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At least 577 records · Page 32

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NASA NTRS2013

Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex

Functional near infrared spectroscopy (fNIRS) is an emerging optical neuroimaging technology that indirectly measures neuronal activity in the cortex via neurovascular coupling. It quantifies hemoglobin concentration ([Hb]) and thus measures the same hemodynamic response as functional magnetic resonance imaging (fMRI), but is portable, non-confining, relatively inexpensive, and is appropriate for long-duration monitoring and use at the bedside. Like fMRI, it is noninvasive and safe for repeated measurements. Patterns of [Hb] changes are used to classify cognitive state. Thus, fNIRS technology offers much potential for application in operational contexts. For instance, the use of fNIRS to detect the mental state of commercial aircraft operators in near real time could allow intelligent flight decks of the future to optimally support human performance in the interest of safety by responding to hazardous mental states of the operator. However, many opportunities remain for improving robustness and reliability. It is desirable to reduce the impact of motion and poor optical coupling of probes to the skin. Such artifacts degrade signal quality and thus cognitive state classification accuracy. Field application calls for further development of algorithms and filters for the automation of bad channel detection and dynamic artifact removal. This work introduces a novel adaptive filter method for automated real-time fNIRS signal quality detection and improvement. The output signal (after filtering) will have had contributions from motion and poor coupling reduced or removed, thus leaving a signal more indicative of changes due to hemodynamic brain activations of interest. Cognitive state classifications based on these signals reflect brain activity more reliably. The filter has been tested successfully with both synthetic and real human subject data, and requires no auxiliary measurement. This method could be implemented as a real-time filtering option or bad channel rejection feature of software used with frequency domain fNIRS instruments for signal acquisition and processing. Use of this method could improve the reliability of any operational or real-world application of fNIRS in which motion is an inherent part of the functional task of interest. Other optical diagnostic techniques (e.g., for NIR medical diagnosis) also may benefit from the reduction of probe motion artifact during any use in which motion avoidance would be impractical or limit usability.

Harrivel, Angela↗

NASA NTRS2013

Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex

Harrivel, Angela↗

DOE OSTI2024

Markov Decision Processes for Intelligent, Risk-Informed Asset-Management Decision-Making

Advanced nuclear reactors are a promising option for aiding the world in achieving its net-zero carbon emission goals, however, there are significant challenges to attaining and maintaining economic competitiveness with other sources of electricity. To improve the economic competitiveness of advanced reactor designs, a project was initiated to explore the use of Markov Decision Processes (MDPs) to guide asset-management decision-making during advanced reactor operation. MDPs are a powerful tool for optimizing decision-making in complex environments and their application to advanced reactors can aid in planning maintenance and repair activities to minimize downtime and maximize generation. The described approach expands on previous work regarding the use of MDPs for operational decision-making through the direct incorporation of real-time plant information. The integral MDP analysis includes information from online component diagnostic tools and the plant’s real-time generation risk assessment (GRA) and probabilistic risk assessment (PRA), which evaluate plant risk from both an economic and safety perspective. The result is an asset-management optimization framework that is based on real-time data regarding plant component status and the current best-estimate of plant risk. The paper presents an overview of the theoretical framework to incorporate the different information pathways into an integral MDP analysis, along with example analyses.

Grabaskas, David↗

DOE OSTI2024

Geometry Optimization of Cable-Based Actuation for Small-Scale Model Testing of a Floating Marine Turbine: Preprint

This research aims to apply combined wave and tidal current loads to a small-scale floating marine current turbine in a wave tank, where an actuation system applies hydrodynamic and mooring forces on the hardware based on results from a simulation. We use a real-time hybrid test setup with physical wave forcing from the wave tank and simulated current and mooring forces implemented through a tensioned cable array. For this paper, we developed an optimization algorithm that adjusts the hardware geometry of the cable array to achieve more efficient tension allocation across the cables for the loads that need to be actuated. By adjusting the points where the cables are attached to the floating platform and the angles between the platform and the winches, an optimal cable geometry can be found to minimize tension variations in the lines, maintain the desired pretension, and prevent excessive tensions. We present the optimization problem formulation, the actuation system evaluation approach, and optimization results that show effective cable actuation setups that are being considered for implementation in the wave tank tests.

cable-based actuation↗

DOE OSTI2022

Selection and development of aptamers for pyoverdine

The rhizosphere is a small region surrounding plant roots that is enriched in biochemicals from root exudates and populated with fungi, nematode, and bacteria. Interaction of rhizosphere organisms with plants is mainly promoted by exudates from the roots. Root exudates contain biochemicals that come from primary and secondary metabolisms of plants. These biochemicals attract microbes, which influence plant nutrition. The rhizosphere bacteria (microbiome) are vital to plant nutrient uptake and influence biotic and abiotic stress and pathogenesis. Pseudomonas is a genus of gammaproteobacteria known for its ubiquitous presence in natural habitats and its striking ecological, metabolic, and biochemical diversity. Within the genus, members of the Pseudomonas fluorescens group are common inhabitants of soil and plant surfaces, and certain strains function in the biological control of plant disease, protecting plants from infection by soilborne and aerial plant pathogens. The soil bacterium Pseudomonas protegens Pf-5 (also known as Pseudomonas fluorescensPf-5) is a well-characterized biological strain, which is distinguished by its prolific production of the secondary metabolite, pyoverdine. Knowledge of the distribution of P. fluorescens secretory activity around plant roots is very important for understanding the interaction between P. fluorescens and plants and can be achieved by real time tracking of pyoverdine. To achieve the capability of real-time tracking in soil, we have used a structure-switching SELEX strategy to select high affinity ssDNA and 2’ F-Y-RNA aptamers with specificity for pyoverdine over other siderophores. Pyoverdines from various strains possess a conserved chromophore along with strain-specific peptide chain. Some of the isolated aptamers bind to chromophore of pyoverdine. These will identify pyoverdines from a variety of pseudomonads. Identification of aptamers that selectively bind the peptide portion of pyoverdine Pf-5 is underway. The identified aptamers that are broadly and narrowly specific for pyoverdines or Pf-5 will be optimized for integration into an electrochemical biosensor to track, in real time, P fluorescens activity and other pseudomonads in and around the rhizosphere.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Comparison of Real-Time Pressure Rail Selection Algorithms for the Hybrid Hydraulic Electric Architecture: Case Study on a Track Loader

Abstract The hybrid hydraulic electric architecture (HHEA) seeks to combine the high power/torque/force density of hydraulics with the efficiency of electric machines. A set of common pressure rails is used to provide a majority of the power and this power is modulated by small electric machines to provide precise control for the operator. The HHEA has been studied in previous work using off-line dynamic programming optimization to determine energy efficient pressure rail selections, but this approach requires drive cycle information apriori. A Lagrange multiplier method has also been investigated where a set of gains (Lagrange multipliers) are optimized off-line with the idea the these gains, once determined, could be used for real-time operation. In this work, three new real-time pressure rail selection algorithms that do not require future drive cycle information are investigated; greedy, torque minimizing, and thresholding. The greedy control is found to only use 1% more energy than the globally optimal dynamic programming solution; but a model of energy loss is required.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Frequency Stability Using MPC-Based Inverter Power Control in Low-Inertia Power Systems

Not provided.

Engineering↗

DOE OSTI2020

Toward fusion plasma scenario planning for NSTX-U using machine-learning-accelerated models

One of the most promising devices for realizing power production through nuclear fusion is the tokamak. To maximize performance, it is preferable that tokamak reactors achieve advanced operating scenarios characterized by good plasma confinement, improved magnetohydrodynamic (MHD) stability, and a largely non-inductively driven plasma current. Such scenarios could enable steady-state reactor operation with high \emph{fusion gain} --- the ratio of produced fusion power to the external power provided through the plasma boundary. Precise and robust control of the evolution of the plasma boundary shape as well as the spatial distribution of the plasma current, density, temperature, and rotation will be essential to achieving and maintaining such scenarios. The complexity of the evolution of tokamak plasmas, arising due to nonlinearities and coupling between various parameters, motivates the use of model-based control algorithms that can account for the system dynamics. In this work, a learning-based accelerated model trained on data from the National Spherical Torus Experiment Upgrade (NSTX-U) is employed to develop planning and control strategies for regulating the density and temperature profile evolution around desired trajectories. The proposed model combines empirical scaling laws developed across multiple devices with neural networks trained on empirical data from NSTX-U and a database of first-principles-based computationally intensive simulations. The reduced execution time of the accelerated model will enable practical application of optimization algorithms and reinforcement learning approaches for scenario planning and control development. An initial demonstration of applying optimization approaches to the learning-based model is presented, including a strategy for mitigating the effect of leaving the finite validity range of the accelerated model. The approach shows promise for actuator planning between experiments and in real-time.

machine learning↗

NASA NTRS1992

Finite element method for optimal guidance of an advanced launch vehicle

A temporal finite element based on a mixed form of Hamilton's weak principle is summarized for optimal control problems. The resulting weak Hamiltonian finite element method is extended to allow for discontinuities in the states and/or discontinuities in the system equations. An extension of the formulation to allow for control inequality constraints is also presented. The formulation does not require element quadrature, and it produces a sparse system of nonlinear algebraic equations. To evaluate its feasibility for real-time guidance applications, this approach is applied to the trajectory optimization of a four-state, two-stage model with inequality constraints for an advanced launch vehicle. Numerical results for this model are presented and compared to results from a multiple-shooting code. The results show the accuracy and computational efficiency of the finite element method.

Hodges, Dewey H.↗

NASA NTRS1971

Real time control of the observing program of an Orbiting Solar Observatory.

Discussion of some innovations in the ground control optimization of the modes of data acquisition once an instrument is in orbit, as illustrated by the Harvard experiment on OSO 6. A detailed description is given of the instrumentation on board OSO 6 which provided a capability of performing spatial scans of the solar disk and the ability to obtain the spectra of selected features on the solar disk. The method of receiving and displaying the data transmitted by the satellite in real time is described, as well as the procedure followed in developing preflight observing objectives and in evaluating completed observations. A typical process of data acquisition to obtain wavelength scans of selected features on the solar disk is illustrated, and a number of collaborative investigations involving simultaneous coordinated observations from the ground and from space are cited.

Reeves, E. M.↗

DOE OSTI2022

The Importance of Nonequilibrium to Equilibrium Transition Pathways for the Efficiency and Stability of Organic Solar Cells

Controlled morphology of solution-processed thin films have realized impressive achievements for non-fullerene acceptor (NFA)–based organic solar cells (OSCs). Given the large set of donor–acceptor pairs, employing various processing conditions to realize optimal morphology for high efficiency and stable OSCs is a strenuous task. Therefore, comprehensive correlations between processing conditions and morphology evolution pathways have to be developed for efficient performance and stability of devices. Within the framework of the blend system, crystallization transitions of NFA molecules are tracked utilizing the first heating scan of differential scanning calorimeter (DSC) measurement correlating with respective morphology evolution of blend films. Real-time dynamics measurements and morphology characterizations are combined to provide optimal morphology transition pathways as NFA molecules are shown to be released from the mixed phase to form balanced ordered packing with variant processing conditions. Polymer:NFA films are fabricated using blade coating incorporating solvent additive or thermal annealing as processing conditions as a correlation is formulated between performance and stability of solar cells with morphology transition pathways. In conclusion, this work demonstrates the significance of processing condition-controlled transition pathways for the realization of optimal morphology leading to superior OSC devices.

14 SOLAR ENERGY↗

NASA NTRS1999

Initial clinical experience of real-time three-dimensional echocardiography in patients with ischemic and idiopathic dilated cardiomyopathy

The geometry of the left ventricle in patients with cardiomyopathy is often sub-optimal for 2-dimensional ultrasound when assessing left ventricular (LV) function and localized abnormalities such as a ventricular aneurysm. The aim of this study was to report the initial experience of real-time 3-D echocardiography for evaluating patients with cardiomyopathy. A total of 34 patients were evaluated with the real-time 3D method in the operating room (n = 15) and in the echocardiographic laboratory (n = 19). Thirteen of 28 patients with cardiomyopathy and 6 other subjects with normal LV function were evaluated by both real-time 3-D echocardiography and magnetic resonance imaging (MRI) for obtaining LV volumes and ejection fractions for comparison. There were close relations and agreements for LV volumes (r = 0.98, p <0.0001, mean difference = -15 +/- 81 ml) and ejection fractions (r = 0.97, p <0.0001, mean difference = 0.001 +/- 0.04) between the real-time 3D method and MRI when 3 cardiomyopathy cases with marked LV dilatation (LV end-diastolic volume >450 ml by MRI) were excluded. In these 3 patients, 3D echocardiography significantly underestimated the LV volumes due to difficulties with imaging the entire LV in a 60 degrees x 60 degrees pyramidal volume. The new real-time 3D echocardiography is feasible in patients with cardiomyopathy and may provide a faster and lower cost alternative to MRI for evaluating cardiac function in patients.

NASA Discipline Cardiopulmonary↗

NASA NTRS1991

Method for providing real-time control of a gaseous propellant rocket propulsion system

The new and improved methods and apparatus disclosed provide effective real-time management of a spacecraft rocket engine powered by gaseous propellants. Real-time measurements representative of the engine performance are compared with predetermined standards to selectively control the supply of propellants to the engine for optimizing its performance as well as efficiently managing the consumption of propellants. A priority system is provided for achieving effective real-time management of the propulsion system by first regulating the propellants to keep the engine operating at an efficient level and thereafter regulating the consumption ratio of the propellants. A lower priority level is provided to balance the consumption of the propellants so significant quantities of unexpended propellants will not be left over at the end of the scheduled mission of the engine.

Morris, Brian G.↗

DOE OSTI2021

Design and Metamodel-Based Optimization of a High Power Density Wound Field Traction Motor

Traction motors onboard electric vehicles (EVs) are faced with ever-increasing power density requirements and cost reduction challenges. Although permanent magnet (PM) traction motors have been favored for their potential of higher power densities, the price and supply volatilities of PM materials are the major drawbacks. Instead of a single load point, the performance of a traction motor needs to be optimized over various combinations of torque and speed to represent real-world vehicular driving scenarios, which tends to be a time-consuming task with direct optimizations. In this paper, as a PM-free solution, a wound field synchronous motor (WFSM) is designed and optimized using a metamodel-based approach to maximize its efficiency over a custom set of load points, while utilizing a fully per-unitized geometry template. The workflow has proven to be timesaving and the selected design is prototyped.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Implementation of a Metamodel-Based Optimization for the Design of a High Power Density Wound Field Traction Motor

Traction motors onboard electric vehicles (EVs) are faced with ever-increasing power density requirements and cost reduction challenges. Although permanent magnet (PM) traction motors have been favored for their potential of higher power densities, the price and supply volatility of PM materials are the major drawbacks. Instead of a single load point, the performance of a traction motor needs to be optimized over various combinations of torque and speed to represent real-world vehicular driving scenarios, which tends to be a time-consuming task with direct optimizations. In this study, as a PM-free solution, a wound field synchronous motor (WFSM) is designed and optimized using a metamodel-based approach to maximize its efficiency over a custom set of load points, while utilizing a fully per-unitized geometry template. The workflow has proven to be timesaving and the optimal design is prototyped and tested.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Lightweight jet reconstruction and identification as an object detection task

We apply object detection techniques based on deep convolutional blocks to end-to-end jet identification and reconstruction tasks encountered at the CERN large hadron collider (LHC). Collision events produced at the LHC and represented as an image composed of calorimeter and tracker cells are given as an input to a Single Shot Detection network. The algorithm, named PFJet-SSD performs simultaneous localization, classification and regression tasks to cluster jets and reconstruct their features. This all-in-one single feed-forward pass gives advantages in terms of execution time and an improved accuracy w.r.t. traditional rule-based methods. A further gain is obtained from network slimming, homogeneous quantization, and optimized runtime for meeting memory and latency constraints of a typical real-time processing environment. We experiment with 8-bit and ternary quantization, benchmarking their accuracy and inference latency against a single-precision floating-point. We show that the ternary network closely matches the performance of its full-precision equivalent and outperforms the state-of-the-art rule-based algorithm. Finally, we report the inference latency on different hardware platforms and discuss future applications.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

A Two-Stage Approach for PV Inverter Engagement in Power Factor Correction and Voltage Regulation

The rapid integration of distributed energy resources, like solar photovoltaics (PVs), can lead to overvolt-age challenges due to reverse power flow and a noticeable decrease in power factor at the substation interface. While existing literature extensively explores utilizing smart inverter capabilities for reactive power flexibility using a volt-var curve (VVC), obtaining time-varying operating points of such curves in real-time is challenging due to computational demands and communication requirements. Similarly, employing optimization-based approaches for reactive power control and active voltage regulation in large-scale distribution feeders is difficult due to the complexity of the problem and the challenges in effectively engaging customer-owned resources. This paper proposes a two-stage strategy to harness smart inverters for reactive power support. The first stage formulates short-term planning by optimally designing VVCs (on a daily or hourly basis) for large-scale solar PVs based on projected system needs and communicating optimal curves to smart inverters in advance. Subsequently, the second stage employs a transactive-based method to involve customer-owned PVs for reactive power support, effectively enhancing overall system performance and addressing real-time demands. In conclusion, the efficacy of this approach will be demonstrated using real-world distribution circuits provided by Vermont Electric Power Company (VELCO) and Vermont Electric Cooperative (VEC).

Poudel, Shiva [Pacific Northwest National Laborato↗

NASA NTRS2000

Passivity-based Robust Control of Aerospace Systems

This report provides a brief summary of the research work performed over the duration of the cooperative research agreement between NASA Langley Research Center and Kansas State University. The cooperative agreement which was originally for the duration the three years was extended by another year through no-cost extension in order to accomplish the goals of the project. The main objective of the research was to develop passivity-based robust control methodology for passive and non-passive aerospace systems. The focus of the first-year's research was limited to the investigation of passivity-based methods for the robust control of Linear Time-Invariant (LTI) single-input single-output (SISO), open-loop stable, minimum-phase non-passive systems. The second year's focus was mainly on extending the passivity-based methodology to a larger class of non-passive LTI systems which includes unstable and nonminimum phase SISO systems. For LTI non-passive systems, five different passification. methods were developed. The primary effort during the years three and four was on the development of passification methodology for MIMO systems, development of methods for checking robustness of passification, and developing synthesis techniques for passifying compensators. For passive LTI systems optimal synthesis procedure was also developed for the design of constant-gain positive real controllers. For nonlinear passive systems, numerical optimization-based technique was developed for the synthesis of constant as well as time-varying gain positive-real controllers. The passivity-based control design methodology developed during the duration of this project was demonstrated by its application to various benchmark examples. These example systems included longitudinal model of an F-18 High Alpha Research Vehicle (HARV) for pitch axis control, NASA's supersonic transport wind tunnel model, ACC benchmark model, 1-D acoustic duct model, piezo-actuated flexible link model, and NASA's Benchmark Active Controls Technology (BACT) Wing model. Some of the stability results for linear passive systems were also extended to nonlinear passive systems. Several publications and conference presentations resulted from this research.

Kelkar, Atul G.↗