Wetting Pattern Models for Drip Irrigation: New Empirical Model

Reliable information about the wetted dimensions of soil under drip irrigation helps designers to determine optimal emitter flow rates and spacings to reduce system equipment costs and provide better soil water conditions for the most efficient and effective use of water. This study presents a new empirical formula that predicts soil wetted dimensions around a drip emitter. The coefficients were obtained by using regression analysis on the results of field experiments done on the Pardis Agricultural Farm of Tehran University in Karaj, Iran. These data were also used to evaluate the semiempirical model of Zur and Schwartzman, the empirical model of Amin and Ekhmaj, and the analytical model WetUp. Statistical comparisons (mean error, root mean square error, and model efficiency) are made of the simulated data with the observed data. To evaluate the models, published experimental data by Risse et?al. and Li et?al. were also used. The results demonstrate that the suggested equations can be used for a wide range of discharge rates and soil types. The best result was obtained from the new empirical model proposed in this investigation. The lowest mean error for the wetted radius and wetted depth was 8.21 and 8.62?cm, respectively.     

Calibration and Validation of an Empirical Dissolved Oxygen Model

A common difficulty in stream health assessments is the scarcity of real-time dissolved oxygen (DO) data. Discrete DO measurements, collected at times often imposed by sampling constraints, are difficult to use in assessments because of diurnal variations. An empirical model is developed here to adjust these discrete measurements to a common time-reference value using an extended stochastic harmonic analysis (ESHA) algorithm, which was originally formulated with a fraction of DO saturation model by the authors. The model was calibrated and validated for different stream sites across Minnesota, incorporating effects of different ecoregions and variable drainage areas. Data were normalized to increase the general applicability of the fitted parameters. Model calibration for five long record stations accurately represented observed diurnal variations in DO. The root-mean-square error (RMSE) for predicting hourly DO ranged from 0.53?to?0.80?mg/L and for predicting DO at a standard time ranged from 0.44?to?0.91?mg/L. Estimated model parameters were robust in terms of both spatial and temporal variations. Analytical as well as numerical analyses of parameter uncertainties were performed using sensitivity coefficients. Model validation with independent data for eight different Minnesota streams was performed using three different approaches for estimating parameters. The best approach considered both ecoregional location and watershed size to select representative model parameters. The RMSE for predicting hourly DO and standard DO respectively ranged from 0.53?to?1.65?mg/L and 0.00?to?1.83?mg/L. The developed model is a useful tool for total maximum daily load assessment of aquatic ecosystem health across a range of temporal and spatial scales. It is more elegant and simpler than the application of the ESHA algorithm for the fraction of DO saturation model.     

Model Development and Validation for Intelligent Data Collection for Lateral Spread Displacements

The geotechnical earthquake engineering community often adopts empirically derived models. Unfortunately, the community has not embraced the value of model validation, leaving practitioners with little information on the uncertainties present in a given model and the model’s predictive capability. In this study, we present a machine learning technique known as support vector regression (SVR) together with rigorous validation for modeling lateral spread displacements and outline how this information can be used for identifying gaps in the data set. We demonstrate the approach using the free face lateral displacement data. The results illustrate that the SVR has relatively better predictive capability than the commonly used empirical relationship derived using multilinear regression. Moreover, the analysis of the SVR model and its support vectors helps in identifying gaps in the data and defining the scope for future data collection.     

CPT-Based Evaluation of Liquefaction and Lateral Spreading in Centrifuge

Two series of centrifuge model tests were conducted using Nevada sand. Four saturated models placed in a mildly inclined laminar box and simulating a 6-m-thick deposit were shaken inducing liquefaction effects and lateral spreading. The sand was deposited at a relative density, Dr = 45 or 75%; two of the 45% models were subjected to overconsolidation or preshaking. The second series involved in-flight measurements of static cone tip penetration resistance, qc, simulating the standard cone penetration test (CPT) 36-mm cone. Values of qc increased with Dr, overconsolidation, and preshaking. A normalized resistance, qc1N, was assigned to each of the four liquefaction/lateral spreading models. Increases in Dr, overconsolidation, and preshaking decreased liquefaction and ground deformation, but relative density alone captured these effects rather poorly. Conversely, qc1N predicted extremely well the liquefaction and lateral spreading response of the four models, confirming Seed’s hypothesis to explain the success of penetration-based seismic liquefaction charts. The depth to liquefaction measured in the four centrifuge models is consistent with the field CPT liquefaction chart.     

Numerical Analysis of a Tunnel Support Design in Conjunction with Empirical Methods

In this paper, preliminary support design of a tunnel was analyzed by numerical and empirical approaches. The case study for this analysis is a tunnel to be constructed on the Bilecik-Istanbul roadway in Turkey. The rock mass properties of the tunnel route and design support recommendations were obtained by using an empirical approach. The rock mass properties obtained from the empirical method were used as input parameters for the numerical analysis. The empirical and numerical results, in terms of support design, were evaluated. It was seen that the numerical analysis results supported by empirical values were logical and reliable.     

Liquefaction Resistance of Sandy Soils under Partially Drained Condition

In order to simulate the effect of drainage on soils adjacent to gravel drains that are installed as countermeasure against liquefaction, several series of cyclic triaxial tests were performed on saturated sands under partially drained conditions. The condition of partial drainage under cyclic loading was simulated in the laboratory using triaxial testing equipment installed with a drainage control valve to precisely regulate the volume of water being drained from test specimens. Effects of both drainage conditions and loading frequencies on cyclic response were incorporated through the coefficient of drainage effect, α*. Experimental results showed that for sand exhibiting strain softening, the partially drained response was controlled by the critical effective stress ratio while for sand showing strain hardening behavior, the controlling factor was the phase transformation stress ratio. Moreover, test results indicated that the minimum liquefaction resistance under partially drained conditions can be used as a parameter to describe the liquefaction resistance of sands improved by the gravel drain method. From these results, a simplified procedure for designing gravel drains based on the factor of safety (FL) concept was proposed.     

Retesting of Liquefaction and Nonliquefaction Case Histories from the 1976 Tangshan Earthquake

A field investigation was performed to retest liquefaction and nonliquefaction sites from the 1976 Tangshan earthquake in China. These sites were carefully investigated in 1978 and 1979 by using standard penetration test (SPT) and cone penetration test (CPT) equipment; however, the CPT measurements are obsolete because of the now nonstandard cone that was used at the time. In 2007, a modern cone was mobilized to retest 18 selected sites that are particularly important because of the intense ground shaking they sustained despite their high fines content and/or because the site did not liquefy. Of the sites reinvestigated and carefully reprocessed, 13 were considered accurate representative case histories. Two of the sites that were originally investigated for liquefaction have been reinvestigated for cyclic failure of fine-grained soil and removed from consideration for liquefaction triggering. The most important outcome of these field investigations was the collection of more accurate data for three nonliquefaction sites that experienced intense ground shaking. Data for these three case histories is now included in an area of the liquefaction triggering database that was poorly populated and will help constrain the upper bound of future liquefaction triggering curves.     

Empirical Analysis of Construction Enterprise Information Systems: Assessing System Integration, Critical Factors, and Benefits

Attaining higher levels of system integration is seen as the primary goal of construction enterprise information systems (CEIS). Increased system integration resulting from CEIS implementation is expected to lead to numerous benefits. These benefits encompass information technology infrastructure and strategic, operational, organizational, and managerial aspects of the firm. By adopting CEIS, firms seek tangible and intangible benefits, such as cost reduction, improved productivity, enhanced efficiency, and business growth. Through the use of statistical analysis, this study quantifies the critical success factors that impact CEIS integration and the ensuing benefits. Furthermore, it analyzes the effects of system integration on CEIS induced benefits. It also investigates the impact of CEIS strategy on CEIS induced benefits and identifies the relationship between CEIS strategy and system integration. Finally, it assesses the effects of CEIS induced benefits on user satisfaction and provides a CEIS implementation guide map for construction firms.     

Simplified Method for Spatial Evaluation of Liquefaction Potential in the St. Louis Area

As a part of an earthquake hazard mapping program being undertaken by the U.S. Geological Survey in the St. Louis metropolitan area, surficial geologic mapping and subsurface geotechnical data have been compiled into a three-dimensional geographic information system (GIS). The potential for soil liquefaction was then spatially evaluated by using subsurface information from 562 boreholes for an assumed M7.5 earthquake emanating from the New Madrid Seismic Zone. Geotechnical data (standard penetration test N-values, overburden pressure, and depth-to-groundwater) and the scenario peak ground accelerations (PGA = 0.1, 0.20, and 0.30??g) were applied to evaluate the factor of safety (FS) against earthquake-induced liquefaction. The liquefaction potential index (LPI) method was used in these evaluations because it allows for calculations of FS with depth for 10–25 discrete stratigraphic horizons overlying the bedrock across the St. Louis metropolitan area. LPI values were derived from the correlation between calculated LPI values and the depths-to-groundwater within late Quaternary stratigraphic units. The St. Louis metropolitan area was then classed according to four levels of severity of risk from liquefaction: (1)?no liquefaction potential, (2)?little-to-no likelihood, (3)?moderate, and (4)?severe.     

Measuring Soil Pressure on a Buried Model Structure for the Validation of Quantitative Frameworks

The paper presents the methodologies and results of an experimental study aimed at measuring the soil contact pressures which develop on a buried structure as it interacts with the surrounding soil under load. The study has been based on measurements made on model structures tested in a pressure chamber filled with a fine uniform sand. The buried model structure was a very rigid right cylinder designed such that it could be fitted with roofs of different thicknesses. The structure bottom and roof were instrumented with newly designed and constructed soil pressure cells based on the null response concept. The device is unaffected by the issues that affect the use of traditional soil pressure cells. The development of pressure on the structure was measured as uniform pressure was applied to the soil surface. The results illustrate the effect of roof stiffness on the development of pressure at the roof center. The midroof pressure was seen to increase with roof stiffness, however the development of pressure was also seen to be dependent upon the actual deflection. In the case of a flexible roof it was seen that the development of contact pressure is a nonlinear function of the pressure applied at the soil surface and is highly dependent upon stress history. In contrast, it was seen that pressure on a stiff roof develops as a linear function of pressure applied at the soil surface and is less dependent of stress history. The results of the model tests together with soil stiffness data supplied in the paper will be useful in the calibration and validation of numerical and analytical frameworks.     

Simplified Approximation Procedure for Performance-Based Evaluation of Liquefaction Potential

Performance-based procedures for evaluation of liquefaction potential have been shown to provide more consistent and accurate indications of the actual likelihood of liquefaction in areas of different seismicity than conventional procedures. The process of performing a complete site-specific performance-based evaluation of liquefaction potential, however, requires numerous calculations involving quantities that many geotechnical engineers are not familiar with. This paper shows how the results of complete performance-based analyses can be expressed in terms of a scalar parameter corresponding to a particular element of soil in a reference soil profile, and presents procedures for adjustment of that parameter to account for site-specific conditions that differ from those of the reference profile. The procedures are shown to closely approximate the results of complete site-specific performance-based evaluations. Engineers can then use mapped values of the scalar parameter, along with the recommended adjustment procedure, to realize the benefits of a performance-based evaluation without having to actually perform the performance-based calculations.     

Empirical Analysis of the Learning Curve Principle in Prestressed Concrete Piles

The principle of learning curves can be applied in construction for the prediction of the time/cycle of future work, work performance levels, and other performance measures. Learning curve principles can be effectively utilized in litigation cases where production is compromised by delays. The objective of this study was to determine if learning curves could be used to accurately predict the production efforts of future units by applying the principles to the prefabrication and driving of prestressed concrete piles. The individual time to cast each of the concrete piles was recorded and used to compute the cumulative average time (CATN) to fabricate the concrete piles. The data were used to compute the learning rate (?) and the theoretical time to complete the first unit (Kc). From this information, predictions were made as to the amount of effort to fabricate future piles. The results showed that the pile fabrication crew improved its learning throughout the pile fabrication effort, but this improvement was quite small. The learning curve theory was found to apply well to large numbers of repeated items, and that the predictions made with learning curves are reasonably accurate.     

Characterization of Liquefaction Susceptibility of Sands by Means of Extreme Void Ratios and/or Void Ratio Range

The liquefaction susceptibility of various graded fine to medium saturated sands are evaluated by stress controlled cyclic triaxial laboratory tests. Cyclic triaxial tests are performed on reconstituted specimens having global relative density of 60%. In all cyclic triaxial tests, loading pattern is selected as a sinusoidal wave form with 1.0 Hz frequency and effective consolidation pressure is chosen as 100 kPa. Liquefaction resistance is defined as the required cyclic stress ratio causing initial liquefaction in 10 cycles during the cyclic triaxial test. The results are used to draw conclusions on the effect of the extreme void ratios and void ratio range on the liquefaction resistance of various graded sands.     

Verification of the Soil-Type Specific Correlation between Liquefaction Resistance and Shear-Wave Velocity of Sand by Dynamic Centrifuge Test

Liquefaction of granular soil deposits is one of the major causes of loss resulting from earthquakes. The accuracy of the liquefaction potential assessment at a site affects the safety and economy of an engineering project. Although shear-wave velocity (Vs)-based methods have become prevailing, very few works have addressed the problem of the reliability of various relationships between liquefaction resistance (CRR) and Vs used in practices. In this paper, both cyclic triaxial and dynamic centrifuge model tests were performed on saturated Silica sand No. 8 with Vs measurements using bender elements to investigate the reliability of the CRR-Vs1 correlation previously proposed by the authors. The test results show that the semiempirical CRR-Vs1 curve derived from laboratory liquefaction test of Silica sand No. 8 can accurately classify the (CRR,Vs1) database produced by dynamic centrifuge test of the same sand, while other existing correlations based on various sandy soils will significantly under or overestimate the cyclic resistance of this sand. This study verifies that CRR-Vs1 curve for liquefaction assessment is strongly soil-type dependent, and it is necessary to develop site-specific liquefaction resistance curves from laboratory cyclic tests for engineering practices.     

砂土液化防治综述

首先介绍了砂土液化给人类带来的灾难,然后从砂土液化研究的历史及砂土液化的机理入手,分析了影响砂土液化的原因,最后阐述了目前用于判别砂土液化所采用的一些先进的方法,每种方法都有各自的优缺点。由于影响砂土液化的因素太多,而且许多的判别条件不容易获取,应用模糊理论判别砂土液化是比较合理的方法。     

Model for Reinforced Concrete Members under Torsion, Bending, and Shear. II: Model Application and Validation

A model was recently proposed for predicting the load-deformation response of a reinforced concrete member under torsion combined with bending and shear to spalling or ultimate. This paper shows the application of the model to create interaction surfaces to predict the failure of a member subjected to different ratios of applied torsion, bending, and shear. The model was validated by comparing the predicted and experimental behavior of 28 members from three experimental studies available in the literature. The members were loaded under torsion combined with different ratios of bending, and shear. The torque-twist behavior, reinforcement stress, and concrete surface strain predicted by the model were in close agreement with the experiments. This paper also describes how the model can be applied to create interaction surfaces. The interaction curves predicted by the model were validated by comparing the predicted and experimental capacities of 17 specimens available in the literature.     

2008 Peck Lecture: The Observational Method: Case History and Models

The observational method was used to design and construct an embankment over a deposit of soft sludge. The first part of the paper describes the case history of the project. The second part describes the use of analytical models as part of the observational method. The finite-element method and one-dimensional consolidation solution were used as prediction models. Bayesian updating was used to revise the material properties with observed performance. Advantages and limitations of updating are presented.     

Empirical Study on the Merit of Web-Based 4D Visualization in Collaborative Construction Planning and Scheduling

This paper reports an empirical study that tested the usefulness of Web-based four-dimensional (4D) construction visualization in collaborative construction planning and scheduling. Several recent construction projects have employed 4D visualization to better understand the construction schedule and make proactive decisions to prevent logical errors in the construction sequence. Other groups have shown that construction information management with asynchronous Web-based communication can improve decision making among dispersed industry practitioners. It seems reasonable to anticipate that combining 4D visualization with Web-based information management would facilitate dispersed industry practitioners to make collaborative decisions for construction planning and scheduling. The empirical study presented here reports how experiment participants at separate locations collaboratively detected logical errors in a construction schedule when the 4D visualization model of the schedule was represented on the Web browser. Our results show that teams using 4D models detected logical errors more frequently, faster, with fewer mistakes, and with less team communication, than teams using 2D drawings and bar charts. These findings show industry practitioners empirical evidence that Web-based 4D construction visualization can improve team collaboration on construction planning and scheduling.     

GCr15钢加热工艺与液析、带状的关系

轴承钢在轧制之前对钢锭进行高温扩散退火对消除碳化物液析、改善碳化物带状是极其关键的一道工序,以前对模铸轴承钢研究较多,而对连铸坯的高温扩散退工艺的研究比较少。此文针对连铸坯的高温扩散工艺-加热温度和时间与碳化物液析、碳化物带状的关系进行了研究,结合车间加热炉的加热能力,确定了比较合适的加热工艺制度：将加热温度调整到1200～1280℃,加热时间接近5小时,可使带状级别控制到2级以下,使碳化物液析得到消除,提升了产品的内在质量,有重要的经济价值,并对我国连铸轴承钢连铸坯的高温扩散工艺有一定的参考价值。     

Exploring the Relationship between Soil Properties and Deterioration of Metallic Pipes Using Predictive Data Mining Methods

Soil corrosivity is considered to be a major factor for the deterioration of metallic water mains. Using a 10-point scoring method as suggested by the American Water Works Association, soil corrosivity potential can be estimated by five soil properties: (1) resistivity; (2) pH value; (3) redox potential; (4) sulfide; and (5) percentage of clay fines. However, the relationship between soil corrosivity and pipe deterioration is often ambiguous and not well-defined. In order to identify the direct relationship between soil properties and pipe deterioration, which is defined as the ratio of the maximum pit depth to pipe age, predictive data mining approaches are investigated in this study. Both single- and multipredictor based approaches are employed to model such relationship. The advantage of combining multiple predictors is also demonstrated. Among all approaches, rotation forest achieves the best result in terms of the prediction error to estimate pipe deterioration rate. Compared to the random forest method, which is next to the best, the normalized mean square error decreased 50%. With the proposed approaches, the assessment of pipe condition can be achieved by analyzing soil properties. This study also highlights the importance for collecting more reliable soil properties data.