Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “replication”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 829 records · Page 46

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↗

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↗

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↗

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↗

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↗

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, ↗

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, ↗

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↗

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↗

Role of Outer Membrane C-Type Cytochromes MtrC and OmcA in Shewanella Oneidensis MR-1 Cell Production, Accumulation, and Detachment During Respiration on Hematite

Solid phase iron oxides are considered to be important terminal electron acceptors for microbial respiration in many anoxic environments. Besides the knowledge that cells attach to and reduce these substrates, other aspects of surface-associated cell behavior and the related cell surface components that influence cell-mineral interactions are not well understood. In the present study, wild-type cells of the dissimilatory iron-reducing bacterium Shewanella oneidensis MR-1 formed thin biofilms one-to-two cell layers in thickness when respiring on natural specular hematite under flow conditions similar to those which exist in aquatic sediments and subsurface environments. The distribution of cells within the biofilm indicated that direct contact was not required for electron transfer from cells to the mineral surface. Detached biomass in the form of single cells represented >99% of the surface-associated wild-type cell production from respiration on hematite over the biofilm life cycle. A mutant deficient in the outer membrane c35 type cytochrome OmcA, while still able to respire and replicate on hematite, established a lower steady-state cell density on the mineral surface than that of the wild-type strain. A mutant deficient in MtrC, another outer membrane c-type cytochrome, and a mutant deficient in both cytochromes were unable to reduce sufficient amounts of hematite to support detectable growth on the mineral surface. When considered in the context of previous work, the results support a growing body of evidence that the relative importance of OmcA and MtrC to cell respiration and replication depends on the form of iron oxide available as terminal electron acceptor.

Mitchell, Andrew C↗

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↗

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↗

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↗

Characterization of a Solid Oxide Fuel Cell Gas Turbine Hybrid System Based on a Factorial Design of Experiments Using Hardware Simulation

A full factorial experimental design and a replicated fractional factorial design were carried out using the Hybrid Performance (HyPer) project facility installed at the National Energy Technology Laboratory (NETL), U.S. Department of Energy to simulate gasifer/fuel cell/turbine hybrid power systems. The HyPer facility uses hardware in the loop (HIL) technology that couples a modified recuperated gas turbine cycle with hardware driven by a solid oxide fuel cell model. A 34 full factorial design (FFD) was selected to study the effects of four factors: cold-air, hot-air, bleed-air bypass valves, and the electric load on different parameters such as cathode and turbine inlet temperatures, pressure and mass flow. The results obtained, compared with former results where the experiments were made using one-factor-at-a-time (OFAT), show that no strong interactions between the factors are present in the different parameters of the system. This work also presents a fractional factorial design (ffd) 34-2 in order to analyze replication of the experiments. In addition, a new envelope is described based on the results of the design of experiments (DoE), compared with OFAT experiments, and analyzed in an off-design integrated fuel cell/gas turbine framework. This paper describes the methodology, strategy, and results of these experiments that bring new knowledge concerning the operating state space for this kind of power generation system.

30 DIRECT ENERGY CONVERSION↗

{sup 103}Pd strings: Monte Carlo assessment of a new approach to brachytherapy source design

Purpose: A new type of{sup 103}Pd source (CivaString and CivaThin by CivaTech Oncology, Inc.) is examined. The source contains {sup 103}Pd and Au radio-opaque marker(s), all contained within low-Z{sub eff} organic polymers that permit source flexibility. The CivaString source is available in lengths L of 10, 20, 30, 40, 50, and 60 mm, and referred to in the current study as CS10–CS60, respectively. A thinner design, CivaThin, has sources designated as CT10–CT60, respectively. The CivaString and CivaThin sources are 0.85 and 0.60 mm in diameter, respectively. The source design is novel and offers an opportunity to examine its interesting dosimetric properties in comparison to conventional {sup 103}Pd seeds. Methods: The MCNP5 radiation transport code was used to estimate air-kerma rate and dose rate distributions with polar and cylindrical coordinate systems. Doses in water and prostate tissue phantoms were compared to determine differences between the TG-43 formalism and realistic clinical circumstances. The influence of Ti encapsulation and 2.7 keV photons was examined. The accuracy of superposition of dose distributions from shorter sources to create longer source dose distributions was also assessed. Results: The normalized air-kerma rate was not highly dependent onL or the polar angle θ, with results being nearly identical between the CivaString and CivaThin sources for common L. The air-kerma strength was also weakly dependent on L. The uncertainty analysis established a standard uncertainty of 1.3% for the dose-rate constant Λ, where the largest contributors were μ{sub en}/ρ and μ/ρ. The Λ values decreased with increasing L, which was largely explained by differences in solid angle. The radial dose function did not substantially vary among the CivaString and CivaThin sources for r ≥ 1 cm. However, behavior for r < 1 cm indicated that the Au marker(s) shielded radiation for the sources having L = 10, 30, and 50 mm. The 2D anisotropy function exhibited peaks and valleys that corresponded to positions adjacent to {sup 103}Pd wells and Au markers, respectively. Dose distributions of both source types had minimal anisotropy in comparison to conventional {sup 103}Pd seeds. Contributions by 2.7 keV photons comprised ≤0.1% of the dose from all photons at positions farther than 0.13 mm from the polymer source surface. Differences between absorbed dose to water and prostate became more substantial as distance from the sources increased, with prostate dose being about 13% lower for r = 5 cm. Using a cylindrical coordinate system, dose superposition of small length sources to replicate the dose distribution for a long length source proved to be a robust technique; a 2.0% tolerance compared with the reference dose distribution did not exceed 0.1 cm{sup 3} for any of the examined source combinations. Conclusions: By design, the CivaString and CivaThin sources have novel dosimetric characteristics in comparison to Ti-encapsulated{sup 103}Pd seeds. The dosimetric characterization has determined the reasons for these differences through analysis using Monte Carlo-based radiation transport simulations.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

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↗

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↗