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At least 1,045 records · Page 58
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NASA NTRSDate not supplied

High-Fidelity Aerodynamic Analysis and Optimization of the SUSAN Electrofan Concept

The Subsonic Single Aft Engine (SUSAN) Electrofan is a new single-aisle regional jet class transport aircraft being studied by NASA, which benefits from reduced fuel consumption through a reduction in the number of hydrocarbon fuel-burning engines from two to one. This is achieved through a hybrid-electric system architecture, where a series of generators are used to extract power from a fuel-consuming tail cone thruster to drive electric propulsors mounted on the wings. To support the development of these propulsion systems, which involve high levels of propulsion-airframe integration, this paper presents high-fidelity analyses through computational fluid dynamics (CFD) simulations provided by the Launch Ascent and Vehicle Aerodynamics (LAVA) framework, which also includes capabilities for modeling the effect of active propulsors. A trade space exploration is performed to investigate the advantages of several wing mounted distributed electric propulsion system configurations, including over-wing, under-wing, and trailing-edge arrangements. For the aft fuselage propulsor, focus is on the sizing of the inlet, core, and bypass ducts. High-fidelity aerodynamic shape optimization is also used to help minimize the inlet distortion intensity experienced by the aft propulsor fan through a reshaping of the fuselage.

CAS↗
DOE OSTI2022

Site demonstration and performance evaluation of MPC for a large chiller plant with TES for renewable energy integration and grid decarbonization

Thermal energy storage (TES) for a cooling plant is a crucial resource for load flexibility. Traditionally, simple, heuristic control approaches, such as the storage priority control which charges TES during the nighttime and discharges during the daytime, have been widely used in practice, and shown reasonable performance in the past benefiting both the grid and the end-users such as buildings and district energy systems. However, the increasing penetration of renewables changes the situation, exposing the grid to a growing duck curve, which encourages the consumption of more energy in the daytime, and volatile renewable generation which requires dynamic planning. The growing pressure of diminishing greenhouse gas emissions also increases the complexity of cooling TES plant operations as different control strategies may apply to optimize operations for energy cost or carbon emissions. This paper presents a model predictive control (MPC), site demonstration and evaluation results of optimal operation of a chiller plant, TES and behind-meter photovoltaics for a campus-level district cooling system. The MPC was formulated as a mixed-integer linear program for better numerical and control properties. Compared with baseline rule-based controls, the MPC results show reductions of the excess PV power by around 25%, of the greenhouse gas emission by 10%, and of peak electricity demand by 10%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Quantifying uncertainty in analysis of shockless dynamic compression experiments on platinum. I. Inverse Lagrangian analysis

Absolute measurements of solid-material compressibility by magnetically driven shockless dynamic compression experiments to multi-megabar pressures have the potential to greatly improve the accuracy and precision of pressure calibration standards for use in diamond anvil cell experiments. Here, to this end, we apply characteristics-based inverse Lagrangian analysis (ILA) to 11 sets of ramp-compression data on pure platinum (Pt) metal and then reduce the resulting weighted-mean stress–strain curve to the principal isentrope and room-temperature isotherm using simple models for yield stress and Grüneisen parameter. We introduce several improvements to methods for ILA and quasi-isentrope reduction, the latter including calculation of corrections in wave speed instead of stress and pressure to render results largely independent of initial yield stress while enforcing thermodynamic consistency near zero pressure. More importantly, we quantify in detail the propagation of experimental uncertainty through ILA and model uncertainty through quasi-isentrope reduction, considering all potential sources of error except the electrode and window material models used in ILA. Compared to previous approaches, we find larger uncertainty in longitudinal stress. Monte Carlo analysis demonstrates that uncertainty in the yield-stress model constitutes by far the largest contribution to uncertainty in quasi-isentrope reduction corrections. We present a new room-temperature isotherm for Pt up to 444 GPa, with 1-sigma uncertainty at that pressure of just under ±1.2%; the latter is about a factor of three smaller than uncertainty previously reported for multi-megabar ramp-compression experiments on Pt. The result is well represented by a Vinet-form compression curve with (isothermal) bulk modulus K 0 = 270.3 ± 3.8 GPa, pressure derivative K$^{'}_{0}$= 5.66 ± 0.10, and correlation coefficient $R_{K_{0},K^{'}_{0}}$= –0.843.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Training self-learning circuits for power-efficient solutions

As the size and ubiquity of artificial intelligence and computational machine learning models grow, the energy required to train and use them is rapidly becoming economically and environmentally unsustainable. Recent laboratory prototypes of self-learning electronic circuits, such as “physical learning machines,” open the door to analog hardware that directly employs physics to learn desired functions from examples at a low energy cost. In this work, we show that this hardware platform allows for an even further reduction in energy consumption by using good initial conditions and a new learning algorithm. Using analytical calculations, simulations, and experiments, we show that a trade-off emerges when learning dynamics attempt to minimize both the error and the power consumption of the solution—greater power reductions can be achieved at the cost of decreasing solution accuracy. Finally, we demonstrate a practical procedure to weigh the relative importance of error and power minimization, improving the power efficiency given a specific tolerance to error.

Stern, Menachem (ORCID:0000000302158082)↗
DOE OSTI2020

Rupture Dynamics Simulations of Shallow Crustal Earthquakes on Reverse Slip Faults

The main goal of this study was to perform dynamic rupture simulations in order constrain the characterization of kinematic rupture models implemented in techniques for simulating strong ground motion for crustal earthquakes. First, we investigated the rupture process of the 2008 Iwate-Miyagi Nairiku earthquake by developing a dynamic rupture model on a reverse fault using a trial-and-error technique that produced a slip distribution and near-fault ground motion that matched the recorded ones. The simulations were performed in the frequency range 0-2 Hz, using a 3D staggered grid finite-difference method and a linear slip weakening friction law. Constrained by the observed slip distribution and consistent with dynamic rupture models, the derived kinematic rupture model of the Iwate-Miyagi Nairiku earthquake contains areas with relatively large slip rate, representing strong motion generation areas, set against lower amplitude heterogeneous background slip, and a relatively low slip rate in the weak zone of the top-most crust (upper 3km). Second, we performed rupture dynamics modeling to constrain shallow slip characterization in rupture models for strike-slip crustal earthquakes. The objective was to establish general rules about the characterization of slip rate function and slip at shallow depths and in the strong motion generation areas (SMGAs). The simulations of spontaneous rupture were performed in the frequency range 0-2.0Hz, using a 3D staggered-grid finite-difference method and a layer over half-space 1D crustal velocity model with a minimum shear-wave velocity of 2.8 km/s. In order to account for changes in material ductility and reduction of stress drop, observed in the shallow crust (upper 3-5 km), and the transition from ductile state to brittle state in the upper seismogenic zone, in our stress models we included a shallow weak zone (<4km). In this zone the stress drop was set to zero at the free surface and gradually increased with depth, while the slip weakening distance was set to 75 cm at the free surface and decreased to 50 cm at the base of the weak zone. As in the case of reverse faulting during the Iwate-Miyagi Nairiku earthquake, from these computations we found a systematic change in the shape of the slip-rate function, from Kostrov-type in the deeper part of the fault to a more symmetric cosine-type in the upper few kilometers, near the free-surface. Moreover, the average slip duration in the weak zone, with respect to slip duration in the deeper parts of the fault, increases by at most a factor of 1.5. We found a systematic and gradual change in the shape of the slip-rate function from Kostrov-type in the asperity areas (SMGAs), to more symmetric cosine-type in the upper few km near the free-surface, on the long period motion generation area (LMGA). The effective rise time in the LMGA, with respect to that in the SMGAs, increases by at most a factor of 2. Effective rise time is the time difference between the time at which the slip rate drops to a level that is equal to 25% of its peak and the onset time of the signal. In addition, the slip in the LMGA located above the SMGAs is almost the same as the one in the SMGAs, and about 1.5 times larger than the average slip.

58 GEOSCIENCES↗
NASA NTRS1990

Acquisition and analysis of accelerometer data

Acceleration data reduction must be undertaken with a complete understanding of the physical process, the means by which the data are acquired, and finally, the calculations necessary to put the data into a meaningful format. Discussed here are the acceleration sensor requirements dictated by the measurements desired. Sensor noise, dynamic range, and linearity will be determined from the physical parameters of the experiment. The digitizer requirements are discussed. Here the system from sensor to digital storage medium will be integrated, and rules of thumb for experiment duration, filter response, and number of bits are explained. Data reduction techniques after storage are also discussed. Time domain operations including decimating, digital filtering, and averaging are covered, as well as frequency domain methods, including windowing and the difference between power and amplitude spectra, and simple noise determination via coherence analysis. Finally, an example experiment using the Teledyne Geotech Model 44000 Seismometer to measure from 1 Hz to 10(exp -6) Hz is discussed. The sensor, data acquisition system, and example spectra are presented.

Verges, Keith R.↗
NASA NTRS1990

Impeller response calculation due to complex pressure loading

An analysis technique is described to calculate the harmonic response of the first-stage impeller of the Space Shuttle Main Engine high pressure fuel turbopump. The excitation is a complex pressure loading at various locations on the impeller blades. The pressure loading was predicted using computational fluid dynamic techniques and was given as a Fourier series at 48 different locations on each of the three impeller blade types. The analysis consisted of mapping the pressures onto a three-dimensional finite element model, then converting these pressure loads to complex nodal force vectors at specified equal time intervals. The resulting vectors were then converted to modal force time histories that were then transformed into the frequency domain where the frequency response was calculated directly. This technique resulted in an improvement to the previously used direct integration technique and in a substantial analysis cost reduction.

Wellstein, Carl↗
NASA NTRS2016

Vibroacoustic Characterization of Corrugated-Core and Honeycomb-Core Sandwich Panels

The vibroacoustic characteristics of two candidate launch vehicle fairing structures, corrugated- core and honeycomb-core sandwich designs, were studied. The study of these structures has been motivated by recent risk reduction efforts focused on mitigating high noise levels within the payload bays of large launch vehicles during launch. The corrugated-core sandwich concept is of particular interest as a dual purpose structure due to its ability to harbor resonant noise control systems without appreciably adding mass or taking up additional volume. Specifically, modal information, wavelength dispersion, and damping were determined from a series of vibrometer measurements and subsequent analysis procedures carried out on two test panels. Numerical and analytical modeling techniques were also used to assess assumed material properties and to further illuminate underlying structural dynamic aspects. Results from the tests and analyses described herein may serve as a reference for additional vibroacoustic studies involving these or similar structures.

Allen, Albert↗
NASA NTRSDate not supplied

Advances in Integrally Formed Metallic Structures

NASA Langley Research Center (LaRC) is applying flow forming technology to aerospace aluminum alloys for the manufacture of integrally stiffened cylinders that meet aircraft fuselage or launch vehicle specifications. High-strength 2xxx series alloys, in various temper/product form conditions, are being compared with medium-strength, very formable AA 6061 as the benchmark. Screening of candidate materials traditionally relies on empirical forming trials, but more recently on metrics derived from constant nominal strain rate tensile testing. In this work, the established hierarchy of formability metrics is adopted as the baseline; tensile area reduction, work hardening exponent, and modulus of resilience. The suite of metrics can be expanded based on phenomenological and mechanistic considerations of plastic flow instabilities to incorporate anisotropy ratio, rate of work hardening, and dynamic strain aging effects. Separate research thrusts at LaRC are aimed at formulating a protocol for scalable production of fully formed, defect-free components: 1) quantifying the extended set of formability metrics from constant and jump strain rate tensile tests with digital image correlation (DIC); 2) using statistically designed experiments on a vertical spin/flow forming facility (WF VUD-600®) to isolate the effect of convenient process variables, such as axial feed rate and thickness reduction; and 3) predicting the effect of feed ratio (roller translation relative to mandrel rotation speeds) on material response via process modeling using the DEFORM® simulation software. Current results will be discussed in terms of correlating intrinsic material properties with the bulk workability characteristics to successfully fabricate cylinders with complex cross-sections.

Aluminum↗
NASA NTRS1999

Large Eddy Simulation of Cirrus Clouds

The Regional Atmospheric Modeling System (RAMS) with mesoscale interactive nested-grids and a Large-Eddy Simulation (LES) version of RAMS, coupled to two-moment microphysics and a new two-stream radiative code were used to investigate the dynamic, microphysical, and radiative aspects of the November 26, 1991 cirrus event. Wu (1998) describes the results of that research in full detail and is enclosed as Appendix 1. The mesoscale nested grid simulation successfully reproduced the large scale circulation as compared to the Mesoscale Analysis and Prediction System's (MAPS) analyses and other observations. Three cloud bands which match nicely to the three cloud lines identified in an observational study (Mace et al., 1995) are predicted on Grid #2 of the nested grids, even though the mesoscale simulation predicts a larger west-east cloud width than what was observed. Large-eddy simulations (LES) were performed to study the dynamical, microphysical, and radiative processes in the 26 November 1991 FIRE 11 cirrus event. The LES model is based on the RAMS version 3b developed at Colorado State University. It includes a new radiation scheme developed by Harrington (1997) and a new subgrid scale model developed by Kosovic (1996). The LES model simulated a single cloud layer for Case 1 and a two-layer cloud structure for Case 2. The simulations demonstrated that latent heat release can play a significant role in the formation and development of cirrus clouds. For the thin cirrus in Case 1, the latent heat release was insufficient for the cirrus clouds to become positively buoyant. However, in some special cases such as Case 2, positively buoyant cells can be embedded within the cirrus layers. These cells were so active that the rising updraft induced its own pressure perturbations that affected the cloud evolution. Vertical profiles of the total radiative and latent heating rates indicated that for well developed, deep, and active cirrus clouds, radiative cooling and latent heating could be comparable in magnitude in the cloudy layer. This implies that latent heating cannot be neglected in the construction of a cirrus cloud model. The probability density function (PDF) of w was analyzed to assist in the parameterization of cloud-scale velocities in large-scale models. For the more radiatively-driven, thin cirrus case, the PDFs are approximately Gaussian. However, in the interior of the deep, convectively unstable case, the PDFs of w are multi-modal and very broad, indicating that parameterizing cloud-scale motions for such clouds can be very challenging. The results of this research are described in detail in a paper submitted to the Journal of Atmospheric Science (Wu and Cotton, 1999), which is enclosed as Appendix 2. Using soundings extracted from a mesoscale simulation of the November 26, 1991 cirrus event, the radiative effects on vapor deposition/sublimation of ice crystals was studied using a two-dimensional cloud-resolving model (CRM) version of RAMS, coupled to an explicit bin-resolving microphysics. The CRM simulations of the November 26, 1991 cirrus event demonstrate that the radiative impact on the diffusional growth (or sublimation) of ice crystals is significant. In this case, the ice particles experienced radiative warming. Model results show that radiative feedbacks in the diffusional growth of ice particles can be very complex. Radiative warming of an ice particle will restrict the particle's diffusional growth. In the case of radiative warming, ice particles larger than a certain size will experience so much radiative warming that surface ice saturation vapor pressures become large enough to cause sublimation of the larger crystals, while smaller crystals are growing by vapor deposition. However, ice mass production can be enhanced in the case of radiative cooling of an ice particle. For the November 26, 1991 cirrus event, radiative feedback results in significant reduction in the total ice mass, especially in the production of large ice crystals, and consequently, both radiative and dynamic properties of the cirrus cloud are significantly affected. A complete description of this research has been submitted as a paper to the Journal of Atmospheric Science (Wu et al., 1999), and included as Appendix 3.

Wu, Ting↗
NASA NTRS2004

Perceptual learning through optimization of attentional weighting: human versus optimal Bayesian learner

Human performance in visual detection, discrimination, identification, and search tasks typically improves with practice. Psychophysical studies suggest that perceptual learning is mediated by an enhancement in the coding of the signal, and physiological studies suggest that it might be related to the plasticity in the weighting or selection of sensory units coding task relevant information (learning through attention optimization). We propose an experimental paradigm (optimal perceptual learning paradigm) to systematically study the dynamics of perceptual learning in humans by allowing comparisons to that of an optimal Bayesian algorithm and a number of suboptimal learning models. We measured improvement in human localization (eight-alternative forced-choice with feedback) performance of a target randomly sampled from four elongated Gaussian targets with different orientations and polarities and kept as a target for a block of four trials. The results suggest that the human perceptual learning can occur within a lapse of four trials (<1 min) but that human learning is slower and incomplete with respect to the optimal algorithm (23.3% reduction in human efficiency from the 1st-to-4th learning trials). The greatest improvement in human performance, occurring from the 1st-to-2nd learning trial, was also present in the optimal observer, and, thus reflects a property inherent to the visual task and not a property particular to the human perceptual learning mechanism. One notable source of human inefficiency is that, unlike the ideal observer, human learning relies more heavily on previous decisions than on the provided feedback, resulting in no human learning on trials following a previous incorrect localization decision. Finally, the proposed theory and paradigm provide a flexible framework for future studies to evaluate the optimality of human learning of other visual cues and/or sensory modalities.

Non-NASA Center↗
NASA NTRS2011

Influence of an Internally-Generated QBO on Modeled Stratospheric Dynamics and Ozone

A GEOS V2 CCM simulation with an internally generated quasi-biennial oscillation (QBO) signal is compared to an otherwise identical simulation without a QBO. In a present-day climate, inclusion of the modeled QBO makes a significant difference to stratospheric dynamics and ozone throughout the year. The QBO enhances variability in the tropics, as expected, but also in the polar stratosphere in some seasons. The modeled QBO also affects the mean stratospheric climate. Because tropical zonal winds in the baseline simulation are generally easterly, there is a relative increase in zonal wind magnitudes in tropical lower and middle stratosphere in the QBO simulation. Extra-tropical differences between the QBO and 'no QBO' simulations thus reflect a bias toward the westerly phase of the QBO: a relative strengthening and poleward shifting the polar stratospheric jets, and a reduction in Arctic lower stratospheric ozone.

Hurwitz, M. M.↗
NASA NTRS2017

Computational Assessment of a 3-Stage Axial Compressor Which Provides Airflow to the NASA 11- by 11-Foot Transonic Wind Tunnel, Including Design Changes for Increased Performance

A 24 foot diameter 3-stage axial compressor powered by variable-speed induction motors provides the airflow in the closed-return 11- by 11-Foot Transonic Wind Tunnel (11-Foot TWT) Facility at NASA Ames Research Center at Moffett Field, California. The facility is part of the Unitary Plan Wind Tunnel, which was completed in 1955. Since then, upgrades made to the 11-Foot TWT such as flow conditioning devices and instrumentation have increased blockage and pressure loss in the tunnel, somewhat reducing the peak Mach number capability of the test section. Due to erosion effects on the existing aluminum alloy rotor blades, fabrication of new steel rotor blades is planned. This presents an opportunity to increase the Mach number capability of the tunnel by redesigning the compressor for increased pressure ratio. Challenging design constraints exist for any proposed design, demanding the use of the existing driveline, rotor disks, stator vanes, and hub and casing flow paths, so as to minimize cost and installation time. The current effort was undertaken to characterize the performance of the existing compressor design using available design tools and computational fluid dynamics (CFD) codes and subsequently recommend a new compressor design to achieve higher pressure ratio, which directly correlates with increased test section Mach number. The constant cross-sectional area of the compressor leads to highly diffusion factors, which presents a challenge in simulating the existing design. The CFD code APNASA was used to simulate the aerodynamic performance of the existing compressor. The simulations were compared to performance predictions from the HT0300 turbomachinery design and analysis code, and to compressor performance data taken during a 1997 facility test. It was found that the CFD simulations were sensitive to endwall leakages associated with stator buttons, and to a lesser degree, under-stator-platform flow recirculation at the hub. When stator button leakages were modeled, pumping capability increased by over 20 of pressure rise at design point due to a large reduction in aerodynamic blockage at the hub. Incorporating the stator button leakages was crucial to matching test data. Under-stator-platform flow recirculation was thought to be large due to a lack of seals. The effect of this recirculation was assessed with APNASA simulations recirculating 0.5, 1, and 2 of inlet flow about stators 1 and 2, modeled as axisymmetric mass flux boundary conditions on the hub before and after the vanes. The injection of flow ahead of the stators tended to re-energize the boundary layer and reduce hub separations, resulting in about 3 increased stall margin per 1 of inlet flow recirculated. In order to assess the value of the flow recirculation, a mixing plane simulation of the compressor which gridded the under-stator cavities was generated using the ADPAC CFD code. This simulation indicated that about 0.65 of the inlet flow is recirculated around each shrouded stator. This collective information was applied during the redesign of the compressor. A potential design was identified using HT0300 which improved overall pressure ratio by removing pre-swirl into rotor 1, replacing existing NASA 65 series rotors with double circular arc sections, and re-staggering rotors and the existing stators. The performance of the new design predicted by APNASA and HT0300 is compared to the existing design.

Turbomachinery↗
NASA NTRS2013

A Computational Fluid Dynamics Study of Swirling Flow Reduction by using Anti-vortex Baffle

An anti-vortex baffle is a liquid propellant management device placed adjacent to an outlet of the propellant tank. Its purpose is to substantially reduce or eliminate the formation of free surface dip and vortex, as well as prevent vapor ingestion into the outlet, as the liquid drains out through the flight. To design an effective anti-vortex baffle, Computational Fluid Dynamic (CFD) simulations were undertaken for the NASA Ares I vehicle LOX tank subjected to the simulated flight loads with and without the anti-vortex baffle. The Six Degree-Of-Freedom (6- DOF) dynamics experienced by the Crew Launch Vehicle (CLV) during ascent were modeled by modifying the momentum equations in a CFD code to accommodate the extra body forces from the maneuvering in a non-inertial frame. The present analysis found that due to large moments, the CLV maneuvering has significant impact on the vortical flow generation inside the tank. Roll maneuvering and side loading due to pitch and yaw are shown to induce swirling flow. The vortical flow due to roll is symmetrical with respect to the tank centerline, while those induced by pitch and yaw maneuverings showed two vortices side by side. The study found that without the anti-vortex baffle, the swirling flow caused surface dip during the late stage of drainage and hence early vapor ingestion. The flow can also be non-uniform in the drainage pipe as the secondary swirling flow velocity component can be as high as 10% of the draining velocity. An analysis of the vortex dynamics shows that the swirling flow in the drainage pipe during the Upper Stage burn is mainly the result of residual vortices inside the tank due to conservation of angular momentum. The study demonstrated that the swirling flow in the drainage pipe can be effectively suppressed by employing the anti-vortex baffle.

Yang, H. Q.↗
NASA NTRS2017

A Computational Fluid Dynamics Study of Swirling Flow Reduction by Using Anti-Vortex Baffle

An anti-vortex baffle is a liquid propellant management device placed adjacent to an outlet of the propellant tank. Its purpose is to substantially reduce or eliminate the formation of free surface dip and vortex, as well as prevent vapor ingestion into the outlet, as the liquid drains out through the flight. To design an effective anti-vortex baffle, Computational Fluid Dynamic (CFD) simulations were undertaken for the NASA Ares I vehicle LOX tank subjected to the simulated flight loads with and without the anti-vortex baffle. The Six Degree-Of-Freedom (6-DOF) dynamics experienced by the Crew Launch Vehicle (CLV) during ascent were modeled by modifying the momentum equations in a CFD code to accommodate the extra body forces from the maneuvering in a non-inertial frame. The present analysis found that due to large moments, the CLV maneuvering has a significant impact on the vortical flow generation inside the tank. Roll maneuvering and side loading due to pitch and yaw are shown to induce swirling flow. The vortical flow due to roll is symmetrical with respect to the tank centerline, while those induced by pitch and yaw maneuverings showed two vortices side by side. The study found that without the anti-vortex baffle, the swirling flow caused surface dip during the late stage of drainage and hence early vapor ingestion. The flow can also be non-uniform in the drainage pipe as the secondary swirling flow velocity component can be as high as 10% of the draining velocity. An analysis of the vortex dynamics shows that the swirling flow in the drainage pipe during the Upper Stage burn is mainly the result of residual vortices inside the tank due to the conservation of angular momentum. The study demonstrated that the swirling flow in the drainage pipe can be effectively suppressed by employing the anti-vortex baffle.

Yang, H. Q.↗
NASA NTRS2017

A Computational Fluid Dynamics Study of Swirling Flow Reduction by Using Anti-Vortex Baffle

An anti-vortex baffle is a liquid propellant management device placed adjacent to an outlet of the propellant tank. Its purpose is to substantially reduce or eliminate the formation of free surface dip and vortex, as well as prevent vapor ingestion into the outlet, as the liquid drains out through the flight. To design an effective anti-vortex baffle, Computational Fluid Dynamic (CFD) simulations were undertaken for the NASA Ares I vehicle LOX tank subjected to the simulated flight loads with and without the anti-vortex baffle. The Six Degree-Of-Freedom (6-DOF) dynamics experienced by the Crew Launch Vehicle (CLV) during ascent were modeled by modifying the momentum equations in a CFD code to accommodate the extra body forces from the maneuvering in a non-inertial frame. The present analysis found that due to large moments, the CLV maneuvering has a significant impact on the vortical flow generation inside the tank. Roll maneuvering and side loading due to pitch and yaw are shown to induce swirling flow. The vortical flow due to roll is symmetrical with respect to the tank centerline, while those induced by pitch and yaw maneuverings showed two vortices side by side. The study found that without the anti-vortex baffle, the swirling flow caused surface dip during the late stage of drainage and hence early vapor ingestion. The flow can also be non-uniform in the drainage pipe as the secondary swirling flow velocity component can be as high as 10% of the draining velocity. An analysis of the vortex dynamics shows that the swirling flow in the drainage pipe during the Upper Stage burn is mainly the result of residual vortices inside the tank due to the conservation of angular momentum. The study demonstrated that the swirling flow in the drainage pipe can be effectively suppressed by employing the anti-vortex baffle.

Yang, H. Q.↗
DOE OSTI2022

Vehicle-to-manufacturing (V2M) system: A novel approach to improve energy demand flexibility for demand response towards sustainable manufacturing

The U.S. manufacturing sector accounts for 77% of the industrial energy consumption, but its participation in demand response (DR) programs is largely lagged behind. The limited flexibility in production scheduling under high capacity utilization and the lack of DR schemes that incorporate energy demand flexibility measures are deemed as major barriers. In this study, a framework of the interactive vehicles-to-manufacturing (V2M) energy sharing system is proposed to improve the energy demand flexibility of the aggregated system and enhance the DR effectiveness for manufacturers. The V2M-based DR scheme aims to reduce the energy cost by load shifting through joint production and energy sharing control, which can eventually promote manufacturing DR implementation even under high capacity utilization requirements and dynamic real-time electricity prices. The V2M system is modeled based on a discrete-Markov chain considering the complex interconnections among various manufacturing resources and multi-directional energy flows among manufacturing facilities, electric vehicles, and the power grid. Based on the system model, a mixed-integer nonlinear programming (MINLP) problem is formulated to identify the optimal DR scheme. The effectiveness of the proposed approach is validated through comparisons with traditional manufacturing DR schemes. Finally, the results show that a 2.1 to 6.5 times energy demand flexibility improvement and an additional 4.7% to 6.9% energy cost reduction can be achieved by the proposed approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

A deep learning-based Bayesian framework for high-resolution calibration of building energy models

Calibrating building energy models (BEMs), i.e., closing discrepancy between modeling and field measurements, is of significance to support its applications in building sustainability and resilience analysis. However, as being widely used in practice, current Bayesian calibration is mostly performed in low-resolution (annual or monthly), instead of high-resolution (hourly or sub-hourly), which is crucial to support emerging BEM applications, such as building-renewable energy integration (demand response) and smart control. This is attributable to the gaps in current Bayesian calibration process, including (1) difficulty in supporting reliable high-resolution calibration with over-parameterization and multi-solution issues, (2) inadequacy of meta-model to capture temporal building dynamics in high-resolution, and (3) excessive computational burdens of covariance matrix calculation in Bayesian inference. Therefore, to close these gaps, this research proposes a novel deep learning-based Bayesian calibration framework, involving pre-calibration mechanism, Long Short-Term Memory as surrogate models, and simplified covariance matrix calculation, to calibrate BEMs in high temporal resolution (i.e., hourly) with enhanced accuracy and computational efficiency. Finally, the case study demonstrates its effectiveness to match modeling outcomes with measurements and realize CV-RMSE of < 30 % and NMBE of < 6 % in hourly resolution, as well as a significant reduction of calibration time (by > 99 %, from > 600 h to ~ 1.5 h).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗