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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Control Co-Design Studies for a 22 MW Semisubmersible Floating Wind Turbine Platform

We present a control co-design software framework that can be used to optimize floating wind turbines and their controllers. Because this framework has many options for design variables, constraints, and merit figures, along with modeling fidelity levels, we seek to demonstrate best practices for using the tool while designing a floating platform for the new 22 MW offshore reference wind turbine developed within the International Energy Agency Wind Technology Commercialization Programme 55 on Reference Wind Turbines and Farms. During these studies, we evaluate the use of different simulation fidelity levels, the effect of using different load cases for controller tuning, and the difference between sequential and simultaneous control co-design solutions. Based on these efforts, we suggest using an algorithm that performs an initial search of the design space before optimization. We find that solving smaller optimization problems, in a sequential manner, leads to more reliable outcomes in fewer iterations than larger, simultaneous control co-design solutions. However a simultaneous CCD solution produces a platform with a 2% lower mass than the sequential CCD outcome.

17 WIND ENERGY↗
DOE OSTI2017

An Augmented Lagrangian Filter Method for Real-Time Embedded Optimization

We present a filter line-search algorithm for nonconvex continuous optimization that combines an augmented Lagrangian function and a constraint violation metric to accept and reject steps. The approach is motivated by real-time optimization applications that need to be executed on embedded computing platforms with limited memory and processor speeds. The proposed method enables primal–dual regularization of the linear algebra system that in turn permits the use of solution strategies with lower computing overheads. We prove that the proposed algorithm is globally convergent and we demonstrate the developments using a nonconvex real-time optimization application for a building heating, ventilation, and air conditioning system. Our numerical tests are performed on a standard processor and on an embedded platform. Lastly, we demonstrate that the approach reduces solution times by a factor of over 1000.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Development of Manufacturing Technology to Accelerate Cost Reduction of Low Concentration and

The purpose of this project was to accelerate deployment of cost-effective US-based manufacturing of Solaria’s unique c-Si module technology. This effort successfully resulted in the development of US-based manufacturing technology to support two highly-differentiated, market leading product platforms. The project was initially predicated on developing Solaria’s low-concentration PV (LCPV) module technology which at the time of the award was uniquely positioned to exceed the SunShot price goal of $0.50/Wp for standard c-Si modules. The Solaria LCPV module is a 2.5x concentrator that leverages proven, high-reliability PV module materials and low silicon cell usage into a technology package that already had the lowest direct material cost and leading Levelized Cost of Electricity (LCOE). With over 25 MW commercially deployed globally, the Solaria module was well positioned to continue to lead in PV module cost reduction. Throughout the term of the contract, market conditions changed dramatically and so to did Solaria’s product offerings to support this. However, the manufacturing technology developed for the LCPV module was successfully leveraged and optimized to support two new and different product platforms. BIPV “PowerVision” and High-efficiency “PowerXT” modules. The primary barrier to enabling high-volume PV module manufacturing in the US is the high manual labor component in certain unique aspects of our manufacturing process. The funding was used to develop unique manufacturing automation which makes the manual labor components of these key processes more efficient and increase throughput. At the core of Solaria’s product offerings are its unique and proprietary techniques for dicing and re-arranging solar cells into modules with highly-differentiated characteristics that address key gaps in the c-Si market. It is these techniques that were successfully evolved and deployed into US-based manufacturing site with SunShot funding. Today, Solaria is currently positioned to become the market leader with these two technologies over the coming 24 months largely due to the successful innovations of the underlying manufacturing technology. This success will leverage US-based manufacturing technology and the associated US-jobs to support. Solaria views the project as highly successful and a great example of SunShot funding enabling the creating of US jobs and the deployment of ubiquitous solar energy products.

14 SOLAR ENERGY↗
DOE OSTI2020

Prediction of Hydroxymethylfurfural Yield in Glucose Conversion through Investigation of Lewis Acid and Organic Solvent Effects

Hydroxymethylfurfural (HMF) is one of the important renewable platform compounds that can be obtained from biomass feedstocks through glucose conversion catalyzed by Brønsted and Lewis acids. However, it is challenging to enhance the HMF yield due to side reactions. In this study, a systematic approach combining theory and experiment was performed to investigate the influence of Lewis acids and organic solvents on the HMF yield. For the Lewis acid effect, a relationship between chemical hardness and experimental HMF yields was found in the rate-limiting step of glucose-to-fructose isomerization for six metal chlorides; HMF production was promoted when the metal chloride and a substrate had a similar chemical hardness. To study the organic solvent effect, a multivariate model was developed based on the insights gained from the mechanistic study of fructose dehydration, to predict HMF yields in a given water-organic cosolvent system. It showed a reliable accuracy in evaluating HMF yields with a mean absolute error (MAE) of 3.0% with respect to experimental HMF yields for 13 solvents, and also predicted HMF yields with a MAE of 10.7% for four new solvents. Chemical interpretation of the model revealed that it is desirable to use a solvent capable of stabilizing the carbocation intermediates with low proton transfer activity and high hydrogen bond basicity, to maximize the HMF yield. This multivariate model informs experimentalists about rational selection of solvents with very low computational costs needed to calculate only six variables for each solvent. It can be expanded to other catalytic systems such as heterogeneous Brønsted–Lewis bifunctional catalysts and enables optimization of reaction conditions to obtain other useful platform molecules through biomass conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Comprehensive Approach towards Multi-Objective EMI Filter Design Optimization in High-Frequency SiC-Based Motor Drives

With rapid penetration of high-frequency, highdensity power electronics into the industry, controlling the system generated EMI becomes one of the major design challenges. Designing practical optimized EMI filters require simultaneous consideration of multiple aspects - including electromagnetic couplings, magnetic materials, practical component parasitics and their impacts at high-frequencies, and also the overall manufacturing costs. The multi-dimensional nature of the problem often results in overcompensated designs that hurt the system efficiency and power density. This paper focuses on a comprehensive design platform (developed in MATLAB) towards designing high-density, optimized, highly efficient EMI filters by analyzing the generated noise spectrum and evaluating a vast array of potential solutions before outputting an optimized filter solution. The proposed tool includes database-based component selection, optimal topology selection, multistage filter design, overall optimization for volume, mass, cost and total loss. The proposed filter has been thoroughly evaluated in a PSIM simulation environment emulating the hardware in CRD300DA12EXM3, a 300kW three-phase inverter from Wolfspeed with an RL load representing a motor drive application. Furthermore, a 20kHz switching frequency is chosen and impacts of the motor high-frequency characteristics on the generated EMI noise spectrum of the overall system have been analyzed.

42 ENGINEERING↗
DOE OSTI2025

Efficient and Selective Chemical Transformations in Highly Charged and Confined Nanodroplets

The acceleration of chemical reaction rates and the increased product selectivity in microdroplets compared to that in bulk solutions has become a topic of increasing interest that has been extensively characterized by electrospray ionization mass spectrometry (ESI-MS). However, the sources of this acceleration and the detailed relationships between droplet properties and resulting reaction rate acceleration are still under debate. Moreover, droplet properties are governed by multiple interrelated experimental parameters, i.e., electrospray voltage, solution flow rate, etc., which makes it difficult and time-consuming to explore this diverse parameter space using traditional manual experimental or computational approaches. In this work, we developed an automated experimental platform integrating reactions in controlled charged microdroplet environments with ESI-MS characterization and sequential hybrid Bayesian modeling, as well as an optimal experimental design framework, to achieve multidimensional parameter optimization for higher reaction turnover rates, based on a model reaction of tetraethylenepentamine (TEPA) with carbon dioxide. With the current platform, we have achieved automated scans with a range of electrospray voltages and solution flow rates, and determined and optimized parameter settings to achieve increased reaction turnovers. We have also linked this platform to the underlying properties of droplets via a hybrid model incorporating physics, high-level theoretical calculations, and machine learning (ML) approaches. The autonomous platform is broadly applicable to a range of chemical reactions relevant to DOE’s mission in chemical separations, catalysis, and materials synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

SimCCS: An open-source tool for optimizing CO 2 capture, transport, and storage infrastructure

Commercial-scale carbon capture and storage (CCS) technology will involve deploying infrastructure on a massive and costly scale. This effort will require careful and comprehensive planning to ensure that capture locations, storage sites, and the dedicated CO 2 distribution pipelines are selected in a robust and cost-effective manner. Presented in 2009, SimCCS is an optimization model for integrated system design that enables researchers, stakeholders, and policy makers to design CCS infrastructure networks. SimCCS 2.0 is a complete, ground-up redesign that is now a portable software package, useable and shareable by the CCS research, industrial, policy, and public communities. SimCCS 2.0 integrates multiple new capabilities including a refined optimization model, novel candidate network generation techniques, and optional integration with high-performance computing platforms. Accessing user-provided CO 2 source, sink, and transportation data, SimCCS 2.0 creates candidate transportation routes and formalizes an optimization problem that determines the most cost-effective CCS system design. This optimization problem is further solved either through a high-performance computing interface, or through third-party software on a local desktop computing platform. Finally, SimCCS 2.0 employs an open-access geographic information system framework to enable analysis and visualization capabilities. SimCCS 2.0 is written in Java and is publicly available via GitHub to encourage collaboration, modification, and community development.

42 ENGINEERING↗
DOE OSTI2021

Scaling laser preheat for MagLIF with the Z-Beamlet laser

Optimizing the performance of the Magnetized Liner Inertial Fusion (MagLIF) platform on the Z pulsed power facility requires coupling greater than 2 kJ of preheat energy to an underdense fuel in the presence of an applied axial magnetic field ranging from 10 to 30 T. Achieving the suggested optimal preheat energies has not been experimentally achieved so far. In this work, we explore the preheat design space for cryogenically cooled MagLIF targets, which represent a viable candidate for increasing preheat energies. Using 2D and 3D HYDRA MHD simulations, we first discuss the various physical effects that occur during laser preheat, such as laser energy deposition, self-focusing, and filamentation. After identifying the changes that different phase plates, gas-fill densities, and magnetic fields bring to the aforementioned physical effects, we, then, consider higher laser energies that are achievable with modest upgrades to the Z Beamlet laser. Lastly, with a 6.0-kJ upgraded laser, 3D calculations suggest that it is possible to deliver 4.25 kJ into the MagLIF fuel, resulting in an expected deuterium neutron yield of Y DD ≃ 1.5 × 10 14 , or roughly 50 kJ of DT equivalent yield, at 20-MA current drive. This represents a 10-fold increase in the currently achieved yields for MagLIF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Understanding Portability of Automotive Workload: A Case Study with the Points-to-Image Kernel in SYCL on Heterogeneous Computing Platforms

SYCL is a promising programming model for heterogenous computing across vendors’ devices. In this paper, we study whether SYCL can be applied to an automotive workload and its portability on heterogeneous computing platforms. We explain the automotive benchmark, describe our implementations and optimizations of the benchmark, and evaluate the performance of the benchmarks using SYCL and other programming models on heterogeneous computing devices. The study also allows us to have a better understanding of portability of the benchmark across these platforms.

Jin, Zheming↗
DOE OSTI2018

Development of an inertial confinement fusion platform to study charged particle-producing nuclear reactions relevant to nuclear astrophysics

This paper describes the development of a platform to study astrophysically relevant nuclear reactions using inertial-confinement fusion implosions on the OMEGA and NIF laser facilities, with a particular focus on optimizing the implosions to study charged-particle-producing reactions. Primary requirements on the platform are high yield, for high statistics in the fusion product measurements, combined with low areal density, to allow the charged fusion products to escape. This is optimally achieved with direct-drive exploding pusher implosions using thin-glass-shell capsules. Mitigation strategies to eliminate a possible target sheath potential which would accelerate the emitted ions are discussed. The potential impact of kinetic effects on the implosions is also considered. The platform is initially employed to study the complementary T(t,2n)??, T(3He,np)?? and 3He(3He,2p)?? reactions. Proof-of-principle results from the first experiments demonstrating the ability to accurately measure the energy and yields of charged particles are presented. Lessons learned from these experiments will be used in studies of other reactions. The goals are to explore thermonuclear reaction rates and fundamental nuclear physics in stellar-like plasma environments, and to push this new frontier of nuclear astrophysics into unique regimes not reachable through existing platforms, with thermal ion velocity distributions, plasma screening and low reactant energies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Thermodynamic modeling of countercurrent chemical looping reverse water gas shift process for redox material screening

The reverse water gas shift (RWGS) reaction is a key pathway for CO 2 utilization, particularly within Power-to-X process chains aimed at sustainable fuel and chemical production. Countercurrent chemical looping (CL-RWGS) using non-stoichiometric oxides can overcome equilibrium limitations of conventional RWGS reactors, enabling significantly higher CO 2 conversions. However, modeling the limiting performance of such systems is challenging due to their multiphase nature and coupled spatial and temporal variation in chemical composition. In this work, we present a discretized batch equilibrium model that simulates CL-RWGS reactors as a series of localized equilibrium exchanges between gas and solid elements. The model is numerically stable, computationally efficient, and free of kinetic source terms, making it well-suited for parametric studies and system-level integration. It is validated against established convection–diffusion models and shown to predict reasonable upper bounds on experimental results. Application of the model to a range of oxygen carrier materials identifies cerium–zirconium solid solutions, particularly Ce 0.80 Zr 0.20 O 2 , as a promising class offering superior oxygen storage characteristics compared to state-of-the-art La 0.6 Sr 0.4 FeO 3 . This framework provides a robust platform for materials screening, reactor sizing, and performance optimization in chemical looping systems. The model implementation is available as open-source software to support further research and development.

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

Coarse-Grained Simulations of Polyrotaxane Hydrogels under Quiescent and Shear Conditions

Cyclodextrin-based polyrotaxanes (PR) form hydrogels in water through cyclodextrin (CD) aggregation and crystallization. These networks can break under shear flows, making them versatile platforms for extrusion-based 3D printing. To optimize the material properties of 3D-printed PR gels, a microscopic understanding of the structural evolution during 3D printing is necessary. Here, we employ coarse-grained (CG) simulations to reveal the PR assembly process at the molecular level. Our simulations reproduce the experimental crystal morphologies of PR at varying concentrations and chain lengths under quiescent conditions. Using nonequilibrium simulations, we show shear flow ruptures crystalline domain connectivity in PR gels and stacks the lamellae in the gradient direction, allowing the materials to flow during 3D printing. After the cessation of flow, the anisotropic crystal alignment and absence of available dangling PR diminish the intercrystal connectivity. The printed materials are therefore mechanically weaker than the pristine hydrogels, in agreement with experimental results. Nonetheless, by relating the microscopic structural evolution with viscoelastic properties of PR gels and solutions, we elucidate how flow conditions and sample composition affect the 3D printing performance of PR hydrogels.

Smith, Cameron D. [Dartmouth College, Hanover, NH ↗
DOE OSTI2020

A Data Exchange Interface for a Standards Based Data Integration Platform

The modern electrical grid is a complex and a data rich system, requiring several sub-systems to provide the capability and support needed to perform functions such as distributed energy resource management, outage management, and fault location and isolation, to name a few. There is a need to develop software solutions and platforms that provide an integrated infrastructure to allow interoperability between these subsystems, while leveraging the abundant data available from today’s grid. In this paper, we present the development and deployment of an application service to integrate GridAPPS-D which is an open source, standards-based software platform with SurvalentONE, a commonly used DNP3 based ADMS platform that allows operation, monitoring, analysis, restoration, and optimization of network operations. We present details of the integration architecture, including its implementation, and provide results from functional testing of the architecture on a 13 bus IEEE system. The results validate that the integration is successful and is able to provide a two-way exchange of communication and translation between different communication protocols.

Singh, Alka↗
DOE OSTI2024

Enabling a Physical Twin for Control Methods Evaluation

Advanced nuclear reactors play an important role in the energy future of the United States and the rest of the world. They are designed and operated based on a different model than that of the current operating fleet, thus enabling deployment in remote locations and allowing for safe semi-autonomous or autonomous operations. Such characteristics require the development of a new reactor control paradigm. A significant factor in the development of control technologies and methods is integration of the various technologies and methods with each other and with hardware (both reactor system hardware and control hardware). A recent workshop on control of advanced reactors identified the lack of a flexible, expandable software/hardware infrastructure to enable such integration as a key gap. A previous phase of the current effort involved developing and demonstrating the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) platform, which is capable of integrating autonomous-control-enabling technologies and methods, without the constraints imposed by existing software solutions. This platform will enable advanced reactor developers to deploy and test any developed technologies and methods by employing a common framework, and to couple them with their own models and hardware. The present phase of this effort entails using the Microreactor Automated Control System (MACS) platform, which was developed by the U.S. Department of Energy (DOE) Microreactor Program, to serve as a control method testbed. MACS can be used by advanced reactor developers to integrate their control related research activities with any reactor system. For the present effort, MACS was customized to mirror Idaho National Laboratory (INL)’s Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and COMMAND was leveraged to enable MACS to emulate the physics of MARVEL, thus positioning MACS as a physical twin of MARVEL.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Intelligent Partitioning based Fully Parallel AC Security-Constrained Optimal Power Flow

Today’s power grid is becoming more diverse and integrated with high-level distributed energy resources and smart control technologies that is creating a new set of grid management challenges in terms of large-scale, nonlinear, and non-convex problem modeling, complex and time-consuming computation, as well as difficult uncertainty handling. This project focused on solving a challenging multi-period security-constrained generation scheduling problem, which is of great importance for maximizing the social welfare of real-time dispatch, day-ahead market, as well as weekly planning of power systems. Our developed software explored parallel optimization algorithms for complex and realistic power system models, and develop fast, efficient, and robust grid optimization solutions on the high-performance computing platform that will enable increased grid economics, flexibility, resilience, as well as energy security in the United States.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Quantum computing hardware for HEP algorithms and sensing

Quantum information science harnesses the principles of quantum mechanics to realize computational algorithms with complexities vastly intractable by current computer platforms. Typical applications range from quantum chemistry to optimization problems and also include simulations for high energy physics. The recent maturing of quantum hardware has triggered preliminary explorations by several institutions (including Fermilab) of quantum hardware capable of demonstrating quantum advantage in multiple domains, from quantum computing to communications, to sensing. The Superconducting Quantum Materials and Systems (SQMS) Center, led by Fermilab, is dedicated to providing breakthroughs in quantum computing and sensing, mediating quantum engineering and HEP based material science. The main goal of the Center is to deploy quantum systems with superior performance tailored to the algorithms used in high energy physics. In this Snowmass paper, we discuss the two most promising superconducting quantum architectures for HEP algorithms, i.e. three-level systems (qutrits) supported by transmon devices coupled to planar devices and multi-level systems (qudits with arbitrary N energy levels) supported by superconducting 3D cavities. For each architecture, we demonstrate exemplary HEP algorithms and identify the current challenges, ongoing work and future opportunities. Furthermore, we discuss the prospects and complexities of interconnecting the different architectures and individual computational nodes. Finally, we review several different strategies of error protection and correction and discuss their potential to improve the performance of the two architectures. This whitepaper seeks to reach out to the HEP community and drive progress in both HEP research and QIS hardware.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

A Cybersecurity Testbed for Smart Buildings

Smart buildings are equipped with a plethora of cyber-physical systems, such as Internet of Things (IoT) devices and building automation systems. These devices, especially in commercial buildings, use legacy communications and hardware that were not designed with cybersecurity in mind. With increasing cyber threats in recent years, smart buildings have become an increasing target for attacks, but not enough published data are available from these incidents to study or replicate the scenarios to defend buildings. As part of the U.S. Department of Energy-funded project focusing on developing the Building Intelligence with Layered Defense Using Security-Constrained Optimization and Security Risk Detection (BUILD-SOS) platform, we developed a cybersecurity test bed for smart buildings. This test bed includes a building simulation tool, virtual devices, emulated operational technology networks, and remote hardware-in-the-loop. Using this test bed, we performed different cyberattacks on the smart building model and collected both physical building data, to understand the impacts on the building, and network data, to aid in separating mechanical faults from cyberattacks during the detection. This test bed is a significant tool in protecting smart buildings from cyberattacks because it can aid in both cybersecurity analysis and the evaluation of other cyberattack detection tools by testing the tools in a secure environment without impacting the building operations.

cyber-physical systems↗
DOE OSTI2024

A Cybersecurity Testbed for Smart Buildings

Smart buildings are equipped with a plethora of cyber-physical systems, such as Internet of Things (IoT) devices and building automation systems. These devices, especially in commercial buildings, use legacy communications and hardware that were not designed with cybersecurity in mind. With increasing cyber threats in recent years, smart buildings have become an increasing target for attacks, but not enough published data are available from these incidents to study or replicate the scenarios to defend buildings. As part of the U.S. Department of Energy-funded project focusing on developing the Building Intelligence with Layered Defense Using Security-Constrained Optimization and Security Risk Detection (BUILD-SOS) platform, we developed a cybersecurity test bed for smart buildings. This test bed includes a building simulation tool, virtual devices, emulated operational technology networks, and remote hardware-in-the-loop. Using this test bed, we performed different cyberattacks on the smart building model and collected both physical building data, to understand the impacts on the building, and network data, to aid in separating mechanical faults from cyberattacks during the detection. This test bed is a significant tool in protecting smart buildings from cyberattacks because they can aid in both cybersecurity analysis and the evaluation of cyberattack detection tools by testing the tools in a secure environment without impacting the building operations.

alfalfa↗