SEARCH · Engineering Papers

Results for “smoothing”

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.

SourceResearch connectionFrom yearThrough year

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

At least 991 records · Page 55

All sources NASA NTRS DOE OSTI

DOE OSTI2023

An ICA-Based HVAC Load Disaggregation Method Using Smart Meter Data

This paper presents an independent component analysis (ICA) based unsupervised-learning method for heat, ventilation, and air-conditioning (HVAC) load disaggregation using row-resolution (i.e., 15 minutes) smart meter data. We first demonstrate that the electricity consumption profiles on mild-temperature days can be used to approximate the base load on hot days. A residual load profile can then be calculated by subtracting the mild-day load profile from the hot-day load profile. The residual load profiles are processed using ICA for HVAC load extraction. An optimization-based algorithm is proposed for post-adjustment of the ICA results, considering two bounding factors for enhancing the robustness of the ICA algorithm. First, we use the hourly HVAC energy bounds computed from the relationship between HVAC load and temperature to remove unrealistic HVAC load spikes. Second, we exploit the dependency between the daily nocturnal and diurnal loads extracted from historical meter data to smooth the base load profile. Pecan Street data with sub-metered HVAC data were used to test and verify the proposed methods. Simulation results demonstrated that the proposed method is computationally efficient and robust across multiple customers.

Kim, Hyeonjin↗

DOE OSTI2022

Adaptive Urban Traffic Signal Control for Multiple Intersections: An LQR Approach

Traffic congestion leads to severe problems especially in urban traffic networks. It increases the chance of accidents, energy waste, and social costs. In order to address these problems, an adaptive linear quadratic regulator (LQR) approach is developed for traffic signal control at multiple intersections in an urban area. The proposed method controls the green time of the traffic signals to reduce traffic congestion and smooth traffic flow. Real-world data from vision-based traffic sensors are used to build the traffic network model, which mimics the real-world traffic behavior. In addition, the proposed control utilizes recursive least square parameter estimation, which is capable of tracking dynamic changes in traffic conditions. Simulation of Urban MObility (SUMO) is used to analyze the efficacy of the proposed method. Results of the simulation show that the proposed method outperforms pretimed control in various aspects.

adaptive LQR control↗

DOE OSTI2021

Solar Transposition Modeling via Deep Neural Networks With Sky Images

This article presents a notable advance toward the development of a new method of increasing the single-axis tracking photovoltaic (PV) system power output by improving the determination and near-term prediction of the optimum module tilt angle. The tilt angle of the plane receiving the greatest total irradiance changes with Sun position and atmospheric conditions including cloud formation and movement, aerosols, and particulate loading, as well as varying albedo within a module's field of view. In this article, we present a multi-input convolutional neural network that can create a profile of plane-of-array irradiance versus surface tilt angle over a full 180° arc from horizon to horizon. As input, the neural network uses the calculated solar position and clear-sky irradiance values, along with sky images. The target irradiance values are provided by the multiplanar irradiance sensor (MPIS). In order to account for varying irradiance conditions, the MPIS signal is normalized by the theoretical clear-sky global horizontal irradiance. Using this information, the neural network outputs an N -dimensional vector, where N is the number of points to approximate the MPIS curve via Fourier resampling. The output vector of the model is smoothed with a Gaussian kernel to account for error in the downsamping and subsequent upsampling steps, as well as to smooth the unconstrained output of the model. Furthermore, these profiles may be used to perform near-term prediction of angular irradiance, which can then inform the movement of a PV tracker.

42 ENGINEERING↗

DOE OSTI2021

Integration of Storage in the DC Link of a Full Converter-Based Distributed Wind Turbine

Energy storage is known to support the dispatchability of variable renewable resources. In this paper, we model a battery energy storage system (BESS) integrated with the DC link of a Type IV full converter-based wind turbine and the necessary controls to achieve efficient dispatch. To support the validation of control methodologies, we build a detailed model of a Type IV research wind turbine at the National Renewable Energy Laboratory (NREL), the Controls Advanced Research Turbine (CART 3), and we integrated a lithium-ion BESS model in grid-following mode into the model. The simulation results illustrate the sizing and control of the DC link-integrated BESS for a given variable wind resource and varying dispatch strategies (i.e., under constant, uncertain, and ramping wind scenarios). The integrated storage can smooth variabilities in distributed wind output, hedge against uncertainties, provide the ramping capability, as well as support stability under voltage and frequency transients. All of these have been illustrated in MATLAB/Simulink.

DC-link voltage↗

DOE OSTI2024

Riemannian Optimization Applied to AC Optimal Power Flow: Preprint

The nonlinear, nonconvex AC optimal power flow problem is of growing importance as the nature of the power grid evolves. This problem can be difficult to solve for interior point methods. However, the advent of optimization algorithms over smooth Riemannian manifolds presents an alternative approach. The nonlinear, nonconvex constraints in the AC power flow problem form an embedded submanifold of Euclidean space. In this paper, the authors explore the performance of Riemannian optimization algorithms for the ACOPF problem where the optimization is performed directly on the AC power flow manifold. They demonstrate that these are viable computational alternatives to interior point methods. This is done by using Julia and the packages PowerModels.jl and Manopt.jl.

manifold optimization↗

DOE OSTI2021

Planarization of Rough (100) GaAs Substrates via Growth by Hydride Vapor Phase Epitaxy

Wafer reuse techniques help offset the cost of III-V growth substrates by using a single wafer for multiple growths, but costly re-polishing after device removal limits the end benefit. In this work, we present planarization growth by hydride vapor-phase epitaxy (HVPE), a potentially low-cost growth technique, as a method of smoothing rough substrates for subsequent high-quality device growth without the need for polishing. First, we show there is a threshold for allowable substrate roughness without device degradation by comparing devices grown by organometallic vapor-phase epitaxy (OMVPE) on epi-ready polished and pre-polished substrates that did not have the final epi-ready polish. We then demonstrate successful smoothing with HVPE growth on substrates with different surface morphologies, with features ranging from general roughness to large facets. Initial devices grown by HVPE on a pre-polished substate showed no degradation compared to a control wafer, indicating that planarizing rough substrates through HVPE growth is a promising path toward being able to use rough substrates directly for growth, without costly polishing steps.

GaAs↗

DOE OSTI2024

Preliminary Assessment of Additively Manufactured Cooling Channel Performance for Helium-Cooled Blanket Concepts

Sufficient cooling of the blanket first wall remains a critical challenge for the design and deployment of fusion power plants. Helium has been targeted as a potential blanket coolant due to its inertness and low neutron interactivity, among other advantages. However, the low thermal mass of helium creates a need for heat transfer enhancements in coolant channels to provide adequate cooling to the blanket’s first wall. Toward this end, a series of ribbed flow channels of various rib cross sections and configurations has been produced via additive manufacturing (AM) to study the efficacy of AM for first wall heat transfer enhancement and the optimization of heat transfer geometries. Helium cooling performance is studied in AM test articles at 4 MPa operating pressure, Reynolds numbers up to 197 000, and outer surface heat fluxes up to 42 kW/m 2 in the recently commissioned helium flow loop experiment (HFLE). Preliminary results of this study are presented herein. Heat transfer performance of nominally smooth (i.e., featureless) AM channels is quantified via measured Nusselt numbers and friction factors and compared to off-the-shelf smooth pipe experiments. Results are compared to existing correlations and used to discuss the effects of the AM processes on thermal-hydraulic performance. It is seen that the inherent roughness of the AM channels leads to an increase in both heat transfer coefficient and pressure drop when compared to the conventional pipe. In conclusion, recommendations are made for future studies based on these findings and additional considerations for the deployment of AM blanket cooling components.

36 MATERIALS SCIENCE↗

DOE OSTI2024

A Novel Design for Switchable Grid-Following and Grid-Forming Control

This paper presents the design of a novel grid- forming (GFM) control structure adapted from a typical grid- following (GFL) control structure with minimal edits, thereby enabling a switchable control structure for voltage sourced converters (VSCs) to operate in either GFL or GFM mode by simply switching a flag manually. The VSC is shown to be able to operate in the GFL control mode synchronizing to the main grid through a phase-locked-loop (PLL) and operate as a GFM controller with power-based synchronization for both grid-connected and islanded conditions. To guarantee smooth operation, the control schemes and the mode switching logic have been carefully designed and examined via a series of experiments. Here, the experiment results show that the switchable control structure can fulfill the desired control and operation functions and enable smooth transition between control modes.

14 SOLAR ENERGY↗

DOE OSTI2020

Vector Field Decompositions Using Multiscale Poisson Kernel

Extraction of multiscale features using scale-space is one of the fundamental approaches to analyze scalar fields. However, similar techniques for vector fields are much less common, even though it is well known that, for example, turbulent flows contain cascades of nested vortices at different scales. The challenge is that the ideas related to scale-space are based upon iteratively smoothing the data to extract features at progressively larger scale, making it difficult to extract overlapping features. Instead, we consider spatial regions of influence in vector fields as scale, and introduce a new approach for the multiscale analysis of vector fields. Rather than smoothing the flow, we use the natural Helmholtz-Hodge decomposition to split it into small-scale and large-scale components using progressively larger neighborhoods. Our approach creates a natural separation of features by extracting local flow behavior, for example, a small vortex, from large-scale effects, for example, a background flow. We demonstrate our technique on large-scale, turbulent flows, and show multiscale features that cannot be extracted using state-of-the-art techniques.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Surface Texture of Macroplastic Pollution in Streams Alters the Physical Structure and Diversity of Biofilm Communities

ABSTRACT Biofilms can develop on nearly any surface, and in aquatic ecosystems they are essential components of biogeochemical cycles and food webs. Plastic waste in waterways is a new type of surface for biofilm colonisation. To analyse the influence of plastic pollution on the development and diversity of microbial freshwater biofilms that colonised them, we incubated 388 cm 2 veneers of high‐density polyethylene (HDPE) with two veneer textures, smooth and rough, and tulip tree wood ( Liriodendron tulipifera ), in three rural headwater streams at the Savannah River Site (Aiken, SC, USA). We collected biofilms from veneers after 14, 28 and 56 days of incubation and analysed 16S rRNA genes and biofilm properties. We found that plastic negatively affected species richness of biofilms compared with wood, but that evenness was greatest on rough textured HDPE. Beta diversity was primarily influenced by stream site. Beta diversity differed more between wood and plastic veneers than with plastic surface texture and became more different over time. Wood had nine times more biomass than rough HDPE and 40 times more biomass than smooth HDPE. Given the projected increase of macroplastic pollution in aquatic ecosystems, our findings emphasise the need to further understand its effects on biofilm characteristics.

Lopez Avila, Fabiola [Odum School of Ecology Unive↗

DOE OSTI2024

Paternal preconception alcohol consumption increased Angiotensin II‐mediated vasoconstriction in male offspring cerebral arteries via oxidative stress‐AT1R pathway

Abstract Alcohol consumption is popular worldwidely and closely associated with cardiovascular diseases. Influences of paternal preconception alcohol consumption on offspring cerebral arteries are largely unknown. Male rats were randomly given alcohol or water before being mated with alcohol‐naive females to produce alcohol‐ and control‐sired offspring. Middle cerebral artery (MCA) was tested with a Danish Myo Technology wire myograph, patch‐clamp, IONOPTIX, immunofluorescence and quantitative PCR. Alcohol consumption enhanced angiotensin II (AngII)‐mediated constriction in male offspring MCA mainly via AT1R. PD123,319 only augmented AngII‐induced constriction in control offspring. AngII and Bay K8644 induced stronger intracellular calcium transient in vascular smooth muscle cells (VSMCs) from MCA of alcohol offspring. L‐type voltage‐dependent calcium channel (L‐Ca 2+ ) current at baseline and after AngII‐stimulation was higher in VSMCs. Influence of large‐conductance calcium‐activated potassium channel (BK C a ) was lower. Caffeine induced stronger constriction and intracellular calcium release in alcohol offspring. Superoxide anion was higher in alcohol MCA than control. Tempol and thenoyltrifluoroacetone alleviated AngII‐mediated contractions, while inhibition was significantly higher in alcohol group. The mitochondria were swollen in alcohol MCA. Despite lower Kcnma1 and Prkce expression, many genes expressions were higher in alcohol group. Hypoxia induced reactive oxygen species production and increased AT1R expression in control MCA and rat aorta smooth muscle cell line. In conclusion, this study firstly demonstrated paternal preconception alcohol potentiated AngII‐mediated vasoconstriction in offspring MCA via ROS‐AT1R. Alcohol consumption increased intracellular calcium via L‐Ca 2+ channel and endoplasmic reticulum and decreased BK Ca function. The present study provided new information for male reproductive health and developmental origin of cerebrovascular diseases.

Zhang, Ze↗

DOE OSTI2021

Resource selection functions based on hierarchical generalized additive models provide new insights into individual animal variation and species distributions

Habitat selection studies are designed to generate predictions of species distributions or inference regarding general habitat associations and individual variation in habitat use. Such studies frequently involve either individually indexed locations gathered across limited spatial extents and analyzed using resource selection functions (RSFs) or spatially extensive locational data without individual resolution typically analyzed using species distribution models. Both analytical methodologies have certain desirable features, but analyses that combine individual- and population-level inference with flexible non-linear functions may provide improved predictions while accounting for individual variation. Here, we describe how RSFs can be fit using hierarchical generalized additive models (HGAMs) using widely available software, providing a means to explore individual variation in habitat associations and to generate species distribution maps. We used GPS tracking data from golden eagles Aquila chrysaetos from across eastern North America with four environmental predictors to generate monthly distribution models. We considered three model structures that assumed different amounts of individual variation in the functional relationship between predictors and habitat use and used k-fold cross-validation to compare model performance. Models accounting for individual variability in shape and smoothness of functional responses performed best. Eagles exhibited the least amount of individual variation in response to land cover variables during winter months, with most individuals more closely adhering to the population-level trend. During the summer months, eagles exhibited more substantial individual variation in shape and smoothness of the functional relationships, suggesting some need to account for individual variation in eagle habitat use for both inferential and predictive purposes, during this time of year. Because they allow users to blend flexible functions with random effects structures and are well-supported by a variety of software platforms, we believe that HGAMs provide a useful addition to the suite of analyses used for modeling habitat associations or predicting species distributions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Multi‐hypothesis comparison of Farquhar and Collatz photosynthesis models reveals the unexpected influence of empirical assumptions at leaf and global scales

Abstract Mechanistic photosynthesis models are at the heart of terrestrial biosphere models (TBMs) simulating the daily, monthly, annual and decadal rhythms of carbon assimilation ( A ). These models are founded on robust mathematical hypotheses that describe how A responds to changes in light and atmospheric CO 2 concentration. Two predominant photosynthesis models are in common usage: Farquhar (FvCB) and Collatz (CBGB). However, a detailed quantitative comparison of these two models has never been undertaken. In this study, we unify the FvCB and CBGB models to a common parameter set and use novel multi‐hypothesis methods (that account for both hypothesis and parameter variability) for process‐level sensitivity analysis. These models represent three key biological processes: carboxylation, electron transport, triose phosphate use (TPU) and an additional model process: limiting‐rate selection. Each of the four processes comprises 1–3 alternative hypotheses giving 12 possible individual models with a total of 14 parameters. To broaden inference, TBM simulations were run and novel, high‐resolution photosynthesis measurements were made. We show that parameters associated with carboxylation are the most influential parameters but also reveal the surprising and marked dominance of the limiting‐rate selection process (accounting for 57% of the variation in A vs. 22% for carboxylation). The limiting‐rate selection assumption proposed by CBGB smooths the transition between limiting rates and always reduces A below the minimum of all potentially limiting rates, by up to 25%, effectively imposing a fourth limitation on A . Evaluation of the CBGB smoothing function in three TBMs demonstrated a reduction in global A by 4%–10%, equivalent to 50%–160% of current annual fossil fuel emissions. This analysis reveals a surprising and previously unquantified influence of a process that has been integral to many TBMs for decades, highlighting the value of multi‐hypothesis methods.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Tracking animal movements via collaborative acoustic telemetry networks: Multiscale habitat use, phenology, and management insights

Abstract Estuaries support diverse fish and invertebrate communities, including resident species that rely on estuarine habitats year‐round and transient migratory species. The unique movement patterns of these animals connect habitats within and far beyond the estuary and are integrally linked to fisheries management objectives. With a focus on Chesapeake Bay, this study leveraged data from collaborative acoustic telemetry networks in the northwest Atlantic to assess habitat use and phenology of movements for seven species of fish (cownose rays, dusky sharks, smooth dogfish, alewife, striped bass, common carp, and blue catfish) and one invertebrate (horseshoe crabs). A total of 288 acoustically tagged individuals were detected >3.2 million times (6,743 to 2,095,717 detections per species) on receivers across ~20.5 degrees of latitude spanning the North American Atlantic seaboard from Florida, USA, to New Brunswick, Canada. Common metrics of movement and phenology grouped these species as resident (common carp, blue catfish, horseshoe crabs), primarily resident in estuaries (juvenile striped bass), and coastal migrant (cownose rays, dusky sharks, smooth dogfish, alewife); maximum distance traveled varied by three orders of magnitude among these species. Further analysis of phenology for coastal migrants elucidated the timing and duration of these species' use of Chesapeake Bay. Collectively, movements linked habitats within Chesapeake Bay and connected the estuary to coastal ecosystems both to the north (e.g., alewife) and south (e.g., cownose rays), creating networks of fisheries management jurisdictions that varied in complexity and identified opportunities for enhancement to current management or co‐management of some species. Our results elucidate the importance of estuaries to species with diverse movement behaviors, identify scales and pathways of habitat connectivity via animal movements, and highlight the utility of collaborative acoustic telemetry networks for quantifying movements relevant to both ecological research and fisheries management.

Livernois, Mariah C.↗

DOE OSTI2021

Experimental and Large Eddy Simulation Study for Visualizing Complex Flow Phenomena of Gas Turbine Internal Blade Cooling Channel With No Bend

Abstract In this study, the internal cooling channel was investigated without any bend. Smooth surfaces and dimpled surfaces were investigated using the different combinations of connecting circular and rectangular holes. The computations were performed using the large eddy simulation (LES) model for Reynolds (Re) numbers from 10,000 to 50,000. A total of six different connecting holes were investigated with a smooth and dimpled surface. A partial spherical dimple with two circular holes showed the highest heat transfer, but it has a higher pressure loss penalty. Even though the leaf dimpled surface with the rectangluar holes indicated a little low heat transfer, it represents the highest efficiency at higher Reynolds numbers because of the low-pressure drops.

Energy & Fuels↗

DOE OSTI2024

Flow and Heat Transfer Experimental Study for 3D-Printed Solar Receiving Tubes With Helical Fins at Internal Surface

3D-printing technology was applied to fabricate novel solar thermal collection tubes that have internal heat transfer enhancement fins and external surfaces with high solar absorptivity and low emissivity due to the ability to use different materials in one tube. Helical fins were selected to introduce circumferential flow and thus minimize the circumferential temperature difference of the tube that receives sunlight on one side. The structures of the helical fins were previously optimized from computational fluid dynamics (CFD) analysis with the objective of low entropy production rate by looking for high heat transfer coefficient and relatively lower pressure loss. High-temperature alloy, Inconel-718, was used to 3D print the tubes, which can resist corrosion for the potential application of molten chloride salts as heat transfer fluid. Experimental tests were carried out using water as the heat transfer fluid with the high heat flux provided by a tubular furnace heater. The tested Reynolds number ranges from 3.9 × 10 3 to 6.1 × 10 4 . Heat transfer coefficients of up to 2.8 times that of the smooth tube could be obtained with the expense of increased pressure loss compared to that of the smooth tube. The total system entropy generation can be significantly reduced due to the benefit of heat transfer enhancement that is greater than the expenses of the increased pressure loss. The experimental results of the 3D-printed heat transfer tubes confirmed the CFD-based results of fin optimization. Furthermore, the novel heat transfer tube is recommended for application in concentrating solar power systems.

14 SOLAR ENERGY↗

DOE OSTI2023

Human-in-the-Loop Motion Control of a Two-DOF Hydraulic Backhoe Powered by the Hybrid Hydraulic Electric Architecture (HHEA)

Abstract The Hybrid Hydraulic-Electric Architecture (HHEA) combines the respective power density and control advantages of hydraulic and electric actuation to save energy for off-road vehicles. It uses a set of selectable common pressure rails to transmit the majority of power and electric actuation to modulate that power. As it is critical that off-road vehicles can perform tasks dexterously and exactly as commanded by the operator, the switchings between discrete pressure rails pose a potential challenge for smooth and precise motion. A control strategy consisting of a backstepping nominal control and least norm transition control has previously been developed to address this issue. It has been tested on 1 degree of freedom (DOF) testbeds where known trajectories were able to be tracked precisely. This paper presents the implementation of the HHEA motion control strategy on a 2-DOF backhoe operated by a human operator via a 2-DOF joystick. Unlike previous studies, the duty cycle is unknown beforehand and the decision to change pressure rails is taken in real-time. The efficacy of the motion control strategy has been validated experimentally. Several strategies to improve the user interface: control in workspace coordinates, pressure feedback, and velocity field-based task specification, have also been implemented and demonstrated to make operating the multiple DOF, HHEA actuated machine more intuitive to novice operators.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Recent Hydrodynamic Modeling Enhancements in OpenFAST

To improve the hydrodynamic modeling capabilities of the offshore wind design and modeling tool OpenFAST, a restructuring of the HydroDyn hydrodynamics module was undertaken with several new features implemented. The generation of the wave field is now separated from HydroDyn into a new module called SeaState. Unlike previous versions of HydroDyn, which precomputed the wave kinematics at the undisplaced positions of the hydrodynamic nodes, the new SeaState module computes the complete time history of the wave field at the vertices of a user-defined wave grid. During the simulation, the wave kinematics at any point within the grid can be efficiently interpolated, allowing the strip-theory wave loads to be evaluated based on the wave kinematics at the displaced structure position. A phase correction was also implemented for the potential-flow wave-exciting loads to account for large structure displacements. Several wave-stretching methods were implemented for the strip-theory solution along with a wave-load redistribution method that ensures smooth variation of the nodal loads as the nodes of a discrete hydrodynamic mesh enter and exit the water. The load smoothing is included to avoid the excitation of unphysical high-frequency structural vibration during hydroelastic simulations. The MacCamy-Fuchs diffraction correction for the strip-theory solution and the capability to insert a constrained NewWave into extreme stochastic sea states with directional spreading were also added. The present article documents the formulations of the new improvements to HydroDyn with example applications and numerical results.

constrained wave↗