The Integrated Test Analysis Process for Structural Dynamic Systems

In this paper two case studies of model validation and verification of large and complex space structures are presented. The first case study focuses on experience gained in performing model validation and verification of the mated Russian Mir Space Station and United States Space Shuttle. This study makes use of dynamic test data taken during the STS-81 flight associated with the Mir Structural Dynamics Experiment. The second case study involves the International Space Station P6 truss segment tested in the launch configuration. In both cases, a newly developed capability within UAI/NASTRAN is used to perform the model validation and verification. Key technical issues raised in these studies provide useful insight for future pretest planning and model validation and verification efforts.

This presentation will provide a summary of the research and applications of structural dynamics model validation at Los Alamos National Laboratory. In this context model validation refers to the assessment of confidence in the usefulness of computational structural dynamics predictions for a particular application. The presentation will cover the problem definition, objectives, and motivation for studying model validation. Current paradigms for the model validation problem will also be presented. Supporting technologies such as uncertainty quantification, global sensitivity analysis, metamodeling, parameter updating, and design of experiments will be discussed, along with their role in the model validation process. The usefulness of model validation results for the computational modeling of system-level structural dynamics will be demonstrated. Examples of model validation techniques applied to transient structural dynamics problems of interest will be shown.

This study focuses on defining and comparing response features that can be used for structural dynamics model validation studies. Features extracted from dynamic responses obtained analytically or experimentally, such as basic signal statistics, frequency spectra, and estimated timeseries models, can be used to compare characteristics of structural system dynamics. By comparing those response features extracted from experimental data and numerical outputs, validation and uncertainty quantification of numerical model containing uncertain parameters can be realized. In this study, the applicability of some response features to model validation is first discussed using measured data from a simple test-bed structure and the associated numerical simulations of these experiments. Issues that must be considered were sensitivity, dimensionality, type of response, and presence or absence of measurement noise in the response. Furthermore, we illustrate a comparison method of multivariate feature vectors for statistical model validation. Results show that the outlier detection technique using the Mahalanobis distance metric can be used as an effective and quantifiable technique for selecting appropriate model parameters. However, in this process, one must not only consider the sensitivity of the features being used, but also correlation of the parameters being compared.

The experimental validation of an accurate dynamic model of flexible multi-body planar mechanisms is presented in this paper. The proposed mathematical model, which is valid for whatever planar mechanism with any number of flexible links, accounts for the geometric and inertial nonlinearities of the mechanism, and considers coupling effects among rigid-body and elastic motion as well. In order to experimentally validate the dynamic model, a flexible five-bar planar linkage actuated by two electric motors is employed as a test case. The experimentally measured deformations and accelerations of the flexible links are compared with the numerical results obtained by simulating the system dynamic behavior through the mathematical model. It turns out that the experimental results are in good agreement with the numerical ones, thus proving that the dynamical model proposed is very effective in the difficult task of accurately representing the dynamic behavior of flexible mechanisms.

Indoor air quality inside chemical laboratories subjected to gaseous contaminants was investigated numerically throughout the current research using Ansys Fluent 13. The lab is 4.8 m (L) * 4.3 m (W) * 2.73 m (H). The model was built and mesh was generated using Gambit 2.2.30 yielding around 1.4 million cells. To ensure the reliability of the Computational Fluid Dynamics (CFD) model validation was done against experimental data of three cases done by Jin et al. [1]. The model could simulate accurately contaminant mole fraction to the order of 10 Indoor air quality inside chemical laboratories subjected to gaseous contaminants was investigated numerically throughout the current research using Ansys Fluent 13. The lab is 4.8 m (L) * 4.3 m (W) * 2.73 m (H). The model was built and mesh was generated using Gambit 2.2.30 yielding around 1.4 million cells. To ensure the reliability of the Computational Fluid Dynamics (CFD) model validation was done against experimental data of three cases done by Jin et al. [1]. The model could simulate accurately contaminant mole fraction to the order of 10.

Dynamic Process Model Development and Validation with Transient Plant Data Collected from an MEA Test Campaign at the CO2 Technology Center Mongstad

Compact steam bottoming cycles: Model validation with plant data and evaluation of control strategies for fast load changes

Model validation is the procedure whereby the fidelity of a model is evaluated. The traditional approaches to dynamic model validation either rely on the magnitude of the prediction error between the process observations and model outputs or consider the observations and model outputs as time series and use their similarity to assess the closeness of the model to the process. Here, we propose transforming these time series into the time-scale domain, to enhance their delineation, and using image distances between these transformed time series to assess the closeness of the model to the process. It is shown that the image distances provide a more consistent measure of model closeness than available from the magnitude of the prediction error.

In this study, the development and validation of a simplified nonlinear dynamic model of a passive twin-tube hydraulic shock absorber is presented. First, the experimental dynamic response is characterized. Then, the numerical model is presented where flow, pressure, displacement, and velocity are considered. Finally, the numerical–experimental correlation is performed on force-movement dynamic behavior to prove the accuracy of the proposed model. The final goal of the model is to be integrated in a real-time driving simulator for ride comfort studies.

Joined structures are of great industrial relevance. The dynamic effects of joints are, however, often practically difficult to accurately account for in numerical models, as they often lead to local changes in stiffness and damping. This paper discusses the comparison between measurements and simulations of joined panels considering four different joining techniques: adhesive bonding, metal inert gas welding, resistance spot welding and flow drill screwing. An experimental modal analysis is performed on the different systems and the power injection method is applied to determine the loss factors of single plate systems and their joined counterparts. The joined panels are modeled in a holistic simulation environment with particular focus on the joining region, by the application of predefined and generic joint models. A very good agreement is obtained between the simulated dynamic behavior and the experimental results, showing that an accurate representation of the joints has been obtained.

Constitutive modeling is of fundamental important for numerical simulation and analysis of soft biological tissues. The mechanical behaviors of soft tissues are usually highly nonlinear and anisotropic. The complex behavior is the results from the interaction of tissue microstructure. By incorporating information of fiber orientation and distribution at tissue microscopic scale, the structural model avoids ambiguities in material characterization. Moreover, structural models produce much more information than just simple stress-strain results, but can provide much insight into how soft tissues internally reorganize to external loads by adjusting their internal microstructure. Moreover, it is only through simulation of an entire organ system can such information be derived and provide insight into physiological function. However, accurate implementation and rigorous validation of these models remains very limited. In the present study we implemented a structural constitutive model into a commercial finite element package. The structural model was verified against experiential test data for native bovine pericardium and fetal membrane. In addition to prediction of the mechanical response, we demonstrate how a structural model can provide deeper insights into fiber reorientation and fiber recruitment.

The proper simulation of the hygrothermal behaviour of historical buildings is a challenging task with several implications regarding the evaluation of indoor thermal comfort and the suitability of retrofit strategies that comply with the conservation of cultural heritage. An inaccurate simulation may lead to inadequate conclusions, which could result in inappropriate and dangerous actions for the preservation of the heritage buildings.Then calibration and validation of hygrothermal simulation models are essential steps to achieve more accurate and reliable results.Now, although some agencies have developed guidelines and methodologies to carry out the validation of building performance models, all of them are based on energy consumption only. However, since in some buildings the energy consumption data are not always available especially when no operating heating, ventilation and air conditioning system is installed, which is the case of many historical buildings, the microclimatic parameters are usually adopted in the validation process. In this case, neither protocols nor specific parameters have been officially recognised to perform the model validation. The present work reviewed the main approaches used by researchers for building performance model validation with special reference to historical buildings based on microclimatic parameters, highlighting the main advantages and drawbacks of the different methods reviewed. Finally, recommendations to properly carry out the model validation based on microclimatic parameters have been provided. The collected information may be useful to different subjects (e.g. designers, energy auditors, researchers, conservators, buildings’ owners and policy makers) and can drive suitable and reliable retrofit and maintenance interventions.

Temporal persistence in vegetation cover changes observed from satellite: Development of an estimation procedure in the test site of the Mediterranean Italy

A new method for determining the causes of discrepancies between dynamic simulation models and measured data is described. Whilst principally aimed at the validation of building thermal simulation codes, the method may rind application in the validation of simulation models from other disciplines. The new method relies on generating a model of the discrepancies in terms of the variables driving the physical reality which produced the experimental data and the corresponding simulation. Inspection of the resulting error model allows the principal contributors to simulation error to be identified, its dynamic nature to be characterised, and the likely cause of the error to be identified. The method is tested by generating a 'quasi-truth' dataset using the building thermal simulation code SERI-RES. A series of simulations is then prepared with perturbations to selected input parameters. The new tool is found to be capable of recovering details of the perturbations. Finally, the power of the new technique is demonstrated in a series of comparisons between the predictions of the model SERI-RES and data collected in outdoor test rooms. These comparisons reveal that the principal source of error in the predictions is the treatment of the interactions between the heater and the air and fabric of the room. The new technique proves sufficiently sensitive to detect the changing structure of the prediction errors as the position of the heater within the room is changed.

Flare and relief systems are inherently dynamic process. Relief devices (PSV, rupture disc and flare tips) depend on system pipage for specified performance. These dependencies cause both transitory and lasting impacts. These impacts can only be understood by dynamic analysis. The past 10years of application confirm the need for and credibility of dynamic models. This paper details the theoretical development, validation and utilization experience of flare system dynamic models. INTRODUCTION Steady state flowsheet simulators are fairly routine software in today's processplant design environments. Pipeline transients and control system design are recognized dynamic problems and are best analyzed by simulation. However, dynamic simulation is still infrequently practiced. with cost to benefit ratio rapidly in favor of computerization, applications of dynamic simulations in process industries will undoubtedly multiply into the future. This paper describes a class of design problems in which we saw advantage in applying dynamic simulation oil field flare systems are inherent dynamic processes. Relief devices depend on system pipage for specified performance - relief valve capacity dependent on discharge back pressure, header peak pressure dependent on rupture disc burst conditions, radiation imposed limits dependent on peak relief rate, flare equipment size dependent on relief load characteristics and particulars of the staging philosophy. These dependencies cause both transitory and lasting impacts, e. g. temporal overpressure, flow cycling, and flame out events. And these impacts can only be understood by dynamic analysis. The past 10years of application confirm the need for dynamic models and the credibility of this technology improved in close association with better understanding of the complex flare system interactions. FLARE SYSTEM DESIGN CONSIDERATIONS Flare systems are final safeguards against overpressure, during plant transient conditions. The flare system must be designed to relieve excessive pressure to insure safety, specifically not to exceed levels allowed by "Code". API Design Practice 520 & 521 are widely observed as voluntary guidelines on the design and operation of flare systems in the American Petroleum Industry. Two key concepts are particularly applicable to this work. "Pressure relieving devices are installed to ensure that a process system or any of its components are not subject to pressures that exceed the Maximum Allowable Accumulated Pressure." "Fail safe device and automatic equipment should not replace pressure relieving devices as protection for individual process equipment." The first paragraph specifies the requirement of relief devices in the protection of equipment against overpressure. The second paragraph further stipulates that pressure relieving devices cannot be replaced nor substituted. This second paragraph therefore excludes all but pressure relieving devices in flare systems. API (ASME) pressure relieving devices for flare systems are clearly defined as PSV (Pressure Safety Valve), rupture disc and flare tip. ASME section VIII, Div. 1 Code stipulates the pressure relief requirements on unfired pressure vessels.