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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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DOE OSTI2022

Rolling Optimization of Transmission Network Recovery and Load Restoration Considering Hybrid Wind-Storage System and Cold Load Pickup

A common solution to deal with the stochasticity introduced by fast-ramping wind power integration is to equip wind farms (WFs) with energy storage systems (ESSs) to formulate hybrid WF-ESSs. In addition to leveling off wind power fluctuations during normal operations, a hybrid WF-ESS can be a flexible power source to accumulate the power system restoration. In this paper, we propose a rolling optimization model for transmission network recovery and load restoration considering the contributions of WF-ESSs. The proposed model is formulated as a mixed integer linear programming problem that simultaneously optimizes the amount and location of restorable load blocks as well as the restoration lines. The cold load pickup features of interrupted loads considering the outage duration are modeled in detail. A chance-constrained method is employed to deal with the uncertainty of wind power, and a rolling horizon-based framework is adopted to reduce the influence of forecast error. Case studies are conducted on both New England 39-bus system and part of a provincial power system in China. The results show that the load restoration process can be significantly accelerated by employing the proposed method and contributions of hybrid WF-ESSs to power system restoration are validated.

chance-constrained optimization↗

DOE OSTI2025

Parallel Programming in MCNP6

Monte Carlo N-Particle (MCNP)1 is a general-purpose Monte Carlo particle transport code developed by Los Alamos National Laboratory (LANL). To efficiently handle long simulations, MCNP version 6 (MCNP6) supports parallel execution using two primary programming models: • Shared-memory task-based threading using OpenMP (Open Multi-Processing), and • Distributed-memory calculations using MPI (Message Passing Interface). The OpenMP and MPI programming models enable MCNP6 to scale from desktop systems to high-performance computing (HPC) clusters, allowing users to run MCNP in one of three parallel modes: • OpenMP-only, • MPI-only, and • Hybrid (MPI + OpenMP). The choice of parallelization mode depends on the underlying computer architecture and the characteristics of the simulation problem.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

42 ENGINEERING↗

DOE OSTI2020

Programmed Wrapping and Assembly of Droplets with Mesoscale Polymers

Not provided.

Chemistry↗

DOE OSTI2023

Wind RD&T: On Site Wind for Rural Load Centers

This presentation will provide an overview of the "On Site Wind for Rural Load Center" project for an FY23 research, development, and technology review with other Wind Energy Technologies Office researchers and DOE program managers. This copy of slides is appropriate for public release.

17 WIND ENERGY↗

DOE OSTI2022

Q-POP-Thermo: A general-purpose thermodynamics solver for ferroelectric materials

We report that Q-POP-Thermo is a program designed to compute thermodynamic monodomain equilibrium states and their properties for ferroelectric single crystals and thin films based on the Landau-Ginzburg-Devonshire (LGD) Theory. Utilizing symbolic manipulation with the SymPy Library, the governing equations along with appropriate boundary conditions are solved for speedy minimization of the free energy of a crystal. Utilizing the popular Differential Evolution algorithm, with appropriate hybridization, multiple phase diagrams, such as the pressure-temperature phase diagram for bulk single crystals and the common strain-temperature phase diagram for monodomain thin-film systems can be readily generated. Furthermore, a variety of material properties of stable ferroelectric phases, including dielectric, piezoelectric, and electrocaloric properties, can simultaneously be calculated. Validation studies are presented for both thin-film and single crystal systems to test the effectiveness and capability of the open-source program.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Flexible Perovskite-Perovskite PV for Mobile Power Applications (Final Technical Report)

14 SOLAR ENERGY↗

DOE OSTI2024

Business Opportunities in Clean Energy Supply Chains: Guidebook for Small and Medium-Sized Automotive Suppliers

This is the final report for the referenced TCF award which ran from Oct. 2019 through Jan. 2024 in conjunction with the industry partner Swift Solar. The long duration of the program was due to several factors including the pandemic and a technical work stoppage due to changes in the scope. Additionally, Swift’s business focus shifted during the course of the program. As a result of these factors, this program underwent two distinct modifications that dramatically changed the work scope. The following report is organized into three separate sections, each of which addresses a distinct work scope. Those scope changes, what necessitated them, and any new tasks/milestones are given, briefly, at the top of each section. The work performed was research on the hybrid halide perovskites (HHP), both the absorber material itself as well as other material layers that are required in a full device stack. At the start of the period of performance, there were two distinct challenges that we sought to address: (1) a wide band gap absorber (>1.6 eV), and (2) a recombination layer for tandem devices that provided good sequestration of the individual cell absorber materials in their respective device layers. NREL had previously published, and patented, advancements in both of these areas and they were the focus of much of the work throughout the program. The auto manufacturing space is evolving quickly. Sales of various electrified vehicles (xEVs) continue to grow steadily, which has medium to long-term ramifications for the thousands of U.S. manufacturers and hundreds of thousands of workers that contribute to the domestic automotive supply chain. In tandem with this growth in xEV sales, domestic clean energy manufacturing is surging (both for the xEV supply chain and other technologies), with public incentives spurring billions in private sector investment. Moreover, the next 2–3 years will see new and expanded industrial facilities come online to make products like hydrogen electrolyzers, solar panels, batteries, advanced electronics—and will create new supply chain needs and business opportunities as they do. DOE’s Office of Manufacturing and Energy Supply Chains (MESC) and Argonne National Laboratory developed this report to help automotive manufacturers—alongside various business support partners— understand these trends and their response options, and to make the most of current federal assistance programs for manufacturers. These market changes may create opportunities for small- and medium-sized manufacturers (SMMs) to expand production, grow profit margins, and diversify their businesses. For instance, SMMs could take advantage of engineering and process design similarities with new end-use industries that might enable greater business growth and stability as markets continue to change.

14 SOLAR ENERGY↗

DOE OSTI2020

Engineering Biomolecular Self–Assembly at Solid–Liquid Interfaces

Biomolecular self–assembly is a key process used by life to build functional materials from the “bottom up.” In the last few decades, bioengineering and bionanotechnology have borrowed this strategy to design and synthesize numerous biomolecular and hybrid materials with diverse architectures and properties. However, engineering biomolecular self–assembly at solid–liquid interfaces into predesigned architectures lags the progress made in bulk solution both in practice and theory. Here, recent achievements in programming self–assembly of peptides, proteins, and peptoids at solid–liquid interfaces are summarized and corresponding applications are described. Recent advances in the physical understandings of self–assembly pathways obtained using in situ atomic force microscopy are also discussed. Furthermore, these advances will lead to novel strategies for designing biomaterials organized at and interfaced with inorganic surfaces.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Programming Function via Soft Materials (PFvSM) (Final Report)

The PFvSM cluster at the University of Illinois greatly deepened the science of soft materials and expanded the means for embedding within them unprecedented functionalities. We pioneered a mesoscopic approach to materials design that combined leading competencies in fundamental experimental and theoretical soft matter science and fabrication that powerfully establishes equilibrium and nonequilibrium assembly of novel and complex building blocks as a preeminent contributor to progress in materials chemistry. Our cluster’s vision was an integrated program of work centered on soft matter science with the ultimate goal of impacting important energy technologies. As elementary units we employed function-encoded colloids, nanoparticles, large mesh fibrillar gels, deterministically fabricated networks and hybrid objects. These materials were employed as building blocks for diverse model systems that allowed fundamental soft matter principles of wide relevance to be established. Their assembly into materials with useful functional behavior provided new approaches to challenging problems in basic energy science including energy harvesting, transport and storage. To achieve these goals the cluster brought together a team of recognized world-leaders in materials synthesis and processing, in-situ characterization, theory and modeling, and materials design, integration and fabrication

36 MATERIALS SCIENCE↗

DOE OSTI2022

Corrosion-Resistant Coatings on Spent Nuclear Fuel Canisters to Mitigate and Repair Potential Stress Corrosion Cracking (FY22 Status)

This report summarizes the activities performed by Sandia National Laboratories in FY22 to identify and test coating materials for the prevention, mitigation, and/or repair of potential chloride-induced stress corrosion cracking in spent nuclear fuel dry storage canisters. This work continues efforts by Sandia National Laboratories that are summarized in previous reports in FY20 and FY21 on the same topic. The previous work detailed the specific coating properties desired for application and implementation to spent nuclear fuel canisters (FY20) and identified several potential coatings for evaluation (FY21). In FY22, Sandia National Laboratories, in collaboration with four industry partners through a Memorandum of Understanding, started evaluating the physical, mechanical, and corrosion-resistance properties of 6 different coating systems (11 total coating variants) to develop a baseline understanding of the viability of each coating type for use to prevent, mitigate, and/or repair potential stress corrosion on cracking on spent nuclear fuel canisters. This collaborative R&D program leverages the analytical and laboratory capabilities at Sandia National Laboratories and the material design and synthesis capabilities of the industry collaborators. The coating systems include organic (polyetherketoneketone, modified polyimide/polyurea, modified phenolic resin), organic/inorganic ceramic hybrids (silane-based polyurethane hybrid and a quasi-ceramic sol-gel polyurethane hybrid), and hybrid systems in conjuncture with a Zn-rich primer. These coatings were applied to stainless steel coupons (the same coupons were supplied to all vendors by SNL for direct comparison) and have undergone several physical, mechanical, and electrochemical tests. The results and implications of these tests are summarized in this report. These analyses will be used to identify the most effective coatings for potential use on spent nuclear fuel dry storage canisters, and also to identify specific needs for further optimization of coating technologies for their application on spent nuclear fuel canisters. In FY22, Sandia National Laboratories performed baseline testing and atmospheric exposure tests of the coating samples supplied by the vendors in accordance with the scope of work defined in the Memorandum of Understanding. In FY23, Sandia National Laboratories will continue evaluating coating performance with a focus on thermal and radiolytic stability.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Supporting Electric Vehicle Supply Equipment Deployment

The U.S. Department of Energy (DOE) Federal Energy Management Program (FEMP) helps federal agencies electrify their fleets and support the deployment of charging infrastructure. To assist agencies with the transition to zero-emission vehicles (ZEVs), including battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), FEMP offers technical guidance on electric vehicle supply equipment (EVSE) installations and site-specific planning through on-site and virtual EVSE Tiger Teams.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2019

Development of a Control Platform for a Building-Scale Hybrid Solar PV-Natural Gas Microgrid

Building-scale microgrids are a type of behind-the-meter microgrids where the building operator has control of the distributed energy resources, including, in this case, a natural gas-fired microturbine in addition to solar PV and battery energy storage systems. There is a growing trend in deploying behind-the-meter microgrids due to their benefits including the resiliency of serving critical loads, especially in regions with abundant natural gas. In order to ensure distributed energy resources are dispatched optimally for the desired mode of operation, a hierarchical control platform including a centralized controller was developed and installed. The platform includes communication and control infrastructure that interface with controllers for distributed energy resources and the building automation system of a recently built energy efficient commercial building. Based on desirable outcomes under different grid and building conditions, operational modes were defined for the microgrid controller. The controller is programmed to map each mode to respective operational modes for distributed energy resources controllers. Experimental data for test runs corresponding to two operational modes confirm the communication and control infrastructure can execute hierarchical control commands. Finally, dispatch optimization for a year-long simulation of system operation is presented and the benefits of the hybrid solar PV-natural gas setup are evaluated.

Energy & Fuels↗

DOE OSTI2022

Model Predictive Control of Discrete-Continuous Energy Systems via Generalized Disjunctive Programming

Generalized Disjunctive Programming (GDP) provides an alternative framework to model optimization problems with both discrete and continuous variables. The key idea behind GDP involves the use of logical disjunctions to represent discrete decisions in the continuous space, and logical propositions to denote algebraic constraints in the discrete space. Compared to traditional mixed-integer programming (MIP), the inherent logic structure in GDP yields tighter relaxations that are exploited by global branch and bound algorithms to improve solution quality. In this paper, we present a general GDP model for optimal control of hybrid systems that exhibit both discrete and continuous dynamics. Specifically, we use GDP to formulate a model predictive control (MPC) model for piecewise-affine systems with implicit switching logic. As an example, the GDP-based MPC approach is used as a supervisory control to improve energy efficiency in residential buildings with binary on/off, relay-based thermostats. A simulation study is used to demonstrate the validity of the proposed approach, and the improved solution quality compared to existing MIPbased control approaches.

Bhattacharya, Arnab↗

DOE OSTI2020

Terry Turbopump Expanded Operating Band Modeling and Simulation Efforts in Fiscal Year 2020 - Progress Report

The Terry Turbine Expanded Operating Band Project is currently conducting testing at Texas A&M University as part of a revised experimental program meant to supplant previous full-scale testing plans under the headings of Milestone 5 and Milestone 6. In consultation with Sandia National Laboratories technical staff and with modeling and simulation support from the same, the hybrid Milestone 5&6 plan is moving forward with experiments aimed at addressing knowledge gaps regarding scale, working fluid, and turbopump self-regulation. Modeling and simulation efforts at Sandia National Laboratories in FY20 fell under the broad umbrella of Milestone 7 and consisted exclusively of MELCOR-related tasks aimed at: 1) Constructing/improving input models of Texas A&M University experiments, 2) Constructing a generic boiling water reactor input model according to best practices with systems-level Teny turbine capabilities, and 3) Adding code capability in order to leverage experimental data/findings, address bugs, and improve general code robustness Project impacts of the Covid-19 pandemic have fortunately been minimal thus far but are mentioned as necessary when discussing the hybrid Milestone 5&6 progress as well as the corresponding Milestone 7 modeling and simulation progress.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Final Technical Report

The capture of CO2 and its simultaneously conversion to useful chemical fuels driven by solar energy represents one of the best solutions to resolve our growing energy and environmental concerns. The most critical challenge to this endeavor is the rational design of a photocatalytic architecture that can effectively couple a given photosensitizer (PS) with an appropriate catalyst, thereby enabling efficient photosensitization of a multi-electron reduction catalysis. This research program aims to address this challenge using an interdisciplinary approach that combines innovative material design and synthesis, fundamental mechanistic studies, and photocatalytic performance evaluation. The strategies include 1) constructing and investigating a novel class of 2D COF hybrid photocatalysts with an effective photoactive organic building block as PS and a precisely incorporated CO2 reduction molecular catalyst (MC); and 2) mechanistic origins of CO2 photoreduction using a set of complementary time-resolved and in situ spectroscopic techniques. The novelty of the proposed hybrid system lies in the unprecedented combination of the unique advantage of porous crystalline COF PS with the precise catalytic function of MC for photocatalytic CO2 reduction. In the periods of the support (09/01/2019-12/31/2022), we have made research progress in four projects: 1) Exploring 2D COFs with incorporated Mn complex for light driven CO2 reduction; 2) The dependence of excited state and charge transfer dynamics on monomer structure of 2D COFs; and 3) Control over Charge Separation by Imine Structural Isomerization in Covalent Organic Frameworks with Implications on CO2 Photoreduction; and 4) The impact of monomer structure on the photoluminescence properties of COFs. We found that both monomer structure and linker chemistry can effectively impact the excited state dynamics, charge transfer properties, and photoluminescence quantum yields, the important properties that dictate their applications in photocatalysis. In addition, we found that the direction of imine linker determines charge transfer direction and thus controls the types of catalytic reactions (e.g. water oxidation or CO2 reduction reactions). The result from these fundamental studies provides important information for correlating the structure of the COF photocatalysts with their photophysical properties and catalytic functions, paving the way for their novel application in photocatalysis. We expect that our findings will contribute to addressing current shortcomings of semiconductor- and molecular-based photocatalytic systems that suffer from inefficient light harvesting and charge separation and poor adsorption and activation of reactants. In turn, this research will contribute towards the development of novel photocatalytic systems for CO2 reduction to generate renewable chemical fuels and simultaneously address the problem of mitigating climate change due to CO2 accumulation. In addition, the experimental approaches employed in this research can be easily transferred to other energy technologies and are expected to broadly impact fields involving photocatalysis, optoelectronic devices, and solar energy conversion. The proposed research has also been integrated with educational activities and serve as a basis to raise awareness around the critical issues of global energy production and consumption, and to develop the next generation of solar energy scientists.

14 SOLAR ENERGY↗

DOE OSTI2022

Real Time Predictive and Adaptive Hybrid Powertrain Control Development via Neuroevolution

The real-time application of powertrain-based predictive energy management (PrEM) brings the prospect of additional energy savings for hybrid powertrains. Torque split optimal control methodologies have been a focus in the automotive industry and academia for many years. Their real-time application in modern vehicles is, however, still lagging behind. While conventional exact and non-exact optimal control techniques such as Dynamic Programming and Model Predictive Control have been demonstrated, they suffer from the curse of dimensionality and quickly display limitations with high system complexity and highly stochastic environment operation. This paper demonstrates that Neuroevolution associated drive cycle classification algorithms can infer optimal control strategies for any system complexity and environment, hence streamlining and speeding up the control development process. Neuroevolution also circumvents the integration of low fidelity online plant models, further avoiding prohibitive embedded computing requirements and fidelity loss. This brings the prospect of optimal control to complex multi-physics system applications. The methodology presented here covers the development of the drive cycles used to train and validate the neurocontrollers and classifiers, as well as the application of the Neuroevolution process.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Modular Hybrid Solid State Transformer (H-SST) for Next Generation Flexible and Adaptable Large Power Transformer (LPT) (Final Technical Report)

A 500 kVA HSST, the world first of such system, has been successfully developed. The HSST has the capability to regulate the power flow of the transmission or distribution power lines, or provide voltage regulation. The HSST design is modular therefore it has the ability to be connected in series of parallel to form a large power transformer with smart controllability. The project has enabled a high TRL level prototype be demonstrated at University of Texas at Austin which can lead to additional commercialization and demonstration opportunities. A large number of students were trained under this program that will benefit the power grid industry. A number of publications are published at well known international conferences and journals, further accomplish the mission of knowledge development and dissemination.

24 POWER TRANSMISSION AND DISTRIBUTION↗