Search NASA⌕ Search

SEARCH · Search NASA

Results for “Speed Control”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

A data driven control strategy for optimal and flexible operation of absorption systems; Stratégie de régulation fondée sur les données pour un fonctionnement optimal et flexible des systèmes à absorption

A novel control strategy for vapor absorption systems with experimental validation is presented. Statistical methods are used to integrate a detailed thermodynamic model and system-specific characteristics into a model based control algorithm. This allows for continuously optimized operation as well as fast response to variations in operating conditions. Autonomous controller performance was tested experimentally for response to changes in heat sink and evaporator temperatures. Continuous turndown with fast response to capacity demand changes, in contrast to suboptimal on/off control, was demonstrated. The thermal compressor concept was employed to develop the variable speed thermal compressor module, with aspects specific to absorption heat pumps, also facilitating cross-applicability of vapor compression system control strategies. Our results of this study enable further development and optimization of absorption systems for a wide range of applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Improving the nonlinear control performance of the supply fan at air handling units using a gain scheduling control strategy

Due to its nonlinear nature, the supply fan at air handling units with the controller tuned at the design condition tends to be aggressive and oscillate under partial load conditions. Here, the objective of this paper is to develop and validate a gain scheduling control strategy to improve its nonlinear control performance. First, a control-oriented model, which does not require numerous physical parameters and extensive test data, is developed to study the nonlinearity of the fan system. Based on the theoretical model and experimental verifications, the issue of an aggressive response with a conventional fixed-gain controller is caused by the fact that the system gain is proportional to the ratio of the duct static pressure to the fan speed. To address the issue, a scheduling function of the measurable duct static pressure and fan speed is proposed to be included in the conventional fixed-gain controller to compensate for the fan system gain variation. The gain scheduling control strategy is found to approximately maintain the identical control performance under all operation conditions. Most importantly, the gain scheduling control strategy can be readily implemented without intensive computation and additional measurements, showing a promising potential in industrial applications.

42 ENGINEERING↗
DOE OSTI2014

Reactivity-controlled compression ignition drive cycle emissions and fuel economy estimations using vehicle system simulations

In-cylinder blending of gasoline and diesel to achieve reactivity-controlled compression ignition has been shown to reduce NO X and soot emissions while maintaining or improving brake thermal efficiency as compared with conventional diesel combustion. The reactivity-controlled compression ignition concept has an advantage over many advanced combustion strategies in that the fuel reactivity can be tailored to the engine speed and load, allowing stable low-temperature combustion to be extended over more of the light-duty drive cycle load range. In this paper, a multi-mode reactivity-controlled compression ignition strategy is employed where the engine switches from reactivity-controlled compression ignition to conventional diesel combustion when speed and load demand are outside of the experimentally determined reactivity-controlled compression ignition range. The potential for reactivity-controlled compression ignition to reduce drive cycle fuel economy and emissions is not clearly understood and is explored here by simulating the fuel economy and emissions for a multi-mode reactivity-controlled compression ignition–enabled vehicle operating over a variety of US drive cycles using experimental engine maps for multi-mode reactivity-controlled compression ignition, conventional diesel combustion, and a 2009 port-fuel injected gasoline engine. Drive cycle simulations are completed assuming a conventional mid-size passenger vehicle with an automatic transmission. Multi-mode reactivity-controlled compression ignition fuel economy simulation results are compared with the same vehicle powered by a representative 2009 port-fuel injected gasoline engine over multiple drive cycles. Finally, engine-out drive cycle emissions are compared with conventional diesel combustion, and observations regarding relative gasoline and diesel tank sizes needed for the various drive cycles are also summarized.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Experimental and Computational Study of a High-Speed Collision of an Aluminum Striker with a Solid and Mesh Obstacle

The results of computational and experimental studies of peculiarities of the process of impact between the striker and obstacle, which imitates shield protection of spacecrafts, have been considered and pictures of fragmentation of the striker and obstacle have been obtained. The numerical calculations were carried out using the method of smooth particle hydrodynamics (SPH). In the experiments, the striker was accelerated using a two-stage light-gas gun; the state of the obstacle and striker at the moment of their interaction was controlled using an X-ray and high-speed video camera. The recording equipment was switched on using induction cross sections. The comparative analysis of the results of numerical simulations and experiments have been considered.

42 ENGINEERING↗
DOE OSTI2022

Region-adaptive, Error-controlled Scientific Data Compression using Multilevel Decomposition

The increase of computer processing speed is significantly outpacing improvements in network and storage bandwidth, leading to the big data challenge in modern science, where scientific applications can quickly generate much more data than that can be transferred and stored. As a result, big scientific data must be reduced by a few orders of magnitude while the accuracy of the reduced data needs to be guaranteed for further scientific explorations. Moreover, scientists are often interested in some specific spatial/temporal regions in their data, where higher accuracy is required. The locations of the regions requiring high accuracy can sometimes be prescribed based on application knowledge, while other times they must be estimated based on general spatial/temporal variation. In this paper, we develop a novel multilevel approach which allows users to impose region-wise compression error bounds. Our method utilizes the byproduct of a multilevel compressor to detect regions where details are rich and we provide the theoretical underpinning for region-wise error control. With spatially varying precision preservation, our approach can achieve significantly higher compression ratios than single-error bounded compression approaches and control errors in the regions of interest.We conduct the evaluations on two climate use cases – one targeting small-scale, node features and the other focusing on long, areal features. For both use cases, the locations of the features were unknown ahead of the compression. By selecting approximately 16% of the data based on multi-scale spatial variations and compressing those regions with smaller error tolerances than the rest, our approach improves the accuracy of post-analysis by approximately 2 × compared to single-error-bounded compression at the same compression ratio. Using the same error bound for the region of interest, our approach can achieve an increase of more than 50% in overall compression ratio.

Gong, Qian↗
DOE OSTI2018

A Riccati Solution for the Ideal MHD Plasma Response with Applications to Real-time Stability Control

To effectuate near real-time feedback control of ideal MHD instabilities in a tokamak geometry, a rapid solution for stability analysis is a prerequisite. Toward this end, we reformulate the δW stability method with a Hamilton-Jacobi theory, elucidating analytical and numerical features of the generic tokamak ideal MHD stability problem. The plasma response matrix is demonstrated to be the solution of an ideal MHD matrix Riccati differential equation (MRDE). Since Riccati equations are prevalent in the control theory literature, such a shift in perspective brings to bear a range of numerical methods that are well-suited to the robust, fast solution of control problems. We discuss the usefulness of Riccati techniques in solving the stiff ODEs often encountered in ideal MHD stability analyses-—for example, in tokamak edge and stellarator physics. We then demonstrate the applicability of such methods to an existing 2D ideal MHD stability code—DCON—enabling its parallel operation in near real-time. Output is shown to match with high accuracy, and with wall-clock time ≪ 1s. Such speed may help enable active feedback ideal MHD stability control, especially in tokamak plasmas whose ideal MHD equilibria evolve with inductive timescale τ > 1s-—as in ITER.

Parallel↗
DOE OSTI2013

Communication Simulations for Power System Applications

New smart grid technologies and concepts, such as dynamic pricing, demand response, dynamic state estimation, and wide area monitoring, protection, and control, are expected to require considerable communication resources. As the cost of retrofit can be high, future power grids will require the integration of high-speed, secure connections with legacy communication systems, while still providing adequate system control and security. While considerable work has been performed to create co-simulators for the power domain with load models and market operations, limited work has been performed in integrating communications directly into a power domain solver. The simulation of communication and power systems will become more important as the two systems become more inter-related. This paper will discuss ongoing work at Pacific Northwest National Laboratory to create a flexible, high-speed power and communication system co-simulator for smart grid applications. The framework for the software will be described, including architecture considerations for modular, high performance computing and large-scale scalability (serialization, load balancing, partitioning, cross-platform support, etc.). The current simulator supports the ns-3 (telecommunications) and GridLAB-D (distribution systems) simulators. Ongoing and future work will be described, including planned future expansions for a traditional transmission solver. A test case using the co-simulator, utilizing a transactive demand response system created for the Olympic Peninsula and AEP gridSMART demonstrations, requiring two-way communication between distributed and centralized market devices, will be used to demonstrate the value and intended purpose of the co-simulation environment.

co-simulation↗
DOE OSTI2023

In Situ Observation of Domain Wall Lateral Creeping in a Ferroelectric Capacitor

As a promising candidate for next-generation nonvolatile memory devices, ferroelectric oxide films exhibit many emergent phenomena with functional applications, making understanding polarization switching and domain evolution behaviors of fundamental importance. However, tracking domain wall motion in ferroelectric oxide films with high spatial resolution remains challenging. Here, in this study, an in situ biasing approach for direct atomic-scale observations of domain nucleation and sideways motion is presented. By accurately controlling the applied electric field, the lateral translational speed of the domain wall can decrease to less than 2.2 Å s −1 , which is observable with atomic resolution STEM imaging. In situ observations on a capacitor structured PbZr 0.1 Ti 0.9 O 3 /La 0.7 Sr 0.3 MnO 3 heterojunction demonstrate the unique creeping behavior of a domain wall under a critical electric field, with the atomic structure of the creeping domain wall revealed. Moreover, the evolution of the metastable domain wall forms an elongated morphology, which contains a large proportion of charged segments. Phase-field simulations unveil the competition between gradient, elastic, and electrostatic energies that decide this unique domain wall creeping and morphology variation. This work paves the way toward a complete fundamental understanding of domain wall physics and potential modulations of domain wall properties in real devices.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Lattice Softening Significantly Reduces Thermal Conductivity and Leads to High Thermoelectric Efficiency

The influence of micro/nanostructure on thermal conductivity is a topic of great scientific interest, particularly to thermoelectrics. The current understanding is that structural defects decrease thermal conductivity through phonon scattering where the phonon dispersion and speed of sound are assumed to remain constant. Experimental work on a PbTe model system is presented, which show that the speed of sound linearly decreases with increased internal strain. This softening of the materials lattice completely accounts for the reduction in lattice thermal conductivity, without the introduction of additional phonon scattering mechanisms. Additionally, it is shown that a major contribution to the improvement in the thermoelectric figure of merit (zT > 2) of high-efficiency Na-doped PbTe can be attributed to lattice softening. While inhomogeneous internal strain fields are known to introduce phonon scattering centers, this study demonstrates that internal strain can modify phonon propagation speed as well. This introduces new avenues to control lattice thermal conductivity, beyond phonon scattering. In practice, many engineering materials will exhibit both softening and scattering effects, as is shown in silicon. Here, we shine new light on studies of thermal conductivity in fields of energy materials, microelectronics, and nanoscale heat transfer.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A Bayesian modeling framework for crash severity effects of active traffic management systems

Transportation agencies utilize Active traffic management (ATM) systems to dynamically manage recurrent and non-recurrent congestion based on real-time conditions. While these systems have been shown to have some safety benefits, their impact on injury severity outcomes is currently uncertain. In this paper, we used full Bayesian mixed logit models to quantify the impact that ATM deployment had on crash severities. The estimation results revealed lower severities with ATM deployment. Marginal effects for ATM deployments that featured hard shoulder running (HSR) revealed lower likelihoods for severe and moderate injury crashes of 15.9 % and for minor injury crashes of 10.1 %. The likelihood of severe and moderate injury crashes and minor injury crashes reduced by 12.4 % and 8.33 % with ATM without HSR. The models were observed to be temporally transferable and had forecast error of 0.301 and 0.304 for the two models, revealing better performance with validation data. These results have implications for improving freeway crash risk at critical locations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Hydrokinetic energy conversion using flow induced oscillations of single-cylinder with large passive turbulence control

Various types of flow-induced oscillations (FIOs) have been implemented in development of marine hydrokinetic (MHK) energy converters. With passive turbulence control (PTC), energy harvesting starts at a flow speed of about 0.5 m/s. However, there is worldwide MHK energy available in even slower currents. In the present study, the effect of damping on FIO and power extraction is investigated for a converter with large turbulence stimulation (PTC) consisting of straight strips with a height of 15% of the cylinder diameter and placed symmetrically on the cylinder surface. The oscillating amplitude decreases, as the damping ratio increases, with unchanged sinusoidal pattern of the displacement time-history. The frequency ratio is also affected by damping especially in the VIV initial branch and transition region between VIV and galloping. An important flow characteristic of the large-PTC cylinder is that a recirculation region is formed behind the PTC, causing appreciable disturbance to the flow past the cylinder. Power can be harvested in the whole FIO range and the harnessed power maximum appears at the largest inflow velocity tested. However, the optimum of harnessing efficiency is located at the beginning of the VIV upper branch. The gap between VIV and galloping is bridged when large PTC is used, eliminating the drop in power and efficiency even at higher damping, which would be a weakness of regular-PTC cylinder for energy harvesting. Finally, the mechanism behind the variation of harnessing efficiency with inflow velocity and damping ratio is revealed, and the optimality criterion for the converter design is discussed.

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Data-driven prediction of geometry- and toolpath sequence-dependent intra-layer process conditions variations in laser powder bed fusion

Geometrical features and toolpath sequence are two important factors that cause process condition variations, such as variations in the meltpool temperature or meltpool size, that might lead to undesired material properties in the laser powder bed fusion (LPBF) process. Due to the high dynamics and complex physics of the LPBF process, it is difficult to predict variations in process conditions with simulations alone. Advances in measurement technology and computational technologies open up new possibilities for smart manufacturing. In this paper, a data-driven method to predict intra-layer variations in the processing conditions that source from the toolpath sequence and part geometry is presented. The approach is demonstrated using two-color on-axis pyrometer measurements. Three demonstration cases are presented in which it is demonstrated (1) how the trained predictive model can be used as a filter to ease the interpretation of process variations and discover patterns related to toolpath and part geometry, and (2) how to generate predictions that can be used for feedforward control, i.e., for adjusting laser power or scanning speed along the toolpath using a meltpool temperature prediction model generated based on on-axis measurements. Results show that the developed prediction model is able to meaningfully predict process variations resulted from toolpath sequence and geometry. Predictions are aligned with the results from the related work of others and for the case of 180° laser path turnarounds in our high-speed X-ray imaging experiments. In conclusion, the potential issues related to the current maturity status of the process and measuring equipment that could in practice affect the performance of the proposed solutions are also discussed.

42 ENGINEERING↗
DOE OSTI2022

Monitoring and prediction of porosity in laser powder bed fusion using physics-informed meltpool signatures and machine learning

In this work we accomplished the monitoring and prediction of porosity in laser powder bed fusion (LPBF) additive manufacturing process. This objective was realized by extracting physics-informed meltpool signatures from an in-situ dual-wavelength imaging pyrometer, and subsequently, analyzing these signatures via computationally tractable machine learning approaches. Porosity in LPBF occurs despite extensive optimization of processing conditions due to stochastic causes. Hence, it is essential to continually monitor the process with in-situ sensors for detecting and mitigating incipient pore formation. In this work a tall cuboid-shaped part (10 mm × 10 mm × 137 mm, material ATI 718Plus) was built with controlled porosity by varying laser power and scanning speed. This test caused various types of porosity, such as lack-of-fusion and keyhole formation, with varying degrees of severity in the part. The meltpool was continuously monitored using a dual-wavelength imaging pyrometer installed in the machine. Physically intuitive process signatures, such as meltpool length, temperature distribution, and ejecta (spatter) characteristics, were extracted from the meltpool images. Subsequently, relatively simple machine learning models, e.g., K-Nearest Neighbors, were trained to predict both the severity and type of porosity as a function of these physics-informed meltpool signatures. These models resulted in a prediction accuracy exceeding 95% (statistical F1-score). The same analysis was carried out with a complex, black-box deep learning convolutional neural network which directly used the meltpool images instead of physics-informed features. The convolutional neural network produced a comparable F1-score in the range of 89–97%. Finally, these results demonstrate that using pragmatic, physics-informed meltpool signatures within a simple machine learning model is as effective for flaw prediction in LPBF as using a complex and computationally demanding black-box deep learning model.

36 MATERIALS SCIENCE↗
DOE OSTI2022

$\mathrm{SIM}$-$\mathrm{STEM}$ $\mathrm{Lab}$: Incorporating Compressed Sensing Theory for Fast STEM Simulation

We report recently it has been shown that precise dose control and an increase in the overall acquisition speed of atomic resolution scanning transmission electron microscope (STEM) images can be achieved by acquiring only a small fraction of the pixels in the image experimentally and then reconstructing the full image using an inpainting algorithm. In this paper, we apply the same inpainting approach (a form of compressed sensing) to simulated, sub-sampled atomic resolution STEM images. We find that it is possible to significantly sub-sample the area that is simulated, the number of g-vectors contributing the image, and the number of frozen phonon configurations contributing to the final image while still producing an acceptable fit to a fully sampled simulation. Here we discuss the parameters that we use and how the resulting simulations can be quantifiably compared to the full simulations. As with any Compressed Sensing methodology, care must be taken to ensure that isolated events are not excluded from the process, but the observed increase in simulation speed provides significant opportunities for real time simulations, image classification and analytics to be performed as a supplement to experiments on a microscope to be developed in the future

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

A Kriging-Based Approach to Autonomous Experimentation with Applications to X-Ray Scattering

Abstract Modern scientific instruments are acquiring data at ever-increasing rates, leading to an exponential increase in the size of data sets. Taking full advantage of these acquisition rates will require corresponding advancements in the speed and efficiency of data analytics and experimental control. A significant step forward would come from automatic decision-making methods that enable scientific instruments to autonomously explore scientific problems—that is, to intelligently explore parameter spaces without human intervention, selecting high-value measurements to perform based on the continually growing experimental data set. Here, we develop such an autonomous decision-making algorithm that is physics-agnostic, generalizable, and operates in an abstract multi-dimensional parameter space. Our approach relies on constructing a surrogate model that fits and interpolates the available experimental data, and is continuously refined as more data is gathered. The distribution and correlation of the data is used to generate a corresponding uncertainty across the surrogate model. By suggesting follow-up measurements in regions of greatest uncertainty, the algorithm maximally increases knowledge with each added measurement. This procedure is applied repeatedly, with the algorithm iteratively reducing model error and thus efficiently sampling the parameter space with each new measurement that it requests. We validate the method using synthetic data, demonstrating that it converges to faithful replica of test functions more rapidly than competing methods, and demonstrate the viability of the approach in an experimental context by using it to direct autonomous small-angle (SAXS) and grazing-incidence small-angle (GISAXS) x-ray scattering experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Experimental validation of advanced regulations for superconducting magnet cooling undergoing periodic heat loads

Superconducting magnets used in tokamaks undergo periodic heat load caused by cycling plasma operations inducing AC losses, neutrons fluxes and eddy currents in magnet structures. In the cryogenic system of JT60-SA tokamak, the Auxiliary Cold Box (ACB) distributes helium from the refrigerator to the cryogenic users and in particular to the superconducting magnets. ACB comprises a saturated helium bath with immersed heat exchangers, extracting heat from independent cooling loops. The supercritical helium flow in each cooling loop is driven by a cold circulator. In order to safely operate the refrigerator during plasma pulses, the interface between the ACB and the refrigerator shall be as stable as possible, with well-balanced bath inlet and outlet mass flows during cycling operation. The solution presented in this paper relies on a combination of regulations to smooth pulsed heat loads and to keep a constant refrigeration power during all the cycle. Two smoothing strategies are presented, both regulating the outlet mass flow of the bath: the first one using the bath as a thermal buffer and the second one storing energy in the loop by varying the cold circulator speed. The bath outlet mass flow is also controlled by an immersed resistive heater which enables a constant evaporation rate in the bath when power coming from the loops is decreasing. The refrigeration power is controlled so that the compensating power remains within an acceptable margin. Experimental validation is achieved using the HELIOS facility. This facility running at CEA Grenoble since 2010 is a scaled down model of the ACB bath and Central Solenoid magnet cooling loop of the JT60-SA tokamak. Test results show performances and robustness of the regulations.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2014

Early time implosion symmetry from two-axis shock-timing measurements on indirect drive NIF experiments

An innovative technique has been developed and used to measure the shock propagation speed along two orthogonal axes in an inertial confinement fusion indirect drive implosion target. This development builds on an existing target and diagnostic platform for measuring the shock propagation along a single axis. A 0.4 mm square aluminum mirror is installed in the ablator capsule which adds a second orthogonal view of the x-ray-driven shock speeds. The new technique adds capability for symmetry control along two directions of the shocks launched in the ablator by the laser-generated hohlraum x-ray flux. Laser power adjustments in four different azimuthal cones based on the results of this measurement can reduce time-dependent symmetry swings during the implosion. Analysis of a large data set provides experimental sensitivities of the shock parameters to the overall laser delivery and in some cases shows the effects of laser asymmetries on the pole and equator shock measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Azimuthal-spin-wave-mode-driven vortex-core reversals

We studied, by micromagnetic numerical calculations, asymmetric vortex-core reversals driven by the m = −1 and m = +1 azimuthal spin-wave modes' excitations in soft magnetic circular nano-disks. We addressed the similarities and differences between the asymmetric core reversals in terms of the temporal evolutions of the correlated core-motion speed, locally concentrated perpendicular gyrofield, and magnetization dip near the original vortex core. The criterion for the core reversals was found to be the magnetization dip that must reach the out-of-plane magnetization component, m{sub z} = −p, with the initial polarization p, where p = +1 (−1) for the upward (downward) core magnetization. The core-motion speed and the associated perpendicular gyrofield, variable and controllable with static perpendicular field, H{sub z}, applied perpendicularly to the disk plane, must reach their threshold values to meet the ultimate core-reversal criterion. Also, we determined the H{sub z} strength and direction dependence of the core-switching time and threshold exciting field strength required for the core reversals, whose parameters are essential in the application aspect. This work offers deeper insights into the azimuthal spin-wave-driven core-reversal dynamics as well as an efficient means of controlling the azimuthal-modes-driven core reversals.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗