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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Quantifying the cooperative evolution of microphase segregation and nanostructural order in annealed polyurethanes of MDI-BDO-PTHF

Here, we quantify the relationship between microphase segregation and local structure development in thermoplastic polyurethanes. Samples were prepared with varying ratios of 4,40 -methylene diphenyl diisocyanate (MDI) and 1,4-butanediol (BDO) to polytetrahydrofuran (PTHF) and annealed at temperatures T a between RT–140 °C for 20 h each. Distinct populations of smaller and larger ordered domains are distinguished by pair distribution func tion analysis. The intermediate-range order of nanoscale hard domains in the paracrystalline state (form I) is directly extracted and characterized. The results suggest that form I of the MDI-BDO:PTHF system presents a conformational and packing order similar to the form III structure, typically obtained from stretching/annealing, but with limited spatial coherence of 3–7 nm. Heating above T g of the hard segments is necessary to achieve a substantial structural response from the annealing treatment. Increasing T a promotes purification of the soft phase via microphase segregation, coalescence of the hard blocks, and growth of paracrystalline phase, while a minority fraction of longer-range ordered domains left over from production remains relatively constant. We observe a composition-dependent decrease in the average nearest-neighbor dis tance that can be correlated with the greater number of C C, C N, and C O bonds with increased hard segment content. A non-linear deviation in the trend is observed to correlate with sample densification. The mechanical and thermal behavior of the samples is intimately tied to the segregation state.

processing-structure-properties↗
DOE OSTI2017

Balancing Authority Cooperation Concepts to Reduce Variable Generation Integration Costs in the Western Interconnection: Consolidating Balancing Authorities and Sharing Balancing Reserves

The study described in this chapter demonstrates the benefits of BA consolidation with the help of a detailed WECC system model and advanced methodology, which is also described in this chapter. The study aims to determine the potential savings in production cost and reduction in balancing reserve requirements in the WECC system. The study has found that effective use of the diversity in load and variable generation over a wide area can indeed help to achieve significant savings. The implementation cost for the consolidation was beyond the scope of this study. The analysis was performed for two different scenarios of VG penetration: 11% (8% wind and 3% solar) and 33% (24% wind and 9% solar) of WECC projected energy demand in 2020. In analysis of balancing reserves, the objective was to determine the reduction in balancing reserve requirements due to BA consolidation, in terms of required capacity and ramp-rates. Hour-ahead and 10-minute ahead forecast errors for load, wind, and solar were simulated. In addition, 1-minute resolution load, wind and solar data were used to derive balancing reserve requirements i.e. load-following and regulation requirements for each individual BA and for the consolidated BA (CBA). The reduction in balancing reserves was determined by calculating the difference between total reserve requirements that need to be carried by different BAs if they operate individually, and reserve requirements that need to be carried by the CBA. The study results show that the consolidated WECC system would have about a 50% overall reduction in balancing reserves for the 11% penetration scenario and a 65% reduction for the 33% penetration scenario in comparison with total reserve requirements that need to be carried by different BAs if they operate individually.

balancing authorities consolidation↗
DOE OSTI2017

A Cooperative Approach to Virtual Machine Based Fault Injection

Resilience investigations often employ fault injection (FI) tools to study the effects of simulated errors on a target system. It is important to keep the target system under test (SUT) isolated from the controlling environment in order to maintain control of the experiement. Virtual machines (VMs) have been used to aid these investigations due to the strong isolation properties of system-level virtualization. A key challenge in fault injection tools is to gain proper insight and context about the SUT. In VM-based FI tools, this challenge of target con- text is increased due to the separation between host and guest (VM). We discuss an approach to VM-based FI that leverages virtual machine introspection (VMI) methods to gain insight into the target s context running within the VM. The key to this environment is the ability to provide basic information to the FI system that can be used to create a map of the target environment. We describe a proof- of-concept implementation and a demonstration of its use to introduce simulated soft errors into an iterative solver benchmark running in user-space of a guest VM.

Naughton, III, Thomas J↗
DOE OSTI2019

Distributed Cooperative Control of Wind Farms with On-Site Battery Energy Storage Systems

This chapter studies the output power regulation in wind farms consisting of doubly-fed induction generator wind turbines, one of the most popular generator configurations in modern multi-MW wind industry, equipped with on-site battery energy storage systems. Traditionally, wind farms were operated as standalone units or were equipped with a central, large-scale, energy storage system. In fact, most of the existing control designs for hybrid wind-storage applications are centralized, where the central unit collects the measured data from all wind turbines and storage systems (if they exist) and compares with the load demand to generate the reference power for each wind turbine controller. Those centralized setups or control structures do not fully exploit the flexibility and locality of the on-site energy storage systems in a wind farm. Moreover, the storage functionality is lost if the central storage system is broken down, while in a distributed architecture, a failure only affects individual on-site storage systems and the others will still operate. Therefore, on-site storage systems and distributed control designs need to be developed for wind farms to provide regulation services for the grid. An approach to tackle that challenge will be presented in this chapter.

17 WIND ENERGY↗
DOE OSTI2023

Vision-based localization for cooperative robot-CNC hybrid manufacturing

Wire and arc additive manufacturing (WAAM) has shown promise in recent years for producing large-scale parts with higher deposition rates than other additive processes. WAAM is often combined with subtractive machining to form a hybrid manufacturing process. This hybrid process can be realized by retrofitting computer numerical control (CNC) machines with deposition heads, adding spindles and deposition heads to robots, or developing part localization methods to transfer parts from an additive cell to a CNC machine. Here, a novel, robot-CNC hybrid configuration is introduced where a maneuverable robot is placed in front of a CNC machine to deposit material within the machine envelop. Furthermore, this method removes the need for part localization and the extensive machine modifications required for retrofitting; however, the problem of robot localization is also added. In this work, the effects of error in vision-based, contactless robot localization on machining parameters in a robot-machine hybrid process were studied. Performance was characterized on an implementation of this system using classical computer vision techniques. In addition, machining simulations were conducted to evaluate the effects of image-induced error on chip thickness, material removal rate, and machining allowance. Initial tests show that computer vision could adequately locate a robot for the hybrid WAAM process within .5 mm.

Hybrid manufacturing↗
DOE OSTI2020

International cooperation in age-dating uranium standards for nuclear forensics using the 231 Pa/ 235 U radiochronometer

During 2017–2018 Los Alamos National Laboratory, Lawrence Livermore National Laboratory and the China Institute of Atomic Energy collaborated in an interlaboratory 231 Pa/ 235 U radiochronometry exercise. The laboratories used different analytical methods to obtain a consensus model purification date for CRM U010 of December 28, 1958 ± 198 days and for CRM U850 of May 20, 1958 ± 363 days. These results agree with previously reported model dates using the 230 Th/ 234 U radiochronometer as well as the production histories of these materials. The concordance of interlaboratory data here confirms the ability of laboratories to make reproducible radiochronometry measurements using distinct analytical approaches.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Selective enhancement of wnt4 expression by cyclic AMP-associated cooperation between rat central astrocytes and microglia

The wnt protein family has important members involved in cell differentiation, proliferation and plasticity expression; however, little is known about its biosynthesis processes. On the other hand, an increase in the intracerebral cyclic adenosine 3′, 5’-monophosphate (cAMP) level leads to synaptic plasticity via the de novo synthesis of any protein. Here, the effect of dibutyryl cAMP (dbcAMP), a membrane permeability cAMP analog, on the wnt family was investigated in rat primary-cultured glial cells containing astrocytes and microglia. Among wnt3a, 4, 5a, 7a and 11 mRNA, only wnt4 expression was increased by longer treatment (24 h), compared with short treatment (2 h), with dbcAMP in a concentration-dependent manner, and its effect reached statistical significance at 1 mM. In cultures of isolated astrocytes or microglia, wnt4 expression was not affected by 1 mM dbcAMP for 24 h, and microglial wnt4 protein was undetectable even when cells were treated with the drug. Mixed glial cells treated for 24 h with 1 mM dbcAMP showed significantly increased wnt4 protein, as well as mRNA. Immunofluorescence manifested that cells that expressed wnt4 protein were astrocytes, but not microglia. Intraperitoneal injection of 1.25 mg/kg rolipram, a phosphodiesterase (PDE) IV inhibitor that can pass through the blood brain barrier and inhibits cAMP degradation specifically, showed a tendency to increase wnt4 expression in the adult rat brain after 24 h, and the increases in wnt4 mRNA and protein levels reached statistical significance in the hippocampus and striatum, respectively. This is the first finding to help elucidate the selective biosynthesis of central wnt4 through cAMP-stimulated microglia and astrocytes interaction. - Highlights: • Dibutyryl cAMP increased wnt4, but not wnt3a, 5a, 7a and 11, mRNA in mixed glia. • Wnt4 protein increased in astrocytes co-cultivated with microglia. • It took a long time to robustly increase wnt4 expression. • Rolipram increased wnt4 expression in the rat striatum and hippocampus.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Cooperative Effects Associated with High Electrolyte Concentrations in Driving the Conversion of CO2 to C2H4 on Copper

Compared to a conventional electrolyte concentration of 1 M HCOOK, the use of a highly concentrated 7.1 M HCOOK electrolyte increases the Faradaic efficiency (FE) ratio of C2H4/CO from 2.2 +- 0.3 to 18.3 +- 4.8 at -1.08 V vs. reversible hydrogen electrode (RHE) on a Cu gas-diffusion electrode. Based on electrochemical analysis and ab initio molecular dynamics (AIMD) simulation, the identity and concentration of the cation and anion play more important roles in controlling the CO2R reaction pathway than the bulk CO2 solubility and the bulk pH of electrolytes. In situ attenuated reflectance surface enhanced infrared absorption spectroscopy (ATR-SEIRAS) suggests that, unlike 1 M HCOOK, the *CO-bridge-binding mode on Cu is dominant in 7.1 M HCOOK electrolyte, which potentially results in less CO release and higher yield of C2H4. This study demonstrates that although we can tailor the electrolyte composition to shift product selectivity, the factors that control the product selectivity are numerous and cannot be distilled down into one correlated property-reactivity relationship.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A non-cooperative meta-modeling game for automated third-party calibrating, validating and falsifying constitutive laws with parallelized adversarial attacks

The evaluation of constitutive models, especially for high-risk and high-regret engineering applications, requires efficient and rigorous third-party calibration, validation and falsification. While there are numerous efforts to develop paradigms and standard procedures to validate models, difficulties may arise due to the sequential, manual, and often biased nature of the commonly adopted calibration and validation processes, thus slowing down data collections, hampering the progress towards discovering new physics, increasing expenses and possibly leading to misinterpretations of the credibility and application ranges of proposed models. This work attempts to introduce concepts from game theory and machine learning techniques to overcome many of these existing difficulties. Here, we introduce an automated meta-modeling game where two competing AI agents systematically generate experimental data to calibrate a given constitutive model and to explore its weakness such that the experiment design and model robustness can be improved through competitions. The two agents automatically search for the Nash equilibrium of the meta-modeling game in an adversarial reinforcement learning framework without human intervention. In particular, a protagonist agent seeks to find the more effective ways to generate data for model calibrations, while an adversary agent tries to find the most devastating test scenarios that expose the weaknesses of the constitutive model calibrated by the protagonist. By capturing all possible design options of the laboratory experiments into a single decision tree, we recast the design of experiments as a game of combinatorial moves that can be resolved through deep reinforcement learning by the two competing players. Our adversarial framework emulates idealized scientific collaborations and competitions among researchers to achieve a better understanding of the application range of the learned material laws and prevent misinterpretations caused by conventional AI-based third-party validation. Numerical examples are given to demonstrate the wide applicability of the proposed meta-modeling game with adversarial attacks on both human-crafted constitutive models and machine learning models.

97 MATHEMATICS AND COMPUTING↗