LOADS@NASA" Leading Outstanding Aerospace Loads & Dynamics Solutions
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Dexter Johnson↗
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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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Distribution of SLS Integrated Load Uncertainty to Surface Pressures and Sectional Loads
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SLS↗
X-57 Maxwell Structural Loads Requirements Loads Analysis for Cruise Nacelle Structure
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Wesley Li↗
Design Load Case (DLC) Generator: Web-based tool to determine IEC 62600-2 standard design load requirements.
Abstract not provided.
Neary, Vincent Sinclair↗
Assessment of New Load Schedules for the Machine Calibration of a Force Balance
New load schedules for the machine calibration of a six-component force balance are currently being developed and evaluated at the NASA Ames Balance Calibration Laboratory. One of the proposed load schedules is discussed in the paper. It has a total of 2082 points that are distributed across 16 load series. Several criteria were applied to define the load schedule. It was decided, for example, to specify the calibration load set in force balance format as this approach greatly simplifies the definition of the lower and upper bounds of the load schedule. In addition, all loads are assumed to be applied in a calibration machine by using the one-factor-at-a-time approach. At first, all single-component loads are applied in six load series. Then, three two-component load series are applied. They consist of the load pairs (N1, N2), (S1, S2), and (RM, AF). Afterwards, four three-component load series are applied. They consist of the combinations (N1, N2, AF), (S1, S2, AF), (N1, N2, RM), and (S1, S2, RM). In the next step, one four-component load series is applied. It is the load combination (N1, N2, S1, S2). Finally, two five-component load series are applied. They are the load combination (N1, N2, S1, S2, AF) and (N1, N2, S1, S2, RM). The maximum difference between loads of two subsequent data points of the load schedule is limited to 33 % of capacity. This constraint helps avoid unwanted load "jumps" in the load schedule that can have a negative impact on the performance of a calibration machine. Only loadings of the single- and two-component load series are loaded to 100 % of capacity. This approach was selected because it keeps the total number of calibration points to a reasonable limit while still allowing for the application of some of the more complex load combinations. Data from two of NASA's force balances is used to illustrate important characteristics of the proposed 2082-point calibration load schedule.
wind tunnel testing↗
Crane-Load Contact Sensor
An electronic instrument has been developed as a prototype of a portable crane-load contact sensor. Such a sensor could be helpful in an application in which the load rests on a base in a horizontal position determined by vertical alignment pins (see Figure 1). If the crane is not positioned to lift the load precisely vertically, then the load can be expected to swing once it has been lifted clear of the pins. If the load is especially heavy, large, and/or fragile, it could hurt workers and/or damage itself and nearby objects. By indicating whether the load remains in contact with the pins when it has been lifted a fraction of the length of the pins, the crane-load contact sensor helps the crane operator determine whether it is safe to lift the load clear of the pins: If there is contact, then the load is resting against the sides of the pins and, hence, it may not be safe to lift; if contact is occasionally broken, then the load is probably not resting against the pins, so it should be safe to lift. It is assumed that the load and base, or at least the pins and the surfaces of the alignment holes in the load, are electrically conductive, so the instrument can use electrical contact to indicate mechanical contact. However, DC resistance cannot be used as an indicator of contact for the following reasons: The load and the base are both electrically grounded through cables (the load is grounded through the lifting cable of the crane) to prevent discharge of static electricity. In other words, the DC resistance between the load and the pins is always low, as though they were always in direct contact. Therefore, instead of DC resistance, the instrument utilizes the AC electrical impedance between the pins and the load. The signal frequency used in the measurement is high enough (.1 MHz) that the impedance contributed by the cables and the electrical ground network of the building in which the crane and the base are situated is significantly greater than the contact impedance between the pins and the load. The instrument includes a signal generator and voltage-measuring circuitry, and is connected to the load and the base as shown in Figure 2. The output of the signal generator (typically having amplitude of the order of a volt) is applied to the load via a 50-resistor, and the voltage between the load and the pins is measured. When the load and the pins are not in contact, the impedance between them is relatively high, causing the measured voltage to exceed a threshold value. When the load and the pins are in contact, the impedance between them falls to a much lower value, causing the voltage to fall below the threshold value. The voltage-measuring circuitry turns on a red light-emitting diode (LED) to indicate the lower-voltage/ contact condition. Whenever the contact has been broken and the non-contact/higher-voltage condition has lasted for more than 2 ms, the voltage-measuring circuitry indicates this condition by blinking a green LED.
Youngquist, Robert↗
IM3 + EPRI Data Center Load Projections
This dataset contains scenarios of hourly total electricity demand with and without projected loads from data centers over the period 2022-2040. The root projections without data center demands are identical to those documented in Burleyson et al. 2024. In short, those projections encompass hourly electricity demands for 54 Balancing Authorities (BAs) in the United States across a range of eight of weather and socioeconomic scenarios. Refer to the root dataset and accompanying publication, Burleyson et al. 2025, for information about how those projections were generated. For this derivative dataset we used the base loads from the following scenarios: rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 The root load projections did not reflect the drastic expansion of data centers that has occurred in the last several years to support artificial intelligence and cloud computing. To reflect growth in data center demand, a second set of load projections were created in which we layered in additional data center load projections based on the data center load growth scenarios described in a 2024 report by the Electric Power Research Institute (EPRI): "Powering Intelligence: Analyzing Artificial Intelligence and Data Center Energy Consumption". The EPRI projections from the report are included in this dataset (EPRI_2024_Projections.xlsx). That report contained annual state-level data center load projections for four year-over-year growth rates for data center demands: Low (3.71% annual growth) Moderate (5% annual growth) High (10% annual growth) Higher (15% annual growth) To homogenize the load projections with and without data centers we had to get them to a common scale. The first step was to take the EPRI annual state-level data center energy consumption values and convert them to 8760-hr loads for each year. We did that by assuming a flat (e.g., not weather- or time-sensitive) load profile and distributing the data center loads in each state evenly across all hours in a year. From there the loads were downscaled from the state-level to the county-level using 2019 county-level populations as weights. Finally, the county-level hourly data center loads were summed to the BA-level using the county-to-BA mapping underpinning the root load projections. The net result is 16 (4 weather and socioeconomic scenarios crossed with 4 data center load growth scenarios) unique load projections for the period 2022-2040. The file format follows that of the root dataset with a single additional column "Scaled_TELL_BA_Load_with_DC_MWh" that contains the hourly loads with the added data center loads for a given BA-year-scenario combination. Please refer to the readme file in the root dataset for more information on the file format.
Burleyson, Casey [Pacific Northwest National Labor↗
Strain Gage Load Calibration of the Wing Interface Fittings for the Adaptive Compliant Trailing Edge Flap Flight Test
The safety-of-flight parameters for the Adaptive Compliant Trailing Edge (ACTE) flap experiment require that flap-to-wing interface loads be sensed and monitored in real time to ensure that the structural load limits of the wing are not exceeded. This paper discusses the strain gage load calibration testing and load equation derivation methodology for the ACTE interface fittings. Both the left and right wing flap interfaces were monitored; each contained four uniquely designed and instrumented flap interface fittings. The interface hardware design and instrumentation layout are discussed. Twenty-one applied test load cases were developed using the predicted in-flight loads. Pre-test predictions of strain gage responses were produced using finite element method models of the interface fittings. Predicted and measured test strains are presented. A load testing rig and three hydraulic jacks were used to apply combinations of shear, bending, and axial loads to the interface fittings. Hardware deflections under load were measured using photogrammetry and transducers. Due to deflections in the interface fitting hardware and test rig, finite element model techniques were used to calculate the reaction loads throughout the applied load range, taking into account the elastically-deformed geometry. The primary load equations were selected based on multiple calibration metrics. An independent set of validation cases was used to validate each derived equation. The 2-sigma residual errors for the shear loads were less than eight percent of the full-scale calibration load; the 2-sigma residual errors for the bending moment loads were less than three percent of the full-scale calibration load. The derived load equations for shear, bending, and axial loads are presented, with the calculated errors for both the calibration cases and the independent validation load cases.
Miller, Eric J.↗
A Data-Driven Pivot-Point-Based Time-Series Feeder Load Disaggregation Method
The load profile at a feeder-head is usually known to utility engineers while the nodal load profiles are not. However, the nodal load profiles are increasingly important for conducting time-series analysis in distribution systems. Therefore, in this paper, we present a pivot-point based, two-stage feeder load disaggregation algorithm using smart meter data. The two stages are load profile selection (LPS) and load profile allocation (LPA). In the LPS stage, a random load profile selection process is first executed to meet the load diversity requirement. Then, a few pairs of pivot points are selected as the matching targets. After that, a matching algorithm will run repetitively to select one load profile at a time for matching the reference load profile at the pivot points. In the LPA stage, the LPS selected load profiles are allocated to each load node on the feeder considering distribution transformer loading limits, load composition, and square-footage. The proposed method is validated using actual data collected in a North Carolina service area. Finally, simulation results show that the proposed method can generate a unique load shape for each load node while match the shape of their aggregated profile with the actual feeder head load profile.
42 ENGINEERING↗
Evaluation of the Hinge Moment and Normal Force Aerodynamic Loads from a Seamless Adaptive Compliant Trailing Edge Flap in Flight
A seamless adaptive compliant trailing edge (ACTE) flap was demonstrated in flight on a Gulfstream III aircraft at the NASA Armstrong Flight Research Center. The trailing edge flap was deflected between minus 2 deg up and plus 30 deg down in flight. The safety-of-flight parameters for the ACTE flap experiment require that flap-to-wing interface loads be sensed and monitored in real time to ensure that the structural load limits of the wing are not exceeded. The attachment fittings connecting the flap to the aircraft wing rear spar were instrumented with strain gages and calibrated using known loads for measuring hinge moment and normal force loads in flight. The safety-of-flight parameters for the ACTE flap experiment require that flap-to-wing interface loads be sensed and monitored in real time to ensure that the structural load limits of the wing are not exceeded. The attachment fittings connecting the flap to the aircraft wing rear spar were instrumented with strain gages and calibrated using known loads for measuring hinge moment and normal force loads in flight. The interface hardware instrumentation layout and load calibration are discussed. Twenty-one applied calibration test load cases were developed for each individual fitting. The 2-sigma residual errors for the hinge moment was calculated to be 2.4 percent, and for normal force was calculated to be 7.3 percent. The hinge moment and normal force generated by the ACTE flap with a hinge point located at 26-percent wing chord were measured during steady state and symmetric pitch maneuvers. The loads predicted from analysis were compared to the loads observed in flight. The hinge moment loads showed good agreement with the flight loads while the normal force loads calculated from analysis were over-predicted by approximately 20 percent. Normal force and hinge moment loads calculated from the pressure sensors located on the ACTE showed good agreement with the loads calculated from the installed strain gages.
Hinge Moment Loads↗
Net Load Forecasting With Disaggregated Behind-the-Meter PV Generation
As worldwide use of residential photovoltaic (PV) systems grows, system operators and utilities will need to transition from forecasting pure demand to forecasting net load with behind-the-meter (BTM) PV generation. However, PV generation can be difficult to predict and the measurements of PV generation from BTM residential systems are often invisible behind a measurement of the net load, making net load forecasting challenging. This paper proposes a novel two-stage framework for net load forecasting in areas with limited observability and high BTM PV generation. First, the profiles of observable customers are used to disaggregate the net load measurements into the pure load and PV generation. Then, separate models are used to forecast the PV generation and pure load individually, and the results are combined for a net load forecast. Further, this paper also proposes a compensator for correcting the error of the net load forecast, using historical forecast errors of the PV generation, pure load, and net load. The proposed framework is tested through two case studies for areas with high BTM PV penetration and less than 10% observable customers. The two-stage forecasting model is compared to two benchmark methods - a time series forecasting model, and a model that forecasts the net load directly using historical net load measurements. Results show that the proposed disaggregation-forecasting framework reduces the error of the net load forecast compared to both benchmark models. In addition, when the net load forecast error is periodic, the compensator can correct the error to improve the forecast accuracy.
14 SOLAR ENERGY↗
Composite load spectra for select space propulsion structural components
The objective of this program is to develop generic load models with multiple levels of progressive sophistication to simulate the composite load spectra that are induced in space propulsion system components, representative of Space Shuttle Main Engines (SSME), such as transfer ducts, turbine blades, and liquid oxygen (LOX) posts and system ducting. These models will be developed using two independent approaches. The first approach consists of using state-of-the-art probabilistic methods to describe the individual loading conditions and combinations of these loading conditions to synthesize the composite load spectra simulation. The methodology required to combine the various individual load simulation models (hot-gas dynamic, vibrations, instantaneous position, centrifugal field, etc.) into composite load spectra simulation models will be developed under this program. A computer code incorporating the various individual and composite load spectra models will be developed to construct the specific load model desired. The second approach, which is covered under the options portion of the contract, will consist of developing coupled models for composite load spectra simulation which combine the (deterministic) models for composite load dynamic, acoustic, high-pressure and high rotational speed, etc., load simulation using statistically varying coefficients. These coefficients will then be determined using advanced probabilistic simulation methods with and without strategically selected experimental data. This report covers the efforts of the third year of the contract. The overall program status is that the turbine blade loads have been completed and implemented. The transfer duct loads are defined and are being implemented. The thermal loads for all components are defined and coding is being developed. A dynamic pressure load model is under development. The parallel work on the probabilistic methodology is essentially completed. The overall effort is being integrated in an expert system code specifically developed for this project.
Newell, J. F.↗
Maximizing TDRS Command Load Lifetime
The GNC software onboard ISS utilizes TORS command loads, and a simplistic model of TORS orbital motion to generate onboard TORS state vectors. Each TORS command load contains five "invariant" orbital elements which serve as inputs to the onboard propagation algorithm. These elements include semi-major axis, inclination, time of last ascending node crossing, right ascension of ascending node, and mean motion. Running parallel to the onboard software is the TORS Command Builder Tool application, located in the JSC Mission Control Center. The TORS Command Builder Tool is responsible for building the TORS command loads using a ground TORS state vector, mirroring the onboard propagation algorithm, and assessing the fidelity of current TORS command loads onboard ISS. The tool works by extracting a ground state vector at a given time from a current TORS ephemeris, and then calculating the corresponding "onboard" TORS state vector at the same time using the current onboard TORS command load. The tool then performs a comparison between these two vectors and displays the relative differences in the command builder tool GUI. If the RSS position difference between these two vectors exceeds the tolerable lim its, a new command load is built using the ground state vector and uplinked to ISS. A command load's lifetime is therefore defined as the time from when a command load is built to the time the RSS position difference exceeds the tolerable limit. From the outset of TORS command load operations (STS-98), command load lifetime was limited to approximately one week due to the simplicity of both the onboard propagation algorithm, and the algorithm used by the command builder tool to generate the invariant orbital elements. It was soon desired to extend command load lifetime in order to minimize potential risk due to frequent ISS commanding. Initial studies indicated that command load lifetime was most sensitive to changes in mean motion. Finding a suitable value for mean motion was therefore the key to achieving this goal. This goal was eventually realized through development of an Excel spreadsheet tool called EMMIE (Excel Mean Motion Interactive Estimation). EMMIE utilizes ground ephemeris nodal data to perform a least-squares fit to inferred mean anomaly as a function of time, thus generating an initial estimate for mean motion. This mean motion in turn drives a plot of estimated downtrack position difference versus time. The user can then manually iterate the mean motion, and determine an optimal value that will maximize command load lifetime. Once this optimal value is determined, the mean motion initially calculated by the command builder tool is overwritten with the new optimal value, and the command load is built for uplink to ISS. EMMIE also provides the capability for command load lifetime to be tracked through multiple TORS ephemeris updates. Using EMMIE, TORS command load lifetimes of approximately 30 days have been achieved.
Brown, Aaron J.↗
Multiplexer/Demultiplexer Loading Tool (MDMLT)
The purpose of the MDMLT is to improve the reliability and speed of loading multiplexers/demultiplexers (MDMs) in the Software Development and Integration Laboratory (SDIL) by automating the configuration management (CM) of the loads in the MDMs, automating the loading procedure, and providing the capability to load multiple or all MDMs concurrently. This loading may be accomplished in parallel, or single MDMs (remote). The MDMLT is a Web-based tool that is capable of loading the entire International Space Station (ISS) MDM configuration in parallel. It is able to load Flight Equivalent Units (FEUs), enhanced, standard, and prototype MDMs as well as both EEPROM (Electrically Erasable Programmable Read-Only Memory) and SSMMU (Solid State Mass Memory Unit) (MASS Memory). This software has extensive configuration management to track loading history, and the performance improvement means of loading the entire ISS MDM configuration of 49 MDMs in approximately 30 minutes, as opposed to 36 hours, which is what it took previously utilizing the flight method of S-Band uplink. The laptop version recently added to the MDMLT suite allows remote lab loading with the CM of information entered into a common database when it is reconnected to the network. This allows the program to reconfigure the test rigs quickly between shifts, allowing the lab to support a variety of onboard configurations during a single day, based on upcoming or current missions. The MDMLT Computer Software Configuration Item (CSCI) supports a Web-based command and control interface to the user. An interface to the SDIL File Transfer Protocol (FTP) server is supported to import Integrated Flight Loads (IFLs) and Internal Product Release Notes (IPRNs) into the database. An interface to the Monitor and Control System (MCS) is supported to control the power state, and to enable or disable the debug port of the MDMs to be loaded. Two direct interfaces to the MDM are supported: a serial interface (debug port) to receive MDM memory dump data and the calculated checksum, and the Small Computer System Interface (SCSI) to transfer load files to MDMs with hard disks. File transfer from the MDM Loading Tool to EEPROM within the MDM is performed via the MILSTD- 1553 bus, making use of the Real- Time Input/Output Processors (RTIOP) when using the rig-based MDMLT, and via a bus box when using the laptop MDMLT. The bus box is a cost-effective alternative to PC-1553 cards for the laptop. It is noted that this system can be modified and adapted to any avionic laboratory for spacecraft computer loading, ship avionics, or aircraft avionics where multiple configurations and strong configuration management of software/firmware loads are required.
Brewer, Lenox Allen↗
Optimal load attachment of a deeply embedded ring anchor in clay
A Deeply Embedded Ring Anchor (DERA) system has been developed as a cost-effective solution for mooring arrays of floating offshore wind turbines (FOWTs) to the seabed. The DERA boasts several key features, including its versatility in various soil types, compact size, compatibility with diverse mooring systems, multi-line potential, and robust performance even under unintentional loading conditions. While prior preliminary studies have provided valuable insights into how the DERA can enhance cost-effectiveness by offering a high load capacity, these studies have predominantly focused on optimizing anchor performance under translational horizontal and vertical loading. However, to design the DERA optimally, we must also consider its ability to handle inclined loading conditions in addition to lateral and axial loadings. Due to its shorter length compared to a conventional caisson, the DERA has less resistance to moments, making it more sensitive to horizontal load capacity and the optimal load attachment depth concerning load angle. For this reason, our study introduces an analytical approach to evaluate the effects of inclined loading on anchor performance, utilizing the previously validated upper bound plastic limit analysis (PLA) method. In investigating the optimal load attachment of the DERA, this paper conducts a parametric study to analyze how factors such as load attachment depth, anchor aspect ratio, and load inclination affect the DERA’s load capacity. Our findings indicate that PLA can serve as a valuable analytical tool for assessing the ultimate load capacity of the DERA, particularly under inclined loading conditions.
42 ENGINEERING↗
The composite load spectra project
Probabilistic methods and generic load models capable of simulating the load spectra that are induced in space propulsion system components are being developed. Four engine component types (the transfer ducts, the turbine blades, the liquid oxygen posts and the turbopump oxidizer discharge duct) were selected as representative hardware examples. The composite load spectra that simulate the probabilistic loads for these components are typically used as the input loads for a probabilistic structural analysis. The knowledge-based system approach used for the composite load spectra project provides an ideal environment for incremental development. The intelligent database paradigm employed in developing the expert system provides a smooth coupling between the numerical processing and the symbolic (information) processing. Large volumes of engine load information and engineering data are stored in database format and managed by a database management system. Numerical procedures for probabilistic load simulation and database management functions are controlled by rule modules. Rules were hard-wired as decision trees into rule modules to perform process control tasks. There are modules to retrieve load information and models. There are modules to select loads and models to carry out quick load calculations or make an input file for full duty-cycle time dependent load simulation. The composite load spectra load expert system implemented today is capable of performing intelligent rocket engine load spectra simulation. Further development of the expert system will provide tutorial capability for users to learn from it.
Newell, J. F.↗