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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Test methodology for validation of multi-frequency models of renewable energy generators using small-signal perturbations

Providing trustworthy and accurate multi-frequency (or harmonic) models for renewable energy generators (REG) is an ongoing challenge for harmonic studies. There have been effective attempts to propose and design a test device to validate the harmonic models, mainly based on shunt current perturbations. However, using additional devices for perturbations is costly for converter-based test sites. This paper provides the test specifications to extend the application of the grid emulators for voltage perturbations and appropriate harmonic model validation. Besides, the effects of the sequence couplings, initial emissions, and power set-points on the test results have been overlooked in the literature. Considering these effects, this paper proposes a generic test methodology to obtain more accurate models in the sequence domain. The experimental verification of the proposed methodology is demonstrated using a 7 MVA grid emulator for testing of a 2 MVA photo-voltaic converter and a 2 MVA Type 3 wind turbine. This way, the test challenges, specifications, and recommendations are presented using the MW-scale experiments on different REGs. Furthermore, the effects of sequence couplings and initial emissions on the calculation results are investigated and compared. The proposed methodology is applicable for harmonic model validation as well as empirical modelling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Hydropower Black Start: A Guidebook for Retrofitting Grid Dependent Hydropower

Not all United States (US) hydropower plants were designed to provide black start, but they are increasingly needed to uphold resilience in the evolving electric grid. This guidance is designed to help understand the minimal retrofits required for grid dependent hydropower (GDH) plants behind the point of interconnection (POI). For distribution connected hydropower plants or those with dedicated cranking paths, such upgrades can be sufficient for the plant to provide black start. For others, more coordination with the transmission system operator will be needed. This guidebook answers a number of questions relevant to retrofitting hydropower plants with black start capabilities. For example, the guidebook answers: • How flexible do the wicket gate controls need to be? • Who needs to do hydro governor model validation, why, and how? • How robust and flexible do the excitation and AVR controls need to be? • What protection settings need to be adjusted? • What relay(s) will need to be bypassed or overridden and at what risk? • What is the electrical energy demand of the station load or auxiliary power systems? • What should the strategy to energize transformer(s) along cranking path to address inrush currents be? • How should the critical load restoration be sequenced? In addition to outlining the specifications that hydropower plants need to meet for each component to be able to perform black start, this guidebook provides a set of case studies for specific upgrades needed at actual plants. Between the case studies of plants that have already performed black start retrofits and the examples of how this guidebook can be applied to scope future retrofits, five key themes have been identified for retrofit needs. 1. Protection needs “black start” mode: hydropower plants that are not designed with black start capabilities will have protections that prevent them from interconnecting to a “dead bus.” These protections will need to be overridden in every retrofit case and a separate black start mode should be established so that operators can safely switch between black start and grid connected modes, minimizing the risk to the plant. 2. Wicket gates need modern controls: digital governors accelerate the parameter tuning process and gate position sensors improve controllability, so plants with mechanical governors should be upgraded. Furthermore, a black start and islanding mode should be established for controls to maximize plant performance. 3. Robust excitation support: the DC system or excitation generator needs to be reliable enough to form and sustain the rotor electromagnetic field. These systems are typically undersized in plants that were not designed for black start, so they will need to be upgraded. 4. Turbine-governor model validation and operator training: validation of a standard hydro governor model is needed to characterize the dynamic response (i.e., inertial and primary frequency response) of the GDH. This is required for control development and old hydropower plants often have outdated or incorrect models. Operator training is also typically required to ensure the hardware retrofits are utilized correctly during the black start process. 5. Transformer and cranking path energization: any upgradation and control adjustment in front of the POI will depend upon the existing interconnection. Coordination with the transmission or distribution operator may be required.

13 HYDRO ENERGY↗
DOE OSTI2021

Hoobas: A highly object-oriented builder for molecular dynamics

Polydispersity and random sequences are ubiquitous features of polymers, and molecular dynamics simulations can help elucidate the impact of disorder in polymer systems. However, currently available packages for building polymer topologies do not enable the user to include randomness in a straightforward fashion. Here, we introduce Hoobas, a molecular builder package that easily handles polydispersity using a prototype-builder design pattern. This enables fast and easy building of systems comprised of thousands of distinct objects. It is written in the Python programming language, which ensures compatibility with a wide range of molecular dynamics packages and tools, as well as easy integration into most workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

GrainNN: A neighbor-aware long short-term memory network for predicting microstructure evolution during polycrystalline grain formation

High fidelity simulations of grain formation in alloys are an indispensable tool for process-to-mechanical-properties characterization. Such simulations, however, can be computationally expensive as they require fine spatial and temporal discretizations. Their cost becomes an obstacle to parametric studies and ensemble runs and ultimately makes downstream tasks like optimal control and uncertainty quantification challenging. To enable such downstream tasks, we introduce GrainNN, an efficient and accurate reduced-order model for epitaxial grain growth in additive manufacturing conditions. GrainNN is a sequence-to-sequence long-short-term-memory (LSTM) deep neural network that evolves the dynamics of manually crafted features. Its innovations are (1) an attention mechanism with grain-microstructure-specific transformer architecture; and (2) an overlapping combination of several clones of the network to generalize to grain configurations that are different from those used for training. This design enables GrainNN to predict grain formation for unseen physical parameters, grain number, domain size and geometry. Furthermore, GrainNN not only reconstructs the quantities of interest but also can be pointwise accurate. In our numerical experiments, we use a polycrystalline phase field method to both generate the training data and assess GrainNN. For multiparametric, ensemble simulations with many grains, GrainNN can be orders of magnitude faster than phase field simulations, while delivering 5%–15% pointwise error. Additionally, this speedup includes the cost of the phase field simulations for generating training data.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Multi-scale model based design of membrane reactor/separator processes for intensified hydrogen production through the water gas shift reaction

This paper aims to first quantify the impact of various diffusion models (Maxwell-Stefan, Wilke, Dusty-Gas) on the predictions of a multi-scale membrane reactor/separator mathematical model, and to then demonstrate this model's use for the design and process intensification of membrane reactor/separator systems for hydrogen production. This multi-scale model captures velocity, temperature and species' concentration profiles along the catalyst pellet's radial direction, and along the reactor's axial direction, by solving the momentum, energy, and species transport equations, accounting for convection, conduction, reaction, and diffusion mechanisms. In the first part of work, the effect of pellet-scale design parameters (mean pore diameter, volumetric porosity, tortuosity factor, etc.) and various species' flux models on the model predictions is studied. In the second part, the study focuses on the comparison, in terms of their process intensification characteristics, of various hydrogen production processes. These include a conventional high-temperature shift reactor (HTSR)/low-temperature shift reactor (LTSR) sequence, a novel HTSR/membrane separator (MS)/LTSR/MS sequence, and a process that involves low-temperature shift membrane reactors-LTSMR in a series.

08 HYDROGEN↗
DOE OSTI2020

Phase evolution and amorphous stability upon solid-state reaction in superlattice like Ge–Sb–Te combinatorial thin-film

In this paper, the superlattice-like (SLL) Ge–Sb–Te combinatorial thin films were prepared by using a high-throughput ion beam sputtering system. The phase evolution and amorphous stability of such films undergoing heat treatment as a function of the coating sequence and modulation period were systematically studied. The composition structure diagram was constructed via an automated process of data obtained by high-throughput synchrotron micro-X-ray diffraction and lab-based micro-X-ray fluorescence. Furthermore, the element distribution and microstructure in the depth direction of the SLL thin films were characterized with time-of-flight secondary ion mass spectrometry and transmission electron microscopy, respectively. These studies demonstrated that the coating sequence has a significant effect on the element distribution in the as-deposited SLL thin films and the structure of the final product upon solid-state reaction. Reducing the modulation period of the SLL thin film improves the stability of the amorphous Ge–Sb–Te phase. This work lays a solid foundation for the rational design of SLL Ge–Sb–Te thin films to improve their performance.

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

Human antibodies to SARS-CoV-2 with a recurring YYDRxG motif retain binding and neutralization to variants of concern including Omicron

Studying the antibody response to SARS-CoV-2 informs on how the human immune system can respond to antigenic variants as well as other SARS-related viruses. Here, we structurally identified a YYDRxG motif encoded by IGHD3-22 in CDR H3 that facilitates antibody targeting to a functionally conserved epitope on the SARS-CoV-2 receptor binding domain. A computational search for a YYDRxG pattern in publicly available sequences uncovered 100 such antibodies, many of which can neutralize SARS-CoV-2 variants and SARS-CoV. Thus, the YYDRxG motif represents a common convergent solution for the human humoral immune system to target sarbecoviruses including the Omicron variant. These findings suggest an epitope-targeting strategy to identify potent and broadly neutralizing antibodies for design of pan-sarbecovirus vaccines and antibody therapeutics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Perturbation-Based Diagnosis of False Data Injection Attack Using Distributed Energy Resources

Modern smart grid relies on various sensor measurements for its operational control. In a successful false data injection attack, the attacker manipulates the measurements from the grid sensors such that undetected errors are introduced into the estimates of the system parameters leading to catastrophic situations. This paper proposes a novel perturbation based false data injection attack detection mechanism that utilizes inverter based distributed energy resources (DERs) to create low magnitude perturbation signal in the distribution system voltage that is inconsequential to the normal grid operation. Two voltage sensitivity analysis based algorithms are designed to identify the optimal set of DERs that can create the voltage perturbation signal of desired magnitude. An analytical method of voltage sensitivity analysis is used to compute the magnitude of voltage perturbation signal at each node in a computationally efficient manner. Then, a detection mechanism is developed that checks for the presence of the perturbation sequence in each sensor measurement. A sensor measurement is deemed authentic if the voltage perturbation signal is present in the data. In case of sensor malfunction or cyber-attack, the perturbation signal will not be present in the measurement data. Performance of the proposed attack detection mechanism is validated via simulation of the IEEE 69 bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Dysfunctionality Hazard Curve: Risk-Based Tool to Support the Resilient Design of Systems Subjected to Multihazards

While resilience metrics have been proposed and studied given a functionality recovery curve, they have not emphasized enough on accounting for the uncertainties in the multihazard occurrences and intensities. Moreover, these resilience metrics are not risk-based (i.e., they do not express the system's resilience loss as a frequency of exceedance), leading to inconsistencies in system performance description when compared to performance-based engineering frameworks. A risk-based tool termed dysfunctionality hazard curve is proposed to assess the resilience of systems subjected to single hazards or multihazards with inter-event dependencies. Dysfunctionality hazard curve expresses system resilience performance as frequency of exceedance of time to full functionality. In doing so, it characterizes system recovery as a sequence of repair activities and also considers the uncertainties in the multihazard occurrences and intensities. Dysfunctionality hazard curve is demonstrated for a residential building susceptible to earthquake and hurricane hazards. Results indicate that Dysfunctionality hazard curve for earthquakes is greater than that for hurricane winds under single hazards. Under multihazards, considering inter-event dependencies during system recovery leads to larger dysfunctionality hazard curve than ignoring them. Finally, the concept of dysfunctionality hazard curve is also extended to a system-of-systems consisting of residential and commercial buildings.

42 ENGINEERING↗
DOE OSTI2023

Up up down down left right left right B A Start for the catalytic hackers of programmable materials

Catalysts have advanced over the last century to accelerate and control reactions based on static active sites. More effective catalysis can be achieved using catalysts that change with time over the course of a reaction, providing a dynamic free energy landscape that is tailored to each step in the reaction sequence. Here, the catalyst is modulated via an input program that directs the surface to change physically or electronically with time, providing information regarding the extent and duration of change optimized for specific combinations of chemistry and programmable catalyst surfaces. While in its infancy, programmable catalysis is advancing with parallel efforts to establish fundamental principles of dynamic catalysts, design of programmable materials, and strategies to design input programs that will control catalysis for faster and more selective reactions.

catalyst↗
DOE OSTI2021

A theoretical approach for transient shock strengthening in high-energy-density laser compression experiments

In high-energy-density shock compression experiments, the desired state of compression is typically achieved by passing shock waves through a sequence of different materials. Here, a theoretical approach for transiently strengthening such shocks passing through interfaces of experimentally relevant impedance ratios is examined. A semi-analytical method based on characteristics analysis is used to solve the problem of a shock passing from one material to another through an intermediate region of non-uniform impedance; by appropriately designing this region, a greater shock strength can be achieved in the second material for a finite duration than in the absence of this region. When a shock passes into a material of higher impedance, the shock strengthening increases to a maximum before decreasing to an asymptotic value as the strength of the incident shock is increased. For shocks passing into materials of decreasing impedance, the shock strengthening increases monotonically as the strength of the incident shock is increased when the impedance ratio is above a critical threshold. Incorporating multiple intermediate materials can further increase the strength of the transmitted shock, with an exponential discretization of intermediate material impedances being the most effective distribution for strengthening strong shocks. The results suggest that up to 25% and 9% increases in pressure behind the leading shock can be achieved for materials of increasing and decreasing impedance, respectively. The technique is applied to the design of laser-driven dynamic compression experiments, and the results of the analysis are verified via comparison to simulations performed with the HYADES hydrodynamics code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Single-component multilayered self-assembling nanoparticles presenting rationally designed glycoprotein trimers as Ebola virus vaccines

Ebola virus (EBOV) glycoprotein (GP) can be recognized by neutralizing antibodies (NAbs) and is the main target for vaccine design. Here, we first investigate the contribution of the stalk and heptad repeat 1-C (HR1 C ) regions to GP metastability. Specific stalk and HR1 C modifications in a mucin-deleted form (GPΔmuc) increase trimer yield, whereas alterations of HR1 C exert a more complex effect on thermostability. Crystal structures are determined to validate two rationally designed GPΔmuc trimers in their unliganded state. We then display a modified GPΔmuc trimer on reengineered protein nanoparticles that encapsulate a layer of locking domains (LD) and a cluster of helper T-cell epitopes. In mice and rabbits, GP trimers and nanoparticles elicit cross-ebolavirus NAbs, as well as non-NAbs that enhance pseudovirus infection. Repertoire sequencing reveals quantitative profiles of vaccine-induced B-cell responses. This study demonstrates a promising vaccine strategy for filoviruses, such as EBOV, based on GP stabilization and nanoparticle display.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

A new crab of the genus Nanoplax from the Gulf of Mexico, and assignment of Micropanope pusilla to a new genus (Crustacea, Brachyura, Pseudorhombilidae)

Nanoplax thomai n. sp. is described from the Gulf of Mexico, representing the second species of the genus. The description is based upon a number of specimens previously misidentified as Micropanope truncatifrons Rathbun, 1898, including one so represented in recent molecular phylogenetic analyses. As restricted, Micropanope truncatifrons remains known with certainty from only the limited type series, which does not include a mature male, and sequence quality tissues are not available for molecular phylogenetic analyses. Its generic placement remains questionable following morphological study of its type materials and comparisons to specimens representing other present and former members of Micropanope Stimpson, 1871. Those comparisons underscore that morphological and molecular distinctions warrant assignment of Micropanope pusilla A. Milne-Edwards, 1880 to a new genus, herein designated as Pseudopanopeus n. gen.

Zoology↗
DOE OSTI2020

Learning reference governor for cycle-to-cycle combustion control with misfire avoidance in spark-ignition engines at high exhaust gas recirculation–diluted conditions

Cycle-to-cycle feedback control is employed to achieve optimal combustion phasing while maintaining high levels of exhaust gas recirculation by adjusting the spark advance and the exhaust gas recirculation valve position. The control development is based on a control-oriented model that captures the effects of throttle position, exhaust gas recirculation valve position, and spark timing on the combustion phasing. Under the assumption that in-cylinder pressure information is available, an adaptive extended Kalman filter approach is used to estimate the exhaust gas recirculation rate into the intake manifold based on combustion phasing measurements. The estimation algorithm is adaptive since the cycle-to-cycle combustion variability (output covariance) is not known a priori and changes with operating conditions. A linear quadratic regulator controller is designed to maintain optimal combustion phasing while maximizing exhaust gas recirculation levels during load transients coming from throttle tip-in and tip-out commands from the driver. During throttle tip-outs, however, a combination of a high exhaust gas recirculation rate and an overly advanced spark, product of the dynamic response of the system, generates a sequence of misfire events. In this work, an explicit reference governor is used as an add-on scheme to the closed-loop system in order to avoid the violation of the misfire limit. The reference governor is enhanced with model-free learning which enables it to avoid misfires after a learning phase. Experimental results are reported which illustrate the potential of the proposed control strategy for achieving an optimal combustion process during highly diluted conditions for improving fuel efficiency.

42 ENGINEERING↗
DOE OSTI2025

Decayheatml

This code is designed to predict and analyze the decay heat generated in molten salt reactors (MSRs) using a hybrid approach that combines machine learning and segmented polynomial fitting. The accurate prediction of decay heat is essential for reactor safety and the optimization of spent fuel storage. The code operates through several key components: 1) Data Architecture: It incorporates a modular data architecture that handles various MSR-specific operational parameters such as power density, humidity content, and air ingress. These parameters are sampled using Sobol sequences to ensure comprehensive coverage of operational uncertainties. 2) Machine Learning Framework: The code employs a diverse set of machine learning models, including polynomial regression, decision trees, random forests, gradient boosting, support vector regression, k-nearest neighbors, multi-layer perceptrons, and symbolic regression. These models are trained to predict decay heat over a wide temporal range, from immediate shutdown up to 10,000 years. 3) Region-Optimized Training: The temporal domain is divided into multiple regions, each modeled separately to capture distinct decay heat characteristics across different time scales. This approach significantly improves the accuracy and interpretability of predictions. 4) Segmented Polynomial Interpretation (SPI): The SPI method translates machine learning predictions into piecewise polynomial equations. These equations are physically interpretable and can be directly integrated into existing engineering workflows and safety analyses. 5) Front-End Interfaces: The code includes both a Jupyter notebook interface for research development and a Streamlit web application for operational deployment. These interfaces allow users to interactively explore decay heat predictions, adjust operational parameters, and visualize results in real-time. 6) Applications: The framework supports various applications, including safety system validation and spent fuel container optimization. It enables real-time evaluation of worst-case decay heat scenarios, informing the design of passive safety systems and optimizing container designs for long-term storage. Overall, this code provides a robust, accurate, and user-friendly tool for predicting decay heat in MSRs, enhancing reactor safety, and optimizing spent fuel management.

Retamales, Mauricio Eduardo Tano [Idaho National L↗
DOE OSTI2024

Design and Characterization of a Transcriptional Repression Toolkit for Plants

Regulation of gene expression is essential for all life. Tools to manipulate the gene expression level have therefore proven to be very valuable in efforts to engineer biological systems. However, there are few well-characterized genetic parts that reduce gene expression in plants, commonly known as transcriptional repressors. We characterized the repression activity of a library consisting of repression motifs from approximately 25% of the members of the largest known family of repressors. Combining sequence information with our trans-regulatory function data, we next generated a library of synthetic transcriptional repression motifs with function predicted in advance. After characterizing our synthetic library, we demonstrated not only that many of our synthetic constructs were functional as repressors but also that our advance predictions of repression strength were better than random guesses. Finally, we assessed the functionality of known transcriptional repression motifs from a wide range of eukaryotes. Our study represents the largest plant repressor motif library experimentally characterized to date, providing unique opportunities for tuning transcription in plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

$\mathrm{REX}$: An analytical tool for reactor operating envelope expansion through fuel-clad thermo-mechanics

Here REX, an analytical reactor design tool for the identification and expansion of reactor operating envelopes, is introduced and detailed. Written in MATLAB, REX takes core geometries and axially discretized detector and depletion output from the Serpent neutron transport code and performs full-core, pin-specific thermal-hydraulic and thermo-mechanical calculations. REX identifies the operating envelopes of advanced, solid-fuel nuclear reactors on the basis of their fuel-cladding, fuel-gas, and coolant-cladding interfacial thermo-mechanics. It iteratively pushes coolant inlet temperatures and modifies fuel pin geometries to induce mechanical failure in their original cladding materials at the fullest extent of their fuel cycle lengths and permissible coolant inlet temperatures. It then attempts to expand their operating envelopes by determining the mechanical responses of alternative cladding materials under the same geometric conditions. The result of the REX calculation sequence is a set of 5-D variables describing the temperatures, pressures, geometries, and mechanics of the core as functions of assembly, fuel pin, axial zone, depletion step, and coolant inlet temperature for each candidate cladding material with the limiting fuel pin geometry for the original material.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗