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Approximate spectral analysis faster and less expensive than transient analysis. Method of vibration analysis combines separate modes of spacecraft and launcher to determine approximate conditions for resonance. Useful for analysis of any complex structure made up of substructures not coupled too closely; however important to note, method includes effect of dynamic impedance between launcher and payload.
The inviscid, incompressible interaction of a wing with a vortex is studied by use of Munk's transverse-flow method. The method assumes that the loading on the wing is such that the local circulatory flow of the vortex is turned so that the wing and its vortex wake act as a barrier to the flow. This permits the analysis to be carried out by mapping the transverse flowfield into the flow about a circle to find the vorticity distribution in the wake. Closed-form expressions are then derived for the bound circulation in the wind and for the lift and rolling moment induced by the vortex on the encountering wing. Comparisons of the loads predicted by these relationships with those of vortex-lattice theory for a flat wing of a rectangular planform indicate that they accurately represent the various parameters when the aspect ratio of the encountering wing is less than about two. When flat rectangular wings of higher aspect ratios are considered, some sort of correction is needed. Examples are then presented to illustrate some applications of the results.
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This paper discusses the modeling approach applied in the Used Nuclear Fuel Storage, Transportation, & Disposal Analysis Resource and Data System (UNF-ST&DARDS) to take credit for the reduced reactivity associated with the burnup of boiling water reactor (BWR) fuel for canister-specific as loaded criticality analysis. Burnup credit is routinely used for the analysis of pressurized water reactor (PWR) spent nuclear fuel (SNF) storage (wet), transportation, and disposal. The fresh fuel assumption has historically been applied to BWR SNF criticality analyses for dry storage and transportation, and the peak reactivity method of burnup credit has been applied to pool storage. The fresh fuel assumption ignores the credit for gadolinium burnable absorbers in BWR fuel, as well as the burnup of the fuel, and is therefore conservative. This work employs the framework traditionally used for PWR burnup credit analyses and applies available data and recently published regulatory guidance to justify a new approach to model the as-loaded burnup and enrichment of SNF assemblies in currently loaded dry casks. The following features of this criticality analysis approach are presented in this paper: (1) selection of axial burnup profiles for BWR fuel from publicly available sources using methods derived from recently published research, (2) justification of the selected axial burnup profiles as relevant to all types of BWR fuel, (3) justification for modeling the fuel assemblies with a uniform axial and radial enrichment, and (4) justification for modeling the axial void profile and control blade insertion during depletion. This analysis approach was used to evaluate 153 already-loaded BWR casks at 8 sites as a function of time in UNF ST&DARDS. Finally, the results of the as-loaded criticality safety margin assessments are presented. The results show the k eff calculated for storage and transportation cases range from 0.71 to 0.83, and the eigenvalues calculated for the disposal cases range from 0.85 to 1.03, though the highest cases are dominated by very limiting hypothetical damaged fuel assumptions.
Abstract not provided.
This paper discusses the modeling approach applied in the Used Nuclear Fuel Storage, Transportation, and Disposal Analysis Resource and Data System (UNF-ST-DARDS) to take credit for the reduced reactivity associated with the burnup of boiling water reactor (BWR) fuel for canister-specific as-loaded criticality analysis. Burnup credit is routinely used for the analysis of pressurized water reactor (PWR) spent nuclear fuel (SNF) storage (wet), transportation, and disposal. The fresh fuel assumption has historically been applied to BWR SNF criticality analyses for dry storage and transportation, and the peak reactivity method of burnup credit has been applied to pool storage. The fresh fuel assumption ignores the credit for gadolinium burnable absorbers in BWR fuel, as well as the burnup of the fuel, and is therefore conservative. This work employs the framework traditionally used for PWR burnup credit analyses and applies available data and recently published regulatory guidance to justify a new approach to model the as-loaded burnup and enrichment of SNF assemblies in currently loaded dry casks. The following features of this criticality analysis approach are presented in this paper: (1- selection of axial burnup profiles for BWR fuel from publicly available sources using methods derived from recently published research, (2- justification of the selected axial burnup profiles as relevant to all types of BWR fuel, (3- justification for modeling the fuel assemblies with a uniform axial and radial enrichment, and (4- justification for modeling the axial void profile and control blade insertion during depletion. This analysis approach was used to evaluate 153 already-loaded BWR casks at 8 sites as a function of time in UNF-ST-DARDS. Finally, the results of the as-loaded criticality safety margin assessments are presented. The results show the k{sub eff} calculated for storage and transportation cases range from 0.71 to 0.83, and the eigenvalues calculated for the disposal cases range from 0.85 to 1.03, though the highest cases are dominated by very limiting hypothetical damaged fuel assumptions. (authors)
Loads methods currently being used to design shuttle orbiter payloads are summarized. Methods used for the design of payloads launched by expendable launch vehicles are described in historical perspective. Experiences gained from expendable launch vehicle payloads are used to develop methodologies for the space shuttle orbiter payloads. The objectives for the development of a new methodology for the shuttle payloads are to reduce the cost and schedule for the payload load analysis by decoupling the payload analysis from the launch vehicle to the maximum extent possible. Methods are described for payload member load estimation or obtaining upper bounds for dynamic loads, as well as load prediction or calculating actual transient member load time histories.
Loads methods currently being used to design planetary spacecraft to be launched on the shuttle orbiter are summarized. Experiences gained from expendable launch vehicle payloads are used to develop methodologies for the space shuttle orbiter payloads. The objectives for the development of a new methodology for the shuttle payloads are to reduce the cost and schedule for the payload load analysis by decoupling the payload analysis from the launch vehicle to the maximum extent possible. Methods are described for payload member load estimation or obtaining upper bounds for dynamic loads, as well as load prediction or calculating actual transient member load time histories.
Motivated by present and forthcoming challenges in the adoption and integration of distributed renewable energy, we develop a machine learning (ML) approach that builds short-fuse mappings connecting the occasionally-unobservable true load in one target community with information-rich signals collected from relatively more instrumented reference communities. Our setting is inspired by and tailored to target communities with significant unobservable behind-the-meter solar generation, where true load (a relatively well-behaved quantity of interest to grid operators) is hard to discern during daytime due to insufficient instrumentation and/or privacy reasons, but that can be related to reference communities with low unobservable distributed variable generation or with sufficient instrumentation. The developed mapping, herein realized with Support Vector Machine regression, is built using nighttime data from all communities, when their distributed generation is low or zero. Our ML algorithm opportunistically learns to correlate signals of interest and then is operationally used the next day to shed light into target community load evolution. The mapping is subsequently rebuilt, rolling its short-fuse scope perpetually forward in time. Here, we demonstrate the efficacy of our approach on nine synthetically generated topologies and associated timeseries stemming from real-world data, on which we observe cumulative error performance that yields lower than 10% and 15% daily-averaged mean absolute percentage errors in target community load estimation on more than about 75% and 90% of days, respectively, in multiple yearly evaluations that shed light on long-term performance also under seasonal and one-off effects. The proposed ML-powered methodology can offer grid operators much-improved visibility into a previously obscure space and can also serve as an additional source of information in broader, multi-modal solar disaggregation solutions.
Impedance testing devices, circuits, systems, and related methods are disclosed. A Device Under Test (DUT) is excited with a multispectral excitation signal for an excitation time period while the DUT is under a load condition from a load operably coupled to the DUT. A response of the DUT is sampled over a sample time period. The sample time period is configured such that it includes an in-band interval during the excitation time period and one or more out-of-band intervals outside of the in-band interval. A response of the DUT to the load condition during the in-band interval is estimated by analyzing samples of the response from the one or more out-of-band intervals. Adjusted samples are computed by subtracting the estimated load response during the in-band interval from the samples from the in-band interval. An impedance of the DUT is estimated by analyzing the adjusted samples.
Impedance testing devices, circuits, systems, and related methods are disclosed. A method may include exciting a device coupled to a load, and capturing a response of the device. The method may further include adjusting the response based on an estimated load response of the device, and estimating an impedance of the device based on the adjusted response.
A new approach for the graphical and numerical description of strain-gage balance interactions is presented. The approach uses data from single-component loads as input. This choice has the two advantages. First, the number of applied loads is at the minimum needed for interactions to be observed. In addition, the loads used for the description of interactions can easily be repeated at different sites. Output differences relative to the outputs of the zero load point of a load series are used for the description of interactions. Similarly, load differences relative to the loads of the zero load point of a load series are used for the description of the loads. Interactions are plotted versus the load differences for each load component while omitting outputs of the primary gage of the chosen load component. The resulting plots have a star pattern as all interactions are zero at zero load. Estimates of the slopes of the interactions can be obtained from the load prediction equations of a balance if calibration data is examined. The slopes are the off-diagonal coefficients of the inverse of the matrix that has the coefficients of the linear terms of the fitted loads if the Non-Iterative Method is used for the analysis. Similarly, the slopes are the off-diagonal coefficients of the inverse of the matrix that is the non-iterative part of the primary load iteration equation if the Iterative Method is used for the analysis. Data sets from a manual and a machine calibration of a force balance are processed to illustrate the proposed description of interactions.
This paper proposes a novel approach to identify the load patterns considering calendar impact and denoising process, which advances the state of art of load identification and load forecasting to a more flexible and adaptive extent by revealing the correlation between load profile and the substantial influence factors. With the rapid development and the promising application of energy intemet and grid modernization, the accurate load modeling and forecasting especially by load pattern modeling (LPM) have become more and more critical to observe and estimate load profile so as to optimize the operation efficiency of the power grid. Traditional methods mostly focus on the static LPM itself which are unable to account the non-linear and highly dynamic load fluctuations in order to balance the demand of the power grid during various calendar period (VCP) scheduling. In this paper, a load pattern modeling method for power grid considering the impact of typical calendar effects is proposed using a combination of improved variational mode decomposition (IVMD) and deep belief network (DBN) algorithm. Firstly, an index of load curve curvature (LCC) is proposed to improve the selection of value K in the conventional VMD algorithm. The value K of the intrinsic modality is determined by adopting LCC to better quantify the average instantaneous frequency of the modal decomposition of the VMD and to reduce the elevated stochasticity of k. Secondly, an optimization formulation is developed based on adaptive segmented loop decomposition of the typical correlation coefficient to suppress the edge effect in VMD decomposition, which would enable the reconstructed curve to incorporate the variabilities from the initial data. Finally, the IVMD and DBN algorithms are jointly implemented to optimize the accuracy of VCP load pattern modeling curve regression. Numerical examples have been performed with the results proving that the proposed method significantly outperforms the state-of-art in reducing the modeling error of VCP load curve, improving the overall forecasting accuracy, and reducing load dispatching cost.
Roadways with dynamic wireless charging systems (DWCS) enable charge-sustaining in-motion EV charging, which can reduce charging idle time while increasing range capabilities. Spatially distributed transmitter coils are controlled in response to traffic load that varies significantly minute to minute with high power levels, very short charging time, and low system utilization like wind turbine power. Traffic load estimation and localized analysis may guide effective sizing and topology adoption for feasible and scalable DWCS deployment. DWCS traffic load approximation is reviewed with measured Automated Traffic Recorder (ATR) data and statistical distributions being used to create a synthetic load analyzed using proposed metrics quantifying system utilization over time. Lumped coil section segmentation is compared between second-based distance and spatial density analysis methods, offering 17-27% greater system utilization. A peak load shifting method is proposed for traffic redirection across two tracks with optional BESS integration increasing system utilization by 50-60% depending on time-based and power reserve-based sizing and control.
Results from a numerical study of the buckling response of a thin-walled compressionloaded isotropic circular cylindrical shell with initial geometric and loading imperfections are used to determine a lower bound buckling load estimate suitable for preliminary design. The lower bound prediction techniques presented herein include an imperfection caused by a lateral perturbation load, an imperfection in the shape of a single stress-free dimple (similar to the lateral pertubation imperfection), and a distributed load imperfection that induces a nonuniform load in the shell. The ABAQUS finite element code is used for the analyses. Responses of the cylinders for selected imperfection amplitudes and imperfection types are considered, and the effect of each imperfection is compared to the response of a geometrically perfect cylinder. The results indicate that compression-loaded shells subjected to a lateral perturbation load or a single dimple imperfection, and a nonuniform load imperfection, exhibit similar buckling behavior and lower bound trends and the predicted lower bounds are much less conservative than the corresponding design recommendation NASA SP-8007 for the design of buckling-critical shells. In addition, the lateral perturbation technique and the distributed load imperfection produce response characteristics that are physically meaningful and can be validated via laboratory testing.
Estimates of flight loads for Voyager 1 and Voyager 2 are summarized. These member loads are obtained by using the measured flight accelerations at the launch vehicle/spacecraft interface as forcing functions for the Voyager mathematical model. The flight loads are compared to the Voyager design loads obtained from the shock spectra/impedance method and to the loads obtained using space vehicle transient loads analysis. Finally, based on these data, an assessment of the shock spectra/impedance loads method used for Voyager is presented.
The possible sources of the cold plasma observed in the outer magnetosphere of Saturn are analyzed. On the basis of the O(+)-H charge exchange species-specific loss mechanism, as well as abundance and rate considerations, it is concluded that the dominant heavy ion populating the equatorial outer magnetosphere is that of atomic nitrogen. Possible sources of hot plasma are also discussed, as are the inhibition of corotation by mass loading and the radial variation of composition. It is found that the observed deviations from corotation and current mass loading estimates indicate either a somewhat higher ionospheric conductance than is implied by the UVS and RSS measurements, or an overestimate of mass loading. It is suggested that the plasma gap observed by Voyager 1 outbound may be associated with a composition change.
This wind turbine digital twin software (wtDigiTwin) provides a digital twin solution for wind turbine applications. The focus of wtDigiTwin is to estimate loads, motions and environmental conditions for an operating wind turbine. The program uses supervisory control and data acquisition (SCADA) measurements as inputs, together with a wind turbine model. The wind industry is currently challenged by the high cost of operation and maintenance. These costs could be mitigated if component failures are predicted, but such predictions are difficult unless the turbines are equipped with expensive measuring devices. The alternative is to use a digital twin such as wtDigiTwin to estimate the necessary signals. wtDigiTwin can perform online prediction of signals that are otherwise not measured, using a limited set of reliable measurements and a physics-based model. The predicted signals can be used in applications that have direct cost benefits: 1) real-time estimation of the fatigue consumption of key components of the wind turbine; 2) root cause analyses and failure detections ; 3) lifetime reassessments ; 4) improvements to follow-on designs. The current version provides examples to estimate wind speed, thrust, torque, tower-top position, and tower loads on an onshore wind turbine using the following measurements tower top acceleration, generator torque, pitch, and rotational speed. The model combines a linear state-space model, a wind speed estimator, and a Kalman filter algorithm that integrates measurements with the state model to perform state estimations. The state space model is obtained either using OpenFAST linearizations, or using the yams package provided with the software.