Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Simulation of distributed computing systems”

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.

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

At least 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

The Uncertainty of Biomass Estimates from Modeled ICESat-2 Returns Across a Boreal Forest Gradient

The Forest Light (FLIGHT) radiative transfer model was used to examine the uncertainty of vegetation structure measurements from NASA's planned ICESat-2 photon counting light detection and ranging (LiDAR) instrument across a synthetic Larix forest gradient in the taiga-tundra ecotone. The simulations demonstrate how measurements from the planned spaceborne mission, which differ from those of previous LiDAR systems, may perform across a boreal forest to non-forest structure gradient in globally important ecological region of northern Siberia. We used a modified version of FLIGHT to simulate the acquisition parameters of ICESat-2. Modeled returns were analyzed from collections of sequential footprints along LiDAR tracks (link-scales) of lengths ranging from 20 m-90 m. These link-scales traversed synthetic forest stands that were initialized with parameters drawn from field surveys in Siberian Larix forests. LiDAR returns from vegetation were compiled for 100 simulated LiDAR collections for each 10 Mg · ha(exp -1) interval in the 0-100 Mg · ha(exp -1) above-ground biomass density (AGB) forest gradient. Canopy height metrics were computed and AGB was inferred from empirical models. The root mean square error (RMSE) and RMSE uncertainty associated with the distribution of inferred AGB within each AGB interval across the gradient was examined. Simulation results of the bright daylight and low vegetation reflectivity conditions for collecting photon counting LiDAR with no topographic relief show that 1-2 photons are returned for 79%-88% of LiDAR shots. Signal photons account for approximately 67% of all LiDAR returns, while approximately 50% of shots result in 1 signal photon returned. The proportion of these signal photon returns do not differ significantly (p greater than 0.05) for AGB intervals greater than 20 Mg · ha(exp -1). The 50m link-scale approximates the finest horizontal resolution (length) at which photon counting LiDAR collection provides strong model fits and minimizes forest structure uncertainty in the synthetic Larix stands. At this link-scale AGB greater than 20 Mg · ha(exp -1) has AGB error from 20-50% at the 95% confidence level. These results suggest that the theoretical sensitivity of ICESat-2 photon counting LiDAR measurements alone lack the ability to consistently discern differences in inferred AGB at 10 Mg · ha(exp -1) intervals in sparse forests characteristic of the taiga-tundra ecotone.

LiDAR↗
NASA NTRSDate not supplied

Comparison of Visual and LiDAR SLAM Algorithms using NASA Flight Test Data

Simultaneous Localization and Mapping (SLAM) is a promising technique that provides localization information and precise mapping of the physical environment without having much prior knowledge of the surroundings. SLAM may have a vital role in aeronautics and aerospace, where vehicles and aircraft must operate in complex environments with traditional localization services that may be degraded or unavailable. This paper compares several pre-canned 3D SLAM algorithms based on vision and LiDAR, namely ORB-SLAM, ORB-SLAM2, LOAM, A-LOAM, and F-LOAM on NASA UAS (Unmanned Aircraft System) flight test data. The NASA ARC UAS flight test demonstrates preliminary SLAM algorithm results, which serve as a stepping stone to simulated AAM (Advanced Air Mobility) concepts. Conducting AFRC UAS flight test for simulated AAM approach and landing with SLAM algorithms provides an Alternative Precision Navigation and Timing solution based on distributed landmarks and fiducials in the landing zone. These algorithms use the telemetry data as ground truth for a baseline comparison. The criteria of the performance comparison include robustness, accuracy, re-localization, response to environmental changes, and real-time effectiveness, which are currently qualitative but to be quantitative in the future.

computer vision↗
NASA NTRSDate not supplied

Comparison of Visual and LiDAR SLAM Algorithms using NASA Flight Test Data

Simultaneous Localization and Mapping (SLAM) is a promising technique that provides localization information and precise mapping of the physical environment without having much prior knowledge of the surroundings. SLAM may have a vital role in aeronautics and aerospace, where vehicles and aircraft must operate in complex environments with traditional localization services that may be degraded or unavailable. This paper compares several pre-canned 3D SLAM algorithms based on vision and LiDAR, namely ORB-SLAM, ORB-SLAM2, LOAM, A-LOAM, and F-LOAM on NASA UAS (Unmanned Aircraft System) flight test data. The NASA ARC UAS flight test demonstrates preliminary SLAM algorithm results, which serve as a stepping stone to simulated AAM (Advanced Air Mobility) concepts. Conducting AFRC UAS flight test for simulated AAM approach and landing with SLAM algorithms provides an Alternative Precision Navigation and Timing solution based on distributed landmarks and fiducials in the landing zone. These algorithms use the telemetry data as ground truth for a baseline comparison. The criteria of the performance comparison include robustness, accuracy, re-localization, response to environmental changes, and real-time effectiveness, which are currently qualitative but to be quantitative in the future.

computer vision↗
NASA NTRS1985

A systems analysis of the erythropoietic responses to weightlessness. Volume 2: Description of the model of erythropoiesis regulation. Part A: Model for regulation of erythropoiesis. Part B: Detailed description of the model for regulation of erythropoiesis

A mathematical model of the erythropoiesis on total red blood cell mass is presented. The loss of red cell mass has been a consistent finding during space flight. Computer simulation of this phenomenon required a model that could account for oxygen transport, red cell production, and red cell destruction. The elements incorporated into the feedback regulation loop of the model are based on the accepted concept that erythrocyte production is governed by the balance between oxygen supply and demand in the body. The mechanisms and pathways of the control circuit include oxygenation of hemoglobin and oxygenation of tissues by blood transport and diffusional processes. Other features of the model include a variable oxygen-hemoglobin affinity, and time delays which represent time for erythropoietin (erythrocyte-stimulating hormone) distribution in plasma, and time for maturation of the erythrocytes in bone marrow.

Leonard, J. I.↗
DOE OSTI2018

Supercomputers, Clouds and Grids powered by BigPanDA for Brain studies

The PanDA WMS - Production and Distributed Analysis Workload Management System - has been developed and used by the ATLAS experiment at the LHC (Large Hadron Collider) for all data processing and analysis challenges. BigPanDA is an extension of the PanDA WMS to run ATLAS and non-ATLAS applications on Leadership Class Facilities and supercomputers, as well as traditional grid and cloud resources. The success of the BigPanDA project has drawn attention from other compute intensive sciences such as biology. In 2017, a pilot project was started between BigPanDA and the Blue Brain Project (BBP) of the Ecole Polytechnique Federal de Lausanne (EPFL) located in Lausanne, Switzerland. This proof of concept project is aimed at demonstrating the efficient application of the BigPanDA system to support the complex scientific workflow of the BBP, which relies on using a mix of desktop, cluster and supercomputers to reconstruct and simulate accurate models of brain tissue.

Computer Science↗
NASA NTRS2004

The Investigation Of Carbon Contamination And Sputtering Effects Of Xenon Ion Thrusters

The Electro-Physics Branch of the NASA Glenn Research Center investigates the effect of atomic oxygen, environmental durability of high performance power materials and surfaces, and low earth orbit. One of its current projects involves the analysis of ion thrusters. Ion thrusters are devices that initiate a beam of ions to a target area. The type of ion thruster that I have been working with this Summer of 2004 emits positively charged Xenon (Xe(+)) atoms through two grids, the screen grid and the accelerator grid, after it enters an ionization chamber. Insulators are used to mechanically hold and separate these two grids. A propellant isolator, an instrument that closely resembles insulators, is placed in front of the ionization chamber. Both the insulator and isolator are made with a ceramic compound and filled with insulating beads. The main difference between the two devices is that the propellant isolator allows gas to flow through, in this case, the gas is Xe(+) and the insulators do not. In order to avoid carbon deposits and other contaminating chemicals to settle on the insulators and propellant isolator, a metal shadow shield is placed around them. These shadow shields function as a protectant and can be shaped in numerous configurations. Part of my job responsibility this summer is to investigate the effectiveness of different shadow shields that are utilized on three different ion engines: the NSTAR (NASA Solar Electric Propulsion Technology Application Readiness), JIMO (Jupiter Icy Moons Orbiter), and NEXIS (Nuclear Electric Xenon Ion System). Using calculus and other mathematical tactics, I was asked to find the total flux of carbon contamination that was able to pass the protectant shadow shield. I familiarized myself with the software program, MathCad2004, to help perform some mathematical computations such as complex integration. Another method of studying the probability of contamination is by experimental simulation. After attaining the precise parameters of the actual shadow shields, I created replicas of three types of shadow shielding to be used to undergo testing. It will be placed in a machine that produces carbon atoms at a high temperature of 200 C. or beam is aimed at a targeted material. As a result of this collision, atoms and other particles are ejected out of the target surface. Another part of my internship consisted of research on sputter ejection, or the angle distribution of sputtered material. This research entailed finding the past results of sputter ejection investigation as well as creating another type of mock simulation. Other minor projects include calculating the path of Xe(+) gas through the insulating beads of the isolators and assisting my mentor in collecting data for his paper for the Joint Propulsion Conference & Exhibit to be held July 11-14,2004 in Fort Lauderdale, Florida.

Prak, Moline K.↗
DOE OSTI2023

Integrating Learning and Physics based Computation for Fast Online Transient Analysis

In this work, a novel method that integrates learning and physics based computation is developed for greatly accelerating the simulation of full power system transient trajectories. To solve the dynamic algebraic equations, the method replaces the time-consuming dynamic computation for generator dynamics with trained predictors, while retaining the time-efficient algebraic computation of solving AC-power flow (PF) for power systems. In particular, a predictor is trained for each generator, and the system trajectories are computed by alternating steps of calling the predictors and solving AC-PF. The proposed method also allows fully parallelizable training strategies and a flexible trade-off between training time and testing accuracy. Comprehensive evaluations of the proposed method for transient/dynamic contingency analysis of the New York/New England 16-machine 68-bus power systems demonstrate excellent performance and significant acceleration of computation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Numerical investigation of a fueled pre-chamber spark-ignition natural gas engine

Pre-chamber spark-ignition (PCSI) is a leading advanced ignition concept for internal combustion engines with the potential to enable diesel-like efficiency in medium-duty/heavy-duty (MD/HD) natural gas (NG) engines. By leveraging distributed ignition sources from multiple turbulent jets, the PCSI technology can deliver extremely short combustion duration in ultra-lean mixtures and significantly improve the engine thermal efficiency. However, in the automotive industry there is a lack of adequate science base and predictive simulation tools required for commercial development of PCSI engines. Here, in this study, Reynolds-Average Navier-Stokes simulations are carried out to describe the combustion process in lean-burn NG engines, focusing on the combustion modeling approach. Two combustion models, multi-zone well-stirred reactor (MZ-WSR) and G-equation, are used to simulate the combustion process in an MD NG engine equipped with a fueled-PCSI system for four operating conditions close to the lean operating limit. A skeletal chemical mechanism and a laminar flame speed tabulation are used to compute the combustion accurately. Simulation results are compared with experimental data regarding measured cylinder pressure, heat release rate, and combustion duration. By dividing the PCSI combustion process into four distinct phases, the difference between the two models’ results for each phase is analyzed in detail. The MZ-WSR model overestimates the combustion duration for early flame kernel growth in the pre-chamber due to the lack of a specific formulation to take turbulence-chemistry interaction into account. Despite the prolonged combustion duration and low pressure built-up inside the pre-chamber, the model matches the combustion rate in the main-chamber. In contrast, the G-equation model delivers good agreements for the pre-chamber combustion and turbulent jet-driven combustion processes. However, the model starts to underestimate the combustion rate in the main-chamber, especially under ultra-lean mixture conditions. Finally, improvements are needed for both models to simulate the later combustion stage that occurred in the near-wall regions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Distributed Optimal Power Management for Battery Energy Storage Systems: A Novel Accelerated Tracking ADMM Approach

Optimal power management (OPM) is critical for large-scale battery energy storage systems. Today’s methods often require formidable computational effort due to the design based on centralized numerical optimization. Thus, this paper investigates computationally distributed OPM where the agents based on the cells communicate over a network to cooperatively solve the OPM problem. We propose an accelerated tracking alternating direction method of multipliers (ADMM) algorithm to solve the distributed OPM. The proposed algorithm embeds dynamic average consensus and Nesterov’s acceleration technique in the ADMM algorithm. Not only is the proposed algorithm fully distributed without a need for fusion or aggregating nodes, but it also accelerates convergence. The paper formulates the OPM in a model predictive control framework where it seeks to regulate the charging/discharging power of each battery cell to minimize the total power losses and promote balanced use of the constituent cells while complying with the safety constraints. The paper provides ample simulation results to demonstrate the effectiveness and advantages of the proposed distributed OPM in terms of computation and convergence.

Farakhor, Amir↗
NASA NTRS1987

NESSUS/expert and NESSUS/FPI in the Probabilistic Structural Analysis Methods (PSAM) program

The Numerical Evaluation of Stochastic Structures under Stress (NESSUS) is the primary computer code being developed in the NASA Probabilistic Structural Analysis Methods (PSAM) project. It consists of four modules NESSUS/EXPERT, NESSUS/FPI, NESSUS/PRE and NESSUS/FEM. This presentation concentrates on EXPERT and FPI. To provide an effective interface between NESSUS and the user, an expert system module called NESSUS/EXPERT is being developed. That system uses the CLIPS artificial intelligence code developed to NASA-JSC. The code is compatible with FORTRAN, the standard language for codes in PSAM. The user interacts with the CLIPS inference engine, which is linked to the knowledge database. The perturbation database generated by NESSUS/FEM and managed in EXPERT is used to develop the so-called response or performance model in the random variables. Two independent probabilistic methods are available in PSAM for the computation of the probabilistic structural response. These are the Fast Probability Integration (FPI) method and Monte Carlo simulation. FPI is classified as an advanced reliability method and has been developed over the past ten years by researchers addressing the reliability of civil engineering structures. Monte Carlo is a well-established technique for computing probabilities by conducting a number of deterministic analyses with specified input distributional information.

Burnside, O. H.↗
NASA NTRS1992

Collapse analysis of a waffle plate strongback for Space Station Freedom

The structural integrity was studied of the Integrated Equipment Assembly (IEA) Strongback of the SSF for the launch environment. The strongback structure supports the electrical power system for SSF. To achieve minimum launch mass, it is essential that flight structures are designed as light as possible. A nonlinear structural analysis was conducted to determine the collapse load of the structure and the associated factor of safety against the service loads. A modeling technique is provided for simulating the load conditions and the buckling and post buckling (collapse) load is evaluated of the IEA Strongback structure, using the finite element computer code MARC. Two of four strongback panels were modeled and analyzed. The effects were examined of the following factors on the global behavior of the strongback panels: (1) load simplification and simulation; (2) type of support boundary conditions; and (3) the possibility of weight reduction of the original structure. For this purpose, several models of the two panels of the strongback were considered. The stress level and distribution in the panels for launch condition, the Eigenvalue critical buckling load and/or the collapse load were determined.

Monasa, Frank F.↗
NASA NTRS1995

The NAS Computational Aerosciences Archive

In order to further the state-of-the-art in computational aerosciences (CAS) technology, researchers must be able to gather and understand existing work in the field. One aspect of this information gathering is studying published work available in scientific journals and conference proceedings. However, current scientific publications are very limited in the type and amount of information that they can disseminate. Information is typically restricted to text, a few images, and a bibliography list. Additional information that might be useful to the researcher, such as additional visual results, referenced papers, and datasets, are not available. New forms of electronic publication, such as the World Wide Web (WWW), limit publication size only by available disk space and data transmission bandwidth, both of which are improving rapidly. The Numerical Aerodynamic Simulation (NAS) Systems Division at NASA Ames Research Center is in the process of creating an archive of CAS information on the WWW. This archive will be based on the large amount of information produced by researchers associated with the NAS facility. The archive will contain technical summaries and reports of research performed on NAS supercomputers, visual results (images, animations, visualization system scripts), datasets, and any other supporting meta-information. This information will be available via the WWW through the NAS homepage, located at http://www.nas.nasa.gov/, fully indexed for searching. The main components of the archive are technical summaries and reports, visual results, and datasets. Technical summaries are gathered every year by researchers who have been allotted resources on NAS supercomputers. These summaries, together with supporting visual results and references, are browsable by interested researchers. Referenced papers made available by researchers can be accessed through hypertext links. Technical reports are in-depth accounts of tools and applications research projects performed by NAS staff members and collaborators. Visual results, which may be available in the form of images, animations, and/or visualization scripts, are generated by researchers with respect to a certain research project, depicting dataset features that were determined important by the investigating researcher. For example, script files for visualization systems (e.g. FAST, PLOT3D, AVS) are provided to create visualizations on the user's local workstation to elucidate the key points of the numerical study. Users can then interact with the data starting where the investigator left off. Datasets are intended to give researchers an opportunity to understand previous work, 'mine' solutions for new information (for example, have you ever read a paper thinking "I wonder what the helicity density looks like?"), compare new techniques with older results, collaborate with remote colleagues, and perform validation. Supporting meta-information associated with the research projects is also important to provide additional context for research projects. This may include information such as the software used in the simulation (e.g. grid generators, flow solvers, visualization). In addition to serving the CAS research community, the information archive will also be helpful to students, visualization system developers and researchers, and management. Students (of any age) can use the data to study fluid dynamics, compare results from different flow solvers, learn about meshing techniques, etc., leading to better informed individuals. For these users it is particularly important that visualization be integrated into dataset archives. Visualization researchers can use dataset archives to test algorithms and techniques, leading to better visualization systems, Management can use the data to figure what is really going on behind the viewgraphs. All users will benefit from fast, easy, and convenient access to CFD datasets. The CAS information archive hopes to serve as a useful resource to those interested in computational sciences. At present, only information that may be distributed internationally is made available via the archive. Studies are underway to determine security requirements and solutions to make additional information available. By providing access to the archive via the WWW, the process of information gathering can be more productive and fruitful due to ease of access and ability to manage many different types of information. As the archive grows, additional resources from outside NAS will be added, providing a dynamic source of research results.

Miceli, Kristina D.↗
DOE OSTI2024

Modeling of H2 Dispersion at ARIES

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower and help decarbonize electricity grids, industry, and transportation. Using the Hydrogen Research Facility under Advanced Research on Integrated Energy Systems (ARIES) at the National Renewable Energy Laboratory's (NREL) Flatirons campus as a test bench, the study examines the feasibility, useability, and value of using computational fluid dynamics (CFD) techniques to model hydrogen dispersion. The ARIES facility was chosen because controlled hydrogen releases can be performed at a rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind speed and temperature were used as inputs to the model. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. Wind conditions are found to significantly impact the release behavior, including the hydrogen cloud's direction and concentrations. At low wind speeds (below 1 mph), hydrogen forms a cloud and at higher wind speeds (> 2-4 mph) hydrogen plume stretches in the direction of wind momentum. From >100 simulations for ARIES site-specific conditions, statistical quantities combined with a clustering algorithm were used to propose sensor location at various elevations from ground.

dispersion↗
DOE OSTI2024

Experimental Setup and Learning-Based AI Model for Developing Accurate PV Inverter Models [Slides]

The integration of power electronics-based interfaces presents challenges due to the absence of detailed models and the high computational complexity. Generic models used in system studies lack accuracy in capturing converter dynamics. This paper proposes a data-driven approach developed from experimental setup data. This approach enhances accuracy in photovoltaic inverter modeling. We used two types of PV inverters in the experiment. The recorded experimental data undergo processing through a machine learning model. Results from the model trained through machine learning is also presented.

14 SOLAR ENERGY↗
DOE OSTI2023

Neural Networks-Based Inverter Control: Modeling and Adaptive Optimization for Smart Distribution Networks

The optimal voltage control of inverter-based resources, especially under the high penetration of solar photovoltaics, is critical to the stability of the distribution power system. However, the computational complexity as well as the coordinated operation performance of the voltage control optimization in the distribution power system limits the real-time applications. To mitigate this issue, a model-free based adaptive optimal control scheme for the smart inverter is proposed to maximize the active power generation, minimize the power loss, and maintain the bus voltages in smart distribution networks. An inverter-based optimization model for coordinated operation is first established, considering the uncertainties of renewable power generation. Subsequently, by collecting the data and control strategies, the neural networks (NNs) based algorithm is proposed to efficiently predict the best possible control strategy. The main objective of this scheme is to accurately predict candidate optimal solutions with near-negligible feasibility and optimization gaps, with the advantage of avoiding complicated iteration-based numerical algorithms. Thereafter, the co-simulation among OpenDSS, MATLAB, and Python is set up to fully take advantage of the three individual software. Experiments are conducted based on different control parameter characteristics and structures of NNs. Finally, the results reveal that an average mean squared error of 0.013 and 1 ms response time are achieved, which is lower than some state-of-the-art methods.

42 ENGINEERING↗
DOE OSTI2020

BEEAM (Building Electrical Efficiency Analysis Model) [SWR-20-107]

Modern high-performance buildings exhibit an increasing number of building loads that use direct current (DC) electricity internally, rather than alternating current (AC), due to the advent of low-cost computing and advanced power electronics. Powering DC devices from the AC grid requires AC/DC power conversion, which introduces energy losses and reduces efficiency. As DC loads proliferate, the cumulative wasted energy associated with hundreds of millions of AC/DC converters has become one of the broadest energy savings opportunities in buildings. DC power distribution systems have been proposed as an elegant and transformative solution to the problem of DC devices. In a DC distribution system, the building's wires carry DC electricity, rather than AC; and a few centralized, highly efficient AC/DC converters replace the many smaller, less efficient converters that serve individual DC loads. Unfortunately, the trade-offs associated with DC distribution systems are not well understood. Reported energy savings associated with DC power distribution differ widely and have not been well validated. The Building Electrical Efficiency Analysis Model (BEEAM) is a Modelica library that simulates the efficiency of building electrical distribution systems using harmonic power flow. BEEAM can model a wide variety of building distribution topologies, including three-phase AC, single-phase AC, unipolar DC, bipolar DC, and hybrid networks under both balanced and unbalanced load conditions. BEEAM accurately models power electronic converter losses, provides granular estimates of losses throughout the distribution system, and properly models efficiency at part load conditions. Users can package BEEAM within a functional mockup unit (FMU), enabling co-simulation with other modeling platform, such as EnergyPlus. In summary, BEEAM provides a tool suite for fair and accurate comparison of the efficiency of building electrical distribution systems, including AC, DC, and hybrid systems.

Frank, Stephen↗
NASA NTRS2001

Challenges Facing Design and Analysis Tools

The design and analysis of future aerospace systems will strongly rely on advanced engineering analysis tools used in combination with risk mitigation procedures. The implications of such a trend place increased demands on these tools to assess off-nominal conditions, residual strength, damage propagation, and extreme loading conditions in order to understand and quantify these effects as they affect mission success. Advances in computer hardware such as CPU processing speed, memory, secondary storage, and visualization provide significant resources for the engineer to exploit in engineering design. The challenges facing design and analysis tools fall into three primary areas. The first area involves mechanics needs such as constitutive modeling, contact and penetration simulation, crack growth prediction, damage initiation and progression prediction, transient dynamics and deployment simulations, and solution algorithms. The second area involves computational needs such as fast, robust solvers, adaptivity for model and solution strategies, control processes for concurrent, distributed computing for uncertainty assessments, and immersive technology. Traditional finite element codes still require fast direct solvers which when coupled to current CPU power enables new insight as a result of high-fidelity modeling. The third area involves decision making by the analyst. This area involves the integration and interrogation of vast amounts of information - some global in character while local details are critical and often drive the design. The proposed presentation will describe and illustrate these areas using composite structures, energy-absorbing structures, and inflatable space structures. While certain engineering approximations within the finite element model may be adequate for global response prediction, they generally are inadequate in a design setting or when local response prediction is critical. Pitfalls to be avoided and trends for emerging analysis tools will be described.

Knight, Norman F., Jr.↗