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Analysis of vortex flow behind stationary and oscillating circular cylinders for application to prediction of ground wind loads on launch vehicles
Electricity load forecasting is essential to utility operation and power grid stability. A wide spectrum of data-driven methods, ranging from linear regression models to more recent deep learning models have been adopted to forecast electric load over the years. However, there still lacks a holistic evaluation of the applicability of conventional statistical and machine learning based algorithms with respect to different temporal and spatial scopes, computational requirements, and sensitivity of model-tuning. Enabled by a large-scale electricity load profile dataset of over 40,000 residential customers in a utility region, we conducted a cross-dimensional analysis of data-driven load forecasting methods. Three regression-based and seven deep learning algorithms with different model configurations were evaluated in terms of their overall and peak load prediction accuracy, and training burdens, across spatial aggregation levels ranging from the transformer, feeder, substation, to neighborhood. We found, first, the load forecasting accuracy is constrained by a predictability boundary, influenced by the forecasting horizon and spatial aggregation level. Specifically, RandomForest, XGBoost, TFT, TSMixer, and TiDE models achieved less than 10 % prediction error for up to 96-h ahead forecasting for district, substation, and feeder levels, while other models struggle at long-horizon predictions; Second, for winter and summer peak load dates, most models were able to predict the peak demand timing within ± 1 h, but the prediction percentage error varied by models, with TFT and TiDE models being the top performers; Third, models with similar prediction accuracy can differ in training burden by an order of magnitude. Therefore, choosing model configurations that balance prediction performance and computational resource is an important practical consideration for large-scale deployment of the machine learning based load forecasting. The outcome of this study can guide researchers and practitioners to choose the proper load forecasting algorithms based on their problem scope, required accuracy, and available resources. The predictability boundary can serve as a benchmark for electricity load forecasting problems with new algorithms and datasets.
Delamination growth in compressively loaded composite laminates was studied analytically and experimentally. The configuration used was a laminate with an across-the-width delamination. An approximate super-position stress analysis was developed to quantify the effects of various geometric, material, and load parameters on mode 2 and mode 2 strain energy release rates G sub/1 and G sub 2, respectively. Calculated values of G sub 1 and G sub 2 were then compared with measured cyclic delamination growth rates to determine the relative importance of G sub 1 and G sub 2. High growth rates were observed only when G sub 1 was large. However, slow growth was observed even when G sub 1 was negligibly small. This growth apparently was due to a large value of G sub 2.
Delamination growth in compressively loaded composite laminates was studied analytically and experimentally. The configuration used was a laminate with an across-the-width delamination. An approximate super-position stress analysis was developed to quantify the effects of various geometric, material, and load parameters on mode 1 and mode 2 strain energy release rates G sub 1 and G sub 2, respectively. Calculated values of G sub 1 and G sub 2 were then compared with measured cyclic delamination growth rates to determine the relative importance of G sub 1 and G sub 2. High growth rates were observed only when G sub 1 was large. However, slow growth was observed even when G sub 1 was negligibly small. This growth was apparently due to a large value of G sub 2.
This paper presents techniques based on a three-dimensional finite-element analysis for the analysis of continuous fiber reinforced metal matrix composite. Examples are shown for specific metal matrix composites such as boron/aluminum and silicon-carbide/aluminum. Specimen stress-strain behavior and stress at first fiber failure were predicted for boron/aluminum laminates containing circular holes and crack-like slits. The predictions compared very well with test data for laminates containing 0 deg fibers and reasonably well for (+/-45)2s laminates. Mesh configuration was shown to have an effect on the calculation of stresses local to the notch. The presence of thin interface layers of matrix material had a significant influence on the slit tip stress state, causing sharper stress gradients near the notch. Interface layers reduced the slit-tip fibers stress in a (+/-45)2s silicon-carbide/aluminum laminate but increased them in a (0/90)2s laminate.
Results of a statistical analysis of horizontal-tail loads on a fighter airplane are presented. The data were obtained from a number of operational training missions with flight at altitudes up to about 50,000 feet and at Mach numbers up to 1.22. The analysis was performed to determine the feasibility of calculating horizontal-tail load from data on the flight conditions and airplane motions. In the analysis the calculated loads are compared with the measured loads for the different types of missions performed. The loads were calculated by two methods: a direct approach and a Monte Carlo technique. The procedures used and some of the problems associated with the data analysis are discussed. frequencies of occurrence of tail loads of given magnitudes are derived from statistical information on the flight quantities. In the direct method, a time history of tail load is calculated from time-history measurements of the flight quantities. The Monte Carlo method could be useful for extending loads information for design of prospective airplanes . For the Monte Carlo method, the The results indicate that the accuracy of loads, regardless of the method used for calculation, is largely dependent on the knowledge of the pertinent airplane aerodynamic characteristics and center-of-gravity location. In addition, reliable Monte Carlo results require an adequate sample of statistical data and a knowledge of the more important statistical dependencies between the various flight conditions and airplane motions.
Retrofitting central HVAC systems in large commercial buildings with advanced technologies like heat recovery chillers (HRCs) offers a significant opportunity to enhance energy efficiency. However, analyzing these retrofits is challenging with traditional whole-building simulation tools, which require intensive calibration and struggle to model innovative system configurations and controls. To overcome these limitations, this study proposes a load profilebased retrofit analysis framework that provides better decisions under uncertainty. The main focus of this paper is the development of a probabilistic load profile model that can be used in the framework by using exploratory data analysis (EDA) of measured building data to properly quantify its inherent variability. A non-parametric Gaussian Process (GP) model was employed to capture the time- and weather-dependent characteristics of the heating load while explicitly modeling its uncertainty. The model's effectiveness is demonstrated through strong predictive performance on unseen data and physically interpretable insights into load behavior. This data-driven, probabilistic load profile serves as a robust and flexible input for subsequent system simulations, enabling a more confident and statistically sound analysis of retrofit potential.
Validation of a progressive damage finite element analysis model using the CompDam material model was performed on a large multi-stringer panel subjected to compressive loading. The panel had a Teflon insert embedded between the skin panel and stiffener to cause an ultimate failure mode of stiffener separation. The compressive loading of the panel caused the skin between the stiffeners to locally buckle before any damage began to occur. The post-buckled behavior of the panel was the driving mechanism to the onset of damage and the damage growth that led to skin-stiffener separation. An integrated global-local modeling approach was used to validate several aspects the overall behavior of the panel from start to failure. The global region captured the pre-buckled stiffness of the test panel within 10% and the buckling load of the skin panel at the critical location within 2%. The skin’s five half-wave buckled mode shape was accurately predicted by the model. The integrated local model captured the load corresponding to the onset of damage within 5% of the average test data. Comparisons are made for key aspects of the damage morphology, such as a growth pattern that included a significant matrix split in the first ply of the skin and a migration of the delamination from the skin-stiffener interface to the skin’sply1-ply2 interface. The ultimate failure mode was shown to be an unstable growth of delamination damage under the stiffeners which led to a peak load of the analysis that was approximately 5% above the average peak load of the testing. The validated global-local modeling approach used on the multi-stringer post-buckled panel with a Teflon insert used a methodology and lessons learned using smaller specimens applied to a subcomponent that captured several aspects of a modern aircraft design.
In this paper, we describe the operation of a two-stage wire array z-pinch driven by the 1.4 MA, 240 ns rise-time Magpie pulsed-power device at Imperial College London. In this setup, an inverse wire array acts as a fast current switch, delivering a current pre-pulse into a cylindrical load wire array, before rapidly switching the majority of the generator current into the load after a 100–150 ns dwell time. A detailed analysis of the evolution of the load array during the pre-pulse is presented. Measurements of the load resistivity and energy deposition suggest significant bulk heating of the array mass occurs. The ∼5 kA pre-pulse delivers ∼0.8 J of energy to the load, leaving it in a mixed, predominantly liquid-vapour state. The main current switch occurs as the inverse array begins to explode and plasma expands into the load region. Electrical and imaging diagnostics indicate that the main current switch may evolve in part as a plasma flow switch, driven by the expansion of a magnetic cavity and plasma bubble along the length of the load array. Analysis of implosion trajectories suggests that approximately 1 MA switches into the load in 100 ns, corresponding to a doubling of the generator dI/dt. Potential scaling of the device to higher current machines is discussed.
The Tank Side Cesium Removal (TSCR) system is currently being constructed to process Hanford tank waste supernates for vitrification. TSCR incorporates a filtration system and cesium (Cs) removal system using columns filled with crystalline silicotitanate (CST) ion exchanger, produced by Honeywell UOP, LLC. The documented safety analysis (DSA) developed for TSCR limits a single column curie loading to 141,600 Ci; given a 137 Cs isotopic mass fraction of 20% and the planned CST bed size of a TSCR column, this equates to 0.10 mmole Cs per g CST. Factors that influence 137Cs loading onto the CST include, but are not limited to, CST production lot (different production lots behave differently), contact temperature, contact duration, 137Cs mass fraction, and competitors in the tank waste feed. Seventeen tank waste feeds (compositions) were identified by Washington River Protection Solutions to be processed through TSCR. These feed compositions were used to develop a simulant (referred to herein as Stage 1) that would provide an upper bound to the Cs loading onto CST based on maximizing the Cs/Na activity coefficient ratios in solution while maintaining Na at no less than 5.0 M. Building upon this Stage 1 simulant, a series of four additional simulants were developed based on the cationic/anionic species that impact Cs exchange, with each successive formulation relaxing one or more matrix component concentration constraints as show in Table S.1
This report deals with the analysis of 2-spar cantilever wings in torsion, taking cognizance of the fact that the spars are not independent, but are interconnected by ribs and other structural members. The principles of interaction are briefly explained, showing that the mutual relief action occurring depends on the "pure torsional stiffness" of the wing cross section. Various practical methods of analysis are outlined. The "Friedrichs-Von Karman equations" are shown to require the least amount of labor. Numerical examples by the several methods of analysis are given and the agreement between the calculation and experiment is shown.
A static load test was performed on the spare Mod-0 wind turbine blade to define load transfer at the root end of the blade, and to validate stress analysis of this particular type of blade construction (frame and stringer). Analysis of the load transfer from the airfoil skin to the shank tube predicted a step change in spanwise stress in the airfoil skin at station 81.5 inches (STA 81.5). For flatwise bending a 40% reduction in spanwise stress was predicted, and for edgewise bending a 6% reduction. Experimental results verified the 40% reduction for flatwise bending, but indicated about a 30% reduction for edgewise bending.
Computer technique aids joint optimization. Load-sharing between fasteners in multirow bolted composite joints computed by nonlinear-analysis computer program. Input to analysis was load-deflection data from 180 specimens tested as part of program to develop technology of structural joints for advanced transport aircraft. Bolt design optimization technique applicable to major joints in composite materials for primary and secondary structures and generally applicable for metal joints as well.
This paper describes techniques to be used to model megawatt Electrified Aircraft Propulsion (MW EAP) components, specifically motor/generators and inverters, DC-DC converters, and long power leads; resulting in impedance-based models which require no information from the component manufacturers. A custom curve fitting method is described, and an example power supply model is fit using measured impedance data. A method called subscale measurement, employing measurement equipment which has much lower power capability than the MW EAP system under test, is described, simulated, and used to generate an impedance transfer function model of a load. Finally, stability analysis using a Nyquist based approach is performed on the combined supply and load system, using the generated models.
Design loads are presented for the General Electric MOD-SA wind turbine. The MOD-SA system consists of a 400 ft. diameter, upwind, two-bladed, teetered rotor connected to a 7.3 mW variable-speed generator. Fatigue loads are specified in the form of histograms for the 30 year life of the machine, while limit (or maximum) loads have been derived from transient dynamic analysis at critical operating conditions. Loads prediction was accomplished using state of the art aeroelastic analyses developed at General Electric. Features of the primary predictive tool - the Transient Rotor Analysis Code (TRAC) are described in the paper. Key to the load predictions are the following wind models: (1) yearly mean wind distribution; (2) mean wind variations during operation; (3) number of start/shutdown cycles; (4) spatially large gusts; and (5) spatially small gusts (local turbulence). The methods used to develop statistical distributions from load calculations represent an extension of procedures used in past wind programs and are believed to be a significant contribution to Wind Turbine Generator analysis. Test/theory correlations are presented to demonstrate code load predictive capability and to support the wind models used in the analysis. In addition MOD-5A loads are compared with those of existing machines. The MOD-5A design was performed by the General Electric Company, Advanced Energy Program Department, under Contract DEN3-153 with NASA Lewis Research Center and sponsored by the Department of Energy.
The advantages of using a hierarchical analysis approach to calculate the buckling load of an axially compressed composite cylindrical shell is demonstrated using an example taken from a recent experimental program. The Delft Interactive Shell DEsign COde (DISDECO) shell design code is used for this hierarchical analysis approach to provide an accurate prediction of the critical buckling load of the actual shell structure. DISDECO includes the influence of the boundary conditions, initial geometric imperfections, the effects of stiffener and load eccentricities, and the effects of prebuckling deformations caused by edge constraints in the analysis. It is shown that the use of DISDECO makes it relatively simple to proceed step by step from simple to more complex models and solution procedures. As a final step in the hierarchical analysis approach, the critical buckling load and the estimated imperfection sensitivity of the shell are verified by conducting an analysis of a large finite element model with one of the current generation two-dimensional shell analysis codes with advanced capabilities needed to represent both geometric and material nonlinearities.
The LOX Expert System (LES), now being developed as a tool for the constraint-based monitoring and analysis of propellant loading at the Kennedy Space Center (KSC), is discussed. The loading of LOX at the KSC and its control and monitoring by the Launch Processing System are summarized, and the relevant problem for LES is presented. The LES database is briefly described, and the interaction of LES with KNOBS, a constraint- and frame-oriented knowledge-based system developed as a demonstration system in aid of tactical air mission planning, is the context of launch processing is discussed in detail. The design and fault isolation techniques of LES are also discussed.
This paper focuses on developing load aggregation methodologies for analyzing quasi-static power flows on high photovoltaic penetrated distribution feeders so statistics of the transformer loading levels, voltage ramping events, and voltage violation events can be properly quantified. A load profile aggregation algorithm is presented to construct 24-hour, minute-by-minute load profiles at each load node on the test feeder so the aggregation of those load profiles matches the load profile measured at the feeder head. A quasi-static power flow analyses are conducted to obtain minute-by-minute power flow results that can be used to quantify transformer overloads and voltage issues in distribution systems. To demonstrate the effectiveness of the developed methodology, the IEEE-123 test feeder model and residential load profiles collected from the PECAN street project are used in the case studies. Simulation results show that the method is effective in producing the required operation statistics.