Integrating production scheduling and process control using latent variable dynamic models
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Automation & Control Systems↗
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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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A dynamic likelihood approach to filtering transport processes: advection-diffusion dynamics
A Bayesian data assimilation scheme is formulated for advection-dominated advective and diffusive evolutionary problems, based upon the Dynamic Likelihood (DLF) approach to filtering. The DLF was developed specifically for hyperbolic problems –waves–, and in this paper, it is extended via a split step formulation, to handle advection-diffusion problems. In the dynamic likelihood approach, observations and their statistics are used to propagate probabilities along characteristics, evolving the likelihood in time. The estimate posterior thus inherits phase information. For advection-diffusion the advective part of the time evolution is handled on the basis of observations alone, while the diffusive part is informed through the model as well as observations. We expect, and indeed show here, that in advection-dominated problems, the DLF approach produces better estimates than other assimilation approaches, particularly when the observations are sparse and have low uncertainty. The added computational expense of the method is cubic in the total number of observations over time, which is on the same order of magnitude as a standard Kalman filter and can be mitigated by bounding the number of forward propagated observations, discarding the least informative data.
97 MATHEMATICS AND COMPUTING↗
Inter-Hemispheric Coupling During Recent North Polar Summer Periods as Predicted by MaCWAVE/MIDAS Rocket Data and Traced by TIMED/SABER Measurements
In July, 2002, the MaCWAVE-MIDAS Rocket Program was launched from Andoya Rocket Range (ARR) in Norway. Data from these flights demonstrated that the polar summer mesosphere during this period was unusual, at least above ARR. Theoretical studies have since been published that imply that the abnormal characteristics of this polar summer were generated by dynamical processes occurring in the southern polar winter hemisphere. We have used data from the SABER instrument aboard the NASA Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) Satellite to study these characteristics and compare them with the features observed in the ensuing eight years. For background, the TIMED Satellite was launched on December 7,2001 to study the dynamics and energy of the mesosphere and lower thermosphere. The SABER instrument is a limb scanning infrared radiometer designed to measure temperature of the region as well as a large number of minor constituents. In this study, we review the MaCWAVE rocket results. Next, we investigate the temperature characteristics of the polar mesosphere as a function of spatial and temporal considerations. We have used the most recent SABER dataset (1.07). Weekly averages are used to make comparisons between the winter and summer hemispheres. Furthermore, the data analysis agrees with recent theoretical studies showing that this behavior is a result of anomalous dynamical events in the southern hemisphere. The findings discussed here clearly show the value of scientific rocket flights used in a discovery mode.
Goldberg, Richard A.↗
Stratwarm Effects in the Ionospheric D Region Wind Field
An analysis is made of the wind field structure in the strato-thermosphere over Eastern Siberia during the winter stratwarms of 1975-1977. It is found that coupling between dynamical processes in the stratosphere and lower thermosphere is effected through changes of the temperature regime of the atmosphere. The circulation regime both in the stratosphere and lower thermosphere depends on location of the source of perturbations that cause stratospheric warmings. The effect of warming-induced perturbations on the dynamics of above- and underlying layers and the meridional extent of the processes are determined by the altitude and region where anti-cyclones originate. In conditions of a warmer stratosphere, there is a considerable loss of wind stability in the ionospheric D-region. A time delay of 1 to 2 days of lower-thermosphere processes is found to occur with respect to stratospheric processes of temperature variation at 30 mb level.
Vergasova, G. V.↗
Machine‐learning‐based predictive control of nonlinear processes. Part II: Computational implementation
Abstract Machine learning is receiving more attention in classical engineering fields, and in particular, recurrent neural networks (RNNs) coupled with ensemble regression tools have demonstrated the capability of modeling nonlinear dynamic processes. In Part I of this two‐article series, the Lyapunov‐based model predictive control (LMPC) method using a single RNN model and an ensemble of RNN models, respectively, was rigorously developed for a general class of nonlinear systems. In the present article, computational implementation issues of this new control method ranging from training of the RNN models, ensemble regression of the RNN models, and parallel computation for accelerating the real‐time model calculations are addressed. Furthermore, a chemical reactor example is used to demonstrate the implementation and effectiveness of these machine‐learning tools in LMPC as well as compare them with standard state‐space model identification tools.
Wu, Zhe↗
Random Quantum Circuits
Quantum circuits—built from local unitary gates and local measurements—are a new playground for quantum many-body physics and a tractable setting to explore universal collective phenomena far from equilibrium. These models have shed light on longstanding questions about thermalization and chaos, and on the underlying universal dynamics of quantum information and entanglement. In addition, such models generate new sets of questions and give rise to phenomena with no traditional analog, such as dynamical phase transitions in quantum systems that are monitored by an external observer. Quantum circuit dynamics is also topical in view of experimental progress in building digital quantum simulators that allow control of precisely these ingredients. Randomness in the circuit elements allows a high level of theoretical control, with a key theme being mappings between real-time quantum dynamics and effective classical lattice models or dynamical processes. Many of the universal phenomena that can be identified in this tractable setting apply to much wider classes of more structured many-body dynamics.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Recent trends in stratospheric ozone - Implications of ozone and temperature correlation
The relation between ozone and temperature in the upper stratosphere is used to estimate the drift in the SBUV spectrometer on Nimbus-7 and the linear trend in ozone from 1979 to 1986. The ozone and temperature variabilities are coupled through chemical and dynamical processes. In the upper stratosphere they are anticorrelated through temperature-dependent loss rates, while in the lower stratosphere their variabilities are positively correlated through dynamical coupling. These relations are used to determine the ozone sensitivity to temperature and ozone trends in terms of temperature trends. It is shown that in the upper stratosphere (approximately 2 mbar), the eight-year trend in ozone is a manifestation of dynamical perturbations. It varies from about +4 percent at the equator to about -1 to -2 percent at high latitudes in both hemispheres.
Chandra, S.↗
Use of GTE, Mozaic, Sonex, and UARS-MLS Data in Understanding Tropospheric Processes Critical to Model Development
During the first year we focused on the analysis of data collected on over 7600 commercial aircraft flights (the MOZAIC program). The aim was to further our understanding of the fundamental dynamical processes that drive mesoscale phenomena in the upper troposphere and lower stratosphere, and their effects on the advection of passive scalars. Through these studies we made the following findings. 2001]: We derived the Kolmogorov equation for the third-order velocity structure function on an f-plane. We showed how the sign of the function yields the direction of the energy cascade. The remarkable linearity of the measured off diagonal third-order structure function was studied. We suggested that the Coriolis term, which appears explicitly in this equation, may be crucial in understanding the observed kinetic energy spectra at scales larger than 100 km, instead of the nonlinear advection term as previously assumed. Also, we showed that decreases with latitude for mid- to high-latitudes, and tabulated the values. Ozone concentration structure functions were calculated by restricting the data points to approximately isentropic pairings. In this way we were able to make comparisons with scalar advection theories. We found that, at even the largest scales, there was no evidence for the simple scaling predicted for smooth advection/diffusion.
Newell, Reginald E.↗
Complex Role of Secondary Electron Emissions in Dust Grain Charging in Space Environments: Measurements on Apollo 11 and 17 Dust Grains
Dust grains in various astrophysical environments are generally charged electrostatically by photoelectric emissions with radiation from nearby sources, or by electron/ion collisions by sticking or secondary electron emissions. Knowledge of the dust grain charges and equilibrium potentials is important for understanding of a variety of physical and dynamical processes in the interstellar medium (ISM), and heliospheric, interplanetary, planetary, and lunar environments. The high vacuum environment on the lunar surface leads to some unusual physical and dynamical phenomena involving dust grains with high adhesive characteristics, and levitation and transportation over long distances. It has been well recognized that the charging properties of individual micron/submicron size dust grains are expected to be substantially different from the corresponding values for bulk materials and theoretical models. In this paper we present experimental results on charging of individual dust grains selected from Apollo 11 and Apollo 17 dust samples by exposing them to mono-energetic electron beams in the 10- 400 eV energy range. The charging rates of positively and negatively charged particles of approximately 0.2 to 13 microns diameters are discussed in terms of the secondary electron emission (SEE) process, which is found to be a complex charging process at electron energies as low as 10-25 eV, with strong particle size dependence. The measurements indicate substantial differences between dust charging properties of individual small size dust grains and of bulk materials.
Abbas, M. M.↗
Atomic electron tomography in three and four dimensions
Atomic electron tomography (AET) has become a powerful tool for atomic-scale structural characterization in three and four dimensions. It provides the ability to correlate structures and properties of materials at the single-atom level. With recent advances in data acquisition methods, iterative three-dimensional (3D) reconstruction algorithms, and post-processing methods, AET can now determine 3D atomic coordinates and chemical species with sub-Angstrom precision, and reveal their atomic-scale time evolution during dynamical processes. In this work, we review the recent experimental and algorithmic developments of AET and highlight several groundbreaking experiments, which include pinpointing the 3D atom positions and chemical order/disorder in technologically relevant materials and capturing how atoms rearrange during early nucleation at four-dimensional atomic resolution.
30 DIRECT ENERGY CONVERSION↗
Development of the INL Thermal Energy Distribution System (TEDS) in the Modelica Eco-System for Validation and Verification
This report provides an overview on the development of the Thermal Energy Distribution System (TEDS) in the Modelica process model eco-system at Idaho National Laboratory as part of the integrated energy system initiative. Model development has led to the creation of a dynamic process model of the experimental TEDS facility housed within the Engineering Science Laboratory (ESL) at INL. The model was then used during the pre-construction phase of the experimental effort to inform experimental design (insulation requirements, bypass line placement, expected performance of components) and to test innovative control schemes prior to the initial operation. The TEDS model developed in Modelica includes the primary components of the TEDS experimental unit including: a 200kW Chromalox heater, a single-tank packed bed thermal energy storage system filled with 0.125 inch Alumina (Al 2 O 3 ), an ethylene-glycol to Therminol-66 heat exchanger, system piping, six control valves, and all associated temperature, pressure, and mass flow sensors. The model does not include nitrogen fill gas tanks, or associated overfill tanks, as these are not part of standard system control. Two simulation sets were run. The first is a five-hour test that operates as a shakedown test for the facility. This simulation puts the facility through all five potential operating modes and showcases the ability of valving, control sensors, and component controllers to meet the system demands. The second case imposes a typical summer day demand on the system from a region with mixed commercial and residential electrical needs where the generator alone cannot meet peak demand but instead requires the thermal storage unit to act as a peaking unit. Over the course of the fifteen-hour discharge cycle heat losses account for a heat loss of approximately 15°C in outlet temperature. Such heat losses would lead to a decrease in overall system efficiency and may lead to additional design changes for such designs in the future that may include a topping heater. Through commencement of this work, a systems level model of TEDS with associated control systems, sensors, piping diameters, and component capabilities has been created. This model has been utilized in the pre-experimental phase to inform system design, insulation thicknesses, and potential control schemes to operate the system effectively and safely. Once TEDS begins operation, this model will be refined, tuned, and used for validation and verification purposes.
24 POWER TRANSMISSION AND DISTRIBUTION↗
AI-Enabled Discovery and Physics-Based Optimization of Energy Efficient Processing Strategies for Advanced Turbine Alloys (Final Technical Report)
In this project, the multi-organizational team of academic and industrial researchers from the University of Kentucky an aerospace and energy generation OEM partner has leveraged novel Digital Process Twin (DPT) models of process/structure interactions (i.e., process-induced surface integrity) to advance a paradigm of fully integrated computational materials engineering (ICME). Using efficient process models as the core of a digital process simulator for a reinforcement learning algorithm, the team has integrated industrial data and metrics of structure/performance/energy relationships and manufacturing-related energy metrics to optimize dynamic processing parameters for significantly improved life-cycle energy efficiency of advanced γ-TiAl low-pressure turbine (LPT) alloys, as indicated by a set of design relevant parameters (e.g., residual stresses and scrap rate). The key objective and anticipated outcome of the project was at least a 10% reduction in life-cycle embodied energy for a recently developed, γ-TiAl low-pressure turbine (LPT) alloy and nickel-based superalloy Inconel 718, through the adoption of the proposed AI-enabled process optimization approach. The final project outcomes significantly exceeded this original target, realizing manufacturing-related energy efficiency improvements of more than 130% for TiAl and up to 80% for Inconel 718. Rather than following the prevailing and highly inefficient empirical paradigm, the proposed study demonstrated the feasibility of adopting a digital, physics-based process design and optimization paradigm. The recurring need for manual intervention, rework, reinspection causes significant production bottlenecks and unnecessary expense associated with delivering the requisite component quality. The OEM partner, and turbine industry in general, expect to reap significant cost and resource savings if an AI-optimized set of parameters can be applied to specific machining operations. The technical scope of the proposed project involved the paving of a realistic path towards model-based and AI-enabled Integrated Computational Materials Engineering (ICME), and away from inefficient empirical process optimization and legacy manufacturing practices, which are no longer able to efficiently process novel high-performance turbine alloy materials. The project team will address the fundamental knowledge gap that currently exists within the ICME paradigm with respect to the process/structure/performance/energy impacts of finishing processes. While significant resources have been devoted to the ‘early stages’ of manufacturing, such as alloy design, primary and secondary processing, finishing processes have not been adequately integrated within ICME. To provide an actionable path towards model-based finishing process design (e.g., machining, burnishing, grinding, polishing), we will employ a novel AI-enabled process optimization paradigm, based on a computationally efficient, physics-based process simulator. Through limited experimental work to calibrate and validate our process simulator model via an advanced in-situ characterization technique and process optimization via reinforcement learning, the project will seek to demonstrate a viable alternative to the inefficient ‘legacy’ processing strategies, empirical testing and broad scope machining learning approaches, all of which fail to adequately consider complex process physics. The project team has identified an intermetallic γ-TiAl LPT alloy, which is currently being used as part of the OEM partner’s advanced gas turbine designs. This particular alloy poses significant manufacturing challenges during finishing operations, which limit the degree to which the current turbine design can be manufactured in an energy- and cost-efficient manner. Empirical testing and numerical modeling efforts to optimize processing parameters for γ-TiAl have not been able to resolve these manufacturing challenges, so the proposed physics-based AI-enabled optimization technology would offer a truly novel and transformative capability. The multi-organizational team of academic and industry experts from the UKY and the OEM partner will work together closely to demonstrate the analytical and experimental critical function and characteristic proof of concept of this novel approach.
20 FOSSIL-FUELED POWER PLANTS↗
A numerical investigation of the President's Day storm of February 18-19, 1979
The reported investigation is based on the use of a three-dimensional, primitive equation model. The President's Day storm, formed in the Gulf of Mexico as a massive anticyclone, affected the northern states with record-breaking cold temperatures. Attention is given to the physical processes relevant to storm formation, the forecast model, a description of experiments and model forecasts, and model results. An attempt is made to determine the important dynamic processes at work during the evolution of the storm. The jet streak interactions which occurred in the cyclogenetic environment, the effects of cold air damming, and the formation of a strong mesoscale coastal front are found to be of particular interest.
Nappi, A. J.↗
Local interstellar gasdynamical stability in spiral arm flow
The stability of two-dimensional interstellar gas flow passing through a spiral potential has been investigated. The background flow is assumed to move in a tightly wound potential, which may be regarded as external or self-generated. The unperturbed flow, which may be time dependent, is self-gravitating and satisfies the Roberts equations of motion. A polytropic, single-fluid assumption has been used. Magnetic effects are not considered. The motivation behind this work is to try to understand how much of the diversity of spiral arm morphology can be understood by large scale gas dynamical processes alone. To this end, it is suggested that spurring and feathering, and forming molecular cloud complexes may be closely related in the sense of having dynamically similar origins.
Balbus, S. A.↗
Insights into the general circulation of the lower stratosphere from TOMS
Total ozone is controlled by dynamical advection as well as chemistry. At least for day-to-day variations, dynamical processes appear to be in control of total ozone. There also appears to be good evidence that seasonal and secular changes in total ozone are also dynamically controlled. For example, the zonal mean changes in total ozone in the two hemispheres in spring appear to be quite different. The TOMS total ozone data suggest a south polar spring upwelling while the Northern Hemisphere shows a clear downwelling in the same period. Radiative transfer computations support this conclusion. The secular changes in total ozone over the South Pole in spring indicate a change in dynamics rather than chemistry.
Schoeberl, Mark R.↗
Status Report on the High-Temperature Steam Electrolysis Plant Model Developed in the Modelica Framework (FY17)
This report has been prepared as part of an effort to design and build a modeling and simulation (M&S) framework to assess the economic viability of a nuclear-renewable hybrid energy system (N-R HES). In order to facilitate dynamic M&S of such an integrated system, research groups in multiple national laboratories have been developing various subsystems as dynamic physics-based components using the Modelica programming language. In fiscal year 2015 (FY15), Idaho National Laboratory (INL) performed a dynamic analysis of two region-specific N-R HES configurations, including the gas-to-liquid (natural gas to Fischer-Tropsch synthetic fuel) and brackish water reverse osmosis desalination plants as industrial processes. In FY16, INL developed two additional subsystems in the Modelica framework: (1) a high-temperature steam electrolysis (HTSE) plant as a high priority industrial plant to be integrated with a light water reactor (LWR) within an N-R HES and (2) a gas turbine power plant as a secondary energy supply. In FY17, five new components (i.e., a feedwater pump, a multi-stage compression system, a sweep-gas turbine, flow control valves, and pressure control valves) have been incorporated into the HTSE system proposed in FY16, aiming to better realistically characterize all key components of concern. Special attention has been given to the controller settings based on process models (i.e., direct synthesis method), aiming to improve process dynamics and controllability. A dynamic performance analysis of the improved LWR/HTSE integration case was carried out to evaluate the technical feasibility (load-following capability) and safety of such a system operating under highly variable conditions requiring flexible output. The analysis (evaluated in terms of the step response) clearly shows that the FY17 model resulted in superior output responses with much smaller settling times and less oscillatory behavior in response to disturbances in the electric load than those observed with the FY16 model. Simulation results involving several case studies show that the suggested control scheme could maintain the controlled variables (including the steam utilization factor, cathode stream inlet composition, and temperatures and pressures of the process streams at various locations) within desired limits under various plant operating conditions. The results also indicate that the proposed HTSE plant could provide operational flexibility to participate in energy management at the utility scale by dynamically optimizing the use of excess plant capacity within an N-R HES.
08 HYDROGEN↗
Machine learning-based ethylene and carbon monoxide estimation, real-time optimization, and multivariable feedback control of an experimental electrochemical reactor
Electrochemical reduction of CO 2 gas is a novel CO 2 utilization technique that has the potential to mitigate the global climate crisis caused by anthropogenic CO 2 emissions, and enable the large-scale storage of energy generated from renewable sources in the form of carbon-based chemicals and fuels. However, due to the complexity of the electrochemical reactions, the explicit first-principles models for CO2 reduction are not available yet, and there has been a limited effort to develop process modeling, optimization and control of CO 2 electrochemical reactors. To this end, a rotating cylinder electrode (RCE) reactor has been constructed at UCLA to understand the mass transfer and reaction kinetics effects separately on the productivity. In the RCE reactor, the applied potential strongly influences the reaction energetics and the electrode rotation speed affects the hydrodynamic boundary layer and modifies the film mass transfer coefficient, which involves convective and diffusive transport. Further, the present work aims to develop a multi-input multi-output (MIMO) control scheme for the RCE reactor that integrates techniques from artificial and recurrent neural network modeling, nonlinear optimization, and process controller design. Specifically, production rates of two products from the experimental reactor, ethylene and carbon monoxide, are controlled by manipulating two inputs, applied potential and catalyst rotation speed. Process dynamics and controllability are analyzed, a feedback control strategy is designed and the controllers are tuned accordingly. The experimental electrochemical cell is employed to gather data for process modeling and implement the multivariable control system. Finally, the experimental results are presented which demonstrate excellent closed-loop performance by the control system and regulation of the outputs at three different set-points including an economically-optimal set-point.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Monitoring autophagic flux using p62/SQSTM1 based luciferase reporters in glioma cells
Highlights: • A luciferase based autophagic flux detection system, Luc2p-p62 vs. Luc2p-p62ΔU, was developed. • This system can be used to detect TMZ-induced autophagic flux changes in U87MG cells. • This system can assay the effect of autophagy modulators in different types of tumor cells. Autophagy is a highly dynamic process characterized with the term of autophagic flux. In the present study, we developed a quantifiable luciferase reporter system to measure the capacity as well as the dynamics of autophagic flux. Briefly, a luciferase variant of Luc2p was fused with p62/SQSTM1 or its UBA domain deletion mutant (p62ΔU) and transfected into cells. The expressed Luc2p-p62 fusion protein was primarily degraded via autophagy, while Luc2p-p62ΔU was employed as a normalization control due to its resistance to autophagic degradation. The luciferase activity of the lysates from two parallel populations of glioma cells expressing either Luc2p-p62 or Luc2p-p62ΔU was determined and the ratio of Luc2p-p62ΔU/Luc2p-p62 was used to assay the autophagic flux. By this approach, the induction of autophagy was manifested as an increased Luc2p-p62ΔU/Luc2p-p62 ratio, which could be neutralized by autophagy inhibitors or knockdown of ATG5. The performance of our autophagic flux detection system was comparable to a recently reported GFP-LC3-RFP-LC3ΔG probe. We tested the system in TMZ treated glioma cells, and found that coadministration of chloroquine to attenuate cellular autophagic flux significantly improved the TMZ efficacy by triggering more early apoptosis. Collectively, our luciferase-based autophagic flux assay may serve as a useful alternative yet sensitive method for autophagic flux detection in tumor cells.
60 APPLIED LIFE SCIENCES↗