Last edited by Kara
Tuesday, July 21, 2020 | History

3 edition of Review of probabilistic analysis of dynamic response of systems with random parameters found in the catalog.

Review of probabilistic analysis of dynamic response of systems with random parameters

Review of probabilistic analysis of dynamic response of systems with random parameters

Written in English

Subjects:
• Displacement.,
• Dynamic response.,
• Frequency response.,
• Large space structures.,
• Probability theory.,
• Random variables.,
• Resonant frequencies.,
• Velocity distribution.

• Edition Notes

The Physical Object ID Numbers Statement by F. Kozin and J.M. Klosner. Series NASA contractor report -- NASA CR-186171. Contributions Klosner, J. M., Langley Research Center. Format Microform Pagination 1 v. Open Library OL16125541M

Strategy for selecting representative points via tangent spheres in the probability density evolution method. This course introduces students to the modeling, quantification, and analysis of uncertainty. The tools of probability theory, and of the related field of statistical inference, are the keys for being able to analyze and make sense of data. These tools underlie important advances in many fields, from the basic sciences to engineering and management.

The basic random variables on which random uncertainties can in a given model depend can be viewed as defining a measure space with respect to which the solution to the mathematical problem can be Cited by: Probabilistic Methods of Signal and System Analysis, 3/e stresses the engineering applications of probability theory, presenting the material at a level and in a manner ideally suited to engineering students at the junior or senior level. It is also useful as a review for .

In analysis of algorithms, probabilistic analysis of algorithms is an approach to estimate the computational complexity of an algorithm or a computational problem. It starts from an assumption about a probabilistic distribution of the set of all possible inputs. This assumption is then used to design an efficient algorithm or to derive the complexity of a known algorithm. A recently proposed concept of interval field is implemented to model the intrinsic spatial dependency of the uncertain-but-bounded system parameters. By employing the appropriate discretization scheme, evaluations of natural frequencies for engineering structures involving interval fields can be executed within the framework of the finite element : Jinwen Feng, Qingya Li, Alba Sofi, Guoyin Li, Di Wu, Wei Gao.

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Review of probabilistic analysis of dynamic response of systems with random parameters Download PDF EPUB FB2

Get this from a library. Review of probabilistic analysis of dynamic response of systems with random parameters. [F Kozin; J M Klosner; Langley Research Center.].

of probability theory. The response of dynamic systems to the product-plus-mean process can be determined by the quasi-steady approximation. The addition of the mean value component presents no fundamental difficulty for the analysis of linear dynamic systems, since the response to the independent product and mean value processes.

Featuring aerospace examples and applications, Reliability Analysis of Dynamic Systems presents the very latest probabilistic techniques for accurate and efficient dynamic system reliability analysis.

While other books cover more broadly the reliability techniques and challenges related to large systems, Dr Bin Wu presents a focused discussion of new methods particularly relevant to the reliability analysis of large aerospace systems.

The geometric parameters of composite used in structure usually has the random properties. It is very significant for the reliability and optimization of structure design to research the random response and statistic characteristics of random parameters nonlinear systems.

In this article, we use both of perturbation method and random central different approximation method to study the random Author: Feng Xiang You, Fu He Lu. Probability density evolution method is proposed for dynamic response analysis of structures with random parameters.

In the present paper, a probability de With the state equation expression, the PDEE is further reduced to a one-dimensional partial differential by: ABSTRACT: Risk Analysis Virtual Environment (RAVEN) is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes.

The initial development was aimed at providing dynamic risk analysis capabilities to the Reactor Excursion and Leak AnalysisFile Size: 1MB. one parameter of the system requires a probabilistic analysis to decide the feasibility of the system. In this paper we introduce for the ﬁrst time a response time analysis for systems that have both worst case execution times and minimal inter-arrival times described by probability distributions.

possibly other parameters). Probabilistic analysis of algorithms: What’s it good for. Univ. von Stellenbosch. and support both dynamic insertions and deletions. In a random BST any element has the same probability of being its root; hence the probability that j L = k is 1 =n.

Indicator Random Variable Indicator Random Variable We require to use the indicator random variable to facilitate the use of probabilistic analysis: I {A} = 0 if A does not ocurr 1 if A does ocurr. Using this we have Lemma Given a sample space S and an event A in the sample space S, let XA = I {A}.

Then E [XA] = Pr {A}. 9 / 19 Effects of uncertainties on the dynamic response of the nonlinear vibration systems with general form are investigated. Based on interval mathematics, modeling the uncertain parameters as interval numbers, a non-probabilistic interval analysis method, which estimates the range of the nonlinear dynamic response with the help of Taylor series expansion, is presented, where the partial Cited by: Based on interval mathematics, modeling the uncertain parameters as interval numbers, a non-probabilistic interval analysis method, which estimates the range of the nonlinear dynamic response.

The probability density evolution method (PDEM) for dynamic responses analysis of non-linear stochastic structures is proposed. In the method, the dynamic response of non-linear stochastic structures is firstly expressed in a formal solution, which is a function of the random parameters.

In this sense, the dynamic responses are mutually uncoupled. By this way, the reduced order perturbed equation of the uncertain system can be obtained. And the response of the uncertain system is obtained using probability method.

As a numerical example, a simple piping system is considered as an example structure. The damping and spring constants of the support are considered as the uncertain : Byung-young Moon, Beom-soo Kang, Jung-hyen Park. year t +1 begins, the bass in the lake multiply by a random factor D, where P(D = d) = q(d).

Formulate a dynamic programming recursion that can be used to determine a bass catching strategy that will maximize the owner’s net profit over the next ten years.

At present, the lake conta Size: KB. Response Time Analysis for Fixed-Priority Tasks with Multiple Probabilistic Parameters Dorin Maxim 1,2 3, Liliana Cucu-Grosjean 1 Universite de Lorraine, LORIA, UMRF, France 2 CNRS, LORIA UMRVandoeuvre-les-Nancy, F, France 3 INRIA Nancy-Grand Est, Villers-les-Nancy, F, France @, @   In Stochastic Dynamics of Structures, Li and Chen present a unified view of the theory and techniques for stochastic dynamics analysis, prediction of reliability, and system control of structures within the innovative theoretical framework of physical stochastic systems.

The authors outline the fundamental concepts of random variables, stochastic process and random field, and orthogonal expansion of random functions.

() PDEM-Based Perspective to Probabilistic Seismic Response Analysis and Design of Earthquake-Resistant Engineering Structures.

Natural Hazards ReviewB () A marginal fractional moments based strategy for points selection in seismic response analysis of nonlinear structures with uncertain by: Its intent is to equip readers to formulate, analyze, and evaluate simple and advanced Markov models of systems, ranging from genetics and space engineering to marketing.

More than a collection of techniques, it constitutes a guide to the consistent application of the fundamental principles of probability and linear system theory.5/5(1). Probabilistic structural dynamics offers unparalleled tools for analyzing uncertainties in structural design.

Once avoided because it is mathematically rigorous, this technique has recently remerged with the aide of computer software.

Written by an author/educator with 40 years of experience in structural design, this user friendly manual integrates theories, formulas and mathematical models. In this study, the non-probabilistic dynamic response analysis of a double-disk rotor with uncertain-but-bounded parameters is carried out based on interval analysis in a non-intrusive way.

The FEM is used to derive the deterministic analysis : Chao Fu, Xingmin Ren, Yongfeng Yang. Analyzing Probabilistic Programs with Dynamic Logic Tong Cheng School of Computer Science and Technology Huazhong University of Science and Technology Wuhan, HubeiChina Email: [email protected] Abstract—We present a uniﬁed framework for the analysis of probabilistic programs based on Dynamic Logic in which.The analysis of structures, whether subjected to random or deterministic external loads, has been developed mainly under the assumption that the structure’s parameters are deterministic quantities.

For a significant number of circumstances, this assumption is not valid, and the probabilistic aspects of the structure need to be taken into by: An approach to obtain with acceptable accuracy probabilistic response transformation factors by training an artificial neural network (ANN) model is presented.

The transformation factors are defined as the ratio of the seismic response of multi-degree-of-freedom structures and their equivalent single-degree-of-freedom systems, associated with a given annual exceedance by: 3.