SEARCH · Engineering Papers
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.
This is an evaluation of composite materials for heliostat cost reduction, including the motivation, reference heliostat model, characteristic wind loads, selection of pultruded structural composites, and technoeconomic analysis using equivalent deformation.
The National Renewable Energy Laboratory's OpenFAST software is utilized by academics and industry professionals alike to simulate offshore wind turbines. The software's modeling of hydrodynamic loads on heave plates attached to these structures relies on user specified hydrodynamic coefficients. To guide the proper selection of these coefficients and potentially develop a new functionality within OpenFAST that automatically prescribes and/or adjust the heave-plate hydrodynamic coefficients, this paper reviews past literature to examine the dependence of the added mass, damping, and drag coefficients on various relevant non-dimensional parameters, including the Keulegan-Carpenter number, the frequency parameter, and the plate thickness ratio. Existing data in the literature show strong dependence of the hydrodynamic coefficients on the Keulegan-Carpenter number. Consistent trends are observed across a range of different plate geometry, plate porosity, and flow conditions. Secondary dependence of the coefficients on the frequency parameter and plate thickness ratio is also present.
The U.S. grid is rapidly transitioning towards utilizing inverter-based renewable energy resources such as solar, wind, and batteries, reducing the carbon emission footprint.Inverter-based microgrid control architectures remain a critical focus to address power system stability issues in future high penetration markets lacking spinning generation assets. Idaho National Laboratory (INL) is researching an active layered inverter based frequency-Watt control scheme that provides distribution level stability in high-penetration markets where grid inertia is lacking. Hardware in the loop case study was implemented using INL’s Microgrid Testbed to combat scalable frequency deviations ranging from 60 Hz down to 50 Hz initialized by a hydropower model implementing step loads using a 540-kW grid emulator. Our research findings demonstrate the importance of distribution level, inverter-based active frequency-Watt controls utilizing a battery energy storage system (BESS) to provide adequate frequency support at the point of common coupling without major power infrastructure upgrades.
At the University of Puerto Rico at Rio Piedras, a central chilled water plant supplies cooling to several campus buildings, contributing significantly to electricity demand during daytime peak hours, particularly in the summer months. These operational challenges are exacerbated by Puerto Rico's tropical rainforest climate and a power grid vulnerable to frequent disruptions caused by hurricanes and tropical storms. This study presents a techno-economic analysis of the existing chilled water plant serving four representative campus buildings and introduces a conceptual alternative: the Geologically connected Seawater Air Conditioning (GeoSWAC) system. GeoSWAC leverages stable low temperatures of deep ocean water (~1 km depth), hydraulically connected to an inland well, to deliver cooling without the use of vapor-compression refrigeration. Using modeled annual cooling loads and chiller performance data, capital costs, energy consumption, and levelized cost of cooling (LCOC) were evaluated for both systems. While GeoSWAC showed higher capital costs than the chiller-based scenario, operational costs were significantly lower at $26k-$53k annually, resulting in a lower LCOC between $2.3/MWh and $8.2/MWh compared to $30.2/MWh-$33.6/MWh for the chiller scenario. These results suggest that the GeoSWAC system offers a promising, low-energy, and climate-resilient alternative for large-scale cooling in tropical coastal environments, with significant potential to reduce peak electricity demand and improve long-term system reliability.
The buckling and postbuckling behavior of two composite tow-steered shells with cutouts of different sizes is assessed using nonlinear finite element (FE) analysis and compared to experimental measurements. The cylindrical shells are manufactured using an automated fiber placement system, where the shells’ fiber orientation angles vary continuously around the shell circumference from ±10 degrees on the crown and keel to ±45 degrees on the sides. One shell features thickness variations due to tow overlaps that result from application of all 24 tows during each pass of the fiber placement system. The second shell uses the system’s tow drop/add capability to achieve a more uniform wall thickness without overlaps. Unreinforced cutouts of two different sizes—the first smaller cutout representing a passenger door on a commercial aircraft and the second larger cutout a cargo door—were machined into each of the two cylinders resulting in a total of four test cases. These cylinders were tested in axial compression and buckled elastically in previous work and are now analyzed using nonlinear FE models to compare bifurcation buckling loads as well as the load-displacement response in the prebuckling and postbuckling regimes. For all four shells analyzed, the prebuckling stiffness, buckling load, and deformation mode sequence throughout the loading-unloading cycle is accurately reproduced by the models. In particular, the shells first buckle locally around the cutouts in a stable (super-critical) manner with only a slight decrease in axial stiffness, which occurs due to the favorable load redistribution facilitated by tow steering. The shells then buckle globally in an unstable (sub-critical) manner with diamond-shaped buckles forming to the left and right of the cutouts. The buckling load of all shells with cutouts is at least 82% of the buckling load of the pristine shells without cutouts. Overall, the ability to sustain local buckling phenomena, and the relatively small reductions in global buckling load compared to pristine shells without cutouts, demonstrates the great potential of using tow steering to mitigate the adverse effects of cutouts in axially-compressed shell structures.
The buckling and postbuckling behavior of two composite tow-steered shells with cutouts of different sizes is assessed using nonlinear finite element (FE) analysis and compared to experimental measurements. The cylindrical shells are manufactured using an automated fiber placement system, where the shells’ fiber orientation angles vary continuously around the shell circumference from 10 degrees on the crown and keel to 45 degrees on the sides. One shell features thickness variations due to tow overlaps that result from application of all 24 tows during each pass of the fiber placement system. The second shell uses the system’s tow drop/add capability to achieve a more uniform wall thickness without overlaps. Unreinforced cutouts of two different sizes—the first smaller cutout representing a passenger door on a commercial aircraft and the second larger cutout a cargo door—were machined into each of the two cylinders resulting in a total of four test cases. These cylinders were tested in axial compression and buckled elastically in previous work and are now analyzed using nonlinear FE models to compare bifurcation buckling loads as well as the load-displacement response in the prebuckling and postbuckling regimes. For all four shells analyzed, the prebuckling stiffness, buckling load, and deformation mode sequence throughout the loading-unloading cycle is accurately reproduced by the models. In particular, the shells first buckle locally around the cutouts in a stable (super-critical) manner with only a slight decrease in axial stiffness, which occurs due to the favorable load redistribution facilitated by tow steering. The shells then buckle globally in an unstable (sub-critical) manner with diamond-shaped buckles forming to the left and right of the cutouts. The buckling load of all shells with cutouts is at least 82% of the buckling load of the pristine shells without cutouts. Overall, the ability to sustain local buckling phenomena, and the relatively small reductions in global buckling load compared to pristine shells without cutouts, demonstrates the great potential of using tow steering to mitigate the adverse effects of cutouts in axially-compressed shell structures.
A conceptual model (CM) can be used to validate a concept in modeling and simulation life cycles. During the 2020-2022 Coronavirus disease 2019 (COVID-19) pandemic, for employee safety NASA implemented center closures and mandatory telework for the entire workforce. During this challenging time, engineers and researchers at NASA Langley Research Center (LaRC) looked for safe and innovative approaches and methods to continue the development of CMs for various projects. Engineers and researchers at LaRC researched Auto-Rigging Payload Handling and Off-Loading System (ARPHOLS) for payload handing and off-loading a system on an inclined lunar lander deck. In this paper, the development of a CM and the verification and validation of a conceptual idea for ARPHOLS using a LEGO Technic system and three-dimensional printed parts is presented.
Residential loads, especially heating, ventilation and air conditioners (HVACs) and electric vehicles (EVs), have great potentials to provide demand flexibility which is an attribute of grid-interactive efficient buildings (GEB). Under this new paradigm, first, EV and HVAC aggregator models are developed in this paper to represent the fleet of GEBs, in which the aggregated parameters are obtained based on a new approach of data generation and least squares parameter estimation (DG-LSPE), which can deal with heterogeneous HVACs. Then, a tri-level bidding and dispatching framework is established based on competitive distribution operation with distribution locational marginal price (DLMP). Furthermore, the first two levels form a bilevel model to optimize the aggregators’ payment and to represent the interdependency between load aggregators and the distribution system operator (DSO) using DLMP, and the third level is to dispatch the optimal load aggregation to all residents by the proposed priority list-based demand dispatching algorithm. Finally, case studies on a modified IEEE 33-Bus system illustrate three main technical reasons of payment reduction due to demand flexibility: load shift, DLMP step changes, and power losses. They can be used as general guidelines for better decision-making for future planning and operation of demand response programs.
A new damage model based on a micromechanical analysis of cracked [+/- Theta/90n]s laminates subjected to multiaxial loads is proposed. The model predicts the onset and accumulation of transverse matrix cracks in uniformly stressed laminates, the effect of matrix cracks on the stiffness of the laminate, as well as the ultimate failure of the laminate. The model also accounts for the effect of the ply thickness on the ply strength. Predictions relating the elastic properties of several laminates and multiaxial loads are presented.
Utilizing a continuous beam model, this report compares the potential stresses imposed on the beam from a random environment with those resulting from a typical static load analysis or test simulation. The Miles' equation used to develop peak response accelerations is shown to become a force equation in the hands of strength assessment personnel. This may prove to be unrealistic since hardware dynamic stresses are related to deflection rather than load. Correlation of the stress state for any static analysis or test with the actual dynamic response stress is strictly dependent upon how well the static deflections simulate the predominant dynamic mode shape. The report proposes that the general shape of this predominant mode, along with the peak response accelerations of major masses be used in strength assessments. From these data, a tailored enforced displacement loading may prove to be more effective in reproducing random induced stresses on flight hardware.
The first results for applying a three-dimensional multimedia ideal MHD model for the mass-loaded flow of Jupiter's corotating magnetospheric plasma past Io are presented. The model is able to consider simultaneously physically realistic conditions for ion mass loading, ion-neutral drag, and intrinsic magnetic field in a full global calculation without imposing artificial dissipation. Io is modeled with an extended neutral atmosphere which loads the corotating plasma torus flow with mass, momentum, and energy. The governing equations are solved using adaptive mesh refinement on an unstructured Cartesian grid using an upwind scheme for AHMED. For the work described in this paper we explored a range of models without an intrinsic magnetic field for Io. We compare our results with particle and field measurements made during the December 7, 1995, flyby of to, as published by the Galileo Orbiter experiment teams. For two extreme cases of lower boundary conditions at Io, our model can quantitatively explain the variation of density along the spacecraft trajectory and can reproduce the general appearance of the variations of magnetic field and ion pressure and temperature. The net fresh ion mass-loading rates are in the range of approximately 300-650 kg/s, and equivalent charge exchange mass-loading rates are in the range approximately 540-1150 kg/s in the vicinity of Io.
Electrification of transport compounded with climate change will transform hourly load profiles and their response to weather. We present a novel approach to generating hourly electric load profiles that considers charging strategies and evolving sensitivity to temperature. The approach consists of downscaling annual state-scale sectoral load projections from the multisectoral Global Change Analysis Model (GCAM) into hourly electric load profiles leveraging high resolution climate and population datasets. Profiles are developed and evaluated at the Balancing Authority scale, with a 5-year increment until 2050 over the Western U.S. Interconnect for multiple decarbonization pathways and climate scenarios. The datasets are readily available for production cost model analysis. Our open source approach is transferable to other regions.
The paper discusses the potential effects on the ozone layer of gases released by the engines of proposed high altitude supersonic aircraft. The major problem arises from the emissions of nitrogen oxides which have the potential to destroy significant quantities of ozone in the stratosphere. The magnitude of the perturbation is highly dependent on the cruise altitude of the aircraft. Furthermore, the depletion of ozone is substantially reduced when heterogeneous conversion of nitrogen oxides into nitric acid on sulfate aerosol particles is taken into account in the calculation. The sensitivity of the aerosol load on stratospheric ozone is investigated. First, the model indicates that the aerosol load induced by the SO2 released by aircraft is increased by about 10-20% above the background aerosols at mid-high latitude of the Northern Hemisphere at 15 km for the NASA emission scenario A (the NASA emission scenarios are explained in Tables I to III). This increase in aerosol has small effects on stratospheric ozone. Second, when the aerosol load is increased following a volcanic eruption similar to the eruption of El Chichon (Mexico, April 1982), the ozone column in spring increases by as much as 9% in response to the injection of NOx from the aircraft with the NASA emission scenario A. Finally, the modeled suggests that significant ozone depletion could result from the formation of additional polar stratospheric clouds produced by the injection of H2O and HNO3 by the aircraft engines.
A new model for local fiber failures in composite materials loaded longitudinally is presented. In developing the model, the goal was to account for the effects of fiber breakage on the global response of a composite in a relatively simple and efficient manner. Towards this end, the model includes the important feature of local stress unloading, even as global loading of the composite continues. The model has been incorporated into NASA Glenn's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) and was employed to simulate the longitudinal tensile deformation and failure behavior of several silicon carbide fiber/titanium matrix (SiC/Ti) composites. The model is shown to be quite realistic and capable of accurate predictions for various temperatures, fiber volume fractions, and fiber diameters. Further- more, the new model compares favorably to Curtin's (1993) effective fiber breakage model, which has also been incorporated into MAC/GMC.
The TAILSIM program uses a 4th order Runge-Kutta method to integrate the standard aircraft equations-of-motion (EOM). The EOM determine three translational and three rotational accelerations about the aircraft's body axis reference system. The forces and moments that drive the EOM are determined from aerodynamic coefficients, dynamic derivatives, and control inputs. Values for these terms are determined from linear interpolation of tables that are a function of parameters such as angle-of-attack and surface deflections. Buildup equations combine these terms and dimensionalize them to generate the driving total forces and moments. Features that make TAILSIM applicable to studies of tailplane stall include modeling of the reversible control System, modeling of the pilot performing a load factor and/or airspeed command task, and modeling of vertical gusts. The reversible control system dynamics can be described as two hinged masses connected by a spring. resulting in a fifth order system. The pilot model is a standard form of lead-lag with a time delay applied to an integrated pitch rate and/or airspeed error feedback. The time delay is implemented by a Pade approximation, while the commanded pitch rate is determined by a commanded load factor. Vertical gust inputs include a single 1-cosine gust and a continuous NASA Dryden gust model. These dynamic models. coupled with the use of a nonlinear database, allow the tailplane stall characteristics, elevator response, and resulting aircraft response, to be modeled. A useful output capability of the TAILSIM program is the ability to display multiple post-run plot pages to allow a quick assessment of the time history response. There are 16 plot pages currently available to the user. Each plot page displays 9 parameters. Each parameter can also be displayed individually. on a one plot-per-page format. For a more refined display of the results the program can also create files of tabulated data. which can then be used by other plotting programs. The TAILSIM program was written straightforwardly assuming the user would want to change the database tables, the buildup equations, the output parameters. and the pilot model parameters. A separate database file and input file are automatically read in by the program. The use of an include file to set up all common blocks facilitates easy changing of parameter names and array sizes.
Data from a high-capacity semi-span balance is used to perform a detailed comparison of the load prediction accuracy of two strain-gage balance load prediction methods. Both methods independently obtain their load prediction equations from multivariate least squares fits of balance calibration data. The first method is called Non-Iterative Method. This approach directly uses regression models of the individual load components of a balance for the load prediction. The second method is called Iterative Method. This alternate approach uses a load iteration equation for the load prediction that is constructed from the regression models of the gage outputs of the balance. Basic characteristics of the two methods are reviewed. Afterwards, both methods are applied to calibration and check load data of the chosen balance. Finally, selected analysis results are compared. These comparisons confirmed that the load prediction accuracy of the two methods is the same for all practical purposes.
This repository contains the code and data necessary to run the FUN-BioCROP (Fixation and Uptake of Nitrogen-Bioenergy Carbon, Rhizosphere, Organisms, and Protection) model with litter decomposition parameters derived from a modified Monte Carlo simulation that used the Long-term Intersite Decomposition Experiment Team dataset. Related publication:Juice, S.M., Ridgeway, J.R., Hartman, M.D., Parton, W.J., Berardi, D.M., Sulman, B.N., Allen, K.E., & Brzostek, E.R. Reparameterizing litter decomposition using a simplified Monte Carlo method improves litter decay simulated by a microbial model and alters bioenergy soil carbon estimates. Description of Files: FUNBioCROP_LIDET Study.Rmd R code with FUN-BioCROP model that can be run with 10 different sets of parameters for litter decomposition (Baseline, LIDET, or eight other best parameter sets identified in the modified Monte Carlo simulation. CORPSE Functions_Bioenergy_V2.R Code with CORPSE model functions, called by FUNBioCROP_LIDET Study.Rmd Model Input Data: bulk.csv, bulk_till.csv, rhizo.csv, rhizo_till.csv, litter.csv Initial C and N (kg C or N/m2) pool values for each soil compartment, final values from spin up. All five files have the same columns: (Column - Description - Units) uFastC - Unprotected fast decomposing carbon - kg carbon/m2 uSlowC - Unprotected slow decomposing carbon - kg carbon/m2 uNecroC - Unprotected necromass carbon - kg carbon/m2 pFastC - Protected fast decomposing carbon - kg carbon/m2 pSlowC - Protected slow decomposing carbon - kg carbon/m2 pNecroC - Protected necromass carbon - kg carbon/m2 livingMicrobeC - Carbon in living microbial biomass - kg carbon/m2 uFastN - Unprotected fast decomposing nitrogen - kg nitrogen/m2 uSlowN - Unprotected slow decomposing nitrogen - kg nitrogen/m2 uNecroN - Unprotected necromass nitrogen - kg nitrogen/m2 pFastN - Protected fast decomposing nitrogen - kg nitrogen/m2 pSlowN - Protected slow decomposing nitrogen - kg nitrogen/m2 pNecroN - Protected necromass nitrogen - kg nitrogen/m2 inorganicN - Inorganic nitrogen - kg nitrogen/m2 CO2 - Carbon in carbon dioxide - kg carbon/m2 livingMicrobeN - Nitrogen in living microbial biomass - kg nitrogen/m2 Model Input Data: FluxTower_AvgSoilT.csv: Average daily soil temperature (oC) at 10 cm depth at University of Illinois Urbana-Champaign (UIUC) Energy Farm flux tower from 7/2008-3/2016. (One year of averaged data) Model Input Data: FluxTower_AvgSoilVWC.csv: Average daily soil volumetric water content (VWC) at 10 cm depth at UIUC Energy Farm flux tower from 7/2008-3/2016. (One year of averaged data) Model Input Data: input_CCS_LIDET Study.csv: This file has daily data to run FUN-BioCROP (Column - Description - Units): yr - calendar year - year doy - day of year (1 to 365) (no leap year) - day anpp - aboveground NPP (DayCent) - kg C/m2/day bnpp - belowground NPP (DayCent) - kg C/m2/day aglivc - live aboveground biomass carbon (DayCent) - kg C/m2 bglivcj - live juvenile fine root biomass carbon (DayCent) - kg C/m2 bglivcm - live mature fine root biomass carbon (DayCent) - kg C/m2 aglivn - live aboveground biomass nitrogen (DayCent) - kg N/m2 bglivnj - live juvenile fine root biomass nitrogen (DayCent) - kg N/m2 bglivnm - live mature fine root biomass nitrogen (DayCent) - kg N/m2 nyr - simulation year - year cult - indicates a cultivation event (0 or 1) crop - indicates a new crop (0 or 1) fert - indicates a fertilizer event (0 or 1) frst - indicates the first day of the growing season (0 or 1) harv - indicates a harvest event (0 or 1) last - indicates the end of the growing season (0 or 1) croptype - crop type (0=none; 1=alfalfa; 2=corn; 3=grass clover pasture; 4=soybean; 5=wheat) cropsrl - crop specific root length - mm/g root cultrhizmix - fraction of rhizosphere mixed with bulk soil during cultivation (0.0-1.0) - fraction cultlitmix - fraction of litter mixed with bulk soil during cultivation (0.0-1.0) - fraction harvremov - fraction of above ground biomass removed during harvest (0.0-1.0) - fraction fertamt - fertilization amount - g N/m2 lifehist - plant life history (0 = annual, 1 = perennial) froot_turnover_c - amount of C in fine root turnover - kg C/m2 froot_turnover_n - amount of N in fine root turnover - kg N/m2 agrd_turnover_c - amount of C in aboveground biomass turnover - kg C/m2 agrd_turnover_n - amount of N in aboveground biomass turnover - kg N/m2 leaf_litter_fastfrac - Fast decomposing fraction of leaf litter (0.0-1.0) - fraction root_litter_fastfrac - Fast decomposing fraction of root litter (0.0-1.0) - fraction root_diameter - root diameter - mm root_length - root length - mm root/m2 rhizo_frac - fraction of total soil volume that is rhizosphere (0.0 - 1.0) - fraction date - date in format YYYY-MM-DD Instructions: Save the model code ("FUN-BioCROP_LIDET Study.Rmd") and accompanything files (data streams and CORPSE function code) in the same folder. In model code "Chunk 3: Load CORPSE Data Streams" set the working directory (setwd) to the folder with the files saved in step #1. In "Chunk 5: Define LIDET parameter sets" select the litter decomposition parameter set to be used in the run, and comment out all other sets. If changing any parameter values, edit them in "Chunk 6: Load parameters." Run all chunks up to and including "Chunk 10: Prepare Data for Export." In "Chunk 11: Export Output Data" edit data frames for export and filenames, as necessary. "Chunk 12: Graph Total Soil C" makes a figure of C remaining over the model run period. Description of each model chunk (in file FUN-BioCROP_LIDET Study.Rmd): Chunk 1: Remove all functions, clear memory. Removes all functions from R environment, clears the memory. Chunk 2: Load Packages. Loads packages necessary to run the code. Chunk 3: Load CORPSE Data Streams. Sets the working directory and loads the data files necessary to run CORPSE. Chunk 4: Load CORPSE Functions. Loads the R script with CORPSE functions from the working directory, "CORPSE Functions_Bioenergy_V2.R". Chunk 5: Define LIDET parameter sets. Has ten different parameter sets for litter decomposition tested in this study: Baseline parameters, LIDET parameters, and the other 8 best performing parameter sets identified in the modified Monte Carlo. To run the model, all but one parameter set must be commented out. Chunk 6: Load Parameters. Loads all fixed parameters to run the model. Data frame with definitions of parameters is in the CORPSE function script "CORPSE Functions_Bioenergy_V2.R" Chunk 7: Prepare Data Streams. Takes data streams loaded in Chunk 3 and puts them in the format necessary to run the model. The model is coded to run at least two sites at a time, so if only one site is being run it must be run in duplicate. Individual data tables of daily values are created in this chunk from the input data file. Chunk 8: Set Initial Conditions. Creates data tables of soil C and N pools for each soil compartment (rhizo_till, rhizo, bulk_till, bulk, litter) and loads initial values into the data tables. Creates lists for each soil compartment to hold model output. Chunk 9: Load FUN Data and Set Up Matrices. Uses DayCent data to calculate FUN input data: root and leaf N demand, total N demand, plant CN, leaf N available for retranslocation, and litter production. Creates matrices for FUN model outputs. Chunk 10: Run Model. Runs the model. Chunk 11: Prepare Data for Export. Combines data from each day saved as lists into data frames for each soil compartment. Adds values from all soil compartments together to calculate total soil values, creates separate data frames for each soil C and N pool (e.g., protected slow C) for the total soil value. Adds different C and N pools together to calculate total soil C and N for all layers. Creates data frame of ratio of protected to unprotected SOC. Organizes FUN data for export. Chunk 12: Export Results. Exports CSV files of model results to the working directory. Chunk 13: Graph Total Soil C. Makes figure of C remaining over time. Related Links: Original FUN-BioCROP model: https://github.com/BrzostekEcologyLab/FUN-BioCROP LIDET dataset: https://andlter.forestry.oregonstate.edu/data/abstract.aspx?dbcode=TD023
An analytical model for calculation of ascent steady state tile loading was developed and validated with wind tunnel data. The analytical model is described and results are given. Results are given for loading due to shocks and skin friction. The analysis included calculation of internal flow (porous media flow and channel flow) to obtain pressures and integration of the pressures to obtain forces and moments on an insulation tile. A heat transfer program was modified by using analogies between heat transfer and fluid flow so that it could be used for internal flow calculation. The type of insulation tile considered was undensified reusable surface insulation (RSI) without gap fillers, and the location studied was the lower surface of the orbiter. Force and moment results are reported for parameter variations on surface pressure distribution, gap sizes, insulation permeability, and tile thickness.