Time domain modeling of constant power loads for electromagnetic transient simulations
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Quantitative analysis of human performance in microgravity is important for both scientific investigations and spacecraft engineering design. By collecting and evaluating the kinematics and kinetics data of astronauts in space, it becomes possible to characterize human motor strategies, postural behavior in weightlessness, improve the design of orbital modules, help maintain a quiescent microgravity for acceleration-sensitive material science and life science experiments (NASA JSC, 1996), and optimize the human operative capabilities during long-duration space missions. Hence, there is a need for a precise measurement of the forces and moments exerted by the astronauts on the space station and their postures and movements.
A series of single-frame and single-stringer compression tests were conducted at NASA Langley Research Center on specimens harvested from a large panel built using the Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) concept. Different frame and stringer designs were used in fabrication of the PRSEUS panel. In this paper, the details of the experimental testing of single-frame and single-stringer compression specimens are presented, as well as discussions on the performance of the various structural configurations included in the panel. Nonlinear finite element models were developed to further understand the failure processes observed during the experimental campaign.
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As aircraft move to using composite materials as their primary structure they become lighter and more flexible as well. This presents some significant challenges in association with gust load alleviation. In this paper we develop an aeroservoelastic model for use in developing controllers that utilize distributed control surfaces for active gust load alleviation in a set of wind tunnel experiments. The model is based on an preexisting aeroelastic wing tunnel model and compares the baseline functionality to it. We also provide simple full state feedback simulations for the model.
The objective of this program is to develop generic load models with multiple levels of progressive sophistication to simulate the composite (combined) 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 posts and system ducting. The first approach will consist 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 second approach 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.
A multiyear program is performed with the objective to develop generic load models with multiple levels of progressive sophistication to simulate the composite (combined) 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. Progress of the first year's effort includes completion of a sufficient portion of each task -- probabilistic models, code development, validation, and an initial operational code. This code has from its inception an expert system philosophy that could be added to throughout the program and in the future. The initial operational code is only applicable to turbine blade type loadings. The probabilistic model included in the operational code has fitting routines for loads that utilize a modified Discrete Probabilistic Distribution termed RASCAL, a barrier crossing method and a Monte Carlo method. An initial load model was developed by Battelle that is currently used for the slowly varying duty cycle type loading. The intent is to use the model and related codes essentially in the current form for all loads that are based on measured or calculated data that have followed a slowly varying profile.
Small-scale wind turbines have market opportunities in distributed energy generation applications but face future challenges in remaining cost competitive compared with solar photovoltaic systems. High unit costs can be attributed to design conservatism when calculating fatigue loads of key structural components such as the blades. In this study, we use the aeroelastic software FAST to highlight limitations of the International Electrotechnical Commission 61400-2:2013 small wind turbine design standard for calculating fatigue life using the simplified load model. We present a modified method for calculating the fatigue spectra of small wind turbine blades. An advantage of this method is that it does not require complex aeroelastic simulations or field measurements. This modified method is intended to be implemented early in the blade design stage, such as during rotor optimization simulations, allowing for multiple rotor configurations to be rapidly compared.
An empirical separation and side load model to obtain applied aerodynamic loads has been developed based on data obtained from full-scale J-2S (265K-pound-thrust engine with an area ratio of 40:1) engine and model testing. Experimental data include visual observations of the separation patterns that show the dynamic nature of the separation phenomenon. Comparisons between measured and applied side loads are made. Correlations relating the separation location to the applied side loads and the methods used to determine the separation location are given.
Abstract. Wind turbines in wind farms often operate in waked or partially waked conditions, which can greatly increase the fatigue damage. Some fatigue considerations may be included, but currently a full fidelity analysis of the increased damage a turbine experiences in a wind farm is not considered in wind farm layout optimization because existing models are too computationally expensive. In this paper, we present a model to calculate fatigue damage caused by partial waking on a wind turbine that is computationally efficient and can be included in wind farm layout optimization. The model relies on analytic velocity, turbulence, and load models commonly used in farm research and design, and it captures some of the effects of turbulence on the fatigue loading. Compared to high-fidelity simulation data, our model accurately predicts the damage trends of various waking conditions. We also perform example wind farm layout optimizations with our presented model in which we maximize the annual energy production (AEP) of a wind farm while constraining the damage of the turbines in the farm. The results of our optimization show that the turbine damage can be significantly reduced, more than 10 %, with only a small sacrifice of around 0.07 % to the AEP, or the damage can be reduced by 20 % with an AEP sacrifice of 0.6 %.
The complex interactions between internal motor generated pressure oscillations and motor structural vibration modes associated with the static test configuration of a Reusable Solid Rocket Motor have potential to generate significant dynamic thrust loads in the 5-segment configuration (Engineering Test Motor 3). Finite element model load predictions for worst-case conditions were generated based on extrapolation of a previously correlated 4-segment motor model. A modal survey was performed on the largest rocket motor to date, Engineering Test Motor #3 (ETM-3), to provide data for finite element model correlation and validation of model generated design loads. The modal survey preparation included pretest analyses to determine an efficient analysis set selection using the Effective Independence Method and test simulations to assure critical test stand component loads did not exceed design limits. Historical Reusable Solid Rocket Motor modal testing, ETM-3 test analysis model development and pre-test loads analyses, as well as test execution, and a comparison of results to pre-test predictions are discussed.
The objective of the Composite Load Spectra (CLS) project is to develop generic load models to simulate the composite load spectra that are included in space propulsion system components. The probabilistic loads thus generated are part of the probabilistic design analysis (PDA) of a space propulsion system that also includes probabilistic structural analyses, reliability, and risk evaluations. Probabilistic load simulation for space propulsion systems demands sophisticated probabilistic methodology and requires large amounts of load information and engineering data. The CLS approach is to implement a knowledge based system coupled with a probabilistic load simulation module. The knowledge base manages and furnishes load information and expertise and sets up the simulation runs. The load simulation module performs the numerical computation to generate the probabilistic loads with load information supplied from the CLS knowledge base.
Owing to the increased use of power electronic based appliances and energy-efficient home equipment such as modern lighting loads, the percentage of nonlinear loads has increased in the distribution system, which can impact system performance, loss, and stability. Thus a comprehensive knowledge of their power quality and harmonic analysis is essential to improve the load models, voltage stability assessment, determination of possible interactions at harmonic frequencies, protection planning, and the effect of system impedance. This paper focuses on harmonic load flow analysis for multiple residential load types to determine the expected impacts on an modeled distribution secondary. For this study, the household appliances include lighting, power electronic, resistive, and motor loads with a nominal supply voltage of 120 V single-phase or 240 V split phase at a nominal frequency of 60 Hz. The harmonic spectrums, as obtained from the experimental evaluation of real loads, are used to inform the harmonic load flow for a detailed secondary network, including the distribution service transformer extracted from a real distribution feeder's model. Additionally, the impact of voltage harmonics on a three-phase test load is presented with experimental results. The harmonic data of the transformer terminal voltage, as obtained from the former load flow study, are scaled to generate the source voltage for the three-phase configuration of the grid simulator to make the test setup very similar to a typical secondary design in the U.S.
Bottom-up load modeling of buildings offers a versatile approach to simulating baseline demand and scenarios of future technology evolution and adoption at the individual building level. This capability is essential to understanding how future load shapes may change with the adoption of electric equipment and vehicles, particularly as it relates to grid planning and infrastructure investments. Traditionally, grid planning techniques have used historical load data to predict future load and infrastructure needs. However, with the anticipated rise in adoption of electrification technologies such as heat pumps and electric vehicles, historical data become less reliable predictors of the future. By employing ResStock, a high-fidelity building stock modeling tool, we can fine-tune electrification scenarios and aggregate models to represent varying geographic resolutions of the grid system, while considering the underlying features of homes. This may enable a more accurate and responsive approach to anticipate and plan for the evolving landscape of energy demands. We present a new framework that leverages building stock energy modeling to identify building models that align with the load shapes and housing attributes of buildings with AMI data. This approach applies two model layers: (1) a classification step that identifies the presence of air conditioning, electric heating, and electric water heating, and (2) an optimization routine that identifies building energy models aligning with load profile data from advanced metering infrastructure meters. This report demonstrates one approach to deploying this framework, and presents results for three test cases that use both modeled and AMI data to assess performance. For a test case using AMI data in Fort Collins, Colorado, we observed a median monthly electricity load CV-RMSE of 16.6%, and a top ten daily heating and cooling median absolute percent error of 7.7% and 8.3%, respectively. For each AMI meter, we identify a set of potential energy models so that downstream use-cases can account for uncertainty driven by variability of baseline technologies and occupant behavior, which impact the response to electrification and energy efficiency scenarios. Our results indicate that ResStock has potential as a scalable solution for modeling residential energy demand at local grid resolutions. Its performance depends on location-specific factors, underlying building characteristics, and the level of aggregation, offering a path towards more precise and adaptive distribution grid planning for the evolving energy landscape.