A SIMPLIFIED STATISTICAL MODEL FOR MISSILE LAUNCHING - III
Statistical analysis of missile launching
LAUNCHING↗
SEARCH · Engineering Papers
Results for “statistical modeling”
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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Study of Analytic Statistical Model for Decay of Light and Medium Mass Nuclei in Nuclear Fragmentation
The angular momentum independent statistical decay model is often applied using a Monte-Carlo simulation to describe the decay of prefragment nuclei in heavy ion reactions. This paper presents an analytical approach to the decay problem of nuclei with mass number less than 60, which is important for galactic cosmic ray (GCR) studies. This decay problem of nuclei with mass number less than 60 incorporates well-known levels of the lightest nuclei (A less than 11) to improve convergence and accuracy. A sensitivity study of the model level density function is used to determine the impact on mass and charge distributions in nuclear fragmentation. This angular momentum independent statistical decay model also describes the momentum and energy distribution of emitted particles (n, p, d, t, h, and a) from a prefragment nucleus.
Cucinotta, Francis A.↗
Statistical Modeling and Analysis of k -Layer Coverage of Two-Dimensional Materials in Inkjet Printing Processes
Two-dimensional layered materials/flakes, also known as crystalline atom-thick layer nanosheets, have recently been receiving great attention in electronics fabrication due to their unique and intriguing properties. The k-layer coverage area (i.e., the area covered by k number of overlapping layers) of the printed flake pattern significantly impacts on the properties of the printed electronics. In this work, we constructed a statistical model to describe the k-layer coverage of randomly distributed two-dimensional materials. A series of results are obtained to provide not only the expectation but also the variance of the coverage area. The boundary effects on the random flakes coverage are also studied. In addition, an approximated statistical testing approach is also developed in this work to detect abnormal coverage patterns. Furthermore, the case studies based on simulated data and real flakes images obtained from the inkjet printing process demonstrate the accuracy and effectiveness of the proposed model and analysis methods.
36 MATERIALS SCIENCE↗
Deconvolving distribution of relaxation times, resistances and inductance from electrochemical impedance spectroscopy via statistical model selection: Exploiting structural-sparsity regularization and data-driven parameter tuning
The distribution of relaxation times (DRT) has drawn increasing attention for interpreting electrochemical impedance spectroscopy (EIS). Deconvolution of DRT from EIS is a challenging ill-posed problem that requires regularization methods. In this work, we formulate DRT reconstruction task as a statistical model selection problem with structural-sparsity penalties. We utilize the Elastic net regularization that simultaneously benefits from Ridge and Lasso regularizations with optimal tuning parameter automatically determined by the information criteria. We benchmark our approach on four synthetic experiments (a ZARC element, ZARC mixtures, a RC circuit and a Fractal element) and two real EIS datasets of a Lithium ion battery and an organic-inorganic halide class of perovskites in oxygen environment at different gas pressures. We demonstrate the superiority of proposed model selection procedure, that is capable of eliminating pseudo peaks and representing asymmetries in DRT as well as precisely estimating resistances. Here, we highlight our approach is robust to reducing and subsampling EIS frequency range, making it a promising tool for timing-resolved, localized and large scale EIS data analysis. For the Lithium ion battery data analysis, we extend the classical DRT model to incorporate the inductive effect and illustrate DRT as a guidance for equivalent circuit modeling to refine impedance reconstruction at low risks of overfitting. Furthermore, the structural-sparsity regularization could be extended for multidimensional and Bayesian EIS data analysis.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A statistical model to estimate refractivity turbulence structure constant C sub n sup 2 in the free atmosphere
A computer program has been tested and documented (Warnock and VanZandt, 1985) that estimates mean values of the refractivity turbulence structure constant in the stable free atmosphere from standard National Weather Service balloon data or an equivalent data set. The program is based on the statistical model for the occurrence of turbulence developed by VanZandt et al. (1981). Height profiles of the estimated refractivity turbulence structure constant agree well with profiles measured by the Sunset radar with a height resolution of about 1 km. The program also estimates the energy dissipation rate (epsilon), but because of the lack of suitable observations of epsilon, the model for epsilon has not yet been evaluated sufficiently to be used in routine applications. Vertical profiles of the refractivity turbulence structure constant were compared with profiles measured by both radar and optical remote sensors and good agreement was found. However, at times the scintillometer measurements were less than both the radar and model values.
Warnock, J. M.↗
Approaching hydro-equivalent ignition in laser direct-drive via target design optimization using novel statistical modeling
Laser direct-drive offers significant advantages in terms of target simplicity, improved energy coupling, and large fuel masses over indirect drive. However, performance degradations from hydrodynamic and laser-plasma instabilities seeded and driven by the direct illumination pose limitations on the parameter space available for achieving ignition. In this paper, new design improvements are identified to forge a path forward for a hydro-equivalent ignition demonstration. The first is related to a new formulation of the statistical model (SM) used to accurately predict target performance directly from input parameters such as laser pulse shape and target specifications. This new SM formulation provides direct guidance on target dimensions and laser beam-to-target radius to achieve the highest fusion yield on the OMEGA laser. The second improvement comes from cooling the deuterium–tritium (DT) ice layer below the triple point right before shot time leading to lower DT vapor densities and higher convergence. Guided by these design improvements, a Bayesian optimization algorithm was used to design an implosion that is predicted to closely approach a Lawson triple product that hydrodynamically scales to ignition if equivalent laser–target coupling is achieved at laser energies typical of the National Ignition Facility.
Deuterium↗
Probability density function shape sensitivity in the statistical modeling of turbulent particle dispersion
The performance of a recently introduced statistical transport model for turbulent particle dispersion is studied here for rigid particles injected into a round turbulent jet. Both uniform and isosceles triangle pdfs are used. The statistical sensitivity to parcel pdf shape is demonstrated.
Litchford, Ron J.↗
Statistical Modeling of Quiet Sonic Boom Community Response Survey Data
The existing ban on commercial supersonic flight overland is largely due to the effects of loud and startling sonic booms on communities. NASA is planning a nationwide campaign of community response surveys using the experimental X-59 Quiet SuperSonic Technology (X-59 QueSST) aircraft to understand how communities perceive the sounds of quiet supersonic flight. The X-59 community response survey data will be presented to noise regulators, who are considering replacing the ban with a noise-based certification limit so quiet supersonic vehicles can fly over land. In this document, we use pilot community response survey data to explore and assess multiple approaches to statistically model the dose-response relationship between single-event sonic boom sound exposure and human annoyance. The models have two primary functions—estimating two types of quantities that support setting regulations and experimental design of future surveys.
Jasme Lee↗
Statistical modelling and Bayesian inversion for a Compton imaging system: application to radioactive source localization
Abstract This paper presents a statistical forward model for a Compton imaging system, called Compton imager. This system, under development at the University of Illinois Urbana Champaign, is a variant of Compton cameras with a single type of sensors which can simultaneously act as scatterers and absorbers. This imager is convenient for imaging situations requiring a wide field of view. The proposed statistical forward model is then used to solve the inverse problem of estimating the location and energy of point-like sources from observed data. This inverse problem is formulated and solved in a Bayesian framework by using a Metropolis within Gibbs algorithm for the estimation of the location, and an expectation-maximization algorithm for the estimation of the energy. This approach leads to more accurate estimation when compared with the deterministic standard back-projection approach, with the additional benefit of uncertainty quantification in the low photon imaging setting.
Tarpau, Cécilia (ORCID:0000000286539490)↗
Proton capture reaction cross section measurements on Er 162 as a probe of statistical model calculations
It is crucial to measure reaction cross sections relevant to the astrophysical γ process so that theoretical reaction rates can be tested and validated with experimental data. Here, the total cross sections for the 162 Er(p,γ) 163 Tm and the 162 Er(p,n) 162 Tm reactions have been measured by the activation method in center-of-mass energies from 3.973 to 8.944 MeV and from 5.962 to 8.944 MeV, respectively. The nucleus 162 Er is the heaviest p nuclide to be measured by the activation method using γ -ray spectroscopy, so far. It is important to note that the energy range for the (p,γ) reaction measurement covers a large fraction of the astrophysically relevant energy region between 2.71 and 5.34 MeV. The targets were prepared by evaporating 28.2 % isotopically enriched 162 Er 2 O 3 powder onto carbon backing foils, and bombarded with proton beams provided by the FN Tandem Accelerator at the University of Notre Dame. The reaction yields have been determined by the observed activity of produced radioactive isotopes, which was detected offline by a high-purity germanium detector. The results are presented and compared with calculations from two statistical model codes: NON-SMOKER and TALYS.
150 ≤ A ≤ 189↗
The beta distribution - A statistical model for world cloud cover
A statistical distribution representing worldwide cloud cover is obtained as a basis for an empirical global cloud cover model incorporating some 29 regions of the globe which are of interest to NASA's Skylab Program. A total of 160 representative empirical cloud cover distributions were investigated with the conclusion that the beta probability distribution is an adequate model for world cloud cover.
Falls, L. W.↗
Statistical Modeling of Peak Accelerating Gradients in LCLS-II and LCLS-II-HE
In this report, we study the vertical test gradient performance and the gradient degradation between vertical test and cryomodule test for the 1.3 GHz LCLS-II cavities. We develop a model of peak gradient statistics, and use our understanding of the LCLS-II results and the changes implemented for LCLS-II-HE to estimate the expected gradient statistics for the new machine. Finally, we lay out a plan to ensure that the LCLS-II-HE cryomodule gradient specifications are met while minimizing cavity disqualification by introducing a variable acceptance threshold for the accelerating gradient.
43 PARTICLE ACCELERATORS↗
A Statistical Model to Predict the Extratropical Transition of Tropical Cyclones
This paper introduces a logistic regression model for the extratropical transition(ET) of tropical cyclones in the North Atlantic and the Western North Pacific, using elastic net regularization to select predictors and estimate coefficients.Predictors are chosen from the 1979-2017 best track and reanalysis datasets, and verification is done against the tropical/extratropical labels in the best track data. In an independent test set, the model skillfully predicts ET at lead times up to two days, with latitude and sea surface temperature as its most important predictors. At a lead time of 24 h, it predicts ET with a Matthews correlation coefficient of 0.4 in the North Atlantic, and 0.6 in the Western North Pacific. It identifies 80% of storms undergoing ET in the North Atlantic, and 92% of those in the Western North Pacific. 90% of transition time errors are less than 24 h. Select examples of the model's performance on individual storms illustrate its strengths and weaknesses.Two versions of the model are presented: an "operational model" that may provide baseline guidance for operational forecasts, and a "hazard model"that can be integrated into statistical TC risk models. As instantaneous diagnostics for tropical/extratropical status, both models' zero lead time predictions perform about as well as the widely used Cyclone Phase Space (CPS) in the Western North Pacific and better than the CPS in the North Atlantic, and predict the timings of the transitions better than CPS in both basins.
Melanie Bieli↗
A Practical Statistical Model for Telecommunications Performance Uncertainty
A statistical method, the probability distribution method, is presented which will give the probability of link performance values. The advantages of a design control procedure are preserved and optimum use of the system capabilities is permitted by improving the accuracy and completeness of the system model.
Yuen, J. H.↗
Statistical model of meteor streams. I - Analysis of the model. II - Major showers
Meteor streams dynamic properties, computing mean orbit elements with statistical mathematical model
Sekanina, Z.↗
A statistical model of carbon/carbon composite failure
A failure model which considers the stochastic nature of the damage accumulation process is essential to assess reliability and to accurately scale the results from standard test specimens to composite structures. A superior filamentary composite for high temperature applications is composed of carbon fibers in a carbon matrix. Carbon-carbon composites are the strongest known material at very high temperatures. Since there appears to be a significant randomness in C-C material strength which cannot be controlled or detected with current technology, a better model of the material failure based upon statistical principles should be used. Simple applications of the model based upon the limited data provide encouraging results that indicate that better design of test specimens would provide a substantially higher prediction for the design strength of C-C composites. An A-basis strength for the C-C tensile rings from a first stage D-5 billets was estimated. A statistical failure model was developed for these rings which indicates that this strength may be very conservative for larger C-C parts. The analysis may be improved by use of a heterogeneous/noncontinuum finite element approach on the minimechanical level.
Slattery, Kerry T.↗
Statistical models of lunar rocks and regolith
The mathematical, statistical, and computational approaches used in the investigation of the interrelationship of lunar fragmental material, regolith, lunar rocks, and lunar craters are described. The first two phases of the work explored the sensitivity of the production model of fragmental material to mathematical assumptions, and then completed earlier studies on the survival of lunar surface rocks with respect to competing processes. The third phase combined earlier work into a detailed statistical analysis and probabilistic model of regolith formation by lithologically distinct layers, interpreted as modified crater ejecta blankets. The fourth phase of the work dealt with problems encountered in combining the results of the entire project into a comprehensive, multipurpose computer simulation model for the craters and regolith. Highlights of each phase of research are given.
Marcus, A. H.↗
Statistical Models of Fracture Relevant to Nuclear-Grade Graphite: Review and Recommendations
The nuclear-grade (low-impurity) graphite needed for the fuel element and moderator material for next-generation (Gen IV) reactors displays large scatter in strength and a nonlinear stress-strain response from damage accumulation. This response can be characterized as quasi-brittle. In this expanded review, relevant statistical failure models for various brittle and quasi-brittle material systems are discussed with regard to strength distribution, size effect, multiaxial strength, and damage accumulation. This includes descriptions of the Weibull, Batdorf, and Burchell models as well as models that describe the strength response of composite materials, which involves distributed damage. Results from lattice simulations are included for a physics-based description of material breakdown. Consideration is given to the predicted transition between brittle and quasi-brittle damage behavior versus the density of damage (level of disorder) within the material system. The literature indicates that weakest-link-based failure modeling approaches appear to be reasonably robust in that they can be applied to materials that display distributed damage, provided that the level of disorder in the material is not too large. The Weibull distribution is argued to be the most appropriate statistical distribution to model the stochastic-strength response of graphite.
Nemeth, Noel N.↗