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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Challenges and opportunities of machine learning control in building operations

Machine learning control (MLC) is a highly flexible and adaptable method that enables the design, modeling, tuning, and maintenance of building controllers to be more accurate, automated, flexible, and adaptable. The research topic of MLC in building energy systems is developing rapidly, but to our knowledge, no review has been published that specifically and systematically focuses on MLC for building energy systems. Here this paper provides a systematic review of MLC in building energy systems. We review technical papers in two major categories of applications of machine learning in building control: (1) building system and component modeling for control, and (2) control process learning. We identify MLC topics that have been well-studied and those that need further research in the field of building operation control. We also identify the gaps between the present and future application of MLC and predict future trends and opportunities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1960

Investigation at Mach Numbers of 0.20 to 3.50 of Blended Wing-Body Combinations of Sonic Design with Diamond, Delta, and Arrow Plan Forms

The models had aspect-ratio-2 diamond, delta, and arrow wings with the leading edges swept 45.00 deg, 59.04 deg, and 70.82 deg, respectively. The wing sections were computed by varying the section shape along with the body radii (blending process) to match the prescribed area distribution and wing plan form. The wing sections had an average value of maximum thickness ratio of about 4 percent of the local chords in a streamwise direction. The models were tested with transition fixed at Reynolds numbers of about 4,000,000 to 9,000,0000, based on the mean aerodynamic chord of the wings. The effect of varying Reynolds number was checked at both subsonic and supersonic speeds. The diamond model was superior to the other plan forms at transonic speeds ((L/D)max = 11.00 to 9.52) because of its higher lift-curve slope and near optimum wave drag due to the blending process. For the wing thickness tested with the diamond model, the marked body and wing contouring required for transonic conditions resulted in a large wave-drag penalty at the higher supersonic Mach numbers where the leading and trailing edges of the wing were supersonic. Because of the low sweep of the trailing edge of the delta model, this configuration was less adaptable to the blending process. Removing a body bump prescribed by the Mach number 1.00 design resulted in a good supersonic design. This delta model with 10 percent less volume was superior to the other plan forms at Mach numbers of 1.55 to 2.35 ((L/D)max = 8.65 to 7.24), but it and the arrow model were equally good at Mach numbers of 2.50 to 3.50 ((L/D)max - 6.85 to O.39). At transonic speeds the arrow model was inferior because of the reduced lift-curve slope associated with its increased sweep and also because of the wing base drag. The wing base-drag coefficients of the arrow model based on the wing planform area decreased from a peak value of 0.0029 at Mach number 1.55 to 0.0003 at Mach number 3.50. Linear supersonic theory was satisfactory for predicting the aerodynamic trends at Mach numbers from 1.55 to 3.50 of lift-curve slope, wave drag, drag due to lift, aerodynamic-center location, and maximum lift-drag ratios for each of the models.

Holdaway, George H.↗
NASA NTRS2005

Modeling and Development of a Magnetic Bearing Controller for a High Speed Flywheel System

This paper describes a modeling effort used to develop an improved type of magnetic bearing controller, called a modal controller, for use on high speed flywheel systems. The controller design is based on models of the flywheel system, is designed to directly control the natural dynamics of the spinning rotor, and is generic enough to be readily adapted to future flywheel systems. Modeling and development are described for two key controller subsystems: the modal controller subsystem, which allows direct control over the rotor rigid body modes, and the bending mode compensation subsystem, which tracks, and prevents interference from, the rotor bending modes during flywheel operation. Integration of modeling results into the final controller is described and data taken on the NASA Glenn D1 flywheel module during high speed operation are presented and discussed. The improved modal controller described in this paper has been successfully developed and implemented and has been used for regular hands-free operation of the D1 flywheel module up to its maximum operating speed of 60,000 RPM.

Dever, Timothy P.↗
NASA NTRS1988

Globally stable control laws for the attitude maneuver problem - Tracking control and adaptive control

An approach using a globally nonsingular representation is proposed for the attitude control problem of a rigid body. The attitude dynamics are described by the nonlinear Euler equation together with the nonlinear kinematic equations which relate a representation of attitude to the angular velocity of the body. When this approach is combined with an energy-motivated Lyapunov function, a large class of globally stable attitude control laws can be derived. This class includes model-independent tracking control, model-dependent tracking control, and adaptive control, allowing tradeoffs between controller complexity, attainable performance, and available model information.

Wen, John T.↗
NASA NTRS1993

Nutrition and human physiological adaptations to space flight

Space flight provides a model for the study of healthy individuals undergoing unique stresses. This review focuses on how physiological adaptations to weightlessness may affect nutrient and food requirements in space. These adaptations include reductions in body water and plasma volume, which affect the renal and cardiovascular systems and thereby fluid and electrolyte requirements. Changes in muscle mass and function may affect requirements for energy, protein and amino acids. Changes in bone mass lead to increased urinary calcium concentrations, which may increase the risk of forming renal stones. Space motion sickness may influence putative changes in gastro-intestinal-hepatic function; neurosensory alterations may affect smell and taste. Some or all of these effects may be ameliorated through the use of specially designed dietary countermeasures.

Review↗
DOE OSTI2020

Secondary-Source Core Reload Modeling with VERA

The CASL reactor simulation package VERA has been adapted to provide high-fidelity simulation capabilities for modeling source range detector response during subcritical reactor configurations. New features include the activation and shuffling of secondary-source assemblies, use of burned fuel neutron emission data from the ORIGEN depletion solver to the MPACT deterministic neutron transport solver, allowance of user-defined sources in MPACT based on material composition, ability to solve the subcritical source-driven system with neutron multiplication using the MPACT diffusion solver, and transfer of the calculated fission source from MPACT to the continuous-energy Monte Carlo solver Shift for final detector response evaluation using the CADIS methodology for variance reduction. These new capabilities were benchmarked against Watts Bar Unit 1 plant operating data for the first few fuel loading steps and were found to demonstrate excellent agreement with the measured data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2001

Horizontal vestibuloocular reflex evoked by high-acceleration rotations in the squirrel monkey. IV. Responses after spectacle-induced adaptation

The horizontal angular vestibuloocular reflex (VOR) evoked by sinusoidal rotations from 0.5 to 15 Hz and acceleration steps up to 3,000 degrees /s(2) to 150 degrees /s was studied in six squirrel monkeys following adaptation with x2.2 magnifying and x0.45 minimizing spectacles. For sinusoidal rotations with peak velocities of 20 degrees /s, there were significant changes in gain at all frequencies; however, the greatest gain changes occurred at the lower frequencies. The frequency- and velocity-dependent gain enhancement seen in normal monkeys was accentuated following adaptation to magnifying spectacles and diminished with adaptation to minimizing spectacles. A differential increase in gain for the steps of acceleration was noted after adaptation to the magnifying spectacles. The gain during the acceleration portion, G(A), of a step of acceleration (3,000 degrees /s(2) to 150 degrees /s) increased from preadaptation values of 1.05 +/- 0.08 to 1.96 +/- 0.16, while the gain during the velocity plateau, G(V), only increased from 0.93 +/- 0.04 to 1.36 +/- 0.08. Polynomial fits to the trajectory of the response during the acceleration step revealed a greater increase in the cubic than the linear term following adaptation with the magnifying lenses. Following adaptation to the minimizing lenses, the value of G(A) decreased to 0.61 +/- 0.08, and the value of G(V) decreased to 0.59 +/- 0.09 for the 3,000 degrees /s(2) steps of acceleration. Polynomial fits to the trajectory of the response during the acceleration step revealed that there was a significantly greater reduction in the cubic term than in the linear term following adaptation with the minimizing lenses. These findings indicate that there is greater modification of the nonlinear as compared with the linear component of the VOR with spectacle-induced adaptation. In addition, the latency to the onset of the adapted response varied with the dynamics of the stimulus. The findings were modeled with a bilateral model of the VOR containing linear and nonlinear pathways that describe the normal behavior and adaptive processes. Adaptation for the linear pathway is described by a transfer function that shows the dependence of adaptation on the frequency of the head movement. The adaptive process for the nonlinear pathway is a gain enhancement element that provides for the accentuated gain with rising head velocity and the increased cubic component of the responses to steps of acceleration. While this model is substantially different from earlier models of VOR adaptation, it accounts for the data in the present experiments and also predicts the findings observed in the earlier studies.

NASA Discipline Neuroscience↗
DOE OSTI2023

Model Predictive Control-Based Trajectory Shaper for Safe and Efficient Adaptive Cruise Control

Recent studies show that commercially-available adaptive cruise control (ACC) systems are string-unstable, indicating that ACC-driven vehicles amplify speed fluctuations from downstream traffic and induce stop-and-go waves. Moreover, it is challenging to revise the original control algorithm of an ACC system to achieve string stability due to its internal complexity and powertrain uncertainties. To achieve desired control performance given a string-unstable ACC system and circumvent revising the original control algorithm, this study proposes a model predictive control-based trajectory shaper (MPC-TS), which only modifies the sensor-measured trajectory information (i.e., position and speed) of the preceding vehicle. The proposed MPC-TS leverages the input shaping technique to generate reference trajectory to improve string stability, while incorporating tracking errors and vehicle acceleration/deceleration magnitude in the MPC cost function and constraining fluctuations of vehicle speed and spacing to ensure desired car-following performance. Numerical experiments validate the control performance of ACC with the proposed MPC-TS in terms of string stability, safety, traffic efficiency, and comfort.

Zhou, Anye↗
NASA NTRS1984

Automated ultrareliability models - A review

Analytic models are required to assess the reliability of systems designed to ultrareliability requirements. This paper reviews the capabilities and limitations of five currently available automated reliability models which are applicable to fault-tolerant flight control systems. 'System' includes sensors, computers, and actuators. A set of review criteria including validation, configuration adaptability, and resource requirements for model evaluation are described. Five models, ARIES, CARE II, CARE III, CARSRA, and CAST, are assessed against the criteria, thereby characterizing their capabilities and limitations. This review should be helpful to potential users of the models.

Bridgman, M. S.↗
DOE OSTI2023

Emergent symmetries in atomic nuclei: Probing nuclear dynamics and physics beyond the standard model

Dominant shapes naturally emerge in atomic nuclei from first principles, thereby establishing the shape-preserving symplectic Sp(3, \mathbb{R} ℝ ) symmetry as remarkably ubiquitous and almost perfect symmetry in nuclei. We discuss the critical role of this emergent symmetry in enabling machine-learning descriptions of heavy nuclei, ab initio modeling of \alpha α clustering and collectivity, as well as tests of beyond-the-standard-model physics. In addition, the Sp(3, \mathbb{R} ℝ ) and SU(3) symmetries provide relevant degrees of freedom that underpin the ab initio symmetry-adapted no-core shell model with the remarkable capability of reaching nuclei and reaction fragments beyond the lightest and close-to-spherical species.

Launey, Kristina D.↗
DOE OSTI2021

Sodium Fire Collaborative Study Progress -- CNWG Fiscal Year 2020

This report discusses the progress on the collaboration between Sandia National Laboratories (Sandia) and Japan Atomic Energy Agency (JAEA) on the sodium fire research in fiscal year 2020. First, the current sodium pool fire model in MELCOR, which is adapted from CONTAIN-LMR code, is discussed. The associated sodium fire input requirements are also presented. These input requirements are flexible enough to permit further model development via control functions to enhance the current model without modifying the source code. The theoretical pool fire model improvement developed at Sandia is discussed. A control function model has been developed from this improvement. Then, the validation study of the sodium pool fire model in MELCOR carried out by both Sandia and JAEA’s staff is described. To validate this pool fire model with the enhancement, a JAEA sodium pool fire experiment (F7-1 test) is used. The results of the calculation are discussed as well as suggestions for further model improvement. Finally, recommendations are made for new MELCOR simulations for next fiscal year, 2021.

36 MATERIALS SCIENCE↗
NASA NTRS1986

Iterative adaption of the bidimensional wall of the French T2 wind tunnel around a C5 axisymmetrical model: Infinite variation of the Mach number at zero incidence and a test at increased incidence

The top and bottom two-dimensional walls of the T2 wind tunnel are adapted through an iterative process. The adaptation calculation takes into account the flow three-dimensionally. This method makes it possible to start with any shape of walls. The tests were performed with a C5 axisymmetric model at ambient temperature. Comparisons are made with the results of a true three-dimensional adaptation.

Archambaud, J. P.↗
DOE OSTI2023

BMX: Biological modelling and interface exchange

Abstract High performance computing has a great potential to provide a range of significant benefits for investigating biological systems. These systems often present large modelling problems with many coupled subsystems, such as when studying colonies of bacteria cells. The aim to understand cell colonies has generated substantial interest as they can have strong economic and societal impacts through their roles in in industrial bioreactors and complex community structures, called biofilms, found in clinical settings. Investigating these communities through realistic models can rapidly exceed the capabilities of current serial software. Here, we introduce BMX, a software system developed for the high performance modelling of large cell communities by utilising GPU acceleration. BMX builds upon the AMRex adaptive mesh refinement package to efficiently model cell colony formation under realistic laboratory conditions. Using simple test scenarios with varying nutrient availability, we show that BMX is capable of correctly reproducing observed behavior of bacterial colonies on realistic time scales demonstrating a potential application of high performance computing to colony modelling. The open source software is available from the zenodo repository https://doi.org/10.5281/zenodo.8084270 under the BSD-2-Clause licence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Masked Particle Modeling on Sets: Towards Self-Supervised High Energy Physics Foundation Models

Abstract We propose masked particle modeling (MPM) as a self-supervised method for learning generic, transferable, and reusable representations on unordered sets of inputs for use in high energy physics (HEP) scientific data. This work provides a novel scheme to perform masked modeling based pre-training to learn permutation invariant functions on sets. More generally, this work provides a step towards building large foundation models for HEP that can be generically pre-trained with self-supervised learning and later fine-tuned for a variety of down-stream tasks. In MPM, particles in a set are masked and the training objective is to recover their identity, as defined by a discretized token representation of a pre-trained vector quantized variational autoencoder. We study the efficacy of the method in samples of high energy jets at collider physics experiments, including studies on the impact of discretization, permutation invariance, and ordering. We also study the fine-tuning capability of the model, showing that it can be adapted to tasks such as supervised and weakly supervised jet classification, and that the model can transfer efficiently with small fine-tuning data sets to new classes and new data domains.

Heinrich, Lukas (ORCID:0000000240487584)↗
DOE OSTI2025

Multi-Omics Reveals Temporal Scales of Carbon Metabolism in Synechococcus Elongatus PCC 7942 Under Light Disturbance

Central carbon metabolism in model cyanobacteria involves multiple pathways to adapt to energy-light limitations across diel cycles. However, the success in mechanistic modeling for phenotypic prediction of the protein regulators in the metabolic state depends on capturing the vast possibilities emerging from multiple regulatory pathways in complex biological processes. Here, we developed a physics-informed machine learning approach based on energy-landscape concepts to predict regulatory proteins responding to cyclic circadian and unforeseen light perturbations in cyanobacterial metabolic networks. Our approach provides interpretable de novo models for inferring gene expression dynamics from Synechococcus elongatus over diel cycles and using redox proteome analysis to distinguish immediate light-responsive elements from circadian-regulated processes in carbon metabolism pathways. We identified distinct temporal signatures with the analysis of the redox proteome: there was an immediate shift in cysteine redox states accompanied by a limited change in protein abundance under constant illumination and after 2 hours of darkness. This discovery indicates that the generation of reductants coordinates photoinduced electron transport with redox metabolic pathways in two discernable molecular mechanisms: fast redox-based protein modifications occur immediately after the light disturbance, followed by slow transcriptional regulations across networks. This temporal regulation reveals how metabolic networks integrate rapid light responses with programmed circadian rhythms to maintain cellular homeostasis under the light-energy limitations over the diel cycle.

Biomolecular & subcellular processes↗
DOE OSTI2020

Evaluating Energy Efficiency Opportunities from Connected and Automated Vehicle Deployments Coupled with Shared Mobility in California

Connected and Automated Vehicles (CAVs) can be considered to be a disruptive transportation technology, with the potential to significantly improve overall transportation system efficiency; however, CAVs may increase induce vehicle miles traveled (VMT) and bring on greater energy consumption. Further, shared mobility is another disruptive transportation event that is reshaping our travel patterns. The primary goal of this project was to extensively collect data from vehicles and associated infrastructure equipped with CAV technologies from both real-world experiments and simulation studies mainly deployed in California, and develop a comprehensive framework for evaluating energy efficiency opportunities from large-scale (e.g., statewide) introduction of CAVs and a wide deployment of shared mobility systems in a variety of scenarios. To quantify the combined impact of CAV and shared mobility on travel behavior, traffic performance, and energy efficiency, a unique mesoscopic simulation-based model was developed for mobility and energy efficiency evaluation considering these disruptive transportation technologies. As a complement to existing studies on nationwide evaluation of CAVs’ energy impacts, this project was focused on data collection efforts and CAV applications under congested traffic environments that are frequently experienced on a massive scale across the major metropolitan areas in California. Extensive real-world data collection supplemented with simulation studies were conducted to cover a variety of CAV and shared mobility scenarios, particularly on scenarios less-explored in the existing research. Another key component of this project was to consider the interaction between different CAV technologies and shared mobility models, and the compound effect on energy efficiency. A comprehensive modeling suite was developed to quantify the impact of new mobility technologies on travel behavior and traffic performance. The developed modeling framework includes an energy intensity module, mode choice module and activity generation module that are integrated into an agent-based BEAM simulation platform to perform impact analysis based on a variety of scenarios. In addition, the RouteE model has been upgraded to incorporate the impact of CAVs on traffic flow, VMT and energy intensity, using micro-simulation data collected from both freeways and urban arterials. A novel fundamental influencing factor (FIF) mode choice model was developed to link CAV and shared mobility components with travel behaviors, and adapted into the BEAM-centered model framework. A statewide energy inventory was constructed under various CAV technology deployment scenarios by incorporating datasets and models for predicting vehicle market share and vehicle usage, which are tightly associated with the penetration of shared mobility systems. Based applying this modeling suite to a calibrated network in Riverside California, it was found that cooperative automated driving in general will improve mobility, but automated vehicles, even when deployed in a shared autonomous fleet, will likely bring an increase of VMT (up to 36%) due to mode shifts and deadheading. Ride-hailing vehicles typically have better energy efficiency and a higher share of electric vehicles, which helps offset the negative impact from VMT increases when estimating the system-level energy consumption. In general, simulation results show a 6% increase in energy consumption for the scenarios with an increasing shift to ride-hailing modes. The statewide analysis based on the National Household Travel Survey (NHTS) sample data is consistent with the findings from the Riverside network and validate the developed clustering-prediction modeling methodology. The outcomes from this project will help close the knowledge gap on recognizing the potential performance and energy impacts of a broad deployment of CAV and shared mobility technologies across a wide range of roadway infrastructure with varying levels of congestion. Results from this project: 1) will support policymakers in steering CAV development and deployment towards an energy favorable direction; 2) reduce uncertainties in estimating energy saving opportunities from new mobility technologies and services; 3) increase the confidence of CAV technology investors both on the infrastructure side (i.e., transportation agencies) and on the vehicle side (i.e., OEMs); and 4) expedite the deployment of energy-efficient CAV and shared mobility applications.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1987

Wall interference tests of a CAST 10-2/DOA 2 airfoil in an adaptive-wall test section

A wind-tunnel investigation of a CAST 10-2/DOA 2 airfoil model has been conducted in the adaptive-wall test section of the Langley 0.3-Meter Transonic Cryogenic Tunnel (TCT) and in the National Aeronautical Establishment High Reynolds Number Two-Dimensional Test Facility. The primary goal of the tests was to assess two different wall-interference correction techniques: adaptive test-section walls and classical analytical corrections. Tests were conducted over a Mach number range from 0.3 to 0.8 and over a chord Reynolds number range from 6 million to 70 million. The airfoil aerodynamic characteristics from the tests in the 0.3-m TCT have been corrected for wall interference by the movement of the adaptive walls. No additional corrections for any residual interference have been applied to the data, to allow comparison with the classically corrected data from the same model in the conventional National Aeronautical Establishment facility. The data are presented graphically in this report as integrated force-and-moment coefficients and chordwise pressure distributions.

Mineck, Raymond E.↗