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Mikaelsson, P., Andersson, T. & Olsson, M. (2019). Including deformation in a model for engine block dynamics: measurement and prediction of vibration. International Journal of Vehicle Design. Heavy Vehicle Design, 26(1), 55-68
Open this publication in new window or tab >>Including deformation in a model for engine block dynamics: measurement and prediction of vibration
2019 (English)In: International Journal of Vehicle Design. Heavy Vehicle Design, ISSN 1744-232X, E-ISSN 1741-5152, Vol. 26, no 1, p. 55-68Article in journal (Refereed) Published
Abstract [en]

Internal combustion engines (ICE) are sources of vibration in many applications. Engine mounted components need to be designed with respect to fatigue, to withstand these vibrations. In order to compute an estimate of the fatigue life of a component, the vibration load needs to be known. A methodology that is based on a seven degree of freedom model to represent the engine block is proposed. By fitting measured accelerometer data to this model, acceleration levels in arbitrary positions and directions, related to the engine block, may be computed. Results presented for an engine vibration measurement show good agreement between measured and computed vibration levels. A measure to find erroneous accelerometer definitions is also proposed and exemplified through measurement results. The method also enables pointing out local dynamic phenomena at measurement points.

Place, publisher, year, edition, pages
INDERSCIENCE ENTERPRISES LTD, 2019
Keywords
engine, engine block vibrations, engine block twist, rigid body vibrations, vibration measurement, vibration estimation
National Category
Applied Mechanics
Identifiers
urn:nbn:se:kth:diva-241191 (URN)10.1504/IJHVS.2019.097107 (DOI)000454252300003 ()2-s2.0-85059785741 (Scopus ID)
Note

QC 20190121

Available from: 2019-01-21 Created: 2019-01-21 Last updated: 2019-01-21Bibliographically approved
Mansour, R., Kulachenko, A., Chen, W. & Olsson, M. (2019). Stochastic constitutive model of isotropic thin fiber networks based on stochastic volume elements. Materials, 12(3), Article ID 538.
Open this publication in new window or tab >>Stochastic constitutive model of isotropic thin fiber networks based on stochastic volume elements
2019 (English)In: Materials, ISSN 1996-1944, E-ISSN 1996-1944, Vol. 12, no 3, article id 538Article in journal (Refereed) Published
Abstract [en]

Thin fiber networks are widely represented in nature and can be found in man-made materials such as paper and packaging. The strength of such materials is an intricate subject due to inherited randomness and size-dependencies. Direct fiber-level numerical simulations can provide insights into the role of the constitutive components of such networks, their morphology, and arrangements on the strength of the products made of them. However, direct mechanical simulation of randomly generated large and thin fiber networks is characterized by overwhelming computational costs. Herein, a stochastic constitutive model for predicting the random mechanical response of isotropic thin fiber networks of arbitrary size is presented. The model is based on stochastic volume elements (SVEs) with SVE size-specific deterministic and stochastic constitutive law parameters. The randomness in the network is described by the spatial fields of the uniaxial strain and strength to failure, formulated using multivariate kernel functions and approximate univariate probability density functions. The proposed stochastic continuum approach shows good agreement when compared to direct numerical simulation with respect to mechanical response. Furthermore, strain localization patterns matched the one observed in direct simulations, which suggests an accurate prediction of the failure location. This work demonstrates that the proposed stochastic constitutive model can be used to predict the response of random isotropic fiber networks of arbitrary size.

Place, publisher, year, edition, pages
MDPI AG, 2019
Keywords
Mechanical failure, Multi-scale modeling, Plastic softening, Stochastic volume element (SVE), Strain localization, Thin fiber networks, Constitutive models, Failure (mechanical), Fibers, Forecasting, Numerical models, Packaging materials, Probability density function, Random processes, Stochastic systems, Mechanical failures, Strain localizations, Thin fibers, Volume elements, Stochastic models
National Category
Mathematics
Identifiers
urn:nbn:se:kth:diva-248188 (URN)10.3390/ma12030538 (DOI)000460768000207 ()2-s2.0-85061487661 (Scopus ID)
Note

QC 20190412

Available from: 2019-04-12 Created: 2019-04-12 Last updated: 2019-05-20Bibliographically approved
Mansour, R. & Olsson, M. (2018). Efficient Reliability Assessment With the Conditional Probability Method. Journal of mechanical design (1990), 140(8), Article ID 081402.
Open this publication in new window or tab >>Efficient Reliability Assessment With the Conditional Probability Method
2018 (English)In: Journal of mechanical design (1990), ISSN 1050-0472, E-ISSN 1528-9001, Vol. 140, no 8, article id 081402Article in journal (Refereed) Published
Abstract [en]

Reliability assessment is an important procedure in engineering design in which the probability of failure or equivalently the probability of survival is computed based on appropriate design criteria and model behavior. In this paper, a new approximate and efficient reliability assessment method is proposed: the conditional probability method (CPM). Focus is set on computational efficiency and the proposed method is applied to classical load-strength structural reliability problems. The core of the approach is in the computation of the probability of failure starting from the conditional probability of failure given the load. The number of function evaluations to compute the probability of failure is a priori known to be 3n+2 in CPM, where n is the number of stochastic design variables excluding the strength. The necessary number of function evaluations for the reliability assessment, which may correspond to expensive computations, is therefore substantially lower in CPM than in the existing structural reliability methods such as the widely used first-order reliability method (FORM).

Place, publisher, year, edition, pages
ASME, 2018
National Category
Applied Mechanics
Identifiers
urn:nbn:se:kth:diva-232386 (URN)10.1115/1.4040170 (DOI)000437343400003 ()2-s2.0-85051027045 (Scopus ID)
Note

QC 20180727

Available from: 2018-07-27 Created: 2018-07-27 Last updated: 2018-10-16Bibliographically approved
Sandberg, D., Mansour, R. & Olsson, M. (2017). Fatigue probability assessment including aleatory and epistemic uncertainty with application to gas turbine compressor blades. International Journal of Fatigue, 95, 132-142
Open this publication in new window or tab >>Fatigue probability assessment including aleatory and epistemic uncertainty with application to gas turbine compressor blades
2017 (English)In: International Journal of Fatigue, ISSN 0142-1123, E-ISSN 1879-3452, Vol. 95, p. 132-142Article in journal (Refereed) Published
Abstract [en]

In, this work, a new method for fatigue probability assessment is introduced. The method is applied to a bladed disk in a gas turbine for computation of the high cycle fatigue probability. Both epistemic and aleatory uncertainties are modeled. The aleatory uncertainty is of two types: Variable aleatory uncertainty is modeled by use of stochastic variables that influence the problem, including both design variables and stochastic parameters. Physical aleatory uncertainty is modeled by use of a probability that remains even if all stochastic variables are replaced by deterministic values. The fatigue behavior of a material exhibits physical aleatory uncertainty. The results show that the epistemic uncertainty in the modeling of the aero-forcing gives the major contribution to uncertainty in the computed failure probability. The new method is also used to study the influence on the probability of high cycle fatigue that comes from the stochastic variables.

Place, publisher, year, edition, pages
Elsevier, 2017
Keywords
Failure probability, Fatigue assessment, High cycle fatigue, Uncertainty, Compressor blade
National Category
Materials Engineering
Identifiers
urn:nbn:se:kth:diva-199462 (URN)10.1016/j.ijfatigue.2016.10.001 (DOI)000389159700012 ()2-s2.0-84992210929 (Scopus ID)
Note

QC 20170123

Available from: 2017-01-23 Created: 2017-01-09 Last updated: 2017-11-29Bibliographically approved
Mansour, R. & Olsson, M. (2016). The response surface single loop reliability-based design optimization method with reliability requirement on system failure. In: Proceedings of the ASME Design Engineering Technical Conference: . Paper presented at ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2016, 21 August 2016 through 24 August 2016. American Society of Mechanical Engineers (ASME)
Open this publication in new window or tab >>The response surface single loop reliability-based design optimization method with reliability requirement on system failure
2016 (English)In: Proceedings of the ASME Design Engineering Technical Conference, American Society of Mechanical Engineers (ASME) , 2016Conference paper, Published paper (Refereed)
Abstract [en]

In reliability-based design optimization (RBDO), an optimal design which minimizes an objective function while satisfying a number of probabilistic constraints is found. As opposed to deterministic optimization, statistical uncertainties in design variables and design parameters have to be taken into account in the design process in order to achieve a reliable design. In the most widely used RBDO approaches, the First-Order Reliability Method (FORM) is used in the probability assessment. This involves locating the Most Probable Point (MPP) of failure, or the inverse MPP, either exactly or approximately. If exact methods are used, an optimization problem has to be solved, typically resulting in computationally expensive double loop or decoupled loop RBDO methods. On the other hand, locating the MPP approximately typically results in highly efficient single loop RBDO methods since the optimization problem is not necessary in the probability assessment. However, since all these methods are based on FORM, which in turn is based on a linearization of the deterministic constraints at the MPP, they may suffer inaccuracies associated with neglecting the nonlinearity of deterministic constraints. In a previous paper presented by the authors, the Response Surface Single Loop (RSSL) Reliability-based design optimization method was proposed. The RSSL-method takes into account the non-linearity of the deterministic constraints in the computation of the probability of failure and was therefore shown to have higher accuracy than existing RBDO methods. The RSSL-method was also shown to have high efficiency since it bypasses the concept of an MPP. In RSSL, the deterministic solution is first found by neglecting uncertainties in design variables and parameters. Thereafter quadratic response surface models are fitted to the deterministic constraints around the deterministic solution using a single set of design of experiments. The RBDO problem is thereafter solved in a single loop using a closed-form second order reliability method (SORM) which takes into account all elements of the Hessian of the quadratic constraints. In this paper, the RSSL method is used to solve the more challenging system RBDO problems where all constraints are replaced by one constraint on the system probability of failure. The probabilities of failure for the constraints are assumed independent of each other. In general, system reliability problems may be more challenging to solve since replacing all constraints by one constraint may strongly increase the non-linearity in the optimization problem. The extensively studied reliability-based design for vehicle crash-worthiness, where the provided deterministic constraints are general quadratic models describing the system in the whole region of interest, is used to demonstrate the capabilities of the RSSL method for problems with system reliability constraints.

Place, publisher, year, edition, pages
American Society of Mechanical Engineers (ASME), 2016
Keywords
Accidents, Computer aided design, Crashworthiness, Design of experiments, Failure analysis, Image segmentation, Inverse problems, Machine design, Optimization, Probability, Product design, Safety engineering, Structural analysis, Surface properties, Systems engineering, Deterministic optimization, First order reliability methods, Probabilistic constraints, Reliability based design, Reliability requirements, Reliability-based design optimization, Second-order reliability methods, System reliability constraints, Reliability
National Category
Computational Mathematics
Identifiers
urn:nbn:se:kth:diva-202160 (URN)10.1115/DETC2016-60505 (DOI)2-s2.0-85007591238 (Scopus ID)9780791850114 (ISBN)
Conference
ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2016, 21 August 2016 through 24 August 2016
Note

QC 20170308

Available from: 2017-03-08 Created: 2017-03-08 Last updated: 2017-03-08Bibliographically approved
Mikaelsson Elmén, P., Andersson, T. & Olsson, M.Including deformation in a model for engine blockdynamics: measurement and prediction of vibration.
Open this publication in new window or tab >>Including deformation in a model for engine blockdynamics: measurement and prediction of vibration
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Internal combustion engines (ICE) are sources of vibration in many applications. Engine mounted components need to be designed with respect to fatigue, to withstand these vibrations. In order to compute an estimate of the fatigue life of a component, the vibration load needs to be known. A methodology that is based on a seven degree of freedom model to represent the engine block is proposed. By fitting measured accelerometer data to this model, acceleration levels in arbitrary positions and directions, related to the engine block, may be computed. Results presented for an engine vibration measurement show good agreement between measured and computed vibration levels. A measure to find erroneous accelerometer definitions is also proposed and exemplified through measurement results. The method also enables pointing out local dynamic phenomena at measurement points.

Keywords
engine, engine block vibrations, engine block twist, rigid body vibrations, vibration measurement, vibration estimation
National Category
Other Mechanical Engineering
Research subject
Solid Mechanics
Identifiers
urn:nbn:se:kth:diva-220536 (URN)
Note

QC 20171229

Available from: 2017-12-22 Created: 2017-12-22 Last updated: 2017-12-29Bibliographically approved
Mikaelsson Elmén, P., Olsson, M. & Andersson, T.Inclusion of assumed bending and torsion modes for prediction of engine block vibrations.
Open this publication in new window or tab >>Inclusion of assumed bending and torsion modes for prediction of engine block vibrations
(English)Manuscript (preprint) (Other academic)
Abstract [en]

For existing engine types, measured vibrations are commonly used as input to computations and shake rig tests. Accelerations are possible to compute in positions that have not been measured by fitting measured accelerometer data to a discretised engine block motion description. The computed accelerations can be used in fatigue risk estimation for engine components, mounted in new positions. In addition to the rigid body motion, engine block twist has previously successfully been included to better describe the engine block vibration. In the current paper, three additional deformation modes, of bending type, are suggested in order to describe engine block motions even better. The motion description is validated with an engine vibration measurement on a Scania inline six cylinder, heavy-duty diesel engine. An error measure for RMS vibration, summed for all sensors, is used to rank the studied deformation modes. In the studied frequency range, the most important deformation mode is the engine block twist. Including bending deformation increases the accuracy of the engine block vibration description but it also increases the demands on instrumentation.

Keywords
engine, engine block vibrations, engine block twist, engine block bending, rigid body vibrations, vibration measurement, vibration estimation, assumed modes, bending modes, torsion modes
National Category
Other Mechanical Engineering
Research subject
Solid Mechanics
Identifiers
urn:nbn:se:kth:diva-220537 (URN)
Note

QC 20171229

Available from: 2017-12-22 Created: 2017-12-22 Last updated: 2017-12-29Bibliographically approved
Mikaelsson Elmén, P., Andersson, T. & Olsson, M.Modification of measured engine vibrations for addition or removal of engine mounted components.
Open this publication in new window or tab >>Modification of measured engine vibrations for addition or removal of engine mounted components
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Internal combustion engines are used in many applications. The same engine type may have different components mounted to it depending on the application. These engine mounted components need to be designed with respect to fatigue to withstand the engine vibrations. Measured engine vibrations are commonly used as input data for fatigue estimation. Some engine mounted components have themselves significant effect on the engine block vibrations. A method is presented on how measured engine vibration time signals can be modified for addition, or removal, of an engine mounted component. The dynamic characteristics of the component are here captured from measurements during engine operation but can also be extracted from a corresponding finite element model. Results of modification are presented for a heavy-duty inline, five cylinder diesel engine, with and without a 29 kg brake air compressor.

Keywords
engine, engine block vibration, engine block twist, vibration measurement, vibration estimation, rigid body vibrations, torsion modes, system modification, vibration modification
National Category
Other Mechanical Engineering
Research subject
Solid Mechanics
Identifiers
urn:nbn:se:kth:diva-220539 (URN)
Note

QC 20171229

Available from: 2017-12-22 Created: 2017-12-22 Last updated: 2017-12-29Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-8068-2360

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