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At least 865 records · Page 48

Reinforcement Learning-based Output Structured Feedback for Distributed Multi-Area Power System Frequency Control

Load frequency control (LFC) is a key factor to maintain the stable frequency in multi-area power systems. As the modern power systems evolve from centralized to decentralized paradigm, LFC needs to consider the decentralized scheme that considers limited information from the information-exchange graph for the generator control of each interconnected area. This paper aims to solve a data-driven constrained LQR problem with mean-variance risk constraints and output structured feedback, and applies this framework to solve the LFC problem in multi-area power systems. By reformulating the constrained optimization problem into a minimax problem, the stochastic gradient descent max-oracle (SGDmax) algorithm with zero-order policy gradient (ZOPG) is adopted to find the optimal feedback gain from the learning, while guaranteeing the convergence. In addition, to improve the adaptation of the proposed learning method to new or varying models, we construct an emulator grid that approximates the dynamics of a physical grid and performs training based on this model. Once the feedback gain is obtained from the emulator grid, it is applied to the physical grid with a robustness test to check whether the controller from the approximated emulator applies to the actual system. Numerical tests show that the obtained feedback controller can successfully control the frequency of each area, while mitigating the uncertainty from the loads, with reliable robustness that ensures the adaptability of the obtained feedback gain to the actual physical grid.

Kwon, Kyung-bin↗

SPH Modeling of Biomass Granular Flow: Engineering Application in Hoppers and Augers

Numerical modeling of granular biomass material flow in handling operations is indispensable to decipher flow upsets, commonly manifested as clogging and jamming in hoppers and augers. With a computational tool developed based on smoothed particle hydrodynamics (SPH), we simulated the hopper flow and auger feeding of six granular biomass materials. The good agreement between the experimental and numerical flow rates demonstrated the capability of the developed SPH solver in modeling the complicated flow of granular biomass materials. Further, the impact of physical and numerical parameters is investigated, and the major results show that the hopper flow pattern is controlled by shear band evolution; hopper clogging is collectively influenced by the opening size, wall friction, and material packing, and the impact of material compressibility on the auger feed rate is minimal. These parametric studies validate the solver’s robustness in simulating biomass flow in handling equipment and demonstrate that the SPH computational tool can provide insights about granular flow mechanics to facilitate handling equipment design and optimize handling operations.

09 BIOMASS FUELS↗

The optimal control of merging aircraft - Implementation of the hybrid air traffic controller.

The control of merging aircraft is formulated as a finite-time, quadratic optimal control problem of a linear system with state and control constraints. The purpose of this paper is to demonstrate that the Hybrid Air Traffic Controller (HAC), which has been previously developed as a solution to this problem, may be easily implemented. Use is made of both the properties of the algebraic solution to the matrix Riccati equation and the structure of the linear model. This approach results in a real-time synthesis procedure for the HAC which does not rely on iterative numerical integration techniques.

Schatz, J. G.↗

Lorentz Body Force Induced by Traveling Magnetic Fields

The Lorentz force induced by a traveling magnetic field (TMF) in a cylindrical container has been calculated. The force can be used to control flow in dectrically conducting melts and the direction of the magnetic field and resulting flow can be reversed. A TMF can be used to partially cancel flow driven by buoyancy. The penetration of the field into the cylinder decreases as the frequency increases, and there exists an optimal value of frequency for which the resulting force is a maximum. Expressions for the Lorentz force in the limiting cases of low frequency and infinite cylinder are also given and compared to the numerical calculations.

Volz, M. P.↗

Selective Heating Through Y-Junction Waveguide Designed by Acoustic Shape Optimization

Unlike phononic crystals or systems designed by topology optimization, waveguides designed by shape optimization do not have voids or internal defects, making the fabrication process more suitable for additive manufacturing. By designing a Y-junction waveguide through shape optimization, an ultrasonic wave can be controlled so that it propagates to a predetermined location just by adjusting its frequency. These demultiplexed ultrasonic waves can be used to transport signals or stimulate nearby materials. As an example, the ultrasonic wave is converted to heat at different locations, which can be applied to mechanisms that can take advantage of heating. First, shape optimization is performed on a cylindrical structure to selectively propagate ultrasonic waves of a particular frequency while attenuating others, which is analyzed through a finite element model. The numerical study results are compared with experimental measurements from samples fabricated through additive manufacturing methods. After verifying the concept, the Y-junction waveguide is fabricated to demultiplex the wave and selectively heat different locations. Here the results show that the method of combining shape optimization with additive manufacturing is exceptionally simple and capable of demultiplexing ultrasonic waves, which can replace complex electrical components with single-material waveguides.

36 MATERIALS SCIENCE↗

Asynchronous quadratic control for constrained hidden markov jump linear systems with incomplete MTPM and MOCPM

Abstract This paper investigates the quadratic optimal control problem for constrained Markov jump linear systems with incomplete mode transition probability matrix (MTPM). Considering original system mode is not accessible, observed mode is utilized for asynchronous controller design where mode observation conditional probability matrix (MOCPM), which characterizes the emission between original modes and observed modes is assumed to be partially known. An LMI optimization problem is formulated for such constrained hidden Markov jump linear systems with incomplete MTPM and MOCPM. Based on this, a feasible state-feedback controller can be designed with the application of free-connection weighting matrix method. The desired controller, dependent on observed mode, is an asynchronous one which can minimize the upper bound of quadratic cost and satisfy restrictions on system states and control variables. Furthermore, clustering observation where observed modes recast into several clusters, is explored for simplifying the computational complexity. Numerical examples are provided to illustrate the validity.

Zhu, Jin↗

Central-Monitor Software Module

One of the software modules of the emergency-vehicle traffic-light-preemption system of the two preceding articles performs numerous functions for the central monitoring subsystem. This module monitors the states of all units (vehicle transponders and intersection controllers): It provides real-time access to the phases of traffic and pedestrian lights, and maps the positions and states of all emergency vehicles. Most of this module is used for installation and configuration of units as they are added to the system. The module logs all activity in the system, thereby providing information that can be analyzed to minimize response times and optimize response strategies. The module can be used from any location within communication range of the system; with proper configuration, it can also be used via the Internet. It can be integrated into call-response centers, where it can be used for alerting emergency vehicles and managing their responses to specific incidents. A variety of utility subprograms provide access to any or all units for purposes of monitoring, testing, and modification. Included are "sniffer" utility subprograms that monitor incoming and outgoing data for accuracy and timeliness, and that quickly and autonomously shut off malfunctioning vehicle or intersection units.

Bachelder, Aaron↗

SCaN Testbed Software Development and Lessons Learned

National Aeronautics and Space Administration (NASA) has developed an on-orbit, adaptable, Software Defined Radio (SDR)Space Telecommunications Radio System (STRS)-based testbed facility to conduct a suite of experiments to advance technologies, reduce risk, and enable future mission capabilities on the International Space Station (ISS). The SCAN Testbed Project will provide NASA, industry, other Government agencies, and academic partners the opportunity to develop and field communications, navigation, and networking technologies in the laboratory and space environment based on reconfigurable, SDR platforms and the STRS Architecture.The SDRs are a new technology for NASA, and the support infrastructure they require is different from legacy, fixed function radios. SDRs offer the ability to reconfigure on-orbit communications by changing software for new waveforms and operating systems to enable new capabilities or fix any anomalies, which was not a previous option. They are not stand alone devices, but required a new approach to effectively control them and flow data. This requires extensive software to be developed to utilize the full potential of these reconfigurable platforms. The paper focuses on development, integration and testing as related to the avionics processor system, and the software required to command, control, monitor, and interact with the SDRs, as well as the other communication payload elements. An extensive effort was required to develop the flight software and meet the NASA requirements for software quality and safety. The flight avionics must be radiation tolerant, and these processors have limited capability in comparison to terrestrial counterparts. A big challenge was that there are three SDRs onboard, and interfacing with multiple SDRs simultaneously complicatesd the effort. The effort also includes ground software, which is a key element for both the command of the payload, and displaying data created by the payload. The verification of the software was an extensive effort. The challenges of specifying a suitable test matrix with reconfigurable systems that offer numerous configurations is highlighted. Since the flight system testing requires methodical, controlled testing that limits risk, a nearly identical ground system to the on-orbit flight system was required to develop the software and write verification procedures before it was installed and tested on the flight system. The development of the SCAN testbed was an accelerated effort to meet launch constraints, and this paper discusses tradeoffs made to balance needed software functionality and still maintain the schedule. Future upgrades are discussed that optimize the avionics and allow experimenters to utilize the SCAN testbed potential.

radio communication↗

Pterodactyl: The Development and Performance of Guidance Algorithms for a Mechanically Deployed Entry Vehicle

Pterodactyl is a NASA Space Technology Mission Directorate (STMD) project focused on developing a design capability for optimal, scalable, Guidance and Control (G&C) solutions that enable precision targeting for Deployable Entry Vehicles (DEVs). This feasibility study is unique in that it focuses on the rapid integration of targeting performance analysis with structural & packaging analysis, which is especially challenging for new vehicle and mission designs. This paper will detail the guidance development and trajectory design process for a lunar return mission, selected to stress the vehicle designs and encourage future scalability. For the five G&C configurations considered, the Fully Numerical Predictor-Corrector Entry Guidance (FNPEG) was selected for configurations requiring bank angle guidance and FNPEG with Uncoupled Range Control (URC) was developed for configurations requiring angle of attack and sideslip angle guidance. Successful G&C configurations are defined as those that can deliver payloads to the intended descent and landing initiation point, while abiding by trajectory constraints for nominal and dispersed trajectories.

Johnson, Breanna J.↗

Heat flow control and segregation in directional solidification

Optimization of the vertical Bridgman technique for growth of electronic materials in single crystal form was investigated. The limitations of the crystal growth configuration were experimentally determined and heat transfer related deficiencies identified. Design of an alternate system was based on the use of heat pipes separated by a gradient region. Heat transfer analyses based on one and two dimensional models indicated the necessity of a flexible gradient zone configuration. Directional melting of binary systems as encountered during seeding in melt growth was analysed for concurrent compositional changes at the crystal-metal interface, and the theoretical treatment numerically applied to HgCdTe and Ga doped germanium. A theoretical and experimental study of the thermal effects associated with current flow was conducted. It was found that experimental measurements of dc induced growth during crystal pulling can be used for the precise determination of the Peltier coefficient.

Witt, A. F.↗

Numerical study to predict the effect of surface roughness on the thermal and hydraulic performance of additively manufactured heat exchangers

Heat exchangers are used in many industries to transfer thermal energy between two or more objects with an associated thermal and hydraulic performance indicated by thermal effectiveness and pressure drop respectively. Many investigations have aimed to enhance the thermal effectiveness of heat exchangers by introducing turbulent flow inducers that increase the heat transfer rate at the expense of increasing pressure drop. Flow inducers like surface roughness can be controlled with advanced manufacturing methods like additive manufacturing for heat exchanger production. Selecting and manufacturing an optimal surface roughness for heat exchangers requires a more comprehensive approach that accounts for the surface roughness effect on the thermal and hydraulic performance of a sample. Since fabricating samples with additive manufacturing to a desired surface roughness can be an extensive experimental process, this study will fundamentally investigate the effect of surface roughness on the thermal and velocity boundary layers for various surface roughness profiles with physics-based computational modeling. To accurately model the surface roughness effect on thermohydraulic performance, correlations like roughness ratio, friction factor, and Nusselt number are investigated. This study expects to indicate correlations for different flow regimes which can successfully predict the effect of surface roughness on thermohydraulic performance. Results generated from modeling surface roughness effect with unique correlations are then compared to experimental data obtained from literature for validation. The results of this study will provide insight to understand the thermal fluid physics associated with surface roughness and design guidelines for heat exchangers produced with additive manufacturing.

36 MATERIALS SCIENCE↗

NUMERICAL MODELING OF A SOLID OXIDE FUEL CELL FOR USE IN REAL-TIME SIMULATION AND CYBER-PHYSICAL SYSTEMS

Cyber-physical systems provide a mechanism with which to investigate the physical phenomena and behavior of traditionally cost-prohibitive or otherwise fragile equipment. For the National Energy Technology Laboratory (NETL), this approach resulted in the Hybrid Performance (Hyper) facility which features a gas turbine-SOFC hybrid cycle utilizing real turbomachinery and a simulated SOFC stack. This allows for the investigation of combined cycle performance and control strategies, in an exhaustive manner, both without fear of destroying delicate state-of-the-art fuel cells, and with the full accuracy of real-world turbomachinery. Issues arose between the transient response of the SOFC model being limited to a sample time of 80 milliseconds, due to the calculation time of the SOFC model taking on average 40 milliseconds to calculate for a given timestep with spikes in calculation time reaching the 80 millisecond threshold. In order to be able to match the speed of transients from the turbomachinery and likewise better discern transient behavior, it was determined that the SOFC model must be optimized to operate at a sample time of 5 milliseconds. Therefore, it is necessary to optimize the SOFC model in order to decrease the calculation time from around 40 milliseconds, down to at the most 5 milliseconds. To do this, both the electrochemical algorithm and the thermal algorithm used to simulate the physical behavior of the SOFC are investigated to determine where improvements can be made. To this end the rootfinding numerical recipes of the electrochemical algorithm are investigated as the complex electrochemistry requires a highly iterative nested dual convergence loop to resolve the voltage-current relationship, and likewise the temporal discretization of the thermal algorithm is modified for the sake of higher accuracy and stability. Ultimately the new electrochemical algorithm featuring higher order rootfinding schemes proves to be efficient enough to reach the sub 5 millisecond target, signifying an order of magnitude reduction in calculation time, and when coupled with the new temporal discretization similar calculation time characteristics show that a fully implicit, higher order temporal discretization can also successfully be used if desired. Ultimately this result means that the cyber-physical simulation system can operate at higher sample rates, and resolve transient events at significantly higher resolution and fidelity.

Arias, Jesus↗

Computational fluid dynamics modeling and analysis of silica nanoparticle synthesis in a flame spray pyrolysis reactor

Flame Spray Pyrolysis (FSP) is a method for large-scale production of nanoparticles and nanoscale powders employed in a wide range of industrial applications. Particle size and morphology are complex functions of the physicochemical phenomena occurring in the FSP reactor. An extensive study of FSP-related phenomena can be utilized to develop effective strategies for achieving desired particle size/morphology and scaling up the overall yield of an FSP system. In this work, a computational fluid dynamics (CFD) model of an FSP reactor is developed to simulate the coupling of key phenomena involved in the particle synthesis process: liquid spray breakup and evaporation, mixing, combustion, and particle formation/growth of silica nanoparticles. Herein, the particle sizes and their distributions from the CFD simulations are validated against experimental data. Subsequently, the simulations are utilized to investigate the impact of process parameters on the resultant flame dynamics and particle growth. Firstly, the CFD results show that the particle sizes are strongly correlated with the precursor concentration in the solvent. At lower precursor concentrations, the spread of the distribution is relatively insensitive to the value of the concentration. At higher concentrations, the spread is higher as the collision probability between particles is higher. Secondly, increasing the pilot flow rate increases the length of the pilot flames impacting the local ignition location of the spray flame. Lastly, it is shown that the dispersion gas flow rate strongly influences the spray flame shape. This shape can be used for control of particle growth as it helps determine the regions of high temperature and the residence time of the particles in the high temperature region enabling the design and process optimization of the FSP reactor.

42 ENGINEERING↗

Research on output feedback control

A summary is presented of the main results obtained during the course of research on output feedback control. The term output feedback is used to denote a controller design approach which does not rely on an observer to estimate the states of the system. Thus, the order of the controller is fixed, and can even be zero order, which amounts to constant gain ouput feedback. The emphasis has been on optimal output feedback. That is, a fixed order controller is designed based on minimizing a suitably chosen quadratic performance index. A number of problem areas that arise in this context have been addressed. These include developing suitable methods for selecting an index of performance, both time domain and frequency domain methods for achieving robustness of the closed loop system, developing canonical forms to achieve a minimal parameterization for the controller, two time scale design formulations for ill-conditioned systems, and the development of convergent numerical algorithms for solving the output feedback problem.

Calise, Anthony J.↗

Learning high-dimensional parametric maps via reduced basis adaptive residual networks

We propose a scalable framework for the learning of high-dimensional parametric maps via adaptively constructed residual network (ResNet) maps between reduced bases of the inputs and outputs. When just few training data are available, it is beneficial to have a compact parametrization in order to ameliorate the ill-posedness of the neural network training problem. By linearly restricting high-dimensional maps to informed reduced bases of the inputs, one can compress high-dimensional maps in a constructive way that can be used to detect appropriate basis ranks, equipped with rigorous error estimates. A scalable neural network learning framework is thus to learn the nonlinear compressed reduced basis mapping. Unlike the reduced basis construction, however, neural network constructions are not guaranteed to reduce errors by adding representation power, making it difficult to achieve good practical performance. Inspired by recent approximation theory that connects ResNets to sequential minimizing flows, we present an adaptive ResNet construction algorithm. This algorithm allows for depth-wise enrichment of the neural network approximation, in a manner that can achieve good practical performance by first training a shallow network and then adapting. We prove universal approximation of the associated neural network class for $L^2_v$ functions on compact sets. Our overall framework allows for constructive means to detect appropriate breadth and depth, and related compact parametrizations of neural networks, significantly reducing the need for architectural hyperparameter tuning. Numerical experiments for parametric PDE problems and a 3D CFD wing design optimization parametric map demonstrate that the proposed methodology can achieve remarkably high accuracy for limited training data, and outperformed other neural network strategies we compared against.

42 ENGINEERING↗

An a priori evaluation of a principal component and artificial neural network based combustion model in diesel engine conditions

A principal component analysis (PCA) and artificial neural network (ANN) based chemistry tabulation approach is presented. ANNs are used to map the thermochemical state onto a low-dimensional manifold consisting of five control variables that have been identified using PCA. Three canonical configurations are considered to train the PCA-ANN model: a series of homogeneous reactors, a nonpremixed flamelet, and a two-dimensional lifted flame. The performance of the model in predicting the thermochemical manifold of a spatially-developing turbulent jet flame in diesel engine thermochemical conditions is a priori evaluated using direct numerical simulation (DNS) data. The PCA-ANN approach is compared with a conventional tabulation approach (tabulation using ad hoc defined control variables and linear interpolation). The PCA-ANN model provides higher accuracy and requires several orders of magnitude less memory. Here, these observations indicate that the PCA-ANN model is superior for chemistry tabulation, especially for modelling complex chemistries that present multiple combustion modes as observed in diesel combustion. The performance of the PCA-ANN model is then compared to the optimal estimator, i.e. the conditional mean from the DNS. The results indicate that the PCA-ANN model gives high prediction accuracy, comparable to the optimal estimator, especially for major species and the thermophysical properties. Higher errors are observed for the minor species and reaction rate predictions when compared to the optimal estimator. It is shown that the prediction of minor species and reaction rates can be improved by using training data that exhibits a variation of parameters as observed in the turbulent flame. The output of the ANN is analysed to assess mass conservation. It is observed that the ANN incurs a mean absolute error of 0.05% in mass conservation. Furthermore, it is demonstrated that this error can be reduced by modifying the cost function of the ANN to penalise for deviation from mass conservation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pterodactyl: An Uncoupled Range Control Approach to Fully Numerical Predictor-Corrector Entry Guidance

Entry, descent, and landing (EDL) has been identified as a core area of investment in NASA's Strategic Technology Investment Plan (NASA STIP). STIP lists the space technologies needed to help achieve NASA's science, technology, and exploration goals across the agency. Within the EDL core area, deployable hypersonic decelerators, also known as deployable entry vehicles (DEVs), have been identified as an area of investment, due to its potential to revolutionize payload delivery methods to Earth and other planets. These vehicles, which can deploy their heat shields or alter their shape before entry, exploit an increased and more effective drag ratio by using less mass than traditional blunt body vehicles with rigid aeroshells. DEVs like Adaptive Deployable Entry and Placement Technology (ADEPT) and Hypersonic Inflatable Aerodynamic Decelerator (HIAD) have demonstrated the capability of transporting the equivalent science payloads of blunt body rigid aeroshells, while using a significantly smaller diameter when stowed within a launch vehicle. While DEVs' increased energy dissipation for less mass is an attractive feature, their ability to contract and expand would require advancements in the current state-of-the-art guidance and control (G&C) architectures used by traditional rigid vehicles. Pterodactyl, a project funded by NASA's Space Technology Mission Directorate (STMD), aims to provide feasible integrated G&C solutions for DEVs, complete with optimized vehicle designs and packaging analyses. Structural and aerodynamic analyses for the explored control systems suggested a need for a bank angle guidance algorithm, a heritage guidance approach that has been used in many entry precision targeting vehicles, as well as an additional need for the development of a non-bank angle guidance. For this reason, Pterodactyl will consider four different G&C configurations during its design phase: i) a reaction control system for bank (sigma) control, ii) a mass movement system for angle of attack (alpha) sideslip (beta) control, iii) flaps for alpha - beta control, and iv) flaps for sigma control. To increase the applicability of each proposed integrated G&C architecture, an 11 km/s lunar return demonstration mission is selected to stress the developed technology capability. The Lifting Nano-ADEPT (LNA) vehicle is chosen as the DEV to demonstrate the integrated solutions. This paper will detail the trajectory design for a lunar return mission, using the validated bank control guidance algorithm Fully Numerical Predictor-Corrector Entry Guidance (FNPEG) and a newly developed guidance algorithm: FNPEG Uncoupled Range Control (URC). FNPEG-URC diverges from traditional bank angle guidances by producing alpha and beta commands to thereby decouple downrange and crossrange control. This presentation will discuss the development and overall performance of FNPEG and FNPEG-URC for each of the four G&C configurations. Successful G&C configurations are defined as those that can deliver payloads to the intended descent and landing site while abiding by trajectory constraints in the face of dispersions.

Johnson, Breanna↗

CO2 Insulation for Thermal Control of the Mars Science Laboratory

The National Aeronautics and Space Administration (NASA) is sending a large (>850 kg) rover as part of the Mars Science Laboratory (MSL) mission to Mars in 2011. The rover's primary power source is a Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) that generates roughly 2000 W of heat, which is converted to approximately 110 W of electrical power for use by the rover electronics, science instruments, and mechanism-actuators. The large rover size and extreme thermal environments (cold and hot) for which the rover is designed for led to a sophisticated thermal control system to keep it within allowable temperature limits. The pre-existing Martian atmosphere of low thermal conductivity CO2 gas (8 Torr) is used to thermally protect the rover and its components from the extremely cold Martian environment (temperatures as low as -130 deg C). Conventional vacuum based insulation like Multi Layer Insulation (MLI) is not effective in a gaseous atmosphere, so engineered gaps between the warm rover internal components and the cold rover external structure were employed to implement this thermal isolation. Large gaps would lead to more thermal isolation, but would also require more of the precious volume available within the rover. Therefore, a balance of the degree of thermal isolation achieved vs. the volume of rover utilized is required to reach an acceptable design. The temperature differences between the controlled components and the rover structure vary from location to location so each gap has to be evaluated on a case-by-case basis to arrive at an optimal thickness. For every configuration and temperature difference, there is a critical thickness below which the heat transfer mechanism is dominated by simple gaseous thermal conduction. For larger gaps, the mechanism is dominated by natural convection. In general, convection leads to a poorer level of thermal isolation as compared to conduction. All these considerations play important roles in the optimization process. A three-step process was utilized to design this insulation. The first step is to come up with a simple, textbook based, closed-form equation assessment of gap thickness vs. resultant thermal isolation achieved. The second step is a more sophisticated numerical assessment using Computational Fluid Dynamics (CFD) software to investigate the effect of complicated geometries and temperature contours along them to arrive at the effective thermal isolation in a CO2 atmosphere. The third step is to test samples of representative geometries in a CO2 filled chamber to measure the thermal isolation achieved. The results of these assessments along with the consistency checks across these methods leads to the formulation of design-guidelines for gap implementation within the rover geometry. Finally, based on the geometric and functional constraints within the real rover system, a detailed design that accommodates all these factors is arrived at. This paper will describe in detail this entire process, the results of these assessments and the final design that was implemented.

CO2↗