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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Portable interactive visualization of large-scale simulations in geotechnical engineering using Unity3D

Development in large-scale geotechnical engineering simulation places tremendous demand for efficient visualization of such simulation data. This study presents a lightweight software tool, i.e. Geotechnical Interactive Visualization (GIV), as a solution to this challenge, which achieves efficient interactive visualization of large-scale simulations data in geotechnical engineering. Visualization data flow and algorithms specifically optimized for common geotechnical engineering applications are implemented in GIV. GIV can visualize geotechnical structure models with time-varying attributes attached to mesh with fixed topology, and also models with time-varying mesh topologies but no attributes attached, the two most common visualization tasks in geotechnical engineering. Furthermore, challenges for large-scale simulation data visualization, including parallel simulation data redundancy, massive data size, dynamic user interaction, and portability are overcome via specifically designed algorithms for simulation data preprocessing and optimized visualization modules using the powerful 3D rendering and interactive game engine Unity3D. Comparison of GIV with several widely used visualization tools for the visualization of large-scale idealized datasets and realistic geotechnical simulations highlights the visualization efficiency, smooth interactivity, and lightweight features of GIV.

42 ENGINEERING↗
DOE OSTI2013

Optimal guidance law in quantum mechanics

Following de Broglie’s idea of a pilot wave, this paper treats quantum mechanics as a problem of stochastic optimal guidance law design. The guidance scenario considered in the quantum world is that an electron is the flight vehicle to be guided and its accompanying pilot wave is the guidance law to be designed so as to guide the electron to a random target driven by the Wiener process, while minimizing a cost-to-go function. After solving the stochastic optimal guidance problem by differential dynamic programming, we point out that the optimal pilot wave guiding the particle’s motion is just the wavefunction Ψ(t,x), a solution to the Schrödinger equation; meanwhile, the closed-loop guidance system forms a complex state–space dynamics for Ψ(t,x), from which quantum operators emerge naturally. Quantum trajectories under the action of the optimal guidance law are solved and their statistical distribution is shown to coincide with the prediction of the probability density function Ψ{sup ∗}Ψ. -- Highlights: •Treating quantum mechanics as a pursuit-evasion game. •Reveal an interesting analogy between guided flight motion and guided quantum motion. •Solve optimal quantum guidance problem by dynamic programming. •Gives a formal proof of de Broglie–Bohm’s idea of a pilot wave. •The optimal pilot wave is shown to be a wavefunction solved from Schrödinger equation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Survival probabilities in the Sisyphus random walk model with absorbing traps

We analyze the dynamics of the Sisyphus random walk model, a discrete Markov chain in which the walkers may randomly return to their initial position x{sub 0}. In particular, we present a remarkably compact derivation of the time-dependent survival probability function S(t;x{sub 0}) which characterizes the random walkers in the presence of an absorbing trap at the origin. The survival probabilities are expressed in a compact mathematical form in terms of the x{sub 0}-generalized Fibonacci-like numbers G{sub t}{sup (x{sub 0})}. Interestingly, it is proved that, as opposed to the standard random walk model in which the survival probabilities depend linearly on the initial distance x{sub 0} of the walkers from the trap and decay asymptotically as an inverse power of the time, in the Sisyphus random walk model the asymptotic survival probabilities decay exponentially in time and are characterized by a non-trivial (non-linear) dependence on the initial gap x{sub 0} from the absorbing trap. We use the analytically derived results in order to analyze the underlying dynamics of the ‘survival-game’, a highly risky investment strategy in which non-absorbed agents receive a reward P(t) which gradually increases in time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Introduction to the special section on learning and security for multi-agent systems

This report features six articles that provide an overview of the emerging research topics at the intersection learning, security, and multi-agent systems. Recent years have witnessed a surge in the number of works at their intersections, and they have appeared in system and control communities as well as many other communities in artificial intelligence, cyber–physical systems, and economics. The articles in this special section give accessible and comprehensive tutorials and surveys for a broad systems and control audience, covering topics including adversarial machine learning, multi-agent reinforcement learning, cyber resilience, resilient control systems, and game design. It is hopeful that this special section will spawn future interest and cross-disciplinary collaborations in this emerging transdisciplinary research area.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Thermodynamic and liquid profiling during the 2010 Winter Olympics

Tropospheric observations by a microwave profiling radiometer and six-hour radiosondes were obtained during the Alpine Venue of the 2010 Winter Olympic Games at Whistler, British Columbia, by Environment Canada. The radiometer provided continuous temperature, humidity and liquid (water) profiles during all weather conditions including rain, sleet and snow. Gridded analysis was provided by the U.S. National Oceanic and Atmospheric Administration. We compare more than two weeks of radiometer neural network and radiosonde temperature and humidity soundings including clear and precipitating conditions. Corresponding radiometer liquid and radiosonde wind soundings are shown. Close correlation is evident between radiometer and radiosonde temperature and humidity profiles up to 10 km height and among southwest winds, liquid water and upper level thermodynamics, consistent with up-valley advection and condensation of moist maritime air. We compare brightness temperatures observed by the radiometer and forward-modeled from radiosonde and gridded analysis. Radiosonde-equivalent observation accuracy is demonstrated for radiometer neural network temperature and humidity retrievals up to 800 m height and for variational retrievals that combine radiometer and gridded analysis up to 10 km height

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Uncertainty quantification and optimization of precipitating hydrometeor parameters for winter precipitation in a cloud microphysics scheme

The precipitating hydrometeor parameters used in cloud microphysics schemes carry inherent uncertainties. The quantification of these uncertainties, together with parameter optimization, can significantly improve precipitation forecasts. This study investigates the effects of 13 parameters in the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) microphysics scheme, which define the hydrometeor characteristics such as fall velocity–diameter and mass–diameter relationships, as well as the shape parameter of the drop size distribution for precipitating particles such as rain, snow, and graupel on simulated winter precipitation. A comparison between the model's pre-defined parameters and observations from the International Collaborative Experiments for the PyeongChang 2018 Olympic and Paralympic winter games (ICE-POP 2018) field campaign reveals that the fall velocity–diameter relationship for rain, the mass–diameter relationships for snow and graupel, and the shape parameters for all precipitating particles in the WDM6 scheme deviate from the median values observed by the two-dimensional video disdrometer (2DVD). To quantify parameter sensitivities, a perturbed parameter ensemble (PPE) of 256 simulations was conducted within parameter ranges constrained by 2DVD observations for three winter precipitation cases. Bayesian optimization was then applied to identify parameter sets that minimized the root mean square error (RMSE) for each case, achieving reductions of up to 30.2 %. These results demonstrate that ensemble-based uncertainty quantification and parameter optimization can help identify key parameters and provide a pathway to improving precipitation simulation performance. In addition, measurement sites can be strategically selected based on regions that show high sensitivity to variations in hydrometeor characteristic parameters.

Bayesian optimization↗
DOE OSTI2023

Reinforcement learning building control approach harnessing imitation learning

Reinforcement learning (RL) has shown significant success in sequential decision making in fields like autonomous vehicles, robotics, marketing and gaming industries. This success has attracted the attention to the RL control approach for building energy systems which are becoming complicated due to the need to optimize for multiple, potentially conflicting, goals like occupant comfort, energy use and grid interactivity. However, for real world applications, RL has several drawbacks like requiring large training data and time, and unstable control behavior during the early exploration process making it infeasible for an application directly to building control tasks. To address these issues, an imitation learning approach is utilized herein where the RL agents starts with a policy transferred from accepted rule based policies and heuristic policies. This approach is successful in reducing the training time, preventing the unstable early exploration behavior and improving upon an accepted rule-based policy - all of these make RL a more practical control approach for real world applications in the domain of building controls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Including health in environmental impact assessments of three mega transport projects in Sydney, Australia: A critical, institutional, analysis

This article details how health impacts came to be assessed in three mega, billion dollar, transport infrastructure projects, two road tunnels and one light rail, in Sydney Australia. The known health impacts of transport decisions include environmental, behavioural and social factors. EIA practice prioritises environmental risks, and there has been scant attention to understanding why this is persistently the case. Here we provide a critical theory lens, using critical realist methodology, to analyse empirical data collected through interviews and documents for the three cases. Our analysis focusses on EIA practice within its institutional context, building on ‘new institutional’ approaches to policy analysis that emphasise actors (the stakeholders involved in the EIA), structures (the ‘rules of the game’ that influence practice in systems), and power. We find that the various actors engaged in the EIAs principally to address particular goals that were pre-determined by the system in which they worked or belonged. Structurally, each EIA was undertaken as a compliance process relatively late in the planning process. Considering project options was not part of the EIA's purpose. Resources to undertake the EIAs were provided by those funding the projects (“the proponents”) and determined the types of issues to be considered. The full range of links between transport and health were not identified. Concerning power, health impacts were considered through inter-professional technical negotiation. The inability to engage in the fundamental options driving projects meant impacted communities questioned the validity of the EIA, and the health assessment within this. Our institutional analysis provides important knowledge about how the EIAs preferenced a focus on specific health risks to the detriment of the known broader determinants that shape the health impacts of transport.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Inverse reinforcement learning control for building energy management

Reinforcement learning (RL) based control is widely considered a promising approach in building automation and control as it has demonstrated the potential to deal with complex objectives in adjacent domains like robotics, autonomous vehicles, gaming applications, and advertisement recommendations. When applied to any environment, model-free RL learns to improve its control performance over time without requiring a control model, by receiving and then analyzing feedback from the building environment after each control action. Operational objectives are becoming increasingly complex through the simultaneous consideration of thermal comfort, carbon emissions, grid services, and indoor air quality. In this context, conventional rule-based control approaches are proving sub-optimal, mostly heuristic, and inadequate. The model-free and self learning nature of RL appears promising and attractive as it may address the scalability issues associated with advanced control approaches. However, it suffers from long training times and unstable control behavior during the early stages of its learning process, which makes it unsuitable to be applied directly to buildings. This paper addresses these issues using an inverse reinforcement learning approach (IRL), a technique utilized to learn the objective of a controller agent which is considered an expert in its respective domain. Here, we consider a rule-based control as the expert demonstrator. IRL is different from a direct imitation (i.e., direct mapping of states to actions) of control actions as it tries to find the underlying intent of an expert's policy, providing the controller with a better-generalized policy for unseen states or environments with slightly different dynamics. This approach propels the RL controller's policy to levels similar to or better than that of a rule-based policy before it starts learning by interacting with the building. This makes RL for building energy management applications more practical as it prevents the erratic and exploratory behavior in the initial training period, simultaneously speeding up the learning process when compared to applying an untrained RL agent directly to a building environment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Effects of heavy metals on biomarkers for oxidative stress in Griffon vulture (Gyps fulvus)

Metals are involved in the formation of reactive oxygen species (ROS) which may result in metal-related oxidative stress that can lead to oxidative damage to lipids, DNA and proteins. It is necessary to understand the mechanisms of metal toxicity in wild birds, and the concentrations that cause effects on oxidative stress biomarkers. The aim of this study is to assess the concentrations of lead (Pb), cadmium (Cd), mercury (Hg), copper (Cu) and zinc (Zn) with regards to oxidative stress in blood samples of 66 Griffon vultures (Gyps fulvus) from two areas of the Autonomous Community of Valencia (East of Spain). The two study areas (Alcoy n=36 and Cinctorres n=30) were selected as random locations of interest that had not yet been studied, and are feeding stations where supplementary food, mainly of pork origin, is provided for vultures. Given that the two study areas are not considered polluted sites, we expected to find low metal concentrations. However, there are no known threshold concentrations at which metals can affect antioxidant systems, and low metal levels may have an effect on antioxidant biomolecules. In this study, since sampling was done at the beginning of the hunting season, the low Pb levels found in most Griffon vultures from Alcoy and Cinctorres (median=12.37 and 16.26 μg/dl, respectively) are suggestive of background levels usually found in vultures that feed on pork carcasses all year round. The ingestion of game meat with bullet fragments in carcasses or with Pb shots embedded in the flesh could be the cause of the high blood Pb concentrations found in three vultures from Cinctorres (83, 290 and 362 μg/dl). Griffon vultures feeding in Cinctorres had enhanced CAT and GST activities and tGSH concentrations, which may be interpreted as protective response against the higher TBARS levels. This study provides threshold concentrations at which metals affect antioxidant system derived from 66 samples of Griffon vulture. Blood Cd concentrations greater than 0.05 μg/dl produced an induction of 33% in GPx and of 44% in CAT activity in erythrocytes of vultures from Alcoy. Hg concentrations in blood higher than 3 μg/dl produced an induction of 10% in SOD activity. Concentrations of Pb above 15 µg/dl in blood produced an inhibition of 12.5% in GPx and 11.3% in CAT activity, and a TBARS induction of 10.7% in erythrocytes of Griffon vultures. - Highlights: • Except for 3 Griffon vultures, lead levels could be considered background levels. • Three vultures may be exposed to meat with bullet fragments (blood Pb=83–362 μg/dl). • Blood Cd levels≥0.05 μg/dl caused an induction of GPx and CAT activity (33% and 44%). • Blood Hg levels≥3 μg/dl caused an induction of 10% in SOD activity. • Blood Pb≥15 µg/dl caused an inhibition of GPx and CAT activity and a TBARS induction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Source identification of human exposure to lead in nine Cree Nations from Quebec, Canada (Eeyou Istchee territory)

Highlights: • Lead exposure remains a public health issue, especially in Indigenous communities who may rely on a subsistence diet. • We investigate sources of lead exposure in all 9 First Nations in Quebec, Canada. • Elevated levels of lead were found to be associated with hunting practices and consumption of traditional foods. • Educational campaigns and cost reductions in non-toxicsubstitutes may aid in reducing lead exposure. While policies to decrease lead in the environment have been implemented to reduce human exposure to various lead sources, the use of lead ammunition to harvest wild game may continue to contribute significantly to human blood lead levels (BLLs). As part of a multi-community environment-and-health study, BLLs representing all age groups were evaluated in the nine Cree Nations located in the James and Hudson Bay regions of Quebec, Canada. Personal, market food, traditional food and 24-h recall questionnaires were administered. Predictor variables were assessed for various exposure sources, including diet and hunting practices. Elevated BLLs were observed in association with increased hunting status, use of firearms and leaded ammunition, and consumption of traditional foods. Significant differences were observed between all communities, age groups and sexes. Recommendations include educational campaigns that promote switching to non-lead ammunition and, if lead ammunition continues to be used, careful removal from tissues of pellets, bullet fragments and ammunition paths.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A hierarchical framework for aggregating grid-interactive buildings with thermal and battery energy storage

The behind-the-meter (BTM) thermal and battery energy storage can help improve energy efficiency, reduce energy costs, and enhance energy resilience, particularly in rural areas and for disadvantaged communities. Aggregating numerous BTM energy storage systems can act as a price influencer with a significant source of load shifting and peak demand reduction. An integrated and scalable control mechanism is required to effectively utilize energy storage systems and flexible building loads to maximize the economic benefits, considering various distribution system constraints. Here, this paper presents an innovative hierarchical coordination framework for energy storage and flexible load in buildings, considering various factors such as electricity prices, thermal comfort, and distribution system modeling and constraints. At the upper level, a distribution system operator optimizes the power flow to minimize its power procurement costs from the electricity wholesale market, while at the lower level, aggregators determine the optimal dispatch of battery and thermal energy storage systems in multiple buildings on behalf of end-users to minimize operating costs according to the power prices. These problems are solved using a game-theoretic approach through negotiations between the distribution system operator and aggregators as a bi-level decision model. Simulation case studies have been performed for a test distribution network with a number of building end-users using energy storage systems to quantify the performance of aggregators. The results demonstrate that the proposed strategy can reduce peak load for a reliable electricity distribution network while saving electricity bills for customers.

25 ENERGY STORAGE↗
DOE OSTI2016

Hybrid massively parallel fast sweeping method for static Hamilton–Jacobi equations

The fast sweeping method is a popular algorithm for solving a variety of static Hamilton–Jacobi equations. Fast sweeping algorithms for parallel computing have been developed, but are severely limited. In this work, we present a multilevel, hybrid parallel algorithm that combines the desirable traits of two distinct parallel methods. The fine and coarse grained components of the algorithm take advantage of heterogeneous computer architecture common in high performance computing facilities. We present the algorithm and demonstrate its effectiveness on a set of example problems including optimal control, dynamic games, and seismic wave propagation. We give results for convergence, parallel scaling, and show state-of-the-art speedup values for the fast sweeping method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Enforcing constraints for interpolation and extrapolation in Generative Adversarial Networks

Generative Adversarial Networks (GANs) are becoming popular choices for unsupervised learning. At the same time there is a concerted effort in the machine learning community to expand the range of tasks in which learning can be applied as well as to utilize methods from other disciplines to accelerate learning. With this in mind, in the current work we suggest ways to enforce given constraints in the output of a GAN both for interpolation and extrapolation. The two cases need to be treated differently. For the case of interpolation, the incorporation of constraints is built into the training of the GAN. The incorporation of the constraints respects the primary game-theoretic setup of a GAN so it can be combined with existing algorithms. However, it can exacerbate the problem of instability during training that is well-known for GANs. We suggest adding small noise to the constraints as a simple remedy that has performed well in our numerical experiments. The case of extrapolation (prediction) is more involved. First, we employ a modified interpolation training process that uses noisy data but does {\it not} necessarily enforce the constraints during training. Second, the resulting modified interpolator is used for extrapolation where the constraints are enforced after each step through projection on the space of constraints.

Stinis, Panagiotis↗
DOE OSTI2021

Probing the electrolyte/electrode interface with vibrational sum frequency generation spectroscopy: A review

Over the past decades, Lithium-ion batteries have seen extensive improvements, and as a result are now the primary choice in many applications for their power, energy, and durability. In recent years, battery cost has reduced by orders of magnitude through adoption of new materials and processes. Despite these advances, interfaces in these battery systems are yet to be fully understood. This is seen as a major limitation to further increase cycle life, calendar life, abuse tolerance, and performances. A major obstacle is a lack of comprehensive understanding of the complex dynamic chemical processes occurring at the electrolyte/electrode interface. In this context, vibrational sum frequency generation (vSFG) spectroscopy possesses the unique capability of probing a molecularly thin interfacial layer to obtain molecular-level information through nonlinear optical interaction. Probing the molecular level processes at the interfaces using such a versatile technique would be a game changer in the advancement of current battery research knowledge. This review article summarizes recent vSFG studies on the electrolyte/electrode interface of various electrode materials and nonaqueous electrolytes for LIBs and discusses future research perspectives. Finally, overall, this focused review highlights the advantages and versatility of vSFG that can be used to further advance present-day battery research.

25 ENERGY STORAGE↗
DOE OSTI2024

Machine learning-guided design of direct methanol fuel cells with a platinum group metal-free cathode

Direct methanol fuel cells (DMFCs) offer a promising solution for clean electricity generation, particularly in small electronics and remote auxiliary power units. However, optimizing their efficiency and performance is challenging due to the complex interactions between various factors. Here, we present a novel approach that integrates experiments with machine learning to model and predict the performance of these fuel cells using atomically dispersed platinum group metal (PGM)-free catalysts at the cathode. Further, our machine learning models, trained on diverse input parameters, allow for the comprehensive optimization of DMFC performance prior to fabrication and testing. Through extensive experimental validation, we demonstrate that this data-driven approach accurately predicts key performance metrics, such as maximum power output and polarization curves. By combining our models with interpretable game-theory methods, we provide deep insights into the factors governing fuel cell performance, ultimately paving the way for the design of scalable and efficient DMFC technologies.

25 ENERGY STORAGE↗
DOE OSTI2020

Tailoring conductive networks within hollow carbon nanospheres to host phosphorus for advanced sodium ion batteries

The formidable sustainability challenges in advancing energy storage technologies call for game-changing research in battery designs. The previous pursuing of novel cathode materials with high redox potentials impedes the vast applications due to the simultaneous electrolyte decomposition at high potentials, though they are expected to deliver high specific capacities. Eventually, people start thinking in an opposite way, desirable anode materials with low redox potentials can also own high specific capacities. Among all the promising candidates, phosphorus-based anodes in sodium ion batteries (SIBs) have received considerable attention owing to the low cost and relatively high natural abundance of phosphorus. More importantly, phosphorus can store three sodium atoms and enable a high theoretical capacity of 2596 mAh g -1 , which overwhelms any other SIB anode currently available. However, the poor electronic conductivity and large volume change of phosphorus during cycling severely deteriorate battery performance. The most widely used strategy is to confine phosphorus within well-designed carbon hosts. Here, we thereby introduce a new type of porous hollow carbon with conductive-network interior as phosphorus host, which not only improves the electrical conductivity, but also creates enough interior surface for maximizing phosphorus utilization and shortening the ion's diffusion distance, compared to those conventional hollow carbon hosts. Therefore, the as-prepared red phosphorus-carbon spheres composites (RP/CS) exhibit superior rate performance (similar to 1083 mAh g -1 at 4 A g -1 , similar to 837 mAh g -1 even at 8 A g -1 ) and excellent cycle life (1027 mAh g -1 at 4 A g -1 more than 2000 cycles).

25 ENERGY STORAGE↗
DOE OSTI2019

Exclusive meson photo- and electro-production, a window on the structure of hadronic matter

At high energy, exclusive meson photo- and electro-production give access to the structure of hadronic matter. At low momentum transfers, the exchange of a few Regge trajectories leads to a comprehensive account of the cross-sections. Among these trajectories, which are related to the mass spectrum of families of mesons, the Pomeron plays an interesting role as it is related to glue-ball excitations. At high momentum transfers, the exchange of these collective excitations is expected to reduce to the exchange of their simplest (quark or gluon) components. However, contributions from unitarity rescattering cuts are relevant even at high energies. In the JLab energy range, the asymptotic regime, where the players in the game are current quarks and massless gluons has not been reached yet. One has to rely on more effective degrees of freedom adapted to the scale of the probe. A consistent picture, the Partonic Non-Perturbative Regime, is emerging. The properties of its various components (dressed propagators, effective coupling constants, quark wave functions, shape of the Regge trajectories, etc) provide us with various links to hadron properties. I will review the status of the field, will put in perspective the current achievements at JLab, SLAC and Hermes, and will assess future developments that are made possible by continuous electron beams at higher energies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗