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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Adaptive nonlinear polynomial neural networks for control of boundary layer/structural interaction

The acoustic pressures developed in a boundary layer can interact with an aircraft panel to induce significant vibration in the panel. Such vibration is undesirable due to the aerodynamic drag and structure-borne cabin noises that result. The overall objective of this work is to develop effective and practical feedback control strategies for actively reducing this flow-induced structural vibration. This report describes the results of initial evaluations using polynomial, neural network-based, feedback control to reduce flow induced vibration in aircraft panels due to turbulent boundary layer/structural interaction. Computer simulations are used to develop and analyze feedback control strategies to reduce vibration in a beam as a first step. The key differences between this work and that going on elsewhere are as follows: that turbulent and transitional boundary layers represent broadband excitation and thus present a more complex stochastic control scenario than that of narrow band (e.g., laminar boundary layer) excitation; and secondly, that the proposed controller structures are adaptive nonlinear infinite impulse response (IIR) polynomial neural network, as opposed to the traditional adaptive linear finite impulse response (FIR) filters used in most studies to date. The controllers implemented in this study achieved vibration attenuation of 27 to 60 dB depending on the type of boundary layer established by laminar, turbulent, and intermittent laminar-to-turbulent transitional flows. Application of multi-input, multi-output, adaptive, nonlinear feedback control of vibration in aircraft panels based on polynomial neural networks appears to be feasible today. Plans are outlined for Phase 2 of this study, which will include extending the theoretical investigation conducted in Phase 2 and verifying the results in a series of laboratory experiments involving both bum and plate models.

Parker, B. Eugene, Jr.↗
DOE OSTI2022

ASPIRES: Airport Shuttle Planning and Improved Routing Event-driven Simulation

Most of the existing traffic simulation packages require significant calibration work to be able to reflect reality. To evaluate special operations including emerging technologies, a microscopic simulation that tracks detailed interactions of all the elements of the traffic systems is usually needed. This type of simulation is usually computationally demanding. This work developed an Airport Shuttle Planning and Improved Routing Event-driven Simulation (ASPIRES) package to simulate and evaluate current, potential, and future airport shuttle operations. Here, the simulation was driven by data and thus did not require much calibration effort. The discrete-event simulation nature of ASPIRES makes the simulation computationally efficient. Simulating 1 day of shuttle operations takes less than 2s. The study site of this work is the Dallas/Fort Worth International Airport in the U.S. The shuttle service that connects the five terminals of the airport and the rental car center was studied. Travel times, dwell times, and passenger arrivals were simulated using empirical distributions derived mainly from real data to capture the stochastic nature of the rental car center shuttle bus operations. Data on bus miles traveled, bus energy consumption, passenger wait times, and passengers left behind at stops were collected to study the trade-off between energy use and passenger experience. Electric bus and on-demand bus operations were also included. The simulation outputs can show passengers statistics at terminals, shuttles statistics, and charging station statistics. ASPIRES cannot be used to model a generic traffic system but is well-suited for fleet systems.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2003

A Eulerian-Lagrangian Model to Simulate Two-Phase/Particulate Flows

Figure 1 shows a snapshot of liquid fuel spray coming out of an injector nozzle in a realistic gas-turbine combustor. Here the spray atomization was simulated using a stochastic secondary breakup model (Apte et al. 2003a) with point-particle approximation for the droplets. Very close to the injector, it is observed that the spray density is large and the droplets cannot be treated as point-particles. The volume displaced by the liquid in this region is significant and can alter the gas-phase ow and spray evolution. In order to address this issue, one can compute the dense spray regime by an Eulerian-Lagrangian technique using advanced interface tracking/level-set methods (Sussman et al. 1994; Tryggvason et al. 2001; Herrmann 2003). This, however, is computationally intensive and may not be viable in realistic complex configurations. We therefore plan to develop a methodology based on Eulerian-Lagrangian technique which will allow us to capture the essential features of primary atomization using models to capture interactions between the fluid and droplets and which can be directly applied to the standard atomization models used in practice. The numerical scheme for unstructured grids developed by Mahesh et al. (2003) for incompressible flows is modified to take into account the droplet volume fraction. The numerical framework is directly applicable to realistic combustor geometries. Our main objectives in this work are: Develop a numerical formulation based on Eulerian-Lagrangian techniques with models for interaction terms between the fluid and particles to capture the Kelvin- Helmholtz type instabilities observed during primary atomization. Validate this technique for various two-phase and particulate flows. Assess its applicability to capture primary atomization of liquid jets in conjunction with secondary atomization models.

Apte, S. V.↗
DOE OSTI2025

Energetic Electron Transport in Magnetized Plasma with Magnetic Islands (Final Technical Report)

The main scientific goal of this project was to investigate the interactions between energetic electrons and magnetic islands in magnetized plasmas from lab to space. The proposed plan of addressed the following specific objectives: (1) Determine if energetic electrons are trapped by magnetic islands. Specifically, test the hypothesis that energetic electrons are trapped near island O-points due to stable orbits and de-confined near island X-points due to X-point tangles. (2) Determine how electron transport changes with island width and location. Specifically, test the hypothesis that electrons are accelerated by contracting magnetic islands through a Fermi acceleration process. (3) Assess how electron transport is affected by island dynamics, including island rotation, bifurcation, and/or island overlap. Specifically, test the hypothesis that electrons are deconfined and possibly accelerated during island rotations, bifurcations, and overlap due to stochastization of the magnetic field lines.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Model Agnostic Bayesian Framework for Online Anomaly/Event Detection in PMU Data

Phasor measurement units (PMU) are integral to the modernization and automation plan of the electric power industry. A PMU data signature contains system-level events (e.g., faults, generation/load change, etc.) and any measurement/device-related errors. Therefore, the reliable and resilient operation of power systems is equivalent to the quality of the PMU data and the situation awareness provided by its data signature. Despite recent progress, current state-of-the-art methods are not fool-proof and have certain limitations tracing an error/abnormality to sensor sub-components and grid systems. This is because of technical challenges imposed by the scarcity of the labeled information, loss of data quality, and non-stationarity of data. In this paper, we consider the online PMU data stream as an output of a stochastic process and pose the anomaly/event detection as a changepoint detection problem dealing with detecting parameter changes in the underlying stochastic processes. The proposed model-agnostic framework relies on: (a) feature extraction utilizing the minimum volume enclosing ellipsoids (MVEE) method from raw PMU observations and (b) a Bayesian framework of changepoint detection. The validity of the proposed methodology is discussed through numerical experiments on real-world utility-scale PMU data.

Hossain, Ramij Raja↗
DOE OSTI2021

A Hybrid Energy System Workflow for Energy Portfolio Optimization

This manuscript develops a workflow, driven by data analytics algorithms, to support the optimization of the economic performance of an Integrated Energy System. The goal is to determine the optimum mix of capacities from a set of different energy producers (e.g., nuclear, gas, wind and solar). A stochastic-based optimizer is employed, based on Gaussian Process Modeling, which requires numerous samples for its training. Each sample represents a time series describing the demand, load, or other operational and economic profiles for various types of energy producers. These samples are synthetically generated using a reduced order modeling algorithm that reads a limited set of historical data, such as demand and load data from past years. Numerous data analysis methods are employed to construct the reduced order models, including, for example, the Auto Regressive Moving Average, Fourier series decomposition, and the peak detection algorithm. All these algorithms are designed to detrend the data and extract features that can be employed to generate synthetic time histories that preserve the statistical properties of the original limited historical data. The optimization cost function is based on an economic model that assesses the effective cost of energy based on two figures of merit: the specific cash flow stream for each energy producer and the total Net Present Value. An initial guess for the optimal capacities is obtained using the screening curve method. The results of the Gaussian Process model-based optimization are assessed using an exhaustive Monte Carlo search, with the results indicating reasonable optimization results. The workflow has been implemented inside the Idaho National Laboratory’s Risk Analysis and Virtual Environment (RAVEN) framework. The main contribution of this study addresses several challenges in the current optimization methods of the energy portfolios in IES: First, the feasibility of generating the synthetic time series of the periodic peak data; Second, the computational burden of the conventional stochastic optimization of the energy portfolio, associated with the need for repeated executions of system models; Third, the inadequacies of previous studies in terms of the comparisons of the impact of the economic parameters. The proposed workflow can provide a scientifically defendable strategy to support decision-making in the electricity market and to help energy distributors develop a better understanding of the performance of integrated energy systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2022

Low-Earth Orbit Trajectory Optimization in the Presence of Atmospheric Uncertainty

The previous 20 to 25 years have seen a tremendous increase in space exploration, and with that an increase in the level of logistics planning needed to ensure mission success. For spacecraft that are designed to be periodically re-supplied, a key logistics consumable is propellant, as it constitutes the greatest up-mass on re-supply vehicles. A trajectory design strategy is therefore desired that minimizes propellant usage in order to ease the demand for propellant re-supply missions. This thesis develops such a strategy in three stages, and uses the International Space Station (ISS) as its testbed, as no other LEO spacecraft is more challenging from a space logistics standpoint. First, the ISS trajectory planning problem is formulated as a constrained burn optimization problem assuming a deterministic atmosphere. The cost function is total ∆v, with constraints imposed on longitude of ascending viii node (LAN) and semi-major axis (SMA) altitude. Analytic derivatives are constructed for both the cost and constraints, which are necessary given the 6-week to 2-year time frames being considered. A gradient-based optimizer is then utilized to find locally-optimal solutions to real-world ISS trajectory planning problems. Second, atmospheric uncertainty is addressed by constructing a probabilistic model of space weather data using Gaussian Processes (GPs). Bayesian inference is performed using the GP model to generate mean and covariance estimates for space weather predictions, whose pedigree is assessed against test data. The predictions are then mapped into atmospheric density via the analytic Jacchia-Roberts density model, and the effect of space weather uncertainty on orbital lifetime is examined. Third, an ISS burn execution uncertainty model is developed. This model, along with the space weather uncertainty model, are deployed in a linear covariance analysis to ascertain their combined effect on LAN and SMA altitude dispersions. The deterministic constraints from the original problem are re-formulated as stochastic constraints, where now the constraint uncertainty interval is required to fall within specified bounds. An updated optimization framework is constructed using the original ∆v cost function along with the stochastic constraints to solve the trajectory optimization problem under atmospheric uncertainty. Finally, the complete architecture is summarized for deployment in an operational setting.

Trajectory Optimization↗
DOE OSTI2023

Life cycle assessment of railway ties fabricated with ductile cementitious composites and carbonation curing

This paper evaluates the lifecycle economic and environmental benefits of implementing CO 2 utilization and storage within advanced engineered cementitious composite (ECC) railway ties. Using CO 2 -treated ECC ties can yield lifecycle benefits primarily due to enhanced material properties – increased lifespan in this case – instead of due to the stored CO 2 that would otherwise enter the atmosphere. Sequestration-based policies such as 45Q in the United States would therefore not incentivize deployment of ECC railway ties, despite their considerable CO 2 avoidance opportunities. To reach these conclusions, cradle-to-grave lifecycle models were developed for ECC ties and conventional concrete ties and evaluated under 1000 possible use-phase scenarios. The models incorporated premature tie failures – consistent with real-world observations – that were used to study a wide range of non-linear impacts arising from the random nature of tie failures and replacements. The results show that past studies that neglected premature failure of ties may have underestimated lifecycle greenhouse gas (GHG) emissions of concrete rail ties by nearly three times. Overall, servicing a track with ECC ties instead of concrete ties can reduce the lifecycle costs and GHG emissions by 12% and 21% respectively, based on median values of 1000 model run results. The expected benefits would be larger for entities like Amtrak that plan to expand concrete tie infrastructure despite significant challenges with premature concrete tie failures. Furthermore, the results of this study suggest that the lifespan of ECC ties needs to be at least 25% longer than concrete ties to achieve net lifecycle benefits. The possibility of this should be tested and confirmed under real-world conditions.

42 ENGINEERING↗
NASA NTRS1998

Study of a Simulation Tool to Determine Achievable Control Dynamics and Control Power Requirements with Perfect Tracking

This paper contains a study of two methods for use in a generic nonlinear simulation tool that could be used to determine achievable control dynamics and control power requirements while performing perfect tracking maneuvers over the entire flight envelope. The two methods are NDI (nonlinear dynamic inversion) and the SOFFT(Stochastic Optimal Feedforward and Feedback Technology) feedforward control structure. Equivalent discrete and continuous SOFFT feedforward controllers have been developed. These equivalent forms clearly show that the closed-loop plant model loop is a plant inversion and is the same as the NDI formulation. The main difference is that the NDI formulation has a closed-loop controller structure whereas SOFFT uses an open-loop command model. Continuous, discrete, and hybrid controller structures have been developed and integrated into the formulation. Linear simulation results show that seven different configurations all give essentially the same response, with the NDI hybrid being slightly different. The SOFFT controller gave better tracking performance compared to the NDI controller when a nonlinear saturation element was added. Future plans include evaluation using a nonlinear simulation.

Ostroff, Aaron J.↗
DOE OSTI2020

Formulation and solution approach for calibrating activity-based travel demand model-system via microsimulation

This study addresses the problem of calibrating utility-maximizing nested logit activity-based travel demand model-systems. After estimation, it is common practice to use aggregate measurements to calibrate the estimated model-system’s parameters prior to their application in transportation planning, policy making, and operations. However, calibration of activity-based model-systems has received much less attention. Existing calibration approaches are myopic heuristics in the sense that they do not consider the fundamental inter-dependencies among choice-models and do not have a systematic way to adjust model parameters. Also, other purely simulation-based approaches do not perform well in large-scale applications. In this study, we focus on utility-maximizing nested logit activity-based model-systems and calibrating aggregate statistics such as activity shares, mode shares, time-dependent & mode-specific OD flows, and time-dependent & mode-specific sensor counts. We formulate the calibration problem as a simulation-based optimization problem and propose a stochastic gradient-based solution procedure to solve it. The solution procedure relies on microsimulation to calculate expectations of the aggregate statistics of interest to the calibration problem. Additionally, we derive approximate analytical expressions for the gradient of the objective function —that are evaluated through microsimulation on mini-batches of the population. The proposed solution procedure is sensitive to the fundamental structure of the activity-based model-system and is non-myopic in considering the dependencies across its model components. The formulated optimization problem is non-convex, highly nonlinear, and potentially has multiple-minima. Lastly, we show —through a real-world application— that the proposed solution procedure outperforms other state-of-the-art purely simulation-based optimization approaches in terms of computational efficiency, stability, and convergence. We also compare various gradient-based solution algorithms to determine the best algorithm to update the parameters. This work has the potential to facilitate wider and easier application of activity-based model-systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

The root cause of disruptive NTMs and paths to stable operation in DIII-D ITER baseline scenario plasmas

Analyses of the DIII-D ITER Baseline Scenario database support that the disruptive m,n=2,1 magnetic islands are pressure gradient driven, non-linear instabilities seeded in a sequence of stochastic transient magnetic perturbations, and that the current profile relaxation does not affect the m,n=2,1 island onset rate. At low torque, these Neoclassical Tearing Modes are most commonly seeded by non-linear 3-wave coupling when the differential rotation between the q=1 & q=2 rational surfaces approaches zero. Lack of statistically significant difference between the current profiles of stable and unstable states, as well as lack of correlation between the tearing mode onset rate and the current profile relaxation both reject causality between the current profile evolution and the 2,1 magnetic island onsets in these plasmas. These support that preserving the differential rotation between the q=1 and q=2 rational surfaces is key to long pulse stable operation in the plasma scenario planned for ITER, while optimization of the current profile within the explored parameter space may lead to much weaker improvements than sustaining the differential rotation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2014

Improving Sensorimotor Function Using Stochastic Vestibular Stimulation

Astronauts experience sensorimotor changes during spaceflight, particularly during G-transition phases. Post flight sensorimotor changes may include postural and gait instability, spatial disorientation, and visual performance decrements, all of which can degrade operational capabilities of the astronauts and endanger the crew. Crewmember safety would be improved if these detrimental effects of spaceflight could be mitigated by a sensorimotor countermeasure and even further if adaptation to baseline could be facilitated. The goal of this research is to investigate the potential use of stochastic vestibular stimulation (SVS) as a technology to improve sensorimotor function. We hypothesize that low levels of SVS will improve sensorimotor performance through stochastic resonance (SR). The SR phenomenon occurs when the response of a nonlinear system to a weak input signal is optimized by the application of a particular nonzero level of noise. Two studies have been initiated to investigate the beneficial effects and potential practical usage of SVS. In both studies, electrical vestibular stimulation is applied via electrodes on the mastoid processes using a constant current stimulator. The first study aims to determine the repeatability of the effect of vestibular stimulation on sensorimotor performance and perception in order to better understand the practical use of SVS. The beneficial effect of low levels of SVS on balance performance has been shown in the past. This research uses the same balance task repeated multiple times within a day and across days to study the repeatability of the stimulation effects. The balance test consists of 50 sec trials in which the subject stands with his or her feet together, arms crossed, and eyes closed on compliant foam. Varying levels of SVS, ranging from 0-700 micro A, are applied across different trials. The subject-specific optimal SVS level is that which results in the best balance performance as measured by inertial measurement units placed on the upper and lower torso of the subjects. Additionally, each individual’s threshold for illusory motion perception of suprasensory electrical vestibular stimulation is measured multiple times within and across days to better understand how multiple SVS test methods compare. The second study aims to demonstrate stochastic resonance in the vestibular system using a perception based motion recognition task. This task measures an individual’s velocity threshold of motion recognition using a 6-degree of freedom Stewart platform and a 3-down/1-up staircase procedure. For this study, thresholds are determined using 150 trials in the upright, head-centered roll tilt motion direction at a 0.2 Hz frequency. We aim to demonstrate the characteristic bell shaped curve associated with stochastic resonance with each subject’s motion recognition thresholds at varying SVS levels ranging from 0 to 1500 micro A. The curve includes the individual’s baseline threshold with no SVS, optimal or minimal threshold at some mid-level of SVS, and finally degraded or increased threshold at a high SVS level. An additional aim is to formally retest each subject at his or her individual optimal SVS level on a different day than the original testing for additional validity. The overall purpose of this research is to further quantify the effects of SVS on various sensorimotor tasks and investigate the practical implications of its use in the context of human space flight so that it may be implemented in the future as a component of a comprehensive countermeasure plan for adaptation to G-transitions.

Galvan, R. C.↗
DOE OSTI2020

Probabilistic impact of electricity tariffs on distribution grids considering adoption of solar and storage technologies

This study models the role of electricity tariffs on the long-term adoption of photovoltaic and storage technologies as well as the consequent impact on the distribution grid. An adoption model that captures the economic rationality of tariff-driven investments and considers the stochastic nature of individual consumers’ decisions is proposed. This model is then combined with a probabilistic load flow to evaluate the long-term impacts of the adoption on the voltage profiles of the distribution grid. To illustrate the methodology, different components of the electricity tariffs, including solar compensation mechanisms and time differentiation of Time-of-Use (ToU) rates, are evaluated, using a case study involving a section of a medium-voltage network with 118 nodes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1993

HL-20 operations and support requirements for the Personnel Launch System mission

The processing, mission planning, and support requirements were defined for the HL-20 lifting-body configuration that can serve as a Personnel Launch System. These requirements were based on the assumption of an operating environment that incorporates aircraft and airline support methods and techniques that are applicable to operations. The study covered the complete turnaround process for the HL-20, including landing through launch, and mission operations, but did not address the support requirements of the launch vehicle except for the integrated activities. Support is defined in terms of manpower, staffing levels, facilities, ground support equipment, maintenance/sparing requirements, and turnaround processing time. Support results were drawn from two contracted studies, plus an in-house analysis used to define the maintenance manpower. The results of the contracted studies were used as the basis for a stochastic simulation of the support environment to determine the sufficiency of support and the effect of variance on vehicle processing. Results indicate the levels of support defined for the HL-20 through this process to be sufficient to achieve the desired flight rate of eight flights per year.

Morris, W. D.↗
DOE OSTI2024

New Advances in Optical Stochastic Cooling

Recently, Optical Stochastic Cooling (OSC) became the first demonstrated method for ultra-high-bandwidth stochastic cooling. The initial experiments at Fermilab’s IOTA ring explored the essential physics of the method and demonstrated cooling, heating and manipulation of beams and single particles. Having been validated in practice, with continued development, OSC carries the potential for dramatic advances in the state-of-the-art performance and flexibility for beam cooling and control. The ongoing program at Fermilab is now focused on the development of an OSC system that includes high-gain optical amplification, which promises a two-order-of-magnitude increase in the strength of the OSC force. In this talk, we briefly review the results of the initial experimental campaign, describe the status of the conceptual and hardware designs for the amplified OSC system, report initial experimental results of our high-gain amplifier development, and explore near-term operational plans and use cases.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

A simple way to integrate distributed storage into a wholesale electricity market

Abstract Current plans to decarbonize the electric supply system imply that the generation from wind and solar sources will grow substantially. This growth will increase the uncertainty of system operations due to the inherent variability of these renewable sources, and as a result, more reserve capacity will be required to provide the ramping (flexibility) needed for reliable operations. This paper assumes that all of the increased uncertainty comes from wind farms on the grid, and it shows how distributed storage managed locally by aggregators can provide the ramping needed without introducing a separate market for flexibility. This can be accomplished when the aggregators minimize the expected daily cost of the energy purchased from the grid for their customers by submitting optimal bids into the wholesale market with high and low price thresholds for discharging and charging the storage. This model is illustrated using a stochastic multi-period security constrained optimal power flow together with realistic data for a reduction of the network in the Northeast Power Coordinating Council region of the United States. The results show that the bidding strategy for distributed storage provides ramping to the grid just as effectively as storage managed by a system operator.

Lamadrid, Alberto J.↗
DOE OSTI2021

Assessing the Relative Climate Impact of Carbon Utilization for Concrete, Chemical, and Mineral Production

Estimates show that 6.2 gigatons of carbon dioxide (CO2) can be captured and utilized across three pathways, concrete, chemical, and minerals, by 2050. However, it is difficult to compare the climate benefit across these three carbon capture and utilization (CCU) pathways to determine the most effective use of captured CO2. The life cycle assessment methods to evaluate the climate benefit of CCU chemicals should additionally account for the change in material properties of concrete due to CO2 utilization. Furthermore, with most CO2 utilization technologies being in the early stages of research and development, the uncertainty and variability in process and inventory data present a significant challenge in evaluating the climate benefit. We present a stochastically determined climate return on investment (ROI) metric to rank and prioritize CO2 utilization across 20 concrete, chemical and mineral pathways based on the realized climate benefit. We show that two concrete pathways, which use CO2 during concrete mixing, and two chemical pathways, which produce formic acid through hydrogenation of CO2 and carbon monoxide through dry reforming of methane, generate the greatest climate ROI and are the only CCU pathways with a higher likelihood of generating a climate benefit than a climate burden.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Data and Multistage Optimization for the New Grid

Three essential capabilities for using exascale computing resources on next generation power grid applications are: generating large renewable energy datasets, modeling damage and operations during and after extreme events, and employing multi-stage optimization for infrastructure planning. Powerscenarios, developed as part of the ExaSGD project, addresses these capabilities by enabling users to build synthetic wind farms for large test systems using numerical weather prediction-based data sources. We share examples of using Powerscenarios to build out wind farms on the ACTIVSg2000 test system, to enable simulated operations and emergency asset allocation during a hurricane strike, and to compute multi-stage infrastructure buildouts.

economic dispatch↗