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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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At least 919 records · Page 51

Differing Air Traffic Controller Responses to Similar Trajectory Prediction Errors: An Interrupted Time-Series Analysis of Controller Behavior

A Human-In-The-Loop simulation was conducted in January of 2013 in the Airspace Operations Laboratory at NASAs Ames Research Center. The simulation airspace included two en route sectors feeding the northwest corner of Atlantas Terminal Radar Approach Control. The focus of this paper is on how uncertainties in the studys trajectory predictions impacted the controllers ability to perform their duties. Of particular interest is how the controllers interacted with the delay information displayed in the meter list and data block while managing the arrival flows. Due to wind forecasts with 20-knot over-predictions and 20-knot under-predictions, delay value computations included errors of similar magnitude, albeit in opposite directions. However, when performing their duties in the presence of these errors, did the controllers issue clearances of similar magnitude, albeit in opposite directions?

human-automation interaction↗

In Vitro Evolution and Computational Approaches to Predict, Prevent and Control Future Pandemics

The natural tendency of virus to mutate and the under-sampling of the environment makes it difficult to become aware of the emergence of new viral strains with pandemic potential. Being able to predict what mutations make a virus more infective might allow to spot such strains with minimal sampling and potentially allow to predict/prevent the next pandemic. The team attempted to mimic natural viral mutations and recombination through computational and experimental methods producing a variety of mutants of a SARS-COV-2 protein (receptor binding domain, RBD, of spike protein) responsible for viral entry in mammalian cells. The library of mutants was then interrogated for ability and lack-there-of to interact with the host cell receptor ushering viral entry, Angiotensin-converting enzyme 2 (ACE2). The negative and positive data set is intended to “teach the rules” of virus-host receptor interaction. Additionally, the positive clones were used to screen a set of antibody mutants designed to widen the breadth of viral mutants recognition, to demonstrate that this kind of libraries could also be a tool to produce antibody therapeutics impervious to viral mutation, even before a pandemic strain is discovered.

59 BASIC BIOLOGICAL SCIENCES↗

Stacked Low-Inertia Converter or Solid-State Transformer: Modeling and Model Predictive Priority-Shifting Control for Voltage Balance

This paper presents control challenges of stacked low-inertia converter (SLIC) or cascaded reduced dc-link solid-state transformer (SST) and proposes a novel model predictive priority-shifting (MPPS) control with implicit modulator and a discrete-time large-signal model for voltage balancing and dc-link regulation. Low-inertia converters, featuring small electrolytic capacitor-less dc links, dramatically reduce cost, size, and weight compared to conventional solutions. However, without a large dc-link buffer, the input and output are tightly coupled, leading to significant control challenges. The control becomes even more challenging with these converters stacked input-series output-parallel (ISOP) for medium-voltage (MV) grid, which causes coupling between the modules besides the coupling within each module. This paper analyzes the multi-objective, multi-degree of freedom control problem, using the modular soft-switching solid-state transformer (M-S4T) as an example of the SLIC. First, distribution of control efforts under controller saturation is critical because multiple control objectives can be conflicting, especially when the module voltages are unbalanced and are being restored. The MPPS can shift the priorities to address this issue. Second, due to the low inertia and high dc-link ripple, classic space vector pulse-width modulation (SVPWM), average model with small-ripple assumption, and control design based on small-signal model cannot accurately modulate, model, and control the nonlinear reduced dc link. Therefore, a discrete-time large-signal model of the M-S4T is established to derive the predictive control in the MPPS. The MPPS and the PI control are compared in MV simulations to show the issue of applying the PI to the SLIC and the effectiveness of the MPPS for voltage balancing and dc-link regulation in a deadbeat manner. Finally, the proposed control is tested on a 5 kV ISOP SiC SST prototype to verify priority shifting to address controller saturation issue and fast and robust voltage balancing.

14 SOLAR ENERGY↗

Evaluation of CFD Predictions of CobraMRV Control Surface Effectiveness at the NASA Langley Unitary Plan Wind Tunnel

The ability of CFD simulations to serve as a surrogate for wind tunnel testing at high supersonic speeds has been evaluated for a sub-scale model of the Co-Optimization Blunt-body Re-entry Analysis-Mid-lift-to-drag Rigid Vehicle (CobraMRV) human Mars entry vehicle concept. The vehicle was tested at the Unitary Plan Wind Tunnel (UPWT) at the NASA Langley Research Center under flow conditions and surface control configurations relevant to the entry stage of a flight mission. The CFD simulations were performed prior to gaining access to test results in order to assess how blind predictions obtained using best practices compare to experiments. Solutions of empty tunnel simulations were used as inflow boundary condition for the CobraMRV simulations in a truncated portion of the test section. Different solvers and turbulence models were used by separate teams to assess sensitivity to numerical methods, physics, and users. After release of the test results, the pre-test computations were compared to the experimental results, and additional analyses have been conducted to explain observed discrepancies. The amount of time and resources dedicated to each phase of the computational work was logged for comparison to that required for wind tunnel tests, and to inform planning of future CFD data base development projects.

ARMD↗

Computational Investigation and Validation of Twin-Tail Buffet Response Including Dynamics and Control

Multidisciplinary tools for prediction of single rectangular-tail buffet are extended to single swept-back-tail buffet in transonic-speed flow, and multidisciplinary tools for prediction and control of twin-tail buffet are developed and presented. The configuration model consists of a sharp-edged delta wing with single or twin tails that are oriented normal to the wing surface. The tails are treated as cantilevered beams fixed at the root and allowed to oscillate in both bending and torsion. This complex multidisciplinary problem is solved sequentially using three sets of equations on a dynamic single or multi-block grid structure. The first set is the unsteady, compressible, Reynolds-averaged Navier-Stokes equations which are used for obtaining the flow field vector and the aerodynamic loads on the tails. The Navier-Stokes equations are solved accurately in time using the implicit, upwind, flux-difference splitting, finite volume scheme. The second set is the coupled bending and torsion aeroelastic equations of cantilevered beams which are used for obtaining the bending and torsion deflections of the tails. The aeroelastic equations'are solved accurately in time using, a fifth-order-accurate Runge-Kutta scheme. The third set is the grid-displacement equations and the rigid-body dynamics equations, which are used for updating the grid coordinates due to the tail deflections and rigid-body motions. The tail-buffet phenomenon is predicted for highly-swept, single vertical tail placed at the plane of geometric symmetry, and for highly-swept, vertical twin tails placed at three different spanwise separation distances. The investigation demonstrates the effects of structural inertial coupling and uncoupling of the bending and torsion modes of vibration, spanwise positions of the twin-tail, angle of attack, and pitching and rolling dynamic motions of the configuration model on the tail buffet loading and response. The fundamental issue of twin-tail buffet alleviation is addressed using two active flow-control methods. These methods are the tangential leading-edge blowing and the flow suction from the leading-edge vortex cores along their paths. Qualitative and quantitative comparisons with the available experimental data are presented. The comparisons indicate that the present multidisciplinary aeroelastic analysis tools are robust, accurate and efficient.

Kandil, Osama A.↗

Integrated Predictive Demand Response Controller for Commercial Buildings (Final Scientific Technical Report)

This project provides algorithms to perform demand response using the thermal mass of a building. Using the thermal mass of the building is an attractive method for performing demand response because there is no need for capital expenditure. The algorithms rely on the thermal capacitance inherent in the building’s construction materials. A near-optimal “day ahead” predictive approach is developed that is meant to keep the building’s electrical demand constant during the high cost periods. This type of approach is appropriate for both time-of-use and critical peak pricing utility rate structures. The approach uses the past days data in order to determine the best temperature setpoints for the building during the high price periods on the next day. A second “model predictive approach” (MPC) uses a thermal model of the building to determine the best temperature for the next sample period. The approach uses constant feedback from the building and is capable of appropriately handling real time pricing. Both approaches are capable of using weather forecasts to improve performance. Algorithm performance was tested on a municipal library in Sacramento, CA and a large office building in Milwaukee, WI. In both cases the algorithms were capable of storing thermal energy in the building mass in such a way that the electrical demand was reduced during periods of high cost.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Design predictions for noise control in the cryogenic National Transonic Facility

Noise control in the National Transonic Facility - a cryogenic wind tunnel - has been examined in terms of acoustical design criteria, drive-fan noise and exhaust system noise. A duct lining with two layers of perforated sheeting and a gas-filled honeycomb core was selected for attenuating drive-fan noise. With the exception of attenuation peaks, attenuation of the lining was found to experimentally agree with predicted values at 20 C air temperatures. Exhaust system noise will be attenuated with a large muffler used in conjunction with a 6.1-m high acoustical enclosure. Fan noise from the fan-ejector system will be attenuated by fan silencers and the acoustic enclosure.

Lassiter, W. S.↗

WE-AB-207B-02: A Bayesian Network Approach for Joint Prediction of Tumor Control and Radiation Pneumonitis (RP) in Non-Small-Cell Lung Cancer (NSCLC)

Purpose: NSCLC radiotherapy treatment is a trade-off between controlling the tumor while limiting radiation-induced toxicities. Here we identify hierarchical biophysical relationships that could simultaneously influence both local control (LC) and RP by using an integrated Bayesian Networks (BN) approach. Methods: We studied 79 NSCLC patients treated on prospective protocol with 56 cases of LC and 21 events of RP. Beyond dosimetric information, each patient had 193 features including 12 clinical factors, 60 circulating blood cytokines before and during radiotherapy, 62 microRNAs, and 59 single-nucleotide polymorphisms (SNPs). The most relevant biophysical predictors for both LC and RP were identified using a Markov blanket local discovery algorithm and the corresponding BN was constructed using a score-learning algorithm. The area under the free-response receiver operating characteristics (AU-FROC) was used for performance evaluation. Cross-validation was employed to guard against overfitting pitfalls. Results: A BN revealing the biophysical interrelationships jointly in terms of LC and RP was developed and evaluated. The integrated BN included two SNPs, one microRNA, one clinical factor, three pre-treatment cytokines, relative changes of two cytokines between pre and during-treatment, and gEUDs of the GTV (a=-20) and lung (a=1). On cross-validation, the AUC prediction of independent LC was 0.85 (95% CI: 0.75–0.95) and RP was 0.83 (0.73–0.92). The AU-FROC of the integrated BN to predict both LC/RP was 0.81 (0.71–0.90) based on 2000 stratified bootstrap, indicating minimal loss in joint prediction power. Conclusions: We developed a new approach for multiple outcome utility application in radiotherapy based on integrated BN techniques. The BN developed from large-scale retrospective data is able to simultaneously predict LC and RP in NSCLC treatments based on individual patient characteristics. The joint prediction is only slightly compromised compared to independent predictions. Our approach shows promise for use in clinical decision support system for personalized radiotherapy subject to multiple endpoints. These studies were supported by a grant from the NCI/NIH P01-CA59827.

60 APPLIED LIFE SCIENCES↗

Controlling accesses to a branch prediction unit for sequences of fetch groups

An electronic device handles accesses of a branch prediction functional block when executing instructions in program code. The electronic device includes a processor having the branch prediction functional block that provides branch prediction information for control transfer instructions (CTIs) in the program code and a minimum predictor use (MPU) functional block. The MPU functional block determines, based on a record associated with a given fetch group of instructions, that a specified number of subsequent fetch groups of instructions that were previously determined to include no CTIs or conditional CTIs that were not taken are to be fetched for execution in sequence following the given fetch group. The MPU functional block then, when each of the specified number of the subsequent fetch groups is fetched and prepared for execution, prevents corresponding accesses of the branch prediction functional block for acquiring branch prediction information for instructions in that subsequent fetch group.

Agrawal, Varun↗

Autonomous monitoring of control hardware to predict off-normal conditions using NIF automatic Alignment Systems

The National Ignition Facility (NIF) is a high power laser system capable of supporting high-energy-density experimentation as a user facility for the next 30 years. In order to maximize the facility availability, preventive maintenance enhancements are being introduced into the system. An example of such an enhancement is a camera-based health monitoring system, integrated into the automated alignment system, which provides an opportunity to monitor trends in measurements such as average beam intensity, size of the beam, and pixel saturation. The monitoring system will generate alerts based on observed trends in measurements to allow scheduled pro-active maintenance before routine off-normal detection stops system operations requiring unscheduled intervention.

42 ENGINEERING↗

Synthetic control and empirical prediction of redox potentials for Co 4 O 4 cubanes over a 1.4 V range: implications for catalyst design and evaluation of high-valent intermediates in water oxidation

The oxo-cobalt cubane unit [Co 4 O 4 ] is of interest as a homogeneous oxygen-evolution reaction (OER) catalyst, and as a functional mimic of heterogeneous cobalt oxide OER catalysts. The synthesis of several new cubanes allows evaluation of redox potentials for the [Co 4 O 4 ] cluster, which are highly sensitive to the ligand environment and span a remarkable range of 1.42 V. The [Co III 4 O 4 ] 4+ /[Co III 3 Co IV O 4 ]5+ and [Co III 3 Co IV O 4 ] 5+ /[Co III 2 Co IV 2 O 4 ] 6+ redox potentials are reliably predicted by the pKas of the ligands. Hydrogen bonding is also shown to significantly raise the redox potentials, by ~500 mV. The potential-p K a correlation is used to evaluate the feasibility of various proposed OER catalytic intermediates, including high-valent Co-oxo species. The synthetic methods and structure–reactivity relationships developed by these studies should better guide the design of new cubane-based OER catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Improving Trustworthiness of Data-Driven Power Grid Contingency Analysis With Bayesian Residual Graph Neural Networks

The evolving energy landscape requires novel tools to efficiently perform contingency analysis and reliability assessment of power grids, potentially in real-time. The high computational cost of traditional power flow solvers limits their applicability in practice. Machine learning (ML) surrogates such as deep neural networks (NNs) accelerate power flow solvers computations, enabling high-order contingency analysis and real-time decision-making by learning highly nonlinear functions and integrating grid topology via graph architectures. However, (graph) NNs lack predictive power away from training data and do not provide predictive confidence estimates. Here, we present a Bayesian residual graph NN that integrates knowledge from low-fidelity data via residual training and embeds granular quantification of uncertainties, improving trustworthiness critical for high-consequence decision-making. Applying Bayesian concepts to NNs is challenging due to the high-dimensionality of both the parameter space, complicating derivation of a meaningful prior, and the output space in large grid systems, requiring enhanced techniques to assess the predicted high-dimensional uncertainties. Our contributions include: (1) Deriving a prior for fully connected and graph NNs that leverages low-fidelity data to guide mean predictions and appropriately control prior predictive uncertainty. (2) Integrating this prior within an ensembling with anchoring scheme for efficient approximate posterior inference. (3) Deriving enhanced metrics to assess accuracy of both the mean and uncertainty predictions in high dimensions, appropriately accounting for correlations propagated through graph layers. The resulting Bayesian residual graph NN is tested on a contingency analysis task for 14-bus and 118-bus grids.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Adaptive RAS/SPS System Settings for Improving Grid Reliability and Asset Utilization through Predictive Simulation and Controls

Remedial Action Schemes (RAS) or Special Protection Schemes (SPS) are used throughout the bulk transmission system as a non-wires method of increasing transmission transfer capability. However, as the population grows within the Western Interconnection, more power needs to be transferred with less ability to build lines. This leads to a greater number of RAS, and the subsequent interaction between these disparate schemes can have unintended consequences. While the large number of RAS within the Western Electricity Coordinating Council (WECC) protect for different things, which can range from the violation of thermal limitations to transient stability issues, they can be described by common methods of operation. In order to understand these methods, a survey was sent out to members of the WECC Modeling & Validation Working Group (MVWG). The response received provides a necessary base in which to understand and build models that can be used within WECC. This report provides information on the survey results regarding RAS/SPS modeling practices for planning and operational studies within the WECC footprint, which is foundational for on-going and future work on RAS. Pacific Northwest National Laboratory (PNNL) and its industry partners are developing innovative methods for adaptively setting RAS parameters based on realistic and near real-time operational conditions to improve power grid reliability and grid asset utilization.

24 POWER TRANSMISSION AND DISTRIBUTION↗