WHAT ABOUT ADIABATIC NORMAL MODES?

2001 ◽  
Vol 09 (01) ◽  
pp. 287-309 ◽  
Author(s):  
A. TOLSTOY
Keyword(s):  
Normal Mode ◽  
Normal Modes ◽  
Single Frequency ◽  
Test Case ◽  
Test Cases ◽  
Flat Bottom ◽  
Energy Conserving ◽  
Water Test ◽  
Independent Behavior ◽  
Benchmark Solutions

In this paper we closely examine the performance of several propagation models, i.e., KRAKEN (coupled and adiabatic) and PE (energy-conserving), applied to a number of the SWAM'99 range-dependent shallow water test cases (FLAT, DOWN, and UP). We begin by considering range-independent behavior (including the ORCA model) in: the CAL case of Workshop'97 (Vancouver, '97),9 the first segment of FLATa, and the Benchmark Wedge test case3 but with a flat bottom of 200 m depth. We next examine the proper Benchmark Wedge behavior for the sloping bottom for our PE (conserving and nonconserving) and for our normal mode model (KRAKEN, adiabatic and coupled). These preliminary tests confirm that the models are behaving properly under known conditions and that the input parameters have been appropriately set. Thus, when we study the models' behavior on the new SWAM'99 cases we will have some confidence that they are being applied properly. It is nontrivial to run these models even when one is familiar with them. The SWAM'99 test cases which are examined here are run only to 10 km range (five-step segments) and at a single frequency of 25 Hz. No elasticity is considered. We find that all the models generally agree, but there are quantitive differences. Since there are no proper benchmark solutions for these SWAM'99 test cases, it is difficult to determine to what extent any of them are in error. However, for the purposes of Matched Field Processing, particularly the tomographic geoacoustic inversion using adibatic normal modes (KRAKEN), it is likely that the simple adiabatic normal mode KRAKEN model is sufficiently accurate under most circumstances, i.e., unless there is a loss or gain of a critical mode.

MODE AND PE PREDICTIONS OF PROPAGATION IN RANGE-DEPENDENT ENVIRONMENTS: SWAM'99 WORKSHOP RESULTS

2001 ◽  
Vol 09 (01) ◽  
pp. 205-225
Author(s):  
PETER L. NIELSEN ◽  
FINN B. JENSEN
Keyword(s):  
Normal Mode ◽  
Sound Speed ◽  
Transmission Loss ◽  
Equation Model ◽  
Test Cases ◽  
Homogeneous Fluid ◽  
Flat Bottom ◽  
Propagation Models ◽  
Propagation Analysis ◽  
Model C

Three numerical acoustic models, a coupled normal-mode model (C-SNAP), an adiabatic normal-mode model (PROSIM), and a parabolic equation model (RAM), are applied to test cases defined for the SWAM'99 workshop. The test cases consist of three shallow water (flat bottom) scenarios with range-dependent sound-speed profiles imitating internal wave fields and a shelf-break case, with range-dependent sound-speed profiles and bathymetry. The bottom properties in all the cases are range-independent and modeled as a homogeneous fluid half-space. The results from the modeling are presented as transmission loss for selected acoustic frequencies and source-receiver geometries, and as received time series. The results are compared in order to evaluate the effect of applying different propagation models to the same range-dependent underwater environment. It should be emphasized that the propagation analysis is not an attempt to benchmark the selected propagation models, but to demonstrate the performance of practical, range-dependent models based on different approximations in particular underwater scenarios.

CONVERGENCE, STABILITY, AND VARIABILITY OF SHALLOW WATER ACOUSTIC PREDICTIONS USING A SPLIT-STEP FOURIER PARABOLIC EQUATION MODEL

2001 ◽  
Vol 09 (01) ◽  
pp. 243-285 ◽  
Author(s):  
KEVIN B. SMITH
Keyword(s):  
Parabolic Equation ◽  
Shallow Water ◽  
Acoustic Field ◽  
Equation Model ◽  
Single Frequency ◽  
Test Case ◽  
Flat Bottom ◽  
Parameter Variations ◽  
Interface Boundary Conditions ◽  
Fourier Algorithm

The Shallow Water Acoustic Modeling (SWAM'99) Workshop was organized to examine the ability of various acoustic propagation models to accurately predict sound transmission in a variety of shallow water environments designed with realistic perturbations. In order to quantify this, tests of reciprocity, convergence, and stability must be considered. This paper presents the results of an established parabolic equation model based on the split-step Fourier algorithm. The test cases examined in this paper include a simple isospeed water column over a flat bottom with geoacoustic parameter variations, a randomly sloping bottom with geoacoustic parameter variations, and a canonical shallow water profile perturbed by internal waves over a flat, homogeneous bottom. Source configurations were generally held constant but numerous single frequency and broadband runs were performed. Model testing is emphasized with specific criteria for accurate solutions being specified. Random perturbations are added to one test case to examine the influence of environmental uncertainty on the details of the propagation. The results indicate that point-wise accurate solutions to the acoustic field in shallow water cannot be achieved beyond a few kilometers. This is partly due to the inaccuracies of the split-step Fourier algorithm employed in these shallow water scenarios and the treatment of the bottom interface boundary conditions, but also due to the inherent variability caused by uncertain environmental specification. Thus, more general features of the acoustic field should be emphasized at longer ranges.

scholarly journals Resource and dependency based test case generation for RESTful Web services

2021 ◽  
Vol 26 (4) ◽  
Author(s):  
Man Zhang ◽  
Bogdan Marculescu ◽  
Andrea Arcuri
Keyword(s):  
Web Services ◽  
Domain Knowledge ◽  
Automated System ◽  
Test Case ◽  
Test Cases ◽  
Evolutionary Search ◽  
Sampling Strategies ◽  
Mutation Operators ◽  
On Line ◽  
Restful Web Services

AbstractNowadays, RESTful web services are widely used for building enterprise applications. REST is not a protocol, but rather it defines a set of guidelines on how to design APIs to access and manipulate resources using HTTP over a network. In this paper, we propose an enhanced search-based method for automated system test generation for RESTful web services, by exploiting domain knowledge on the handling of HTTP resources. The proposed techniques use domain knowledge specific to RESTful web services and a set of effective templates to structure test actions (i.e., ordered sequences of HTTP calls) within an individual in the evolutionary search. The action templates are developed based on the semantics of HTTP methods and are used to manipulate the web services’ resources. In addition, we propose five novel sampling strategies with four sampling methods (i.e., resource-based sampling) for the test cases that can use one or more of these templates. The strategies are further supported with a set of new, specialized mutation operators (i.e., resource-based mutation) in the evolutionary search that take into account the use of these resources in the generated test cases. Moreover, we propose a novel dependency handling to detect possible dependencies among the resources in the tested applications. The resource-based sampling and mutations are then enhanced by exploiting the information of these detected dependencies. To evaluate our approach, we implemented it as an extension to the EvoMaster tool, and conducted an empirical study with two selected baselines on 7 open-source and 12 synthetic RESTful web services. Results show that our novel resource-based approach with dependency handling obtains a significant improvement in performance over the baselines, e.g., up to + 130.7% relative improvement (growing from + 27.9% to + 64.3%) on line coverage.

scholarly journals Performance of Enhanced Multiple-Searching Genetic Algorithm for Test Case Generation in Software Testing

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1779
Author(s):  
Wanida Khamprapai ◽  
Cheng-Fa Tsai ◽  
Paohsi Wang ◽  
Chi-En Tsai
Keyword(s):  
Genetic Algorithm ◽  
Software Testing ◽  
Random Search ◽  
Automatic Generation ◽  
Superior Performance ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Network Systems ◽  
Routing Problem

Test case generation is an important process in software testing. However, manual generation of test cases is a time-consuming process. Automation can considerably reduce the time required to create adequate test cases for software testing. Genetic algorithms (GAs) are considered to be effective in this regard. The multiple-searching genetic algorithm (MSGA) uses a modified version of the GA to solve the multicast routing problem in network systems. MSGA can be improved to make it suitable for generating test cases. In this paper, a new algorithm called the enhanced multiple-searching genetic algorithm (EMSGA), which involves a few additional processes for selecting the best chromosomes in the GA process, is proposed. The performance of EMSGA was evaluated through comparison with seven different search-based techniques, including random search. All algorithms were implemented in EvoSuite, which is a tool for automatic generation of test cases. The experimental results showed that EMSGA increased the efficiency of testing when compared with conventional algorithms and could detect more faults. Because of its superior performance compared with that of existing algorithms, EMSGA can enable seamless automation of software testing, thereby facilitating the development of different software packages.

Acoustic Green's Function Approximations

1998 ◽  
Vol 06 (04) ◽  
pp. 435-452 ◽  
Author(s):  
Robert P. Gilbert ◽  
Zhongyan Lin ◽  
Klaus Hackl
Keyword(s):  
Inverse Problem ◽  
Normal Mode ◽  
Eigenvalue Problems ◽  
Normal Modes ◽  
Modal Parameters ◽  
Mindlin Plate ◽  
Ocean Bottom ◽  
Hankel Transformation ◽  
Poroelastic Materials ◽  
Function Approximations

Normal-mode expansions for Green's functions are derived for ocean–bottom systems. The bottom is modeled by Kirchhoff and Reissner–Mindlin plate theories for elastic and poroelastic materials. The resulting eigenvalue problems for the modal parameters are investigated. Normal modes are calculated by Hankel transformation of the underlying equations. Finally, the relation to the inverse problem is outlined.

scholarly journals Automated Search-Based Robustness Testing for Autonomous Vehicle Software

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Kevin M. Betts ◽  
Mikel D. Petty
Keyword(s):  
Monte Carlo ◽  
Performance Metrics ◽  
Initial Conditions ◽  
Autonomous Vehicle ◽  
Vehicle Control ◽  
Test Case ◽  
Test Cases ◽  
Control Software ◽  
Robustness Testing ◽  
Testing Techniques

Autonomous systems must successfully operate in complex time-varying spatial environments even when dealing with system faults that may occur during a mission. Consequently, evaluating the robustness, or ability to operate correctly under unexpected conditions, of autonomous vehicle control software is an increasingly important issue in software testing. New methods to automatically generate test cases for robustness testing of autonomous vehicle control software in closed-loop simulation are needed. Search-based testing techniques were used to automatically generate test cases, consisting of initial conditions and fault sequences, intended to challenge the control software more than test cases generated using current methods. Two different search-based testing methods, genetic algorithms and surrogate-based optimization, were used to generate test cases for a simulated unmanned aerial vehicle attempting to fly through an entryway. The effectiveness of the search-based methods in generating challenging test cases was compared to both a truth reference (full combinatorial testing) and the method most commonly used today (Monte Carlo testing). The search-based testing techniques demonstrated better performance than Monte Carlo testing for both of the test case generation performance metrics: (1) finding the single most challenging test case and (2) finding the set of fifty test cases with the highest mean degree of challenge.

scholarly journals PRIORITIZATION OF COMBINATORIAL TEST CASES BY INCREMENTAL INTERACTION COVERAGE

2013 ◽  
Vol 23 (10) ◽  
pp. 1427-1457 ◽  
Author(s):  
RUBING HUANG ◽  
XIAODONG XIE ◽  
DAVE TOWEY ◽  
TSONG YUEH CHEN ◽  
YANSHENG LU ◽  
...  
Keyword(s):  
Test Case ◽  
Test Cases ◽  
New Strategy ◽  
Testing Cost ◽  
Test Prioritization ◽  
Interaction Testing ◽  
Parameter Interactions ◽  
Combinatorial Interaction Testing ◽  
Alternative Assumption ◽  
Better Than

Combinatorial interaction testing is a well-recognized testing method, and has been widely applied in practice, often with the assumption that all test cases in a combinatorial test suite have the same fault detection capability. However, when testing resources are limited, an alternative assumption may be that some test cases are more likely to reveal failure, thus making the order of executing the test cases critical. To improve testing cost-effectiveness, prioritization of combinatorial test cases is employed. The most popular approach is based on interaction coverage, which prioritizes combinatorial test cases by repeatedly choosing an unexecuted test case that covers the largest number of uncovered parameter value combinations of a given strength (level of interaction among parameters). However, this approach suffers from some drawbacks. Based on previous observations that the majority of faults in practical systems can usually be triggered with parameter interactions of small strengths, we propose a new strategy of prioritizing combinatorial test cases by incrementally adjusting the strength values. Experimental results show that our method performs better than the random prioritization technique and the technique of prioritizing combinatorial test suites according to test case generation order, and has better performance than the interaction-coverage-based test prioritization technique in most cases.

Experimental Study for Extraction of Normal Modes

1995 ◽  
Author(s):  
S. Y. Chen ◽  
M. S. Ju ◽  
Y. G. Tsuei
Keyword(s):  
Frequency Response ◽  
Normal Mode ◽  
Normal Modes ◽  
Measurement Data ◽  
Mode Shapes ◽  
Complex Frequency ◽  
Response Functions ◽  
Frequency Response Functions ◽  
Incomplete System ◽  
Coupled Structures

Abstract A frequency-domain technique to extract the normal mode from the measurement data for highly coupled structures is developed. The relation between the complex frequency response functions and the normal frequency response functions is derived. An algorithm is developed to calculate the normal modes from the complex frequency response functions. In this algorithm, only the magnitude and phase data at the undamped natural frequencies are utilized to extract the normal mode shapes. In addition, the developed technique is independent of the damping types. It is only dependent on the model of analysis. Two experimental examples are employed to illustrate the applicability of the technique. The effects due to different measurement locations are addressed. The results indicate that this technique can successfully extract the normal modes from the noisy frequency response functions of a highly coupled incomplete system.

MuSim: Mutation-based Fault Localization Using Test Case Proximity

2021 ◽  
Vol 31 (05) ◽  
pp. 725-744
Author(s):  
Arpita Dutta ◽  
Amit Jha ◽  
Rajib Mall
Keyword(s):  
Fault Localization ◽  
Test Case ◽  
Test Cases ◽  
Similarity Metrics ◽  
Localization Technique ◽  
Evaluation Metric

Fault localization techniques aim to localize faulty statements using the information gathered from both passed and failed test cases. We present a mutation-based fault localization technique called MuSim. MuSim identifies the faulty statement based on its computed proximity to different mutants. We study the performance of MuSim by using four different similarity metrics. To satisfactorily measure the effectiveness of our proposed approach, we present a new evaluation metric called Mut_Score. Based on this metric, on an average, MuSim is 33.21% more effective than existing fault localization techniques such as DStar, Tarantula, Crosstab, Ochiai.

Comparison of Supercritical CO2 Power Cycles to Steam Rankine Cycles in Coal-Fired Applications

2017 ◽  
Author(s):  
Jason D. Miller ◽  
David J. Buckmaster ◽  
Katherine Hart ◽  
Timothy J. Held ◽  
David Thimsen ◽  
...  
Keyword(s):  
Power Plants ◽  
Cooling Tower ◽  
Test Case ◽  
Test Cases ◽  
Power Cycles ◽  
Air Preheater ◽  
Power Cycle ◽  
Inlet Conditions ◽  
Cycle Efficiency ◽  
Steam Plant

Increasing the efficiency of coal-fired power plants is vital to reducing electricity costs and emissions. Power cycles employing supercritical carbon dioxide (sCO2) as the working fluid have the potential to increase power cycle efficiency by 3–5% points over state-of-the-art oxy-combustion steam-Rankine cycles operating under comparable conditions. To date, the majority of studies have focused on the integration and optimization of sCO2 power cycles in waste heat, solar, or nuclear applications. The goal of this study is to demonstrate the potential of sCO2 power cycles, and quantify the power cycle efficiency gains that can be achieved versus the state-of-the-art steam-Rankine cycles employed in oxy-fired coal power plants. Turbine inlet conditions were varied among the sCO2 test cases and compared with existing Department of Energy (DOE)/National Energy Technology6 Laboratory (NETL) steam base cases. Two separate sCO2 test cases were considered and the associated flow sheets developed. The turbine inlet conditions for this study were chosen to match conditions in a coal-fired ultra-supercritical steam plant (Tinlet = 593°C, Pinlet = 24.1 MPa) and an advanced ultra-supercritical steam plant (Tinlet = 730°C, Pinlet = 27.6 MPa). A plant size of 550 MWe, was selected to match available information on existing DOE/NETL bases cases. The effects of cycle architecture, combustion-air preheater temperature, and cooling source type were considered subject to comparable heat source and reference conditions taken from the steam Rankine reference cases. Combinations and variants of sCO2 power cycles — including cascade and recompression and variants with multiple reheat and compression steps — were considered with varying heat-rejection subsystems — air-cooled, direct cooling tower, and indirect-loop cooling tower. Where appropriate, combustion air preheater inlet temperature was also varied. Through use of a multivariate nonlinear optimization design process that considers both performance and economic impacts, curves of minimum cost versus efficiency were generated for each sCO2 test case and combination of architecture and operational choices. These curves indicate both peak theoretical efficiency and suggest practical limits based on incremental cost versus performance. For a given test case, results for individual architectural and operational options give insight to cost and performance improvements from step-changes in system complexity and design, allowing down selection of candidate architectures. Optimized designs for each test case were then selected based on practical efficiency limits within the remaining candidate architectures and compared to the relevant baseline steam plant. sCO2 cycle flowsheets are presented for each optimized design.

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