Absolute stability and parameter sensitivity.
Absolute stability extension to include parameter variations in linear part of system
Siljak, D.↗
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Absolute Stability and Parameter Sensitivity
Absolute stability notion extended to include parameter variations of linear part of system
Siljak, D.↗
Parameter sensitivity in the dynamics of rotor-bearing systems
When designing a rotor system it is frequently desirable to have at hand a set of design sensitivity coefficients which quantitatively predict a change in specific system characteristics to changes in design parameters. This paper presents eigenvalue sensitivity coefficients for the damped natural frequencies of whirl of general linear rotor system modelled by finite element discretization. In addition, a simple and direct method for calculation of the damped critical speeds is presented, which utilizes the eigenvalue sensitivity with respect to the spin speed. It is shown that the combination of design parameter and spin speed whirl frequency sensitivity coefficients may be used to also evaluate the damped critical speed sensitivity coefficients.
Rajan, M.↗
Sensitive parameter identification and uncertainty quantification for the stability of pipeline conveying fluid
In this study, several uncertainty quantification and sensitivity analysis methods are used to determine the most sensitive geometric and material input parameters of a cantilevered pipeline conveying fluid when uncertainty is introduced to the system at the onset of instability. The full nonlinear equations of motion are modeled using the extended Hamilton’s principle and then discretized using Galerkin’s method. A parametric study is first performed, and the Morris elementary effects are calculated to obtain a preliminary understanding of how the onset speed changes when each parameter is introduced to a ± 5% uncertainty. Then, four different input uncertainty distributions, mainly, uniform and Gaussian distribution, are chosen to investigate how input distributions affect uncertainty in the output. A convergence analysis is used to determine the number of samples needed to maintain simulation accuracy while saving the most computational time. Then, Monte Carlo simulations are run, and the output distributions for each input distribution at ± 1%, ± 3% and ± 5% input uncertainty range are found and discussed. Additionally, the Pearson correlation coefficients are evaluated for different uncertainty ranges. A final Monte Carlo study is performed in which single parameters are held constant while all others still have uncertainty. Overall, the flow speed at the onset of instability is the most sensitive to changes in the outer diameter of the pipe.
36 MATERIALS SCIENCE↗
Primordial black hole dark matter: A quantitative parameter sensitivity comparison across formation mechanisms and particle candidates
Primordial black holes (PBHs) in the asteroid-mass window ( 10 17 – 10 22 g ) can account for all of the dark matter without violating any observational constraint, yet are routinely dismissed as fine-tuned. I put that dismissal to the test by applying three complementary sensitivity measures uniformly across a broad landscape: three noninflationary PBH production mechanisms, six classes of inflationary PBH models, and seven particle dark matter benchmarks, all evaluated against the same observable target. Three distinct naturalness universality classes emerge, determined entirely by the analytic structure of the abundance map rather than by the nature of the dark matter candidate. Biased-domain-wall PBHs, in their least model-dependent (free- V b ) form, have the same low sensitivity, Δ = 4.5 , as off-resonance weakly interacting massive particles and freeze-in particles ( Δ = 2 ), a sensitivity that, because it is constant over the entire parameter space of the construction, also coincides trivially with its own Wilson-normalized average within that parameter space (Section Definition and conventions), an equivalence that concerns only the space over which Δ is computed and is not a naturalness statement about the construction as a whole; a further reduction to Δ = 2 is possible only under the additional, independently motivated but not required, assumption that the domain-wall bias is generated by Planck-suppressed operators; early matter-domination PBHs occupy an intermediate tier alongside coannihilating weakly interacting massive particles (WIMPs), unified by a structural identity in which the sensitivity measure equals the logarithm of the ratio of the formation scale to the matter–radiation equality scale; first-order phase transition PBHs, once the more accurate super-exponential collapse probability is used in place of the single-exponential approximation, instead belong to the same highly sensitive tier as resonant WIMP annihilation and single-field inflationary collapse, for a structurally distinct reason; single-field ultraslow-roll inflationary collapse is severely tuned for a distinct reason: a double exponential in which the power spectrum amplitude is itself exponentially sensitive to the inflaton potential coefficients, on top of the exponential collapse sensitivity of the abundance map. My main conclusion is that the claim that PBH dark matter is generically fine-tuned conflates the worst case with a landscape spanning every naturalness tier. The Barbieri-Giudice sensitivity computed here and the Wilson-normalized measure of Iovino and Riotto answer distinct and mutually consistent questions about the same construction, a distinction I clarify within the two-layer decomposition.
Profumo, Stefano [University of California, Santa ↗
Design of LQG controllers with reduced parameter sensitivity
A method is presented for improving the tolerance of LQG controllers to parameter errors. The improvement is achieved by introducing terms reflecting the structure of the errors into the LQR cost function and the process and measurement noise models. Adjusting the sizes of these additional terms permits a tradeoff between robustness and nominal performance.
Lin, J. Y.↗
Linear-quadratic-Gaussian synthesis with reduced parameter sensitivity
We present a method for improving the tolerance of a conventional LQG controller to parameter errors in the plant model. The improvement is achieved by introducing additional terms reflecting the structure of the parameter errors into the LQR cost function, and also the process and measurement noise models. Adjusting the sizes of these additional terms permits a trade-off between robustness and nominal performance. Manipulation of some of the additional terms leads to high gain controllers while other terms lead to low gain controllers. Conditions are developed under which the high-gain approach asymptotically recovers the robustness of the corresponding full-state feedback design, and the low-gain approach makes the closed-loop poles asymptotically insensitive to parameter errors.
Lin, J. Y.↗
Parameter Sensitivity Analysis of the SparTen High Performance Sparse Tensor Decomposition Software (Extended Analysis)
Tensor decomposition models play an increasingly important role in modern data science applications. One problem of particular interest is fitting a low-rank Canonical Polyadic (CP) tensor decomposition model when the tensor has sparse structure and the tensor elements are nonnegative count data. SparTen is a high-performance C++ library which computes a low-rank decomposition using different solvers: a first-order quasi-Newton or a second-order damped Newton method, along with the appropriate choice of runtime parameters. Since default parameters in SparTen are tuned to experimental results in prior published work on a single real-world dataset conducted using MATLAB implementations of these methods, it remains unclear if the parameter defaults in SparTen are appropriate for general tensor data. Furthermore, it is unknown how sensitive algorithm convergence is to changes in the input parameter values. This report addresses these unresolved issues with large-scale experimentation on three benchmark tensor data sets. Experiments were conducted on several different CPU architectures and replicated with many initial states to establish generalized profiles of algorithm convergence behavior.
97 MATHEMATICS AND COMPUTING↗
Pyrocumulonimbus Events Over British Columbia in 2017: An Ensemble Model Study of Parameter Sensitivities and Climate Impacts of Wildfire Smoke in the Stratosphere
Abstract The Pyrocumulonimbus (pyroCb) events over British Columbia in 2017 were observed in the lower stratosphere for about 8–10 months after the smoke injections. Several previous studies used global climate models to investigate the physical parameters for the 2017 pyroCb events, but the conclusions show strong model dependency. In this study, we use the Energy Exascale Earth System Model (E3SM) and complete an ensemble of runs exploring three injection parameters: smoke aerosol mass, the percentage of black carbon within the smoke aerosols, and plume injection height. Additionally, we consider the heterogeneous reaction of ozone and primary organic matter. According to the satellite daily observed aerosol optical depth (AOD), we find that the best ensemble member is the simulation with 0.4 Tg of smoke, 3% of which is black carbon, a 13.5 km smoke injection height, and a 10 −5 probability factor of the heterogeneous reaction. Besides AOD, we examine the ensemble score based on the metrics used in previous studies: the metrics of the extinction coefficient at 18 km altitude and the maximum plume height. The conclusion of the best estimate of the injection parameters for 2017 pyroCb events shows strong not only model but also evaluation metric dependency. We use the Random Forest machine learning technique to quantify the relative importance of each parameter in accurately simulating the 2017 pyroCb events and find that the injection height is the most critical feature, no matter which metric is used to score the ensemble members.
54 ENVIRONMENTAL SCIENCES↗
Automated high-throughput tensile testing reveals stochastic process parameter sensitivity
The mechanical properties of additively manufactured metals tend to show high variability, due largely to the stochastic nature of defect formation during the printing process. This study seeks to understand how automated high throughput testing can be utilized to understand the variable nature of additively manufactured metals at different print conditions, and to allow for statistically meaningful analysis. This is demonstrated by analyzing how different processing parameters, including laser power, scan velocity, and scan pattern, influence the tensile behavior of additively manufactured stainless steel 316L utilizing a newly developed automated test methodology. Microstructural characterization through computed tomography and electron backscatter diffraction is used to understand some of the observed trends in mechanical behavior. Specifically, grain size and morphology are shown to depend on processing parameters and influence the observed mechanical behavior. In the current study, laser-powder bed fusion, also known as selective laser melting or direct metal laser sintering, is shown to produce 316L over a wide processing range without substantial detrimental effect on the tensile properties. Ultimate tensile strengths above 600 MPa, which are greater than that for typical wrought annealed 316L with similar grain sizes, and elongations to failure greater than 40% were observed. As a result, it is demonstrated that this process has little sensitivity to minor intentional or unintentional variations in laser velocity and power.
36 MATERIALS SCIENCE↗
A two-fluid single-column model of turbulent shallow convection, Part III: Results and parameter sensitivity
Two-fluid modelling has recently emerged as a promising approach to representing cumulus convection in weather and climate models. This study applies the two-fluid model described in Part II Thuburn et al., 2021b to a shallow cumulus convection case study over land (ARM). Large eddy simulation data is used to tune the majority of the closures that determine the properties of entrained and detrained air. The two-fluid model is generally able to reproduce the profiles of the mean and turbulent quantities over all stages of the diurnal cycle. As such, the initiation of shallow convection and the evolution of the cloud layer are well captured. The robustness of the two-fluid model is further verified using a steady-state test case (BOMEX), in which the cloud properties are also well modelled.
54 ENVIRONMENTAL SCIENCES↗
Predicting High Energy Arcing Fault Zones of Influence for Aluminum Using an Arc Flash Modeling Approach: Evaluation of a model bias, uncertainty, parameter sensitivity and zone of influence estimation
This report documents the development of an arc flash hazard model to calculate the incident energy and zone of influence from high energy arcing faults involving aluminum. The NRC has identified the potential for (HEAFs) involving aluminum to increase the damage zone beyond what is currently postulated in fire probabilistic risk assessment (PRA) methodologies. To estimate the hazard from HEAFs involving aluminum an arc flash model was developed. Differences between the initial model and nuclear power plant (NPP) fire PRA scenarios were identified. Modification of the initial model established from existing literature and test data was used to minimize these differences. The developed model was evaluated against NRC datasets to understand the model prediction and relative uncertainties. Finally, a range of fire PRA zone of influences (ZOI) were developed based on the developed model, target fragility estimates and update HEAF PRA methodology. The results were developed to support an NRC LIC-504 evaluation in tandem with other modeling efforts. The report documents the effort and provides a reference for any future advancements in arc flash modeling.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Ducted Fuel Injection versus Conventional Diesel Combustion: An Operating-Parameter Sensitivity Study Conducted in an Optical Engine with a Four-Orifice Fuel Injector
Ducted fuel injection (DFI) has been shown to attenuate engine-out soot emissions from diesel engines. The concept is to inject fuel through a small tube within the combustion chamber to enable lower equivalence ratios at the autoignition zone, relative to conventional diesel combustion. Previous experiments have demonstrated that DFI enables significant soot attenuation relative to conventional diesel combustion for a small set of operating conditions at relatively low engine loads. This is the first study to compare DFI to conventional diesel combustion over a wide range of operating conditions and at higher loads (up to 8.5 bar gross indicated mean effective pressure) with a four-orifice fuel injector. This study compares DFI to conventional diesel combustion through sweeps of intakeoxygen mole fraction (XO 2 ), injection duration, intake pressure, start of combustion (SOC) timing, fuel-injection pressure, and intake temperature. DFI is shown to curtail engine-out soot emissions at all tested conditions. Under certain conditions, DFI can attenuate engine-out soot by over a factor of 100. In addition to producing significantly lower engine-out soot emissions, DFI enables the engine to be operated at low-NO x conditions that are not feasible with conventional diesel combustion due to high soot emissions.
42 ENGINEERING↗
Identification of visual evoked response parameters sensitive to pilot mental state
Systems analysis techniques were developed and demonstrated for modeling the electroencephalographic (EEG) steady state visual evoked response (ssVER), for use in EEG data compression and as an indicator of mental workload. The study focused on steady state frequency domain stimulation and response analysis, implemented with a sum-of-sines (SOS) stimulus generator and an off-line describing function response analyzer. Three major tasks were conducted: (1) VER related systems identification material was reviewed; (2) Software for experiment control and data analysis was developed and implemented; and (3) ssVER identification and modeling was demonstrated, via a mental loading experiment. It was found that a systems approach to ssVER functional modeling can serve as the basis for eventual development of a mental workload indicator. The review showed how transient visual evoked response (tVER) and ssVER research are related at the functional level, the software development showed how systems techniques can be used for ssVER characterization, and the pilot experiment showed how a simple model can be used to capture the basic dynamic response of the ssVER, under varying loads.
Zacharias, G. L.↗
Preliminary investigation of parameter sensitivities for atmospheric entry and aerobraking at Mars
The proposed manned Mars mission will need to be as weight efficient as possible. A way of lowering the weight of the vehicle by using aeroassist braking instead of retro-rockets to slow a craft once it reaches its destination is discussed. The two vehicles studied are a small vehicle similar in size to the Mars Rover Sample Return (MRSR) vehicle and a larger vehicle similar in size to a six-person Manned Mars Mission (MMM) vehicle. Simulated entries were made using various coefficients of lift (C sub L), coefficients of drag (C sub D), and lift-to-drag ratios (L/D). A range of acceptable flight path angles with their corresponding bank angle profiles was found for each case studied. These ranges were then compared, and the results are reported here. The sensitivity of velocity and acceleration to changes in flight path angle and bank angle is also included to indicate potential problem areas for guidance and navigation system design.
Lee, Mary C.↗
Ducted Fuel Injection vs. Conventional Diesel Combustion: An Operating-Parameter Sensitivity Study Conducted in an Optical Engine with a Four-Orifice Fuel Injector.
Abstract not provided.
Nilsen, Christopher William↗
Ducted Fuel Injection vs. Conventional Diesel Combustion: An Operating-Parameter Sensitivity Study Conducted in an Optical Engine with a Four-Orifice Fuel Injector.
Abstract not provided.
Nilsen, Christopher William↗