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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Deep Reinforcement Learning Based HVAC Control for Reducing Carbon Footprint of Buildings

In this paper, we present our work on deep reinforcement learning (DRL) based intelligent control of Heating, Ventilation, and Air Conditioning (HVAC) with the goal of reducing carbon emission. We performed this task using 1) Marginal Operating Emission Rates (MOER), where the objective was to shift the demand to the low emission period of the day and 2) Time-Of-Use (TOU) demand-response price where the objective was to shift the demand to low price period of the day. This was achieved by learning an optimal pre-cooing strategy. We found the carbon emission reduction in the range of 6%-16% depending on the opportunity presented by the MOER signal. Similarly, we observed the carbon emission reduction in the range of 23%-29% during the peak price period when TOU price was used. The results clearly demonstrated the applicability of our approach in reducing the carbon footprint of the building.

carbon emission↗
DOE OSTI2016

Image segmentation for uranium isotopic analysis by SIMS: Combined adaptive thresholding and marker controlled watershed approach

A novel approach to particle identification and particle isotope ratio determination has been developed for nuclear safeguard applications. This particle search approach combines an adaptive thresholding algorithm and marker-controlled watershed segmentation (MCWS) transform, which improves the secondary ion mass spectrometry (SIMS) isotopic analysis of uranium containing particle populations for nuclear safeguards applications. The Niblack assisted MCWS approach (a.k.a. SEEKER) developed for this work has improved the identification of isotopically unique uranium particles under conditions that have historically presented significant challenges for SIMS image data processing techniques. Particles obtained from five NIST uranium certified reference materials (CRM U129A, U015, U150, U500 and U850) were successfully identified in regions of SIMS image data 1) where a high variability in image intensity existed, 2) where particles were touching or were in close proximity to one another and/or 3) where the magnitude of ion signal for a given region was count limited. Analysis of the isotopic distributions of uranium containing particles identified by SEEKER showed four distinct, accurately identified 235U enrichment distributions, corresponding to the NIST certified 235U/238U isotope ratios for CRM U129A/U015 (not statistically differentiated), U150, U500 and U850. Additionally, comparison of the minor uranium isotope (234U, 235U and 236U) atom percent values verified that, even in the absence of high precision isotope ratio measurements, SEEKER could be used to segment isotopically unique uranium particles from SIMS image data. Although demonstrated specifically for SIMS analysis of uranium containing particles for nuclear safeguards, SEEKER has application in addressing a broad set of image processing challenges.

adaptive thresholding↗
DOE OSTI2014

Growth of arrays of oriented epitaxial platinum nanoparticles with controlled size and shape by natural colloidal lithography

Here, we developed a method for production of arrays of platinum nanocrystals of controlled size and shape using templates from ordered silica bead monolayers. Silica beads with nominal sizes of 150 and 450 nm were self-assembl into monolayers over strontium titanate single crystal substrates. The monolayers were used as shadow masks for platinum metal deposition on the substrate using the three-step evaporation technique. Produced arrays of epitaxial platinum islands were transformed into nanocrystals by annealing in a quartz tube in nitrogen flow. The shape of particles is determined by the substrate crystallography, while the size of the particles and their spacing are controlled by the size of the silica beads in the mono- layer mask. As a proof of concept, arrays of platinum nanocrystals of cubooctahedral shape were prepared on (100) strontium titanate substrates. We also characterized the nanocrystal arrays by atomic force microscopy, scanning electron microscopy, and synchrotron X-ray diffraction techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Field Testing LIDAR Based Feed-Forward Controls on the NREL Controls Advanced Research Turbine: Preprint

Wind turbines are complex, nonlinear, dynamic systems driven by aerodynamic, gravitational, centrifugal, and gyroscopic forces. The aerodynamics of wind turbines are nonlinear, unsteady, and complex. Turbine rotors are subjected to a chaotic three-dimensional (3-D) turbulent wind inflow field with imbedded coherent vortices that drive fatigue loads and reduce lifetime. In order to reduce cost of energy, future large multimegawatt turbines must be designed with lighter weight structures, using active controls to mitigate fatigue loads, maximize energy capture, and add active damping to maintain stability for these dynamically active structures operating in a complex environment. Researchers at the National Renewable Energy Laboratory (NREL) and University of Stuttgart are designing, implementing, and testing advanced feed-back and feed-forward controls in order to reduce the cost of energy for wind turbines.

17 WIND ENERGY↗
DOE OSTI2018

Control Signals of a Predictive Industrial PID Controller

To expand the functional capabilities of industrial controllers for systems subject to external disturbances, developments to date are reviewed, and an approach permitting the generation of control signals on the basis of predictions is proposed and tested. The benefits of this approach are assessed. It is best used for large industrial equipment and systems in manufacturing and the oil and gas industry.

42 ENGINEERING↗
DOE OSTI2010

Co-Simulation of Building Energy and Control Systems with the Building Controls Virtual Test Bed

This article describes the implementation of the Building Controls Virtual Test Bed (BCVTB). The BCVTB is a software environment that allows connecting different simulation programs to exchange data during the time integration, and that allows conducting hardware in the loop simulation. The software architecture is a modular design based on Ptolemy II, a software environment for design and analysis of heterogeneous systems. Ptolemy II provides a graphical model building environment, synchronizes the exchanged data and visualizes the system evolution during run-time. The BCVTB provides additions to Ptolemy II that allow the run-time coupling of different simulation programs for data exchange, including EnergyPlus, MATLAB, Simulink and the Modelica modelling and simulation environment Dymola. The additions also allow executing system commands, such as a script that executes a Radiance simulation. In this article, the software architecture is presented and the mathematical model used to implement the co-simulation is discussed. The simulation program interface that the BCVTB provides is explained. The article concludes by presenting applications in which different state of the art simulation programs are linked for run-time data exchange. This link allows the use of the simulation program that is best suited for the particular problem to model building heat transfer, HVAC system dynamics and control algorithms, and to compute a solution to the coupled problem using co-simulation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Cooperative Adaptive Cruise Control (CACC) in Controlled and Real-World Environments: Testing and Results

The transportation industry annually travels more than 6 times as many miles as passenger vehicles. The fuel cost associated with this represents 38% of the total marginal operating cost for this industry. As a result, industry’s interest in applications of autonomy have grown. One application of this technology is Cooperative Adaptive Cruise Control (CACC) using Dedicated Short-Range Communications (DSRC). Auburn University outfitted four class 8 vehicles, two Peterbilt 579’s and two M915’s, with a basic hardware suite, and software library to enable level 1 autonomy. These algorithms were tested in controlled environments, such as the American Center for Mobility (ACM), and on public roads, such as highway 280 in Alabama, and Interstates 275/696 in Michigan. This paper reviews the results of these real-world tests and discusses the anomalies and failures that occurred during testing.

42 ENGINEERING↗
DOE OSTI2015

Global patterns and controls of soil organic carbon dynamics as simulated by multiple terrestrial biosphere models. Current status and future directions

Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and loss from soil accounts for a large pro portion of land-atmosphere C exchange. Due to large pool size and variable residence time from years to millennia, even small changes in soil organic C(SOC) have substantial effects on the terrestrial C budget, thereby affecting atmospheric carbon dioxide (CO2)concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil exchange with the atmosphere through site measurements, inventories, and empirical/process-based modeling. However, these estimates are highly uncertain and identifying major driving forces controlling soil C storage and fluxes remains a key research challenge his study has compiled century-long (1901-2010)estimates of SOC storage and heterotrophic respiration (Rh) from ten terrestrial biosphere models (TBMs) in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) and two observation based datasets. The ten-TBM ensemble shows that global SOC estimate range from 4 to 2111 Pg C (1 Pg = 10 15 g) with a median value of 1158 Pg C33 in 2010. Modeling approach estimates a broad range of Rh from 35 to 69 Pg C yr -1 with a median value of 51Pg C yr -1 during 200–2010. The largest uncertainty in SOC stocks exists in the 40–65°N latitude band while Rh differences are the largest in the tropics. All the models agreed that climate and land use changes have decreased SOC stocks while elevated CO 2 and atmospheric nitrogen deposition have increased SOC stocks though the response varied significantly among models. Model representations of temperature and moisture sensitivity,nutrient limitation and land use partially explain the divergent estimates of global SOC stocks and soil fluxes in this study. In addition, major sources of uncertainty from model estimation include exclusion of SOC storage in wetlands and peatlands as well as C storage in deep soil layers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Functional approach to exploring climatic and landscape controls of runoff generation: 1. Behavioral constraints on runoff volume

Abstract Inspired by the Dunne diagram, the climatic and landscape controls on the partitioning of annual runoff into its various components (Hortonian and Dunne overland flow and subsurface stormflow) are assessed quantitatively, from a purely theoretical perspective. A simple distributed hydrologic model has been built sufficient to simulate the effects of different combinations of climate, soil, and topography on the runoff generation processes. The model is driven by a sequence of simple hypothetical precipitation events, for a large combination of climate and landscape properties, and hydrologic responses at the catchment scale are obtained through aggregation of grid‐scale responses. It is found, first, that the water balance responses, including relative contributions of different runoff generation mechanisms, could be related to a small set of dimensionless similarity parameters. These capture the competition between the wetting, drying, storage, and drainage functions underlying the catchment responses, and in this way, provide a quantitative approximation of the conceptual Dunne diagram. Second, only a subset of all hypothetical catchment/climate combinations is found to be “behavioral,” in terms of falling sufficiently close to the Budyko curve, describing mean annual runoff as a function of climate aridity. Furthermore, these behavioral combinations are mostly consistent with the qualitative picture presented in the Dunne diagram, indicating clearly the commonality between the Budyko curve and the Dunne diagram. These analyses also suggest clear interrelationships amongst the “behavioral” climate, soil, and topography parameter combinations, implying these catchment properties may be constrained to be codependent in order to satisfy the Budyko curve.

Li, Hong‐Yi↗
DOE OSTI2016

Strain Control of Oxygen Vacancies in Epitaxial Strontium Cobaltite Films

The ability to manipulate oxygen anion defects rather than metal cations in complex oxides can facilitate creating new functionalities critical for emerging energy and device technologies. However, the difficulty in activating oxygen at reduced temperatures hinders the deliberate control of important defects, oxygen vacancies. Here, strontium cobaltite (SrCoOx) is used to demonstrate that epitaxial strain is a powerful tool for manipulating the oxygen vacancy concentration even under highly oxidizing environments and at annealing temperatures as low as 300 degrees C. By applying a small biaxial tensile strain (2%), the oxygen activation energy barrier decreases by approximate to 30%, resulting in a tunable oxygen defi cient steady-state under conditions that would normally fully oxidize unstrained cobaltite. These strain-induced changes in oxygen stoichiometry drive the cobaltite from a ferromagnetic metal towards an antiferromagnetic insulator. The ability to decouple the oxygen vacancy concentration from its typical dependence on the operational environment is useful for effectively designing oxides materials with a specific oxygen stoichiometry.

Petrie, Jonathan R.↗