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Results for “simultaneous optimization”

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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Process intensification for generating and decomposing formic acid, a liquid hydrogen carrier

We preview two processes that facilitate using formic acid (HCOOH) as a liquid hydrogen carrier to store renewably-generated electrical energy and then release it to generate electrical power cleanly for backup or emergency applications. First, we show that simultaneously oxidizing an organic solute (typically a waste stream) can assist the electrochemical synthesis of formic acid by lowering the cell potential. The electrolyser comprises a hybrid 3-chamber PEM stack that reduces CO₂ via a gas-diffusion cathode boosted by the oxidation of aqueous methanol. However, the extent of the boosting needs to be optimized across the whole operation of the cell. Next, we present results from an intensified reactor for decomposing formic acid back into H₂ and CO₂ at elevated pressure so that the H₂ can be used in a fuel cell. The reactor combines three operations: Vaporization of the formic acid, its decomposition, and separation of the product stream. Their close coupling affords energy savings and a compact design that could be mounted on a mobile skid. We briefly discuss the electrode catalyst that facilitates the first process and two thermally activated catalysts (Ir supported on covalent triazine framework and Pd supported on carbon) that enable the second process.

25 ENERGY STORAGE↗
DOE OSTI2020

Diesel Generator Model Parameterization for Microgrid Simulation Using Hybrid Box-Constrained Levenberg-Marquardt Algorithm

Existing generator parameterization methods, typically developed for large turbine generator units, are difficult to apply to small kW-level diesel generators in microgrid applications. Here, this article presents a model parameterization method that estimates a complete set of kW-level diesel generator parameters simultaneously using only load-step-change tests with limited measurement points. This method provides a more cost-efficient and robust approach to achieve high-fidelity modeling of diesel generators for microgrid dynamic simulation. A two-stage hybrid box-constrained Levenberg-Marquardt (H-BCLM) algorithm is developed to search the optimal parameter set given the parameter bounds. A heuristic algorithm, namely Generalized Opposition-based Learning Genetic Algorithm (GOL-GA), is applied to identify proper initial estimates at the first stage, followed by a modified Levenberg-Marquardt algorithm designed to fine tune the solution based on the first-stage result. The proposed method is validated against dynamic simulation of a diesel generator model and field measurements from a 16kW diesel generator unit.

42 ENGINEERING↗
DOE OSTI2021

Double Image Polarimeter—Ultra Fast: Simultaneous Three-color (BVR) Polarimeter with Electron-multiplying Charge-coupled Devices

We describe a new instrument capable of high-precision (10{sup −5}) polarimetric observations simultaneously in three passbands (BVR). The instrument utilizes electron-multiplying charge-coupled device (EM CCD) cameras for high efficiency and fast image readout. The key features of the Double Image Polarimeter—Ultra Fast (DIPol-UF) are: (i) the optical design with high throughput and inherent stability; (ii) great versatility, which makes the instrument optimally suitable for observations of bright and faint targets; and (iii) a control system, which allows the use of the polarimeter remotely. Examples are given of the first results obtained from high signal-to-noise observations of bright nearby stars and of fainter sources such as X-ray binaries in their quiescent states.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Cyclic moisture reactivation of calcium sorbents for long duration thermochemical energy storage

The transition to a flexible and reliable energy infrastructure, using electro-thermal energy generation technologies such as geothermal, concentrated solar power, and nuclear, usually demands simultaneous advancement of thermal energy storage (TES) to support on-demand electricity generation and industrial applications while mitigating the inherent intermittency of renewable energy sources and power outages from direct energy generation. Among TES technologies, thermochemical energy storage (TCES) based on calcium looping emerges as a compelling high-power energy storage candidate due to its high reaction enthalpy, compatibility with elevated operating temperatures, and abundance of low-cost materials. However, the long-term durability of calcium-based sorbents for TCES is hindered by surface sintering and particle aggregation, leading to performance degradation over repeated thermal cycles. This study explores a moisture hydration-based strategy to regenerate a degraded calcium sorbent and mitigate performance degradation for long duration TCES. The addition of moisture transforms calcium oxide into calcium hydroxide and produces intercalation water layers, associated with a regenerated surface area and reduced calcium oxide crystallite size. Both these effects are beneficial in restoring the sorbents' reactivity for carbonization. Additionally, an optimized hydration-assisted reactivation protocol balances the recovered energy storage capacity with heating penalty required for moisture removal from hydrated samples, resulting in an enhanced energy storage capacity up to 176% compared to benchmark sorbents that undergo cycling without reactivation after 60 cycles. In conclusion, these results highlight the potential of hydration-assisted reactivation to enhance the long-term performance of TCES, providing an effective pathway to advancing electro-thermal storage technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Perovskite-Type Solid Solution Nano-Electrocatalysts Enable Simultaneously Enhanced Activity and Stability for Oxygen Evolution

A trade-off between catalytic activity and structural stability generally exists in oxygen evolution electrocatalysis, especially in acidic environment. This dilemma limits the development of higher-performance electrocatalysts that are required by next-generation electrochemical technologies. In this work it is demonstrated that the inverse catalytic activity–structural stability relation can be broken by alloying catalytically inert strontium zirconate with the other catalytically active perovskite, strontium iridate. This strategy results in an alloyed perovskite electrocatalyst with simultaneously improved iridium mass activity and structural stability, by about five times, for the oxygen evolution reaction under acidic conditions. The experimental and theoretical results suggest that the alloying strategy generates multiple positive effects, mainly including the reduction of catalyst size, the decrease of catalyst covalency, and the weakening of surface oxygen-binding ability. The synergistic optimization of bulk and surface properties, as a result, enhances the intrinsic activity and availability of surface iridium sites, whilst significantly inhibiting the surface cation corrosion during electrocatalysis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Biological conversion of methane to methanol at high H 2 S concentrations with an H 2 S-tolerant methanotrophic consortium

To develop biological biogas to methanol conversion technology without costly hydrogen sulfide (H 2 S) removal, a high H 2 S tolerant methanotrophic consortium (HTMC), was enriched from an anaerobic digester effluent in presence of 5.64 g/m 3 H 2 S in the gas phase. The HTMC can grow stably and produce methanol under conditions with CH 4 /air mixtures containing 5.64 g/m 3 of H 2 S. There is no significant (p>0.05) difference in cell yield or CH 4 to methanol conversion efficiency between trials with different H 2 S concentrations from 0 g/m 3 to 5.64 g/m 3 . Further, under optimal conditions, a cell yield of 0.333 g cells/g CH 4 , a methanol concentration of 0.28 mg/mL, and a CH 4 to methanol conversion efficiency of 0.22 mol/mol were obtained, respectively. Besides methanotrophs (14.85%) and other bacteria, Cyanobacteria were also identified in the HTMC with a high abundancy (32.16%), which could broaden the application of HTMC for simultaneous utilization of CH 4 and CO 2 from raw biogas.

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

Diabatic error and propagation of Majorana zero modes in interacting quantum dots systems

Motivated by recent experimental progress in realizing Majorana zero modes (MZMs) using quantum dot systems, we investigate the diabatic errors associated with the movement of those MZMs. The movement is achieved by tuning time-dependent gate potentials applied to individual quantum dots, effectively creating a moving potential wall. To probe the optimized movement of MZMs, we calculate the experimentally accessible time-dependent fidelity and local density-of-states using many-body time-dependent numerical methods. Furthermore, our analysis reveals that an optimal potential wall height is crucial to preserve the well-localized nature of the MZM during its movement. Moreover, we analyze diabatic errors in realistic quantum-dot systems, incorporating the effects of repulsive Coulomb interactions and disorder in both hopping and pairing terms. Additionally, we provide a comparative study of diabatic errors arising from the simultaneous versus sequential tuning of multiple gates during the MZMs movement. Finally, we estimate the timescale required for MZM transfer in a six-quantum-dot system, demonstrating that MZM movement is feasible and can be completed well within the qubit's operational lifetime in practical quantum-dot setups.

Density of states↗
DOE OSTI2022

Redundantly Amplified Information Suppresses Quantum Correlations in Many-Body Systems

We establish bounds on quantum correlations in many-body systems. They reveal what sort of information about a quantum system can be simultaneously recorded in different parts of its environment. Specifically, independent agents who monitor environment fragments can eavesdrop only on amplified and redundantly disseminated—hence, effectively classical—information about the decoherence-resistant pointer observable. We also show that the emergence of classical objectivity is signaled by a distinctive scaling of the conditional mutual information, bypassing hard numerical optimizations. Our results validate the core idea of quantum Darwinism: objective classical reality does not need to be postulated and is not accidental, but rather a compelling emergent feature of quantum theory that otherwise—in the absence of decoherence and amplification—leads to “quantum weirdness.” In particular, a lack of consensus between agents that access environment fragments is bounded by the information deficit, a measure of the incompleteness of the information about the system.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Measurements of Higgs boson production in the decay channel with a pair of τ leptons in proton–proton collisions at $\sqrt{s}=13$ TeV

Measurements of Higgs boson production, where the Higgs boson decays into a pair of τ leptons, are presented, using a sample of proton-proton collisions collected with the CMS experiment at a center-of-mass energy of , corresponding to an integrated luminosity of 138 fb –1 . Three analyses are presented. Two are targeting Higgs boson production via gluon fusion and vector boson fusion: a neural network based analysis and an analysis based on an event categorization optimized on the ratio of signal over background events. These are complemented by an analysis targeting vector boson associated Higgs boson production. Results are presented in the form of signal strengths relative to the standard model predictions and products of cross sections and branching fraction to τ leptons, in up to 16 different kinematic regions. For the simultaneous measurements of the neural network based analysis and the analysis targeting vector boson associated Higgs boson production signal strengths are found to be 0.82 ± 0.11 for inclusive Higgs boson production, 0.67 ± 0.19 (0.81 ± 0.17) for the production mainly via gluon fusion (vector boson fusion), and 1.79 ± 0.45 for vector boson associated Higgs boson production.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Room temperature plasma-etching and surface passivation of far-ultraviolet Al mirrors using electron beam generated plasmas

The development of optical systems operating in the far ultraviolet range (FUV, λ=100-200 nm) is limited by the efficiency of passivated aluminum (Al) mirrors. Although it is presently possible to obtain high-reflectivity FUV mirrors through physical vapor deposition, the process involves deposition with substrates at high temperatures, which is technically challenging for large optical elements. A novel passivation procedure for bare Al mirrors is reported. The treatment consisted of using a low-temperature electron-beam generated plasma produced in a gas mixture of Ar and SF6 to etch away the native oxide layer from the Al film, while simultaneously promoting the generation of a thin aluminum tri-fluoride (AlF3) layer on the Al surface. In the first section we analyze the effect of varying both ion energy and SF6 concentration on the FUV reflectance, thickness, composition, and surface morphology of the resulting AlF3 protective layers. In the second section, the reflectivity of samples is optimized at selected important FUV wavelengths for astronomical observations. Notably, samples attained state-of-the-art reflectances of 75% at 108.5 nm (He Lyman γ), 91% at 121.6 nm (H Lyman α), 90% at 130.4 nm (OI), and of 95% at 155.0 nm (C IV). The stability over time of these passivated mirrors is also investigated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Dispatch Manager for NEML2 Constitutive Model Calculations Embedded in MOOSE

This report describes the extended capabilities of the NEML2 constitutive modeling library, including a flexible and efficient work dispatching system designed to leverage both CPU and GPU resources. This enhancement addresses one of the primary computational challenges in large-scale simulations: the ability to distribute and execute batches of material model evaluations across heterogeneous computing devices. The new dispatch system introduces a modular set of dispatcher and scheduler classes that coordinate the flow of data and execution between devices. The dispatcher is responsible for efficiently packaging work, managing device-specific memory operations, and synchronizing results. This modularity allows for extensibility, making it straightforward to integrate additional computing backends in the future. From an implementation standpoint, the dispatcher system interfaces seamlessly with NEML2's existing models. They handle device-aware tensor operations, optimize memory transfers, and support asynchronous execution when applicable. This design ensures that batches of material points can be evaluated concurrently, substantially improving throughput compared to previous single-device or serial implementations. These improvements not only enhance the raw performance of NEML2 but also improve its usability in multiscale and high-fidelity simulations, where the simultaneous evaluation of large material point batches is critical. Benchmarks included in the report demonstrate the system’s scalability, highlighting its effectiveness when leveraging modern GPU architectures.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Bridging paradigms: Designing for HPC-Quantum convergence

Here, this paper presents a comprehensive software stack architecture for integrating quantum computing (QC) capabilities with High-Performance Computing (HPC) environments. While quantum computers show promise as specialized accelerators for scientific computing, their effective integration with classical HPC systems presents significant technical challenges. We propose a hardware-agnostic software framework that supports both current noisy intermediate-scale quantum devices and future fault-tolerant quantum computers, while maintaining compatibility with existing HPC workflows. The architecture includes a quantum gateway interface, standardized APIs for resource management, and robust scheduling mechanisms to handle both simultaneous and interleaved quantum–classical workloads. Key innovations include: (1) a unified resource management system that efficiently coordinates quantum and classical resources, (2) a flexible quantum programming interface that abstracts hardware-specific details, (3) A Quantum Platform Manager API that simplifies the integration of various quantum hardware systems, and (4) a comprehensive tool chain for quantum circuit optimization and execution. We demonstrate our architecture through implementation of quantum–classical algorithms, including the variational quantum linear solver, showcasing the framework’s ability to handle complex hybrid workflows while maximizing resource utilization. This work provides a foundational blueprint for integrating QC capabilities into existing HPC infrastructures, addressing critical challenges in resource management, job scheduling, and efficient data movement between classical and quantum resources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Design and synthesis of biobased superhydrophobic biochar catalyst derived from Citrus sinensis for biodiesel production using inedible oil feedstocks

In an one-pot in situ trans/esterification of low-grade feedstocks, the simultaneous presence of triglycerides (TAGs) and free fatty acids (FFAs) presents a dual catalytic challenge. While TAGs undergo transesterification to form biodiesel and glycerol, FFAs present in the feedstocks are esterified simultaneously, producing water as a by-product. This water can deactivate acid catalysts by interacting with their active sites, reducing catalytic efficiency and reusability. To overcome this, we developed a hydrophobic sulfonic acid-functionalized biochar catalyst derived from Citrus sinensis (orange peel) via sulfonation with H 2 SO 4 and subsequent silylation using hexamethyldisilazane (HMDS). The optimized catalyst exhibited a high surface area (355.09 m 2 g −1 ), sulfur content (5.33 wt%), and strong hydrophobicity (water contact angle: 154°). Compared to non-hydrophobic analogs, it showed enhanced activity and reusability (up to 10 cycles). Using response surface methodology with central composite design, a biodiesel yield of 99.1 ± 0.4% was achieved under optimal conditions. Life cycle assessment was performed to evaluate the environmental impacts of biodiesel production utilising the synthesized catalyst, considering 1000 kg of biodiesel produced as 1 functional unit. In conclusion, the recorded results showed the cumulative abiotic depletion of fossil resources over the entire biodiesel production process as 87 243.423 MJ and global warming potential as 4103.494 kg CO 2 equivalent.

Biochar↗
DOE OSTI2025

Durable, Ultra-Thin Diaphragms for Liquid Alkaline Water Electrolysis

W. L. Gore & Associates assembled a world class team (De Nora Tech, LLC; New York University; and thyssenkrupp nucera) to develop durable, ultra-low resistance diaphragms that dramatically improve system efficiency, dynamic response, and operational flexibility. To enable the use of ultra-thin diaphragms, an optimized electrode package was chosen as part of an electrode down select study. Ultra-thin diaphragms based on microporous polymer scaffolds imbibed with zirconia nanoparticles were developed and tested. Performance and durability on par with incumbent materials was demonstrated. A transparent electrolyzer to directly observe in-situ diaphragm-bubble interactions was designed and built, and simultaneous optical and electrochemical performance tests were performed. A Pressurized Alkaline Water Electrolysis (PAWE) single cell test station was designed to support advanced R&D in high-pressure electrolysis, particularly for evaluating novel electrode and separator configurations under elevated temperature and pressure operating conditions. Due to early project termination, the original scope could not be fully achieved.

08 HYDROGEN↗
DOE OSTI2020

Use of the Manuela 3D/Radiation Scanning Tool at Nuclear Facilities - 20437

Licensees, facility operators and decommissioning contractors have a need for comprehensive, accurate and precise radiological and topographical data to plan and execute safe and efficient Decontamination and Decommissioning (D and D) projects. Traditional approaches rely greatly upon labor and administratively intensive data collection methods that require considerable time and effort to glean the relevant data to plan and perform work in a radiological work area. Orano Decommissioning Services has developed and utilized at French nuclear facilities a lightweight portable scanning instrument called MANUELA (Mobile Apparatus for Nuclear Expertise Localization Assistance). Recently Orano conducted demonstrations at two United States nuclear facilities using MANUELA that may prove useful in areas of the fuel cycle including: - ALARA (As Low As Reasonably Achievable) planning during facility operations; - Scoping and site characterization during the D and D planning phase; - Remedial action support during active decommissioning work; - Radiation and modeling planning for plant modifications; - Support Final Status Survey and demonstration of 'end state' compliance for license termination. MANUELA is currently being evaluated for use during decommissioning of nuclear facilities and could aide in demonstrating compliance with end state criteria after decommissioning. Of particular interest are decommissioning projects planned for various sites across the United States. Most of these sites present unique challenges and opportunities to safely and efficiently decommission in a regulatory compliant manner. The two demonstration site's current conditions of relatively low radiation levels inside containment proved to be ideal platforms to deploy the MANUELA instrument for evaluation of the complex geometries typically found in a nuclear facility. The MANUELA instrument was able to precisely identify local hot spots of the reactor system's primary equipment and was able to simultaneously overlay the dose information onto the scanned 3D images. Using data like this, a licensee would be able to make informed technical and personnel decisions on methods to remediate, shield or properly dispose of the radioactive source term. MANUELA can be used throughout the decommissioning process to validate progress and continue to refine the work activities to optimize the efforts of the crew which reduces downtime waiting for survey results, whereas traditional survey methodology relies on a physical survey to be performed and the data transcribed onto survey maps that are only two dimensional. The traditional format tends to be inaccurate and difficult to interpret the precise location(s) of hot spots or generalized dose rates. The resultant scan also allows the user to know the exact extent of the survey versus transposing information onto a map with only a portion of the map area scanned. MANUELA also compiles all of the relevant survey data into a downloadable table format which includes the measurement identification number, time stamp, point space location on the XYZ plane, and the dose rate value. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

The Importance of Surface Oxygen for Lithiation and Morphology Evolution during Calcination of High-Nickel NMC Cathodes

Nanoscale morphology has a direct impact on the performance of materials for electrochemical energy storage. Despite this importance, little is known about the evolution of primary particle morphology nor its effect on chemical pathways during synthesis. In this work, operando characterization is combined with atomic-scale and continuum simulations to clarify the relationship between morphology of cathode primary particles and their lithiation during calcination of LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC-811). This combined approach reveals a key role for surface oxygen adsorption in facilitating the lithiation reaction by promoting metal diffusion and oxidation, and simultaneously providing surface sites for lithium insertion. Furthermore, oxygen surface termination is shown to increase the activation energy for sintering, leading to smaller primary particle sizes at intermediate temperatures. Smaller particles provide both shorter diffusion lengths for lithium incorporation and increased surface site density for lithium insertion. These insights provide a foundation for more tailored syntheses of cathode materials with optimized performance characteristics.

25 ENERGY STORAGE↗
DOE OSTI2023

Variational Neural-Network Ansatz for Continuum Quantum Field Theory

Physicists dating back to Feynman have lamented the difficulties of applying the variational principle to quantum field theories. In nonrelativistic quantum field theories, the challenge is to parametrize and optimize over the infinitely many n-particle wave functions comprising the state’s Fock-space representation. Here we approach this problem by introducing neural-network quantum field states, a deep learning ansatz that enables application of the variational principle to nonrelativistic quantum field theories in the continuum. Our ansatz uses the Deep Sets neural network architecture to simultaneously parametrize all of the n-particle wave functions comprising a quantum field state. We employ our ansatz to approximate ground states of various field theories, including an inhomogeneous system and a system with long-range interactions, thus demonstrating a powerful new tool for probing quantum field theories.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Decomposition and Algorithmic Approaches for Solving Large-Scale Process Family Design Problems

Our most recent work expands the water desalination case study from 76 variants to 10,897 variants using the equation-oriented model built in Pyomo as part of the PARETO project. Using the discretization formulation presented in Stinchfield (2024a), rather than solving for all 10,897 variants simultaneously, we decompose the formulation into subproblems containing subsets of variants from the process family. We solve the overall problem with Progressive Hedging (PH) deployed in parallel on a distributed HPC cluster using the open-source Python package mpi-sppy (Knueven et al., 2023). This approach allowed us to solve this process family design problem to ~1.5% relative optimality gap in about 5 hours; in comparison, Gurobi reached ~50% relative optimality gap in about 6 hours (Stinchfield et al., 2024b). However, this approach still requires discretization of the common unit module design ranges; additionally, PH acts as a heuristic for MILP’s with gap-closing capabilities. Ideally, we would not have to use ML surrogates or discretization to solve this problem, instead solving the process family design problem with the equation-oriented model directly to achieve the most accurate results. However, recall that we did not consider solving the MINLP directly due to complexity and size. In this work, we aim to decompose and solve this large-scale MINLP using a Structured Nonlinear Global Optimization algorithm presented by Cao and Zavala (2019).

Stinchfield, Georgia↗