hydroxide concentration above 1.0 M is required for tank corrosion control. Simulant studies indicate no decrease in TPB decomposition by permanganate until pH 14. The simulant studies show an increase in TPB decomposition as the temperature of the solution is increased to 40 °C. The post-reaction analysis of previous simulant tests did not look at all of the organic degradation products. Investigations into what these organic products are and in what quantity will help guide determinations as to whether the downstream processing facilities are able to handle the material that will be generated. Study on the time frame for the reaction between permanganate and TPB should be investigated as the literature reports only extend out to two weeks reaction time. The permanganate treatment conditions indicate no corrosion control concerns and a longer timescale reaction may be needed for in-tank treatment. In addition, further study would be useful to identify a lower boundary condition for the ratio of TPB and oxidant. The simulant tests applied large excesses of permanganate, and this may be unnecessary. The size constraint of the tank means that there will be practical limitations on the amount of sodium permanganate that can be added to the tank. The amount of permanganate should be minimized as much as possible while still ensuring decomposition of the TPB to minimize the amount of manganese dioxide solids generated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

AC Power Flow Based DLMP Calculation and Decomposition Method to Smooth Power Fluctuation of Distributed Renewable Energy Sources

As the penetration of renewable energy sources increases, the growing renewable power variability brings ramping issues to power systems. Meanwhile, the development of distributed energy resources (DERs) makes the distribution systems to provide both energy and ancillary services. To incentivise individual resources and customers to alleviate ramping issues on the demand side, a two-stage distribution locational marginal price (DLMP) calculation and decomposition method is developed to formulate the marginal power ramping price for DERs. In the first stage of the proposed method, a distribution system operator market scheduling model based on AC optimal power flow is designed to estimate the optimal operating point of the distribution system. Subsequently, the voltage and power flow constraints are linearised in stage two to calculate DLMP. Finally, based on the Lagrange function and sensitivity factors, DLMP is decomposed to the marginal costs for active/reactive power, voltage management, power loss and power variability. Case studies demonstrate that the proposed model can effectively smooth the power fluctuation and reduce the ramping flexibility requirements of distribution systems.

AC optimal power flow↗
DOE OSTI2021

From Intermolecular Interaction Energies and Observable Shifts to Component Contributions and Back Again: A Tale of Variational Energy Decomposition Analysis

Quantum chemistry in the form of density functional theory (DFT) calculations is a powerful numerical experiment for predicting intermolecular interaction energies. However, no chemical insight is gained in this way beyond predictions of observables. Energy decomposition analysis (EDA) can quantitatively bridge this gap by providing values for the chemical drivers of the interactions, such as permanent electrostatics, Pauli repulsion, dispersion, and charge transfer. These energetic contributions are identified by performing DFT calculations with constraints that disable components of the interaction. This review describes the second-generation version of the absolutely localized molecular orbital EDA (ALMO-EDA-II). The effects of different physical contributions on changes in observables such as structure and vibrational frequencies upon complex formation are characterized via the adiabatic EDA. Example applications include red- versus blue-shifting hydrogen bonds; the bonding and frequency shifts of CO, N 2 , and BF bound to a [Ru(II)(NH 3 ) 5 ] 2 + moiety; and the nature of the strongly bound complexes between pyridine and the benzene and naphthalene radical cations. Additionally, the use of ALMO-EDA-II to benchmark and guide the development of advanced force fields for molecular simulation is illustrated with the recent, very promising, MB-UCB potential.

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

Spinor representations for fields with any spin: Lorentz tensor basis for operators and covariant multipole decomposition

This paper discusses a framework to parametrize and decompose operator matrix elements for particles with higher spin (j > 1/2) using chiral representations of the Lorentz group, i.e. the (j, 0) and (0, j) representations and their parity-invariant direct sum. Unlike traditional approaches that require imposing constraints to eliminate spurious degrees of freedom, these chiral representations contain exactly the 2j + 1 components needed to describe a spin-j particle. The central objects in the construction are the t-tensors, which are generalizations of the Pauli four-vector σ μ for higher spin. For the generalized spinors of these representations, we demonstrate how the algebra of the t-tensors allows to formulate a generalization of the Dirac matrix basis for any spin. For on-shell bilinears, we show that a set consisting exclusively of covariant multipoles of order 0 ≤ m ≤ 2j forms a complete basis. We provide explicit expressions for all bilinears of the generalized Dirac matrix basis, which are valid for any spin value. As a byproduct of our derivations we present an efficient algorithm to compute the t-tensor matrix elements. The formalism presented here paves the way to use a more unified approach to analyze the non-perturbative QCD structure of hadrons and nuclei across different spin values, with clear physical interpretation of the resulting distributions as covariant multipoles.

Angular momentum of light↗
DOE OSTI2025

Predicting Flow in Fracture Networks With Quantum Algorithms

Uncertainty quantification plays a crucial role in the modeling of subsurface flow. For instance, uncertainties in the properties of geologic fracture networks significantly impact flow, requiring numerous simulations to accurately estimate quantities of interest. However, each simulation is computationally expensive because it requires solving a large linear system to capture features that involve both small and large fractures. An example is in percolation, where the interaction of many small fractures (which cumulatively can have a large surface area) with the rock matrix must be modeled precisely. Quantum computing is an emerging tool with the potential to address this issue. Quantum algorithms offer a significant speedup in solving linear systems, achieving efficiencies that are challenging to match with classical approaches. These classical approaches include direct solvers, such as LU decomposition, and iterative methods, notably preconditioned conjugate gradient, commonly used in subsurface modeling to solve large sparse systems. However, applying quantum algorithms to geologic fracture flow requires careful attention to algorithmic and problem-specific constraints to fully realize this quantum advantage. In this work we describe a quantum algorithm for generalized Monte Carlo applications with a quadratic speedup over the classical approaches which can be combined with the quantum speedup, currently under investigation, for solving quantum linear systems for subsurface flow. We show that for quantum algorithms the computational cost of estimating a quantity of interest for a statistical ensemble of networks is roughly the same as that of a single realization, essentially implying that one can get uncertainty quantification for free.

58 GEOSCIENCES↗
DOE OSTI2024

Thermodynamic control on the decomposition of organic matter across different electron acceptors

The increasing availability of high-resolution characterization of natural organic matter (OM) data has shifted the paradigm of lumped descriptions of OM components and potential microbial activities. Our recent development of a substrate-explicit thermodynamic model uniquely enables incorporating complex OM pools to formulate biogeochemical reaction models based on their elemental compositions. While this previous work facilitates prediction of aerobic respiration of complex OM, it is equally imperative to consider the role of non-oxygenic electron acceptors in regulating OM turnover and the fate of carbon. In this study, we significantly expand our previous model by flexibly incorporating both detailed OM chemistry and electron acceptors other than oxygen. Here, our modeling analysis has revealed substantial variations in the energy status of OM molecules across different soils, which drive the co-occurrence of different electron-accepting processes. We demonstrated the effectiveness of the proposed model using a consistency check with experimental data. Through systematic evaluation of the impact of diverse chemical inputs (both electron donors and acceptors) on OM decomposition, the new model also revealed how key microbial growth parameters such as carbon use efficiency (CUE) and reaction rates vary across different electron-accepting processes. Our model provides a unified framework integrating thermodynamic and kinetic constraints on microbial metabolic activities. It complements traditional kinetic models, which are often designed solely to capture mass fluxes. We conclude that thermodynamic modeling emerges as a powerful tool for describing the mechanisms underlying the interplay between microbial growth and OM chemistry and cycling across different electron acceptors, enhancing our ability to project complex ecosystem behaviors in dynamic environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A Fundamentally New Coupled Approach to Contact Mechanics via the Dirichlet‐Neumann Schwarz Alternating Method

Contact phenomena are crucial for understanding the behavior of mechanical systems. However, existing computational approaches for simulating mechanical contact often face numerical challenges, such as inaccurate physical predictions, energy conservation errors, and unwanted oscillations. Here, we introduce an alternative technique for simulating dynamic contact based on the non‐overlapping Schwarz alternating method, originally developed for domain decomposition. In multibody contact scenarios, this method treats each body as a separate, non‐overlapping domain and prevents interpenetration using an alternating Dirichlet–Neumann iterative process. This approach has a strong theoretical foundation, eliminates the need for contact constraints, and offers flexibility, making it ideal for multiscale and multiphysics applications. We conducted a numerical comparison between the Schwarz method and traditional methods, such as the Lagrange multiplier and penalty methods, focusing on a benchmark impact problem. Our results indicate that the Schwarz alternating method outperforms traditional methods in several key areas: it provides more accurate predictions for various measurable quantities and demonstrates exceptional energy conservation capabilities. To address unwanted oscillations in contact velocities and forces, we explored various algorithms and stabilization techniques, ultimately opting for the naïve‐stabilized Newmark scheme for its simplicity and effectiveness. Additionally, we validated the efficiency of the Schwarz method in a three‐dimensional impact problem, highlighting its inherent capacity to accommodate different mesh topologies, time‐integration schemes, and time steps for each interacting body.

Schwarz alternating method↗
DOE OSTI2022

Microscale spatial distribution and soil organic matter persistence in top and subsoil

The spatial distribution of organic substrates and microscale soil heterogeneity significantly influence organic matter (OM) persistence as constraints on OM accessibility to microorganisms. However, it is unclear how changes in OM spatial heterogeneity driven by factors such as soil depth affect the relative importance of substrate spatial distribution on OM persistence. This work evaluated the decomposition and persistence of 13 C and 15 N labeled water-extractable OM inputs over 50 days as either hotspot (i.e., pelleted in 1–2 mm-size pieces) or distributed (i.e., added as OM < 0.07 μm suspended in water) forms in topsoil (0–0.2 m) and subsoil (0.8–0.9 m) samples of an Andisol. We observed greater persistence of added C in the subsoil with distributed OM inputs relative to hotspot OM, indicated by a 17% reduction in cumulative mineralization of the added C and a 10% higher conversion to mineral-associated OM. A lower substrate availability potentially reduced mineralization due to OM dispersion throughout the soil. NanoSIMS (nanoscale secondary ion mass spectrometry) analysis identified organo-mineral associations on cross-sectioned aggregate interiors in the subsoil. On the other hand, in the topsoil, we did not observe significant differences in the persistence of OM, suggesting that the large amounts of particulate OM already present in the soil outweighed the influence of added OM spatial distribution. Here, we demonstrated under laboratory conditions that the spatial distribution of fresh OM input alone significantly affected the decomposition and persistence of OM inputs in the subsoil. On the other hand, spatial distribution seems to play a lower role in topsoils rich in particulate OM. The divergence in the influence of OM spatial distribution between the top and subsoil is likely driven by differences in soil mineralogy and OM composition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Using Additives to Control the Decomposition Temperature of Sodium Borohydride

Hydrogen (H 2 ) shows great promise as zero-carbon emission fuel, but there are several challenges to overcome in regards to storage and transportation to make it a more universal energy solution. Gaseous hydrogen requires high pressures and large volume tanks while storage of liquid hydrogen requires cryogenic temperatures; neither option is ideal due to cost and the hazards involved. Storage in the solid state presents an attractive alternative, and can meet the U.S. Department of Energy (DOE) constraints to find materials containing > 7 % H 2 (gravimetric weight) with a maximum H 2 release under 125 °C. While there are many candidate hydrogen storage materials, the vast majority are metal hydrides. Of the hydrides, this review focuses solely on sodium borohydride (NaBH 4 ), which is often not covered in other hydride reviews. However, as it contains 10.6% (by weight) H 2 that can release at 133 ± 3 JK -1 mol -1 , this inexpensive material has received renewed attention. NaBH 4 should decompose to H 2 (g), Na(s), and B(s), and could be recycled into its original form. Unfortunately, metal to ligand charge transfer in NaBH 4 induces high thermodynamic stability, creating a high decomposition temperature of 530 °C. In an effort make H 2 more accessible at lower temperatures, researchers have incorporated additives to destabilize the structure. This review highlights metal additives that have successfully reduced the decomposition temperature of NaBH 4 , with temperatures ranging from 522 °C (titanium (IV) fluoride) to 379 °C (niobium (V) fluoride). We describe synthetic methods employed, chemical pathways taken, and the challenges of boron derivative formation on H 2 cycling. Though no trends can be found across all additives, it is our hope that compiling the data here will enable researchers to gain a better understanding of the additives’ influence and to determine how a new system might be designed to make NaBH 4 a more viable H 2 fuel source.

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

Extracting band edge profiles at semiconductor heterostructures from hard-x-ray core-level photoelectron spectra

Hard-x-ray photoelectron spectroscopy (HAXPES) is a valuable source of information on band-edge profiles deep inside semiconductor thin films and heterojunctions. However, extracting this information requires robust and physically meaningful decomposition of spectra into contributions from individual atomic planes. We present an approach that utilizes the physical requirements of a monotonic dependence of the built-in electrostatic potential on depth and continuity of the potential function and its derivatives. These constraints enable efficient extraction of band-edge profiles and allow one to capture details of the electronic structure, including determination of the signs and magnitudes of the band bending as well as the valence band offsets. The utility of this approach to generate quantitative insight into the electronic structure of complex materials is illustrated for epitaxial SrTiO 3 on intrinsic Si(001).

97 MATHEMATICS AND COMPUTING↗