Dynamic data flow testing

Data flow testing is a particular form of testing that identifies data flow relations as test objectives. Data flow testing has recently attracted new interest in the context of testing object oriented systems, since data flow information is well suited to capture relations among the object states, and can thus provide useful information for testing method interactions. Unfortunately, classic data flow testing, which is based on static analysis of the source code, fails to identify many important data flow relations due to the dynamic nature of object oriented systems. This thesis presents Dynamic Data Flow Testing, a technique which rethinks data flow testing to suit the testing of modern object oriented software. Dynamic Data Flow Testing stems from empirical evidence that we collect on the limits of classic data flow testing techniques. We investigate such limits by means of Dynamic Data Flow Analysis, a dynamic implementation of data flow analysis that computes sound data flow information on program traces. We compare data flow information collected with static analysis of the code with information observed dynamically on execution traces, and empirically observe that the data flow information computed with classic analysis of the source code misses a significant part of information that corresponds to relevant behaviors that shall be tested. In view of these results, we propose Dynamic Data Flow Testing. The technique promotes the synergies between dynamic analysis, static reasoning and test case generation for automatically extending a test suite with test cases that execute the complex state based interactions between objects. Dynamic Data Flow Testing computes precise data flow information of the program with Dynamic Data Flow Analysis, processes the dynamic information to infer new test objectives, which Dynamic Data Flow Testing uses to generate new test cases. The test cases generated by Dynamic Data Flow Testing exercise relevant behaviors that are otherwise missed by both the original test suite and test suites that satisfy classic data flow criteria

High-frequency data observations from space shuttle main engine low pressure fuel turbopump discharge duct flex joint tripod failure investigation

Observations made by Marshall Space Flight Center (MSFC) engineers during their participation in the Space Shuttle Main Engine (SSME) low pressure fuel turbopump discharge duct flex joint tripod failure investigation are summarized. New signal processing techniques used by the Component Assessment Branch and the Induced Environments Branch during the failure investigation are described in detail. Moreover, nonlinear correlations between frequently encountered anomalous frequencies found in SSME dynamic data are discussed. A recommendation is made to continue low pressure fuel (LPF) duct testing through laboratory flow simulations and MSFC-managed technology test bed SSME testing

Artificial neural network to determine dynamic effect in capillary pressure relationship for two-phase flow in porous media with micro-heterogeneities

Open access articleAn artificial neural network (ANN) is presented for computing a parameter of dynamic two-phase flow in porous media with water as wetting phase, namely, dynamic coefficient (τ), by considering micro-heterogeneity in porous media as a key parameter. τ quantifies the dependence of time derivative of water saturation on the capillary pressures and indicates the rates at which a two-phase flow system may reach flow equilibrium. Therefore, τ is of importance in the study of dynamic two-phase flow in porous media. An attempt has been made in this work to reduce computational and experimental effort by developing and applying an ANN which can predict the dynamic coefficient through the “learning” from available data. The data employed for testing and training the ANN have been obtained from computational flow physics-based studies. Six input parameters have been used for the training, performance testing and validation of the ANN which include water saturation, intensity of heterogeneity, average permeability depending on this intensity, fluid density ratio, fluid viscosity ratio and temperature. It is found that a 15 neuron, single hidden layer ANN can characterize the relationship between media heterogeneity and dynamic coefficient and it ensures a reliable prediction of the dynamic coefficient as a function of water saturation

Artificial neural network to determine dynamic effect in capillary pressure relationship for two-phase flow in porous media with micro-heterogeneities

An artificial neural network (ANN) is presented for computing a parameter of dynamic two-phase flow in porous media with water as wetting phase, namely, dynamic coefficient (τ), by considering micro-heterogeneity in porous media as a key parameter. τ quantifies the dependence of time derivative of water saturation on the capillary pressures and indicates the rates at which a two-phase flow system may reach flow equilibrium. Therefore, τ is of importance in the study of dynamic two-phase flow in porous media. An attempt has been made in this work to reduce computational and experimental effort by developing and applying an ANN which can predict the dynamic coefficient through the “learning” from available data. The data employed for testing and training the ANN have been obtained from computational flow physics-based studies. Six input parameters have been used for the training, performance testing and validation of the ANN which include water saturation, intensity of heterogeneity, average permeability depending on this intensity, fluid density ratio, fluid viscosity ratio and temperature. It is found that a 15 neuron, single hidden layer ANN can characterize the relationship between media heterogeneity and dynamic coefficient and it ensures a reliable prediction of the dynamic coefficient as a function of water saturation

Dynamic Characteristics and Stability Analysis of Space Shuttle Main Engine Oxygen Pump

The dynamic characteristics of the Space Shuttle high pressure oxygen pump are presented. Experimental data is presented to show the vibration spectrum and response under actual engine operation and also in spin pit testing for balancing. The oxygen pump appears to be operating near a second critical speed and is sensitive to self excited aerodynamic cross coupling forces in the turbine and pump. An analysis is presented to show the improvement in pump stability by the application of turbulent flow seals, preburner seals, and pump shaft cross sectional modifications

Evaluation of seals for high-performance cryogenic turbomachines

An approach to computing flow and dynamic characteristics for seals or bearings is discussed. The local average velocity was strongly influenced by inlet and exit effects and fluid injection, which in turn drove zones of secondary flow. For the restricted three-dimensional model considered, the integral averaged results were in reasonable agreement with selected data. Unidirectional pressure measurements alone were insufficient to define such flow variations. However, for seal and bearing leakage correlations the principles of corresponding states were found to be useful. Also discussed are three phenomena encountered during testing of three eccentric nonrotating seal configurations for the Space Shuttle Main Engine (SSME) Program. Fluid injection, choking within a seal, and pressure profile crossover are related to postulated zones of secondary flow or separation and to direct stiffness

Preliminary experimental results for a cryogenic brush seal configuration

Preliminary fluid nitrogen flow data are reported for a five-brush, ceramic-coated-rub-runner brush seal system, where the brushes and the rub runner were placed at each end of a centrally pressurized multifunction tester ('back-to-back' set of brushes) and tested at rotor speeds of 0, 10, 18, and 22.5 krpm. After testing, both the brushes and the ceramic-coated rub runner appeared pristine. The coating withstood both the thermomechanical and dynamic loadings with minor wear track scarring. The bristle tips showed some indication of material shearing (smearing) wear. The Ergun porous flow equation was applied to the brush seal data. The Ergun relation, which required heuristic information to characterize the coefficients, fit the gaseous data but was in poor agreement with the fluid results. The brush seal exit conditions were two phase. Two-phase, choked-flow design charts were applied but required one data point at each rotor speed to define the (C(sub f)A x Constant) flow and area coefficients. Reasonable agreement between prediction and data was found, as expected, but such methods are not to be construed as two-phase-flow brush seal analyses

Video Interpolation using Optical Flow and Laplacian Smoothness

Non-rigid video interpolation is a common computer vision task. In this paper we present an optical flow approach which adopts a Laplacian Cotangent Mesh constraint to enhance the local smoothness. Similar to Li et al., our approach adopts a mesh to the image with a resolution up to one vertex per pixel and uses angle constraints to ensure sensible local deformations between image pairs. The Laplacian Mesh constraints are expressed wholly inside the optical flow optimization, and can be applied in a straightforward manner to a wide range of image tracking and registration problems. We evaluate our approach by testing on several benchmark datasets, including the Middlebury and Garg et al. datasets. In addition, we show application of our method for constructing 3D Morphable Facial Models from dynamic 3D data

Visualization design and verification of Ada tasking using timing diagrams

The use of timing diagrams is recommended in the design and testing of multi-task Ada programs. By displaying the task states vs. time, timing diagrams can portray the simultaneous threads of data flow and control which characterize tasking programs. This description of the system's dynamic behavior from conception to testing is a necessary adjunct to other graphical techniques, such as structure charts, which essentially give a static view of the system. A series of steps is recommended which incorporates timing diagrams into the design process. Finally, a description is provided of a prototype Ada Execution Analyzer (AEA) which automates the production of timing diagrams from VAX/Ada debugger output