Study of stress waves in geomedia and effect of a soil cover layer on wave attenuation using a 1-D finite-difference method

The propagation and attenuation of blast-induced stress waves differs between geomedia such as rock or soil mass. This paper numerically studies the propagation and attenuation of blast-induced elastoplastic waves in deep geomedia by using a one-dimensional (1-D) finite-difference code. Firstly, the elastoplastic Cap models for rock and soil masses are introduced into the governing equations of spherical wave motion and a FORTRAN code based on the finite difference method is developed. Secondly, an underground spherical blast is simulated with this code and verified by software, RENEWTO. The propagation of stress-waves in rock and soil masses is numerically investigated, respectively. Finally, the effect of a soil cover layer on the attenuation of stress waves in the rear rock mass is studied. It is determined that large plastic deformation of geomedia can effectively dissipate the energy of stress-waves inward and the developed 1-D finite difference code coupled with elastoplastic Cap models is convenient and effective in the numerical simulations for underground spherical explosion.     

Response of structures to planar blast loads – A finite element engineering approach

Design and validation of structures against blast loads are important for modern society in order to protect and secure its citizen. Since it is a challenge to validate and optimise protective structures against blast loads using full-scale experimental tests, we have to turn our attention towards advanced numerical tools like the finite element method. Several different finite element techniques can be used to describe the response of structures due to blast loads. Some of these are: (1) a pure Lagrangian formulation, (2) an initial Eulerian simulation (to determine the load) followed by a Lagrangian simulation (for the structural response) and (3) a hybrid technique that combines the advantages of Eulerian and Lagrangian methods to have a full coupling between the blast waves and the deformation of the structure. Ideally, all blast simulations should be carried out using the fully coupled Eulerian–Lagrangian approach, but this may not be practical as the computational time increases considerably when going from a pure Lagrangian to a fully coupled Eulerian–Lagrangian simulation. A major goal in this study is to investigate if a pure Lagrangian formulation can be applied to determine the structural response in a specified blast load problem or if more advanced approaches such as the fully coupled Eulerian–Lagrangian approach is required for reliable results. This is done by conducting numerical simulations of an unprotected 20 ft ISO container exposed to a blast load of 4000 kg TNT at 120 m standoff distance using the three different approaches presented above. To validate and discuss the results, the simulated response of the container is compared to available data from a full-scale blast test under such conditions.     

Evaluation and prediction of blast-induced ground vibration at Shur River Dam, Iran, by artificial neural network

The purpose of this article is to evaluate and predict blast-induced ground vibration at Shur River Dam in Iran using different empirical vibration predictors and artificial neural network (ANN) model. Ground vibration is a seismic wave that spreads out from the blasthole when explosive charge is detonated in a confined manner. Ground vibrations were recorded and monitored in and around the Shur River Dam, Iran, at different vulnerable and strategic locations. A total of 20 blast vibration records were monitored, out of which 16 data sets were used for training of the ANN model as well as determining site constants of various vibration predictors. The rest of the 4 blast vibration data sets were used for the validation and comparison of the result of ANN and different empirical predictors. Performances of the different predictor models were assessed using standard statistical evaluation criteria. Finally, it was found that the ANN model is more accurate as compared to the various empirical models available. As such, a high conformity (R ² = 0.927) was observed between the measured and predicted peak particle velocity by the developed ANN model.     

Nonlinear modeling of soil deformation modulus through LGP-based interpretation of pressuremeter test results

Soil deformation modulus is an essential parameter for the analysis of behavior of substructures. Despite its importance, little attention is paid to developing empirical models for predicting the deformation moduli obtained from the field tests. To cope with this issue, this paper presents the development of a new prediction model for the pressuremeter soil deformation modulus utilizing a linear genetic programming (LGP) methodology. The LGP model relates the soil secant modulus obtained from the pressuremeter tests to the soil index properties. The best model was selected after developing and controlling several models with different combinations of the influencing parameters. The experimental database used for developing the models was established upon several pressuremeter tests conducted on different soil types at depths of 3–40 m. To verify the applicability of the derived model, it was employed to estimate the soil moduli of portions of test results that were not included in the analysis. Further, the generalization capability of the model was verified via several statistical criteria. The sensitivity of the soil deformation modulus to the influencing variables was examined and discussed. Moisture content and soil dry unit weight were found to be efficient representatives of the initial state and consolidation history of the soil for determining its deformation modulus. The results indicate that the LGP approach accurately characterizes the soil deformation modulus leading to a very good prediction performance. The correlation coefficients between the experimental and predicted soil modulus values are equal to 0.908 and 0.901 for the calibration and testing data sets, respectively.     

Prediction of strain energy-based liquefaction resistance of sand-silt mixtures: An evolutionary approach

Liquefaction is a catastrophic type of ground failure, which usually occurs in loose saturated soil deposits under earthquake excitations. A new predictive model is presented in this study to estimate the amount of strain energy density, which is required for the liquefaction triggering of sand-silt mixtures. A wide-ranging database containing the results of cyclic tests on sand-silt mixtures was first gathered from previously published studies. Input variables of the model were chosen from the available understandings evolved from the previous studies on the strain energy-based liquefaction potential assessment. In order to avoid overtraining, two sets of validation data were employed and a particular monitoring was made on the behavior of the evolved models. Results of a comprehensive parametric study on the proposed model are in accord with the previously published experimental observations. Accordingly, the amount of strain energy required for liquefaction onset increases with increase in initial effective overburden pressure, relative density, and mean grain size. The effect of nonplastic fines on strain energy-based liquefaction resistance shows a more complicated behavior. Accordingly, liquefaction resistance increases with increase in fines up to about 10-15% and then starts to decline for a higher increase in fines content. Further verifications of the model were carried out using the valuable results of some downhole array data as well as centrifuge model tests. These verifications confirm that the proposed model, which was derived from laboratory data, can be successfully utilized under field conditions.     

The effects of pressurized partial pressure suits on operational ergonomics

A study on capstan partial pressure suits (PPSs) was conducted to determine their effects on pilots' operational performance on a series of ergonomic measures at different pressure levels using objective and subjective approaches. Tests of range of motion, operational performance and operational strength were carried out on ten male subjects wearing PPSs under 6 different pressure conditions. Subjective tests related to pressure tolerance and operational performance were also conducted. A video-based motion capture and analysis system was used to record the trajectories of body motions. Analysis of variance was used to test the effects of the different pressures. It was concluded that a pressurized PPS had a significant impact on the pilot's range of motion (ROM) and operational performance, but no significant effect on their operational strength. Range of motion and operational performance decreased as pressure increased, but they were affected differently. The results may provide mission planners, suit designers and human factors engineers with better insight into the understanding of pilots' operational function, mobility and strength capabilities when wearing pressurized PPS.Relevance to industryThis paper presents pilots' range of motion, operational performance and operational strength with pressurized PPS dressed and can help mission planners, suit designers and human factors engineers to improve PPS' performance.     

Validating a model-driven software architecture evaluation and improvement method: A family of experiments

ContextSoftware architectures should be evaluated during the early stages of software development in order to verify whether the non-functional requirements (NFRs) of the product can be fulfilled. This activity is even more crucial in software product line (SPL) development, since it is also necessary to identify whether the NFRs of a particular product can be achieved by exercising the variation mechanisms provided by the product line architecture or whether additional transformations are required. These issues have motivated us to propose QuaDAI, a method for the derivation, evaluation and improvement of software architectures in model-driven SPL development.ObjectiveWe present in this paper the results of a family of four experiments carried out to empirically validate the evaluation and improvement strategy of QuaDAI.MethodThe family of experiments was carried out by 92 participants: Computer Science Master’s and undergraduate students from Spain and Italy. The goal was to compare the effectiveness, efficiency, perceived ease of use, perceived usefulness and intention to use with regard to participants using the evaluation and improvement strategy of QuaDAI as opposed to the Architecture Tradeoff Analysis Method (ATAM).ResultsThe main result was that the participants produced their best results when applying QuaDAI, signifying that the participants obtained architectures with better values for the NFRs faster, and that they found the method easier to use, more useful and more likely to be used. The results of the meta-analysis carried out to aggregate the results obtained in the individual experiments also confirmed these results.ConclusionsThe results support the hypothesis that QuaDAI would achieve better results than ATAM in the experiments and that QuaDAI can be considered as a promising approach with which to perform architectural evaluations that occur after the product architecture derivation in model-driven SPL development processes when carried out by novice software evaluators.     

Adaptation of an automotive dialogue system to users’ expertise and evaluation of the system

Spoken dialogue systems (SDSs) can be used to operate devices, e.g. in the automotive environment. People using these systems usually have different levels of experience. However, most systems do not take this into account. In this paper, we present a method to build a dialogue system in an automotive environment that automatically adapts to the user’s experience with the system. We implemented the adaptation in a prototype and carried out exhaustive tests. Our usability tests show that adaptation increases both user performance and user satisfaction. We describe the tests that were performed, and the methods used to assess the test results. One of these methods is a modification of PARADISE, a framework for evaluating the performance of SDSs [Walker MA, Litman DJ, Kamm CA, Abella A (Comput Speech Lang 12(3):317–347, 1998)]. We discuss its drawbacks for the evaluation of SDSs like ours, the modifications we have carried out, and the test results.

基于生理舌头模型的语音可视化系统

目的 目前针对舌头的语音同步动画技术还未得到广泛的研究。在此背景下,提出了一种基于生理模型的舌头动画合成方法。方法 首先构建了一个精细的、能够在肌肉激励下产生逼真舌头变形的舌头生理模型;其次利用该舌头模型合成了大量的舌头运动样本,并据此通过学习得到一个从肌肉激励到舌头轮廓的转换模型;然后对采集的动态2维舌头轮廓数据进行运动参数估计以得到与音素对应的体素(肌肉激励序列和刚体位移序列);最后将体素按一定的排列方式输入到舌头生理模型进行仿真以生成相应的舌头动画。结果 该系统可以合成听觉效果逼真的语音和视觉效果逼真且与合成语音同步的舌头动画。结论 本文方法可以根据汉语普通话或其他语言的2维舌头轮廓数据构建音素—体素数据库,并据此合成该语言对应的高真实感的3维舌头动画。     

Test overlay in an emerging software product line – An industrial case study

ContextIn large software organizations with a product line development approach, system test planning and scope selection is a complex task. Due to repeated testing: across different testing levels, over time (test for regression) as well as of different variants, the risk of redundant testing is large as well as the risk of overlooking important tests, hidden by the huge amount of possible tests.AimsThis study assesses the amount and type of overlaid manual testing across feature, integration and system test in such context, it explores the causes of potential redundancy and elaborates on how to provide decision support in terms of visualization for the purpose of avoiding redundancy.MethodAn in-depth case study was launched including both qualitative and quantitative observations.ResultsA high degree of test overlay is identified originating from distributed test responsibilities, poor documentation and structure of test cases, parallel work and insufficient delta analysis. The amount of test overlay depends on which level of abstraction is studied.ConclusionsAvoiding redundancy requires tool support, e.g. visualization of test design coverage, test execution progress, priorities of coverage items as well as visualized priorities of variants to support test case selection.     

Mapping of understory lichens with airborne discrete-return LiDAR data

High backscatter reflectance at NIR wavelengths has been observed for reindeer lichens (Cladina sp.) in the laboratory. The results suggested that lichens could be separated from soil and other parts of forest understory using this property. An experiment was carried out to test this hypothesis in situ. The lichen vegetation of a 960-m² plot in a barren pine stand in Juupajoki, Finland was mapped in 3D, using methods of close-range photogrammetry. The data of two airborne discrete-return sensors were compared for their ability to classify understory lichen vegetation. Normalization of the LiDAR intensities was carried out, using natural targets. The results showed that lichen surfaces had a higher intensity than on average. Normalization of the intensities improved separability of lichens from other surfaces, and the best-case classification accuracy was 75%. Detailed analysis of geometric errors revealed small, decimeter-level planimetric offsets in the LiDAR datasets that affected the results notably.     

Systematic scenario test case generation for nuclear safety systems

ContextThe current validation tests for nuclear software are routinely performed by random testing, which leads to uncertain test coverage. Moreover, validation tests should directly verify the system’s compliance with the original user’s needs. Unlike current model-based testing methods, which are generally based on requirements or design models, the proposed model is derived from the original user’s needs in text through domain-specific ontology, and then used to generate validation tests systematically.ObjectiveOur first goal is to develop an objective, repeatable, and efficient systematic validation test scheme that is effective for large systems, with analyzable test coverage. Our second goal is to provide a new model-based validation testing method that reflects the user’s original safety needs.MethodA model-based scenario test case generation for nuclear digital safety systems was designed. This was achieved by converting the scenarios described in natural language in a Safety Analysis Report (SAR) prepared by the power company for licensing review, to Unified Modeling Language (UML) sequence diagrams based on a proposed ontology of a related regulatory standard. Next, we extracted the initial environmental parameters and the described operational sequences. We then performed variations on these data to systematically generate a sufficient number of scenario test cases.ResultsTest coverage criteria, which are the equivalence partition coverage of initial environment, the condition coverage, the action coverage and the scenario coverage, were met using our method.ConclusionThe proposed model-based scenario testing can provide improved testing coverage than random testing. A test suite based on user needs can be provided.     

Using remote sensing to estimate the change of carbon storage: A case study in the estuary of Yellow River delta

Land cover change can exert a crucial effect on the terrestrial carbon cycle. To estimate changes in the carbon pools and carbon fluxes to the atmosphere, Landsat Thematic Mapper (TM) data of 1992 and 1996 were used to calculate the extent of different land cover types and their changes in the estuary area of the Yellow River delta. Image processing and the unsupervised classification allowed accurate land cover maps for 1992 and 1996 to be generated, by which the changes in the carbon pools were detected. Estimation of the carbon pools and the carbon fluxes to the atmosphere was carried out employing the results of Landsat image analysis and the published data on carbon stocks in vegetation and soil. By calculating the area changed between different types of vegetation and their different carbon stocks, the quantity of the terrestrial carbon cycle in the estuary area of the Yellow River delta was acquired. The results shows that the vegetation carbon storage was 11.43 2 10 11 g and soil carbon pool 7.24 2 10 12 g in 1992, and the vegetation carbon pool increased by 3.77 2 10 11 g during the 4 years from 1992 to 1996.     

Improving the effectiveness of test suite reduction for user-session-based testing of web applications

ContextTest suite reduction is the problem of creating and executing a set of test cases that are smaller in size but equivalent in effectiveness to an original test suite. However, reduced suites can still be large and executing all the tests in a reduced test suite can be time consuming.ObjectiveWe propose ordering the tests in a reduced suite to increase its rate of fault detection. The ordered reduced test suite can be executed in time constrained situations, where, even if test execution is stopped early, the best test cases from the reduced suite will already be executed.MethodIn this paper, we present several approaches to order reduced test suites using experimentally verified prioritization criteria for the domain of web applications. We conduct an empirical study with three subject applications and user-session-based test cases to demonstrate how ordered reduced test suites often make a practical contribution. To enable comparison between test suites of different sizes, we develop Mod_APFD_C, a modification of the traditional prioritization effectiveness measure.ResultsWe find that by ordering the reduced suites, we create test suites that are more effective than unordered reduced suites. In each of our subject applications, there is at least one ordered reduced suite that outperforms the best unordered reduced suite and the best prioritized original suite.ConclusionsOur results show that when a tester does not have enough time to execute the entire reduced suite, executing an ordered reduced suite often improves the rate of fault detection. By coupling the underlying system’s characteristics with observations from our study on the criteria that produce the best ordered reduced suites, a tester can order their reduced test suites to obtain increased testing effectiveness.     

Soil erosion assessment and simulation by means of SGEOS and ancillary digital data

Abstract

Due to soil erosion processes fertile soils are washed out almost anywhere in the world. Soil erosion protection measures are necessary, especially for food security reasons. This study uses the well-known Universal Soil Loss Equation (USLE) to assess the long-term soil erosion in a small catchment area and to simulate various soil protection alternatives. After completion at this test site the techniques can be applied for larger regions to detect areas that are most afTected by soil erosion and to guide precisely the efficient soil erosion prevention measures that proved to be valuable according to the computer simulation results.

This raster-oriented study uses a very accurate multi-temporal land-use classification to determine the land-cover (C-factor). The other input variables have been determined from ancillary data (e.g., digital elevation model and soil data). The compiled data layers of this geographical information system (GIS) allow the calculation of the long-term soil erosion per pixel as well as inquiries about all data layers for every pixel.

In addition to the resulting soil erosion risk map it is possible to simulate soil protection measures with the computer. This ensures that only the most effective ones are introduced to the field.     

Evaluation of the influence of yellow substance absorption on the remote sensing of water quality in the Gulf of Naples: a case study

Abstract

The yellow substance absorption in the coastal waters of the Gulf of Naples was measured by a method combining beam transmission and induced fluorescence measurements. A water optical model specific to that test area, derived from experimentation carried out in situ has been used to evaluate the impact of the measured yellow substance absorption on the remote sensing of water quality parameters, such as chlorophyll-like pigment and total suspended sediment concentrations.     

基于超像素的点追踪方法

目的由于当前大多数的追踪算法都是使用目标外观模型和特征进行目标的匹配,在长时间的目标追踪过程中,目标的尺度和形状均会发生变化,再加上计算机视觉误差,都会导致追踪的失误。提出一种高效的目标模型用于提高追踪的效率和成功率。方法采用分割后提取的目标特征来进行建模表示外观结构,利用图像分割的方法,将被追踪的目标区域分割成多个超像素块,结合SIFT特征,形成词汇本,并计算每个词在词汇本中的权值,作为目标的外观模型。利用外观模型确定目标对象的关键点位置后,通过使用金字塔Lucas-Kanade追踪器预测关键点在下一帧图像中的位置,并移动追踪窗口位置。结果结合点位移的加权计算有效地克服目标尺度和形状变化产生的问题。结论实验结果表明在目标发生形变或光照变化的情况下,算法也能准确地、实时地追踪到目标。     

使用线约束运动最小二乘法的视差图像拼接

目的 图像配准是影响拼接质量的关键因素。已有的视差图象拼接方法没有解决匹配特征点对间的错误配准问题,容易引起不自然的拼接痕迹。针对这一问题,提出了使用线约束运动最小二乘法的配准算法,减少图像的配准误差,提高拼接质量。方法 首先,计算目标图像和参考图像的SIFT（scale-invariant feature transform）特征点,应用RANSAC（random sample consensus）方法建立特征点的匹配关系,由此计算目标到参考图像的最佳单应变换。然后,使用线约束运动最小二乘法分别配准两组图像：1）第1组是目标图像和参考图像;2）第2组是经单应变换后的目标图像和参考图像。第1组用逐点仿射变换进行配准,而第2组配准使用了单应变换加上逐点仿射变换。最后,在重叠区域,利用最大流最小割算法寻找最优拼接缝,沿着拼接缝评估两组配准的质量,选取最优的那组进行融合拼接。结果 自拍图库和公开数据集上的大量测试结果表明,本文算法的配准精度超过95%,透视扭曲比例小于17%。与近期拼接方法相比,本文配准算法精度提高3%,拼接结果中透视扭曲现象减少73%。结论 运动最小二乘法可以准确地配准特征点,但可能会扭曲图像中的结构对象。而线约束项则尽量保持结构,阻止扭曲。因此,线约束运动最小二乘法兼顾了图像结构的完整性和匹配特征点的对准精度,基于此配准模型的拼接方法能够有效减少重影和鬼影等人工痕迹,拼接结果真实自然。     

InSAR中应用可靠度导向改进的分级表相位展开算法

目的 在干涉合成孔径雷达的相位展开过程中,如果相位展开的展开路径穿过残差点就会产生相位展开的误差。在相位展开的时候,希望将相位展开的误差限制在局部区域,提高相位展开的精度。方法 首先通过判断截断相位图的残差点,并以InSAR的干涉一致性图作为相位展开的可靠性度量,对截断相位图进行量化,将残差处的可靠度设为排序中的最低等级。在进行可靠度排序后进行干涉合成孔径雷达相位图的相位展开。结果 使用该算法改进了经典可靠度导向相位展开算法中可靠度排序的缓慢问题。与经典菱形算法相比,展开精度高很多。与洪水算法相比,展开速度能快上百倍。通过可靠度排序的改进,对干涉合成孔径雷达相位展开后的结果进行分析,可以看到提高了相位展开的精度,有效的控制了相位展开过程中误差的传递。结论 相位展开算法的改进提高了干涉合成孔径雷达相位展开的精度,在干涉合成孔径雷达的相位展开中可以广泛应用。     

高低温和水平突风条件下舱门变形适航仿真验证方法研究

解析与舱门及其密封件形变相关的适航规章和条款,研究确定与形变相关的主要适航要求。构建基于SolidWorks的舱门及其密封件形变分析模型,开展极高低温、水平突风及其组合条件下舱门及其密封件形变的详细分析,提出基于仿真的舱门及其密封件形变适航符合性验证流程。开展基于虚力原理的舱门挡块部位的形变分析,并与仿真进行了比较研究。结果表明,讨论的舱门及其密封件形变仿真方法和适航符合性验证流程是合理可行的。