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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

In‐mold rheology and automated process control for injection molding of recycled polypropylene

Abstract Manufacturing plastic parts with secondary feedstocks has risen to the forefront of importance in recent years. However, the variation in molecular weight and rheology of secondary feedstock can lead to inconsistent part quality. This work evaluates the effectiveness of a novel closed‐loop adaptive process control system that adjusts nozzle pressure in response to in‐mold pressure data. Five different recycled polypropylene blends, with a broad distribution of flow properties, were evaluated to determine the effectiveness of the control system at reducing processing variation. The experimental results show that the process control strategy reduced the variation within the mold, as seen by in‐mold pressure curves and calculated in‐mold viscosity values. Additionally, the parameters that control the automated process adjustments were investigated, showing the importance of optimization. The analysis of the correlation between in‐mold rheology and mechanical properties showed a slight variation in the mechanical properties and parts weight with a coefficient of variation of under 5%. Overall, the results demonstrate the ability of pressure‐controlled molding and automated viscosity adjustment to reduce the variability when molding a secondary feedstock. Highlights Pressure‐controlled injection molding of recycled polypropylene. Automated closed‐loop adaptive process control methodology. Methodology resulted in a reduction in pressure variation during molding. Changes in mechanical properties and in‐mold viscosity were investigated. Results show the potential of pressure‐controlled molding at reducing variation.

Krantz, Joshua↗
DOE OSTI2023

Bi-Level Adaptive Storage Expansion Strategy for Microgrids Using Deep Reinforcement Learning

Battery energy storage (BES) is a versatile resource for the secure and economic operation of microgrids (MGs). Prevailing stochastic optimization-based approaches for BES expansion planning for MGs are computationally complicated. This work proposes a data-driven bi-level multi-period BES expansion planning framework to determine the siting, sizing, and timing of BES installations. The proposed planning framework unifies deep reinforcement learning (DRL) and linear programming, thereby decoupling the determinations for the integer and continuous decision variables in two time scales, respectively. In the upper level, a rainbow DRL agent with quantile regression is trained to provide dynamic planning policies to accommodate stochastic renewable energy resources (RESs), load, and battery price changes efficiently. Further, the lower level computes the optimal operation of MGs with frequency constraints to hedge the islanding contingency. The two levels communicate with one another by exchanging storage configuration and operating expenses in order to accomplish the shared goal of minimizing investment and operation costs. Comparative case studies on an MG are carried out to demonstrate the superiority of the proposed DRL-based solution to the mixed-integer linear programming counterpart on efficiency, scalability, and adaptability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Reliable Power for Remote Applications

Optical power beaming has the potential to fundamentally change how remote devices receive power, leading to technological innovation across many sectors. NREL is interested in teaming with partners to engineer field-ready (and space-ready) solutions for long-range power beaming and adapt new ideas to important applications.

14 SOLAR ENERGY↗
NASA NTRS1991

Adaptive control of interface by temperature and interface profile feedback in transparent multi-zone crystal growth furnace

The objective of this research is to control the dynamics of multizone programmable crystal growth furnaces. Due to the inevitable heat exchange among different heating zones and the transient nature of the process, the dynamics of multizone furnaces is time varying, distributed, and therefore complex in nature. Electrical power to heating zones and the translational speed of the ampoule are employed as inputs to control the dynamics. Structural properties of the crystal is the ultimate aim of this adaptive control system. These properties can be monitored in different ways. Following an order of complexity, these may include: (1) on line measurement of the material optical properties such as the refractive index of crystal; (2) on line x-ray imaging of the interface topology; (3) on line optical quantification of the interface profile such as the determination of concavity or convexity of the interface shape; and (4) on line temperature measurement at points closest to the material such as measurements of the ampoule's outside and inside surface temperatures. The research performed makes use of the temperature and optical measurements, specified in (3) and (4) as the outputs of furnace dynamics. However, if the instrumentation is available, the proposed control methodology can be extended to the measurements listed in (1) and (2).

Batur, Celal↗
DOE OSTI2021

Root traits explain plant species distributions along climatic gradients yet challenge the nature of ecological trade-offs

Ecological theory is built on trade-offs, where trait differences among species evolved as adaptations to different environments. Trade-offs are often assumed to be bidirectional, where opposite ends of a gradient in trait values confer advantages in different environments. However, unidirectional benefits could be widespread if extreme trait values confer advantages at one end of an environmental gradient, whereas a wide range of trait values are equally beneficial at the other end. Here, we show that root traits explain species occurrences along broad gradients of temperature and water availability, but model predictions only resembled trade-offs in two out of 24 models. Forest species with low specific root length and high root tissue density (RTD) were more likely to occur in warm climates but species with high specific root length and low RTD were more likely to occur in cold climates. Unidirectional benefits were more prevalent than trade-offs: for example, species with large-diameter roots and high RTD were more commonly associated with dry climates, but species with the opposite trait values were not associated with wet climates. Directional selection for traits consistently occurred in cold or dry climates, whereas a diversity of root trait values were equally viable in warm or wet climates. Explicit integration of unidirectional benefits into ecological theory is needed to advance our understanding of the consequences of trait variation on species responses to environmental change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Survey on Sustainable Software Ecosystems to Support Experimental and Observational Science at Oak Ridge National Laboratory

In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. The study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and ii) data management requirements for data-driven science using artificial intelligence.

Bernholdt, David↗
DOE OSTI2024

Trajectory Shaper: A Solution for Disrupted Cooperative Adaptive Cruise Control

Cooperative adaptive cruise control (CACC) can effectively reduce energy consumption, alleviate traffic congestion, and enhance safety. However, communication-related constraints and uncooperative vehicle users can disrupt CACC during real-world operations, significantly undermining the putative benefits of CACC. To alleviate the negative impacts of disrupted CACC, this study develops the trajectory shaper (TS) methods as backup solutions for two scenarios: (i) communication between vehicles is infeasible, and vehicles execute adaptive cruise control (ACC) using local sensor measurements; (ii) follower vehicles reject forming a cooperative platoon and execute their local distributed controllers using the information attained via communication. When communication is infeasible, a distributed TS is devised on each vehicle to modify the sensor measurements, enabling safe and efficient ACC operations. When communication is available but uncooperative agents are involved, the lead vehicle of the platoon executes a centralized TS to modify the information shared with uncooperative agents, achieving optimal platoon-level performance. The centralized and distributed TSs are implemented based on the model predictive control algorithms to yield optimal modifications on input information. Robustness is also factored to tackle model uncertainties during TS operations to ensure safety and efficiency. Numerical experiments validate the control performance of the proposed TSs.

Zhou, Anye [ORNL] (ORCID:0000000301455579)↗
DOE OSTI2023

Experiential findings for sustainable software ecosystems to support experimental and observational science

In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. Here, the study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: (i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and (ii) data management requirements for data-driven science using artificial intelligence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Nanolatticed Architecture Mitigates Damage in Shark Egg Cases

Structural versatility and multifunctionality of biological materials have resulted in countless bioinspired strategies seeking to emulate the properties of nature. The nanostructured egg case of swell sharks is one of the toughest permeable membranes known and, thus, presents itself as a model system for materials where the conflicting properties, strength and porosity, are desirable. The egg case possesses an intricately ordered structure that is designed to protect delicate embryos from the external environment while enabling respiratory and metabolic exchange, achieving a tactical balance between conflicting properties. Herein, structural analyses revealed an enabling nanolattice architecture that constitutes a Bouligand-like nanoribbon hierarchical assembly. Three distinct hierarchical architectural adaptations enhance egg case survival: Bouligand-like organization for in-plane isotropic reinforcement, noncylindrical nanoribbons maximizing interfacial stress distribution, and highly ordered nanolattices enabling permeability and lattice-governed toughening mechanisms. Furthermore, these discoveries provide fundamental insights for the improvement of multifunctional membranes, fiber-reinforced soft composites, and mechanical metamaterials.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Recombination of Autodissociated Water Ions in a Nanoscale Pure Water Droplet

The recombination of water ions has diverse scientific and practical implications, ranging from acid-base chemistry and biological systems to planetary environments and applications in fuel cell and carbon conversion technologies. While spatial confinement affects the physicochemical properties of water dynamics, its impact on the recombination process has rarely been studied. In this work, we investigate the dynamics of water, the water ion distribution, and the ion recombination process in water droplets as a function of droplet size through molecular dynamics simulations and adaptive quantum mechanical/molecular mechanical calculations. We compare the dynamics of recombination in water droplet sizes ranging from 100 to 18 000 waters, both in their interiors and on their surfaces. We found that the self-diffusion of water dramatically decreases in droplets with a diameter below 2.2 nm. Using a classical RexPoN force-field, we found that the ions in 1000 H2O's spend almost 50% of the time on the surface and 0.5 nm beneath it with a slight preference for OH- ion to reside longer on the surface. We estimate that, on average, recombination in these drops occurs at 400 ps in 1000 H2O's and 1 ns in 3000 H2O's. We also found that recombination is not limited by the local structure of the surface or the size of the droplet but can be influenced by the geometry of the water wire connecting the ions as they approach each other, which can often prevent recombination. Our results provide insights to the reaction microenvironments presented by nanoscopic water droplets.

Kwon, Soonho↗
DOE OSTI2020

Genomics of sorghum local adaptation to a parasitic plant

Host–parasite coevolution can maintain high levels of genetic diversity in traits involved in species interactions. In many systems, host traits exploited by parasites are constrained by use in other functions, leading to complex selective pressures across space and time. Here, we study genome-wide variation in the staple crop Sorghum bicolor (L.) Moench and its association with the parasitic weed Striga hermonthica (Delile) Benth., a major constraint to food security in Africa. We hypothesize that geographic selection mosaics across gradients of parasite occurrence maintain genetic diversity in sorghum landrace resistance. Suggesting a role in local adaptation to parasite pressure, multiple independent loss-of-function alleles at sorghum LOW GERMINATION STIMULANT 1 (LGS1) are broadly distributed among African landraces and geographically associated with S. hermonthica occurrence. However, low frequency of these alleles within S. hermonthica-prone regions and their absence elsewhere implicate potential trade-offs restricting their fixation. LGS1 is thought to cause resistance by changing stereochemistry of strigolactones, hormones that control plant architecture and below-ground signaling to mycorrhizae and are required to stimulate parasite germination. Consistent with trade-offs, we find signatures of balancing selection surrounding LGS1 and other candidates from analysis of genome-wide associations with parasite distribution. Experiments with CRISPR–Cas9-edited sorghum further indicate that the benefit of LGS1-mediated resistance strongly depends on parasite genotype and abiotic environment and comes at the cost of reduced photosystem gene expression. Our study demonstrates long-term maintenance of diversity in host resistance genes across smallholder agroecosystems, providing a valuable comparison to both industrial farming systems and natural communities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The emergence and transmission dynamics of HIV-1 CRF07_BC in Mainland China

A total of 1155 partial pol gene sequences of human immunodeficiency virus (HIV)-1 CRF07_BC were sampled between 1997 and 2015, spanning 13 provinces in Mainland China and risk groups [heterosexual, injecting drug users (IDU), and men who have sex with men (MSM)] to investigate the evolution, adaptation, spatiotemporal and risk group dynamics, migration patterns, and protein structure of HIV-1 CRF07_BC. Due to the unequal distribution of sequences across time, location, and risk group in the complete dataset (‘full1155’), subsampling methods were used. Maximum-likelihood and Bayesian phylogenetic analysis as well as discrete trait analysis of geographical location and risk group were carried out. To study mutations of a cluster of HIV-1 CRF07_BC (CRF07-1), we performed a comparative analysis of this cluster to the other CRF07_BC sequences (‘backbone_295’) and mapped the mutations observed in the respective protein structure. Our findings showed that HIV-1 CRF07_BC most likely originated among IDU in Yunnan Province between October 1992 to July 1993 [95 per cent hightest posterior density (HPD): May 1989–August 1995] and that IDU in Yunnan Province and MSM in Guangdong Province likely served as the viral sources during the early and more recent spread in Mainland China. We also revealed that HIV-1 CRF07-1 has been spreading for roughly 20 years and continues to cause local transmission in Mainland China and worldwide. Overall, our study sheds light on the dynamics of HIV-1 CRF07_BC distribution patterns in Mainland China. Our research may also be useful in formulating public health policies aimed at controlling acquired immune deficiency syndrome in Mainland China and globally.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Tsuchinoko v1.0.0

Tsuchinoko is a Qt application for adaptive experiment execution and tuning. Live visualizations show details of measurements, and provide feedback on the adaptive engine's decision-making process. The parameters of the adaptive engine can also be tuned live to explore and optimize the search procedure. While Tsuchinoko is designed to allow custom adaptive engines to drive experiments, the gpCAM engine is a featured inclusion. This tool is based on a flexible and powerful Gaussian process regression at the core. A Tsuchinoko system includes 4 distinct components: the GUI client, an adaptive engine, and execution engine, and a core service. These components are separable to allow flexibility with a variety of distributed designs.

Pandolfi, Ronald↗
DOE OSTI2025

Uncertainty based Online Ensemble on Non-Stationary Data for Fusion Science

Machine Learning (ML) is poised to play a pivotal role in the development and operation of next-generation fusion devices. Fusion data shows non-stationary behavior due to drifts in the data. The drifts can arise from both experimental evolution and machine wear-and-tear. ML models assume stationary distribution and fail to maintain performance when encountered with non-stationary data streams.Online learning can be used to continuously adapt the models with new data as it is acquired. However, traditional online learning can suffer from short-term performance degradation, as ground truth are not available before making the prediction. To address this challenge, we propose uncertainty aware ensemble approach for online learning. We use Deep Gaussian Process Approximation (DGPA) technique for calibrated uncertainty estimation and use the uncertainty values to guide a meta-algorithm that produces predictions based on ensemble of learners. Moreover, DGPA also provides uncertainty estimation along with the predictions for decision makers. This paper demonstrates that the proposed method outperforms traditional online learning approach, and a naive ensemble without uncertainty guidance by about 7% and 6%, respectively, on B-coil deflection prediction at DIII-D Fusion Facility.

Rajput, Kishansingh [Thomas Jefferson National Acc↗
NASA NTRS1990

Integrated communication and information fabric for space applications

The results of preliminary research into infrastructures for integrated communication and information fabrics, which can meet the needs of space applications of the future, are presented. Technologies that foster scaleability and adaptability and support self-organizing mechanisms are needed to effectively integrate the working fabric of a large-scale distributed system. A multigrid network architecture that uses a completely distributed packet-routing scheme is derived. The first part of the paper introduces a simple model of a communication and information system for space applications, the second discusses the known limitations of the large-scale future communication and information systems, and the third part describes the results of preliminary research in this area. It is expected that this technology will result in inexpensive networks utilizing multigigabit-per-second data links.

Maitan, J.↗
NASA NTRS1991

Grid quality improvement by a grid adaptation technique

A grid adaptation technique is presented which improves grid quality. The method begins with an assessment of grid quality by defining an appropriate grid quality measure. Then, undesirable grid properties are eliminated by a grid-quality-adaptive grid generation procedure. The same concept has been used for geometry-adaptive and solution-adaptive grid generation. The difference lies in the definition of the grid control sources; here, they are extracted from the distribution of a particular grid property. Several examples are presented to demonstrate the versatility and effectiveness of the method.

Lee, K. D.↗
NASA NTRS1997

Comparison of Light Emitting Diodes (LED) and Fluorescent Light on Suppression of Pineal Melatonin in the Rat

To validate a novel LED array for use in animal habitat lighting by comparing its effectiveness to cool-white fluorescent (CWF) lighting in suppressing pineal gland melatonin. Male Sprague-Dawley rats, 175-200 g, were maintained under control conditions for 2 weeks (food and water ad lib, 12L: 12D CWF, 18 uW/square cm). Dark adapted animals (animals before lights on) were exposed to 5 min of LED or CWF light of similar spectral power distribution. Two groups of rats (LED vs. CWF) were compared at 5 light intensities (100, 40, 1, 1.0, and 0. 1 lux). A control group was placed into the exposure apparatus but not exposed to light. After exposure, pineal glands were rapidly removed and assayed for melatonin by RIA. Results. The dark-exposed control groups matched with the 5 intensity groups (100, 40, 10, 1.0, and 0.1 lux) showed mean + SEM pineal melatonin values of 1167 +/- 136, 1569 +/- 126, 353 +/- 34, 650 +/- 124, and 464 +/- 85, pg/ml respectively. The corresponding CWF exposure data were 393 1 41, 365 +34, 257 +/- 13, 218 +/- 42, and 239 +/- 71 pg/ml, respectively. Corresponding LED exposure data were 439 +/- 25, 462 +/- 50, 231 +/- 6, 164 +/- 12, and 158 +/- 12 pg/ml, respectively. Rats exposed to both experimental light conditions at all illuminances studied showed significant melatonin suppression (p less than 0.01, ANOVA). In no case was the melatonin suppression induced by LED illuminance significantly different from the melatonin suppression elicited by the same intensity of CWF light. The results show that a novel LED light source can suppress pineal melatonin equal to that of a conventional CWF light source.

Winget, Charles M.↗
NASA NTRS2001

A Study on a Microwave-Driven Smart Material Actuator

NASA s Next Generation Space Telescope (NGST) has a large deployable, fragmented optical surface (greater than or = 2 8 m in diameter) that requires autonomous correction of deployment misalignments and thermal effects. Its high and stringent resolution requirement imposes a great deal of challenge for optical correction. The threshold value for optical correction is dictated by lambda/20 (30 nm for NGST optics). Control of an adaptive optics array consisting of a large number of optical elements and smart material actuators is so complex that power distribution for activation and control of actuators must be done by other than hard-wired circuitry. The concept of microwave-driven smart actuators is envisioned as the best option to alleviate the complexity associated with hard-wiring. A microwave-driven actuator was studied to realize such a concept for future applications. Piezoelectric material was used as an actuator that shows dimensional change with high electric field. The actuators were coupled with microwave rectenna and tested to correlate the coupling effect of electromagnetic wave. In experiments, a 3x3 rectenna patch array generated more than 50 volts which is a threshold voltage for 30-nm displacement of a single piezoelectric material. Overall, the test results indicate that the microwave-driven actuator concept can be adopted for NGST applications.

Choi, Sang H.↗