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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Structure of a double hexamer of the Pyrococcus furiosus minichromosome maintenance protein N-terminal domain

The crystal structure of the N-terminal domain of the Pyrococcus furiosus minichromosome maintenance (MCM) protein as a double hexamer is described. The MCM complex is a ring-shaped helicase that unwinds DNA at the replication fork of eukaryotes and archaea. Prior to replication initiation, the MCM complex assembles as an inactive double hexamer at specific sites of DNA. The presented structure is highly consistent with previous MCM double-hexamer structures and shows two MCM hexamers with a head-to-head interaction mediated by the N-terminal domain. Minor differences include a diminished head-to-head interaction and a slightly reduced inter-hexamer rotation.

Meagher, Martin↗
DOE OSTI2024

Towards Resilient Near Real-Time Analysis Workflows in Fusion Energy Science

Nuclear fusion holds the promise of an endless source of energy. Several research experiments across the world and joint modeling and simulation efforts between the nuclear physics and high performance computing communities are actively preparing the operation of the International Thermonuclear Experimental Reactor (ITER). Both experimental reactors and their simulated counterparts generate data that must be analyzed quickly and in a resilient way to support decision making for the configuration of subsequent runs or prevent a catastrophic failure. However, the cost if the traditional techniques used to improve the resilience of analysis workflows, i.e., replicating datasets and computational tasks, becomes prohibitive with explosion of the volume of data produced by modern instruments and simulations. Therefore, we advocate in this paper for an alternate approach based on data reduction and data streaming. The rationale is that by allowing for a reasonable, controlled, and guaranteed loss of accuracy it becomes possible to transfer smaller amounts of data, shorten the execution time of analysis workflows, and lower the cost of replication to increase resilience. We develop our research and development roadmap towards resilient near real-time analysis workflows in fusion energy science and present early results showing that data streaming and data reduction is a promising way to speed up the execution and improve the resilience of analysis workflows.

Suter, Fred↗
DOE OSTI2023

EMT Simulation of Large PV Plant & Power Grid for Disturbance Analysis

One of the challenges faced during the analysis of various disturbances with inverter-based resources is the ability to replicate the same disturbance in simulations. The main issue arises from lack of electromagnetic transient (EMT) models and adequate fidelity of models. To overcome this problem, in this paper, EMT simulation of power grid and one of the affected photovoltaic (PV) plants is performed to replicate the observations during the Angeles Forest disturbance in 2018. The processes to (i) develop the EMT model of the power grid from traditional transient stability (TS) data, and (ii) develop high-fidelity EMT model of PV plant from data collected on a PV plant are described in the paper. The requirements in the high-fidelity EMT model of the PV plant are also described. Finally, simulation of the Angeles Forest disturbance is performed and similar simulation results (as compared to the observed disturbances) are observed.

Debnath, Suman↗
DOE OSTI2019

Field Validated Utility-Scale Battery Storage Control Models for Quasi-Static Analyses

This paper presents a co-simulation based approach to implement and validate advanced battery storage control modes in OpenDSS that replicate behavior of a utility scale vanadium red-ox flow battery (VRFB). Inverter-interfaced utiliy-scale battery storage systems (BSS) have modes of operation to facilitate multiple grid-support functions. In order to enable accurate understanding of the impacts from grid-support functions modes of operation it is required to develop validated models that replicates behavior of the actual control system. This paper presents the pseudo code for the implemented control schemes including peak shaving and capacity firming control modes. Additionally, this paper also provides insight on convergence sensitivity of the presented algorithms to related parameters. The results obtained from simulation studies will be compared against field operated utility-scale BSS measurements to verify the implemented algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Design of a Non-PLL Grid-Forming Inverter for Smooth Microgrid Transition Operation

This paper develops a controller for a grid-forming (GFM) inverter that is capable of operating as either a GFM or grid-feeding source that can improve the operation of a microgrid during on-off grid transitions through use of a novel synchronization approach. Furthermore, this controller avoids use of a phase-locked loop (PLL) and the inverter is able to synchronize with the grid with self-generated voltage and frequency. This prevents the inverter from replicating any grid voltage disturbances in its output—a key disadvantage of many grid-connected inverters that use a PLL. To enable fast synchronization, active synchronization control is adopted both during inverter start-up and microgrid reconnection operation and a method of coordinating synchronization of the inverter with a microgrid controller and grid interconnection circuit breaker is presented. Simulation results for multiple microgrid transition operations and unplanned islanding events demonstrate that the developed non-PLL grid-connected GFM inverter controller and synchronization method are effective in synchronizing the inverter and microgrid to the grid, avoiding phase jump during microgrid transition operation, and improving microgrid islanding transients versus a traditional configuration.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2017

Experimental Evaluation of Load Rejection Over-Voltage from Grid-Tied Solar Inverters

This paper investigates the impact of load rejection over-voltage (LRO) from commercially available grid-tied photovoltaic (PV) solar inverters. LRO can occur when a local feeder or breaker opens and the power output from a distributed energy resource exceeds the load power. Simplified models of current controlled inverters can over-predict over-voltage magnitudes, thus it is useful to quantify testing. The load rejection event was replicated using a hardware testbed at the National Renewable Energy Laboratory (NREL), and a set of commercially available PV inverters was tested to quantify the impact of LRO for a range of generation-to-load ratios. The magnitude and duration of the over-voltage events are reported in this paper along with a discussion of characteristic inverter output behavior. The results for the inverters under test showed that maximum over-voltage magnitudes were less than 200 percent of nominal voltage, and much lower in many test cases. These research results are important because utilities that interconnect inverter-based DER need to understand their characteristics under abnormal grid conditions.

14 SOLAR ENERGY↗
DOE OSTI2016

Degradation in PV Encapsulant Strength of Attachment: An Interlaboratory Study Towards a Climate-Specific Test

Reduced strength of attachment of the encapsulant resulting from the outdoor environment, including ultraviolet (UV) radiation, may decrease photovoltaic (PV) module lifetime by enabling widespread corrosion of internal components. To date, few studies exist showing how the adhesion of PV components varies with environmental stress. We have conducted an interlaboratory experiment to provide an understanding that will be used to develop climatic specific module tests. Factors examined in the study included the UV light source (lamp type), temperature, and humidity to be proposed for use in accelerated aging tests. A poly (ethylene-co-vinyl acetate) (EVA) formulation often used in veteran PV installations was studied using a compressive shear test - to quantify the strength of attachment at the EVA/glass interface. Replicate laminated glass/polymer/glass coupon specimens were weathered at 12 institutions using a variety of indoor chambers or field aging. Shear strength, shear strain, and toughness were measured using a mechanical load-frame for the compressive shear test, with subsequent optical imaging and electron microscopy of the separated surfaces.

14 SOLAR ENERGY↗
DOE OSTI2023

Traffic Signal Optimization by Integrating Reinforcement Learning and Digital Twins

Machine learning (ML) methods, especially reinforcement learning (RL), have been widely considered for traffic signal optimization in intelligent transportation systems. Most of these ML methods are centralized, lacking in scalability and adaptability in large traffic networks. Further, it is challenging to train such ML models due to the lack of training platforms and/or the cost of deploying and training in a real traffic networks. This paper presents an approach for the integration of decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin (DT) to optimize traffic signals for the reduction of traffic congestion and network-wide fuel consumption related to stopping. Specifically, the DGMARL agents learn traffic state patterns and make decisions regarding traffic signal control with assistance from a Digital Twin module, which simulates and replicates the traffic behaviors of a real traffic network. The proposed approach was evaluated using PTV-Vissim [1], a microscopic traffic simulation platform. PTV-Vissim is also the simulation engine of the DT, enabling emulation and optimization of the traffic signals on the MLK Smart Corridor in Chattanooga, Tennessee. Compared to an actuated signal control baseline approach, experiment results show that Eco_PI, a developed performance measure capturing the impact of stops on fuel consumption, was reduced by 44.27% in a 24-hour and an average of 29.88% in a PM-peak-hour scenario.

Multi-Agent Reinforcement Learning, Digital Twin, ↗
DOE OSTI2018

Guidelines and considerations for designing field experiments simulating precipitation extremes in forest ecosystems

1. Precipitation regimes are changing in response to climate change, yet understanding of how forest ecosystems respond to extreme droughts and pluvials remains incomplete. As future precipitation extremes will likely fall outside the range of historical variability, precipitation manipulation experiments (PMEs) are critical to advancing knowledge about potential ecosystem responses. However, few PMEs have been conducted in forests compared to short-statured ecosystems, and forest PMEs have unique design requirements and constraints. Moreover, past forest PMEs have lacked coordination, limiting cross-site comparisons. Here, we review and synthesize approaches, challenges, and opportunities for conducting PMEs in forests, with the goal of guiding design decisions, while maximizing the potential for coordination. 2. We reviewed 63 forest PMEs at 70 sites world-wide. Workshops, meetings, and communications with experimentalists were used to generate and build consensus around approaches for addressing the key challenges and enhancing coordination. 3. Past forest PMEs employed a variety of study designs related to treatment level, replication, plot and infrastructure characteristics, and measurement approaches.Important considerations for establishing new forest PMEs include: selecting appropriate treatment levels to reach ecological thresholds; balancing cost, logistical complexity, and effectiveness in infrastructure design; and preventing unintended water subsidies. Response variables in forest PMEs were organized into three broad tiers reflecting increasing complexity and resource intensiveness, with the first tier representing a recommended core set of common measurements. 4. Differences in site conditions combined with unique research questions of experimentalists necessitate careful adaptation of guidelines for forest PMEs to balance local objectives with coordination among experiments. We advocate adoption of a common framework for coordinating forest PME design to enhance cross-site comparability and advance fundamental knowledge about the response and sensitivity of diverse forest ecosystems to precipitation extremes.

Climate Extremes, drought, ecological thresholds, ↗
DOE OSTI2020

Comparing traditional and Bayesian approaches to ecological meta‐analysis

Abstract Despite the wide application of meta‐analysis in ecology, some of the traditional methods used for meta‐analysis may not perform well given the type of data characteristic of ecological meta‐analyses. We reviewed published meta‐analyses on the ecological impacts of global climate change, evaluating the number of replicates used in the primary studies ( n i ) and the number of studies or records ( k ) that were aggregated to calculate a mean effect size. We used the results of the review in a simulation experiment to assess the performance of conventional frequentist and Bayesian meta‐analysis methods for estimating a mean effect size and its uncertainty interval. Our literature review showed that n i and k were highly variable, distributions were right‐skewed and were generally small (median n i = 5, median k = 44). Our simulations show that the choice of method for calculating uncertainty intervals was critical for obtaining appropriate coverage (close to the nominal value of 0.95). When k was low (<40), 95% coverage was achieved by a confidence interval (CI) based on the t distribution that uses an adjusted standard error (the Hartung–Knapp–Sidik–Jonkman, HKSJ), or by a Bayesian credible interval, whereas bootstrap or z distribution CIs had lower coverage. Despite the importance of the method to calculate the uncertainty interval, 39% of the meta‐analyses reviewed did not report the method used, and of the 61% that did, 94% used a potentially problematic method, which may be a consequence of software defaults. In general, for a simple random‐effects meta‐analysis, the performance of the best frequentist and Bayesian methods was similar for the same combinations of factors ( k and mean replication), though the Bayesian approach had higher than nominal (>95%) coverage for the mean effect when k was very low ( k < 15). Our literature review suggests that many meta‐analyses that used z distribution or bootstrapping CIs may have overestimated the statistical significance of their results when the number of studies was low; more appropriate methods need to be adopted in ecological meta‐analyses.

Pappalardo, Paula↗
DOE OSTI2024

Coinfection of Influenza A and B and Human OC43 Coronavirus in Normal Human Bronchial Epithelial Cells

Influenza viruses and seasonal coronaviruses are pathogens transmitted via an airborne route that can cause respiratory diseases in humans that have similar symptoms such as fever, cough, and pneumonia. These two viruses can infect similar human tissues, such as the respiratory tract and nasal, bronchial, and alveolar epithelial cells. Influenza virus and seasonal coronavirus coinfections are poorly understood. Here, we coinfected normal human bronchial epithelial (NHBE) cells with influenza A/California/04/09 (IAV) or B/Victoria/504/2000 (IBV) strains and the seasonal human beta-coronavirus OC43 and evaluated viral replication capacities. We also examined changes in the expression of various cytokines/chemokines by qPCR and Luminex assay. We observed that the replication of IAV and IBV was not affected by coinfection with OC43. However, coinfection reduced OC43 titers (~3-fold) compared with infection with OC43 alone. Select cytokine/chemokine expression was increased in coinfected cells compared with all single infections with greater differences seen between coinfected cells and cells infected with OC43 alone compared with IAV- or IBV-infected cells. In addition, IL-8 and IL-1RA showed the highest expression among a panel of 22 cytokines by Luminex. As the rate of influenza and seasonal coronavirus coinfection continue to increase, our findings may help set guidelines for the treatments of the individuals coinfected with both viruses.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Lab-Scale, Closed-Loop Experimental Characterization, Model Refinement, and Validation of a Hydrokinetic Energy-Harvesting Ocean Kite

This paper presents a study wherein we experimentally characterize the dynamics and control system of a lab-scale ocean kite, and then refine, validate, and extrapolate this model for use in a full-scale system. Ocean kite systems, which harvest tidal and ocean current resources through high-efficiency cross-current motion, enable energy extraction with an order of magnitude less material (and cost) than stationary systems with the same rated power output. However, an ocean kite represents a nascent technology that is characterized by relatively complex dynamics and requires sophisticated control algorithms. In order to characterize the dynamics and control of ocean kite systems rapidly, at a relatively low cost, the authors have developed a lab-scale, closed-loop prototyping environment for characterizing tethered systems, whereby 3D printed systems are tethered and flown in a water channel environment. While this system has been shown to be capable of yielding similar dynamic characteristics to some full-scale systems, there are also fundamental limitations to the geometric scales and flow speeds within the water channel environment, making many other real-world scenarios impossible to replicate from the standpoint of dynamic similarity. Here, to address these scenarios, we show how the lab-scale framework is used to refine and validate a scalable dynamic model of a tethered system, which can then be extrapolated to full-scale operation. In this work, we present an extensive case study of this model refinement, validation, and extrapolation on an ocean kite system intended for operation in the Gulf Stream or similar current environments.

42 ENGINEERING↗
DOE OSTI2021

Discrete-Direct Model Calibration and Uncertainty Propagation Method Confirmed on Multi-Parameter Plasticity Model Calibrated to Sparse Random Field Data

A discrete direct (DD) model calibration and uncertainty propagation approach is explained and demonstrated on a 4-parameter Johnson-Cook (J-C) strain-rate dependent material strength model for an aluminum alloy. The methodology's performance is characterized in many trials involving four random realizations of strain-rate dependent material-test data curves per trial, drawn from a large synthetic population. The J-C model is calibrated to particular combinations of the data curves to obtain calibration parameter sets which are then propagated to “Can Crush” structural model predictions to produce samples of predicted response variability. These are processed with appropriate sparse-sample uncertainty quantification (UQ) methods to estimate various statistics of response with an appropriate level of conservatism. This is tested on 16 output quantities (von Mises stresses and equivalent plastic strains) and it is shown that important statistics of the true variabilities of the 16 quantities are bounded with a high success rate that is reasonably predictable and controllable. The DD approach has several advantages over other calibration-UQ approaches like Bayesian inference for capturing and utilizing the information obtained from typically small numbers of replicate experiments in model calibration situations—especially when sparse replicate functional data are involved like force–displacement curves from material tests. The DD methodology is straightforward and efficient for calibration and propagation problems involving aleatory and epistemic uncertainties in calibration experiments, models, and procedures.

42 ENGINEERING↗
DOE OSTI2015

Experimental and Measurement Uncertainty Associated with Characterizing Slurry Mixing Performance of Pulsating Jets at Multiple Scales

Understanding how uncertainty manifests itself in complex experiments is important for developing the testing protocol and interpreting the experimental results. This paper describes experimental and measurement uncertainties, and how they can depend on the order of performing experimental tests. Experiments with pulse-jet mixers in tanks at three scales were conducted to characterize the performance of transient-developing periodic flows in Newtonian slurries. Other test parameters included the simulant, solids concentration, and nozzle exit velocity. Critical suspension velocity and cloud height were the metrics used to characterize Newtonian slurry flow associated with mobilization and mixing. During testing, near-replicate and near-repeat tests were conducted. The experimental results were used to quantify the combined experimental and measurement uncertainties using standard deviations and percent relative standard deviations (%RSD) The uncertainties in critical suspension velocity and cloud height tend to increase with the values of these responses. Hence, the %RSD values are the more appropriate summary measure of near-replicate testing and measurement uncertainty.

pulse jet mixing↗
DOE OSTI2015

SU-E-J-263: Repeatability of SUV and Texture Parameters in Serial PET Studies

Purpose: Standardized uptake values (SUV) are standard quantitative PET measures of FDG tumor uptake used,and are used as a tool to monitor response to therapy. Textural analysis is emerging as a new tool for assessing intratumoral heterogeneity which may allow better tissue characterization and improved prediction of response and survival rate.Understanding what variations may be expected in these parameters is key in order to make decisions based on how the change throughout the course of treatment. The aim of this study was to assess repeatability in SUV measures and texture parameters,and establish criteria that differentiate changes associated with treatment rather than statistical variability. Methods: Eighty patients,167 random lesions total,were scanned in a GE Discovery STE PET/CT Scanner. One field-of-view was chosen centered on the largest lesion observed in a clinical whole-body FDG PET.Immediately following,a gated 9 min scan was acquired in list mode,without changing the patient’s position between any scans. Data was replayed into 3 time bins,3 min each,in order to insure equivalent noise characteristics in each replicate.Data was reconstructed into 128×128×47 square matrices.One VOI was drawn over each lesion for each patient and used to segment all 3 replicates. The mean.max and peak SUV were calculated for each VOI and replicate. First-order textural features were also calculated (skewness and kurtosis). Repeatability was calculated as the average standard deviation over the mean for the 3 repeated measurements for each lesion. Results: The average percent error in the SUV max,peak and mean were 3.4%(0– 12.9%),1.9% (0–7.5%),2.8% (0–12.2%),respectively.For skewness and kurtosis they were 10.9% and 17.8%. Conclusion: We have shown that there is a large variation in %error in SUV measures across patients. SUVpeak is the least variable and kurtosis and skewness parameters are less reliable thatn SUVs.Higher order textures are be.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-09: In Phantom Full-Implant Validation of Plastic Scintillation Detectors for in Vivo Dosimetry During Low Dose Rate Brachytherapy

Purpose: To validate in a water phantom the use of plastic scintillation detectors to measure dose to the urethra and the rectal wall during a clinically realistic low dose rate (LDR) brachytherapy implant. Methods: A template was designed to replicate a clinically realistic LDR brachytherapy prostate implant inside a water phantom. Twenty-two catheters were inserted, including one mimicking the urethra and another the rectal wall. The needles inserted in the remaining 20 catheters were composed of thin-walled nylon tubes in which I-125 radioactive seeds (Air Kerma Strengths of (0.328±0.020)U) were abutted together with plastic spacers to replicate a typical loading. A plastic scintillation detector (PSD) with a 5-mm long × 1-mm diameter sensitive element was first placed inside the urethra and 1-second measurements were performed for 60s after each needle implant. Measurements were also performed at multiple positions along the urethra once all the needles were inserted. The procedure was then repeated with the PSD placed at the rectal wall. Results: Individual dose-rates ranging from 0.07µGy/s to 1.5µGy/s were measured after each needle implant. The average absolute relative differences were (6.2±3.6)% and (6.9±6.5)% to the values calculated with the TG-43 formalism, for the urethra and rectal wall respectively. These results are within expectations from the error uncertainty budget once accounting for uncertainties in seeds’ strength and positioning. Interestingly, the PSD allowed for unplanned error detection as the study was performed. Finally, the measured dose after the full implant at different positions along the mimicked organs at risk were in agreement with TG-43 values for all of the positions tested. Conclusion: Plastic scintillation detectors could be used as in vivo detectors for LDR brachytherapy as they would provide accurate dose information after each needle implant as well as along the organs at risk at the end of the implant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

High-throughput genetic engineering of nonmodel and undomesticated bacteria via iterative site-specific genome integration

Efficient genome engineering is critical to understand and use microbial functions. Despite recent development of tools such as CRISPR-Cas gene editing, efficient integration of exogenous DNA with well-characterized functions remains limited to model bacteria. Here, we describe serine recombinase–assisted genome engineering, or SAGE, an easy-to-use, highly efficient, and extensible technology that enables selection marker–free, site-specific genome integration of up to 10 DNA constructs, often with efficiency on par with or superior to replicating plasmids. SAGE uses no replicating plasmids and thus lacks the host range limitations of other genome engineering technologies. We demonstrate the value of SAGE by characterizing genome integration efficiency in five bacteria that span multiple taxonomy groups and biotechnology applications and by identifying more than 95 heterologous promoters in each host with consistent transcription across environmental and genetic contexts. We anticipate that SAGE will rapidly expand the number of industrial and environmental bacteria compatible with high-throughput genetics and synthetic biology.

59 BASIC BIOLOGICAL SCIENCES↗