Standard Test Data Research Articles

Statistical Prediction of Liquefaction Potential in Mining Dump Areas of the Nagpur Region Using Standard Penetration Test (SPT) Data

Liquefaction could be a complicated and questionable but critical subject in ground building, particularly in places that are inclined to seismic tremors. Since of the visit seismic tremors in Nagpur, the developing mining industry makes it difficult to construct successful strategies for getting freed of mine squander. Seismic tremors are a major reason why structures fall flat, for the most part since of liquefaction, which does a parcel of harm to framework. This consider is for the most part approximately Nagpur, which is the third-largest city in Maharashtra and is growing very rapidly. The most objective is to form a arrange of the Nagpur mine dump ranges, figure out how likely it is that the dumps will liquefy, and make the information accessible for future investigate. The think about looks at soil liquefaction within the mine zone utilizing an SPT-N-based strategy. The liquefaction potential is measured utilizing the factor of security (FS) at distinctive soil levels that were found amid the think about. Standard Entrance Testing (SPT) was exhausted 11 test spots around the mine dumping range, and the comes about were composed down in boreholes. Modern investigate shows that the affectability to liquefaction is influenced by the number of SPT blows and the most extreme ground movement. The SPT-N esteem is balanced for the Cyclic Resistance Ratio (CRR), which appears that the soil's qualities and water table levels alter, and higher N values are ordinarily display. This implies that the soil contains a much lower chance of liquefying.

Time Histories Finite Element Modelling for Irrigation Canal Stability Analysis under the Effects of Liquefaction in the Sibowi Sigi Regency, Indonesia

Abstract The Gumbasa irrigation canals are one of the water resource infrastructures damaged by the 7.5 Mw Palu-Donggala Earthquake in 2018. Canal reconstruction was performed to restore the function of the irrigation network, supllying a potential area of 8000 ha. Main canal construction is known to pass through areas with liquefaction vulnerability, and seismic factors also play a role in the stability of construction. This study discusses the stability of construction under the influence of earthquake loads on the Gumbasa irrigation main canal in the Sibowi area, Tanambulava district, Sigi Regency. The irrigation main canals are built in a landfill on a subbase soil with the potential for liquefaction. Numerical simulations were carried out using the finite element method under two conditions, namely static and dynamic conditions on soil parameters obtained from the Standard Penetration Test (N-SPT) data obtained previously. Based on the analysis results, depths of 6.5 m to 9 m have partial potential for liquefaction, with no significant decrease in safety factor (SF). In the static analysis, the SF is 1.65 and 2.13. In the dynamic analysis, the SF is 1.64 and 2.12. The vertical displacement is minimum 0.03 m and maximum 0.10 m.

The Role of Pathways Early Autism Intervention in Improving Social Skills and Respeto for Young Hispanic Autistic Children.

We know very little about Hispanic autistic children's response to intervention as, historically, Hispanic children are underrepresented in intervention studies. Pathways parent-mediated early autism intervention is one of the few naturalistic developmental behavioral interventions (NDBIs) that is contextually and linguistically responsive to Hispanic families. However, some child-centered NDBI strategies do not align with the Hispanic caregiving value of respeto. A child exhibiting respeto demonstrates affiliative obedience by displaying deference and respect toward adults. Furthermore, theories of the ontogeny of cultural learning suggest that certain levels of social development may be necessary to learn cultural values. The current study investigates (1) the relationship between Hispanic autistic children's social skills and affiliative obedience and (2) the efficacy of Pathways in improving affiliative obedience in Hispanic children. This quasi-experimental design study used preexisting standardized test data and video recordings from 26 Hispanic participants who took part in a previous Pathways efficacy study. Recordings were coded for affiliative obedience and social connectedness. Residual change variables were used to measure progress from baseline to post-intervention, and correlation and hierarchical regression analyses were conducted to analyze the data. We found significant positive correlations between social skills and children's affiliative obedience for baseline and change variables. In addition, we found Pathways had a significant medium-large magnitude effect on change in affiliative obedience skills. This study highlights the benefits of NDBI interventions that advance social development in autistic children and support Hispanic parents in enculturating their children in the value of respeto.

A Machine Learning-Based Approach for Predicting Installation Torque of Helical Piles from SPT Data

Helical piles are advantageous alternatives in constructions subjected to high tractions in their foundations, like transmission towers. Installation torque is a key parameter to define installation equipment and the final depth of the helical pile. This work applies machine learning (ML) techniques to predict helical pile installation torque based on information from 707 installation reports, including Standard Penetration Test (SPT) data. It uses this information to build three datasets to train and test eight machine-learning techniques. Decision tree (DT) was the worst technique for comparing performances, and cubist (CUB) was the best. Pile length was the most important variable, while soil type had little relevance for predictions. Predictions become more accurate for torque values greater than 8 kNm. Results show that CUB predictions are within 0.71,1.59 times the real value with a 95% confidence. Thus, CUB successfully predicted the pile length using SPT data in a case study. One can conclude that the proposed methodology has the potential to aid in the helical pile design and the equipment specification for installation.

Fire Safety Research Institute Materials and Products database—A resource to support fire modeling

For decades, there has been a need in the fire safety science community for a reliable source of material properties and standard fire test data to accurately represent solid materials in fire models. The project described herein has made advancements in experimental data collection and property determination for a multitude of materials commonly encountered in the built environment for the purpose of making the data easily accessible and to elevate the base knowledge and tools available for all model practitioners and investigators. This article includes a description of the experimental methods, procedures, and estimated uncertainty in the measurements that have been adopted to collect the data necessary to describe common materials in the most advanced comprehensive pyrolysis models. A case study is provided in which all the experiments to characterize polycarbonate are described, analytical procedures and derived properties are presented, and validation of the properties against experimental data is presented.

Analysis Of Bearing Capacity Of Pile Foundations Using Analytical Method And Finite Element Method

The foundation is the lower part of a structure used as a load distributor for loads generated. The selection of foundation types in building construction must consider the type and characteristics of the soil at the construction site to avoid construction failures. This analysis is conducted to determine the bearing capacity of pile foundations using analytical and finite element methods. The type of foundation used in this analysis is a pile foundation with a pile length of 8 meters and a pile diameter of 0.4 meters. For the analytical calculation, Standard Penetration Test (SPT) data obtained from PT. Adhi Karya (Persero) for the Infrastructure Green House Biodiversity LIPI Cibinong-Bogor project are used, employing the analytical method (Alpha Method) and the finite element method with the assistance of Plaxis 2D V.8 software. The results of the analysis show that the bearing capacity of the group pile foundation (Qg) for a pile diameter of 0.4 meters and a pile length of 8 meters on clayey soil, based on SPT data using the analytical method (Alpha Method), is 60.432 tons. Meanwhile, the bearing capacity of the horizontal pile foundation using the Broms method is 6.03 tons. The bearing capacity obtained using the Finite Element Method yields an ultimate load on the group pile (Qq) of 57.89 tons. The bearing capacity of the group pile foundation (Qg) from both sets of data, with a difference of 2.5%, meets the requirement, being greater than the axial load (P) of 42.6 tons that must be supported.

Liquefaction potential analysis based on standard penetration test data at irrigation canals in Sibowi Area-Central Sulawesi Province

A phenomenon in which non-cohesive soil in saturated conditions loses its carrying capacity owing to the reduced stiffness and strength of the soil during earthquake shaking or rapid loading is called liquefaction. This occurs under the structure and can cause damage during earthquakes. In this study, we estimated the possibility of liquefaction in the main irrigation canals in the Sibowi area of Central Sulawesi Province, considering that the soil type in this area is sandy. Liquefaction analysis uses a simplified procedure using Standard Penetration Test data to obtain the Safety Factor and estimate the potential level of liquefaction using the Liquid Potential Index (LPI) method. According to the analysis, with the 7.5 Mw earthquake and groundwater levels observed, most of the soil layer below the irrigation canals still has liquefaction potential at 15 m to 19.5 m. The LPI result that 5 (five) out of 10 (ten) boreholes have the potential for liquefaction in low to moderate categories, and the boreholes that have liquefaction potential have groundwater depths between 14 and 16 m.

Assessment of liquefaction potential and damage on the toll road construction in earthquake-prone area, Sleman Regency, Yogyakarta

The construction of toll roads in earthquake-prone areas presents significant challenges due to the potential occurrence of liquefaction, a seismic phenomenon in fine-grained soils losing strength during earthquakes. The research was conducted at a toll road construction site in Sleman Regency, Yogyakarta, an area near the active Opak fault which increases its vulnerability to liquefaction. The objective of this study is to analyse the liquefaction potential and damage on the surface in research area. The method used is simplified procedure by Idriss and Boulanger which assessing the cyclic stress ratio and cyclic resistance ratio based on standard penetration test and laboratory data. Then, Liquefaction Potential Index (LPI) and Liquefaction Severity Index (LSI) are calculated. Finally, vertical displacement caused by liquefied soil is estimated using the post-cyclic reconsolidation model to understand its impact on the surface. The study shows low to very high liquefaction potential at the toll road construction site in Sleman Regency. With a vertical displacement of 4.69 cm to 38.83 cm, surface damage can range from low to extensive, emphasizing the need for liquefaction mitigation in earthquake-prone areas like Yogyakarta during toll road infrastructure planning.

Thromboelastometric Analysis of the Correlation Between Burn-Induced Coagulopathy and Severity of Burn Injury.

Background In this study, we aimed to analyze the association between the burn index (BI) and burn-induced coagulopathy. Methods Adult burn patients transported to our emergency department who underwent rotational thromboelastometry (ROTEM) between April 1, 2013, and December 31, 2021, were enrolled in this study. The patients were categorized into two groups based on burn severity. Severe burns were defined as BI scores of > 15. Patient demographics, clinical variables of burns, standard laboratory test data, ROTEM data, and clinical outcomes of both groups were evaluated. In addition, the correlation between severe burns and significant variables was evaluated using a univariate analysis. Results Seven patients were enrolled and categorized into the severe (n = 2) and control (n = 5) groups. The severe group had a significantly worse consciousness level and higher mortality rate and showed higher tendencies of burn severity and clinical severity scores. Disseminated intravascular coagulation was confirmed in one patient. All ROTEM variables in the severe group regarding clot firmness in the extrinsic coagulation cascade (EXTEM) and fibrinogen-specific coagulation cascade (FIBTEM) showed a decreasing tendency as compared to those in the control group. Moreover, correlation analyses revealed strong correlations between the BI and clot firmness (rho = -0.946 to -0.721). Conclusions Severe BI was strongly associated with decreased blood clot firmness in EXTEM, FIBTEM, and ROTEM. Future research using viscoelastic devices may provide new possibilities for the treatment of severe burns.

Perbandingan Daya Dukung Tiang Pancang dengan Alat Berat Drop Hammer dan Hydraulic Static Pile Driver (HSPD)

The foundation is a base or bottom structure that can carry all the loads above it. Foundation bearing capacity and foundation settlement are very important for foundation planning. In the construction project for the Faculty of Agricultural Technology building at Jember Polytechnic, a recalculation analysis was carried out to compare the carrying capacity using two methods, namely HSPD and Drop Hammer. Soil bearing capacity is calculated based on Standard Penetration Test (SPT) data from 2 soil investigation points. Next, the soil bearing capacity is calculated using the Drop Hammer assumption. The research results show that there is a difference in the carrying capacity of HSPD and Drop Hammer. And the results can be carried out using 2 HSPD heavy equipment and a Drop Hammer at that location. In comparison, Drop Hammer and HSPD driving on a 25 x 25cm mini pile foundation can be carried out. And in the field you can use 2 heavy equipment simultaneously, namely HSPD for spun pile D 50 cm at the smallest permitted carrying capacity value of 68 tonnes at a depth of approximately 12 meters and drop hammer for mini piles at a permitted carrying capacity value of 40.94 tonnes at a depth of approximately 6 meters. However, if you use a drop hammer in areas near residents, don't forget to plan the trench work to reduce vibrations to the surrounding area.

Environmental Risk Assessment with Energy Budget Models: A Comparison Between Two Models of Different Complexity.

The extrapolation of effects from controlled standard laboratory tests to real environmental conditions is a major challenge facing ecological risk assessment (ERA) of chemicals. Toxicokinetic-toxicodynamic (TKTD) models, such as those based on dynamic energy budget (DEB) theory, can play an important role in filling this gap. Through the years, different practical TKTD models have been derived from DEB theory, ranging from the full "standard" DEB animal model to simplified "DEBtox" models. It is currently unclear what impact a different level of model complexity can have on the regulatory risk assessment. In the present study, we compare the performance of two DEB-TKTD models with different levels of complexity, focusing on model calibration on standard test data and on forward predictions for untested time-variable exposure profiles. The first model is based on the standard DEB model with primary parameters, whereas the second is a reduced version with compound parameters, based on DEBkiss. After harmonization of the modeling choices, we demonstrate that these two models can achieve very similar performances both in the calibration step and in the forward prediction step. With the data presented in the present study, selection of the most suitable TKTD model for ERA therefore cannot be based alone on goodness-of-fit or on the precision of model predictions (within current ERA procedures for pesticides) but would likely be based on the trade-off between ease of use and model flexibility. We also stress the importance of modeling choices, such as how to fill gaps in the information content of experimental toxicity data and how to accommodate differences in growth and reproduction between different data sets for the same chemical-species combination. Environ Toxicol Chem 2024;43:440-449. © 2023 ibacon GmbH. Bayer AG and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Exploring the influence of collaborative data-based decision making among teachers in professional learning communities on teaching practice

Educational policies such as the No Child Left Behind Act in 2001 and Every Student Succeeds Act in 2015 have emphasized the need for hard evidence such as standardized test data to make educational decisions. Therefore, teachers have been expected to use student assessment data to make informed curricular decisions and adjustments in teaching practice. This has led school districts to turn to data-based decision-making (DBDM) to create an effective process of student assessment data analysis, and reflection during professional learning communities (PLCs). The study explored teachers’ collaboration on the DBDM when teachers were analyzing student assessment data from common, district, and state assessments, as well as its influence on their instructional decisions. Participating teachers’ department and PLC meetings were recorded, and individual teachers’ classrooms were also observed. Teacher interview data and their lesson plans were also included and analyzed qualitatively. Results revealed that the purpose of collaboration determined types of data used, modes of analysis, and the impact on their teaching. Furthermore, teachers used varied assessment data to plan and adjust their instruction. Their motivation to enhance their teaching practices was also increased by exchanging ideas and insights rooted in the data.

Development and Validation of an Individualized and Weighted Prognostic Model in Patients with Newly Diagnosed Multiple Myeloma

Introduction Multiple myeloma (MM) is a malignancy of terminally differentiated antibody-secreting plasma cells in the bone marrow with highly variable survival outcomes. Precise risk stratification not only plays a vital role in predicting patient prognoses, but critically can be used to develop risk-adapted treatment regimens. However, current risk stratification models do not adequately account for the heterogeneity of patients with new-diagnosed multiple myeloma (NDMM). Methods In this retrospective, multicohort study, we collected clinical data from 1792 NDMM patients and formulated a weighted Myeloma Prognostic Score System (MPSS) risk model to predict overall survival (OS). Construction of the MPSS model was carried out based on the National Longitudinal Cohort of Hematological Diseases in China (NCT04645199) cohort, external validation cohort was created using TT2, TT3a, and TT3b cohorts from a series of randomized prospective studies from the University of Arkansas for Medical Sciences (UAMS). Results Each risk factor was defined as its weighted value respectively according to their hazard ratio for OS (thrombocytopenia 2, elevated LDH 1, ISS III 2, one high-risk cytogenetic aberration [HRA] 1, and ≥2 HRA 2 points). In the training cohort, patients were furtherly stratified into four risk groups: MPSS I (22.5%, 0 points), II (17.6%, 1 points), III (38.6%, 2-3 points), and IV (21.3%, 4-7 points). MPSS risk stratification showed optimal discrimination, as well as calibration, of four risk groups with median OS of 91.0, 69.8, 45.0, and 28.0 months, for patients in MPSS I to IV groups (P< 0.001), respectively. Importantly, the MPSS model retained its prognostic value in the internal validation cohort and an independent external validation cohort, and exhibited significant risk distribution compared with conventional prognostic models (R-ISS, R2-ISS, and MASS). Conclusions In conclusion, we formulated and validated the MPSS risk model to predict the prognosis of patients with MM using readily available standard clinical and genetic test data. The established MPSS profile shows a better performance in risk discrimination than the current R-ISS, R2-ISS, and MASS. A score-based risk stratification is derived, and identifies patients with high and ultra-high risk of death after diagnosis and may therefore aid the development of more personalized treatment strategies, especially for patients for whom current therapies are likely to fail.

Knowledge-based U-Net and transfer learning for automatic boundary segmentation

An effective soil classification method is essential for soil layering interpretation. Traditional methods rely on empirical formulae or a general unified system, which may not be accurate for every site. Recent advancements in deep learning have shown promising results in a wide range of practical domains, which provides motivation to explore its potential application in soil classification. A “U-shaped” convolutional neural network (U-Net), coupled with multiple source data to incorporate prior knowledge, is adopted in this study to predict the depths of soil stratum boundaries based on cone penetration testing (CPT), standard penetration testing (SPT) and laboratory index testing data. The U-Net model is first pre-trained on open-access data from other sites around the world and then trained through transfer learning on datasets gathered specifically for the Suzhou No.6 metroline project. Comparison is made from different metrics to investigate how pre-training benefits model performance. The soil boundaries in nine selected output images are extracted and reversed to their original depth for visualization of a subsurface profile. Comparisons to the benchmark interpretations show that the predicted soil profiles have reasonably good agreement with the benchmark profiles developed by an engineering expert. The results indicate that the proposed method is effective and efficient for the prediction of soil stratification.

Improved computational methods for probabilistic liquefaction hazard analysis

Current procedures for analysis of and design against liquefaction hazards focus primarily on the use of probabilistic ground motions at a single ground-shaking hazard level, with the cyclic loading represented by a peak ground acceleration (PGA) corresponding to a target return period and a single representative moment magnitude Mw. These parameters are typically used in conjunction with deterministic simplified procedures for estimating liquefaction triggering and consequences that largely neglect the considerable uncertainties inherent to liquefaction problems. Motivated by these limitations and the resulting inconsistencies in liquefaction design levels, early methods for probabilistic liquefaction hazard analysis (PLHA) were proposed that incorporate the full ground motion hazard space, integrated with probabilistic liquefaction triggering models. Such methods provide liquefaction factor of safety (FSL) hazard curves for standard penetration test (SPT) data. Recognizing the increased use of higher-resolution cone penetrometer test (CPT) data in engineering analysis and design and the potential computational challenges it presents, an expanded suite of probabilistic triggering models, and wider availability of more detailed seismic hazard data, an improved PLHA computational methodology is presented in this study. The methods described utilize the U.S. Geological Survey National Seismic Hazard Model directly through web services to obtain PGA hazard and disaggregation calculations for any site and average shear wave velocity in the upper 30 m of the site (Vs30) in the conterminous United States, to reconstruct the PGA hazard space for use in PLHA calculations, and to employ array calculations for efficient liquefaction hazard curve estimates for the thousands of CPT measurements in a given profile. The framework presented here is modular in nature, and discussion on the use of alternative models and extension to probabilistic liquefaction consequence evaluation is presented. The importance of appropriate representation of probabilistic liquefaction model uncertainties is also highlighted, along with the impacts of different levels of uncertainty on the PLHA calculation. Finally, a potential roadmap for incorporation of the PLHA framework in seismic provisions is presented, with an illustration of how it can address current limitations and impacts in liquefaction hazard analysis and design.

Knowledge-based multiple point statistics for soil stratigraphy simulation

An accurate representation of subsurface stratigraphy in the form of geotechnical profiles is a prerequisite for optimal underground design and safe construction. This paper proposes a novel knowledge-based multiple point statistics (KMPS) method to simulate the heterogeneities and spatial trends of subsurface strata and to generate geotechnical profiles. This approach incorporates domain knowledge in the form of cone penetration test and standard penetration test data as well as results from laboratory testing to increase simulation accuracy. A novel varying search template size and similarity threshold is adopted to alleviate the computational cost of the simulations. Ablation analyses are used to quantify the improvement of the proposed KMPS algorithm over existing baseline multiple point statistics algorithms. By way of example, the proposed approach is applied to real-world exploration data from the Suzhou No.6 metroline project. The results show that the computational cost of KMPS is effectively minimized whilst the simulation accuracy can be improved by up to 13.3%. The algorithm is further validated by extending the simulation to a test image. With sparse exploration data, the KMPS method is shown to effectively and efficiently predict soil profiles based on prior experience embodied by a training image, thus enabling a reduction in the number of field exploration boreholes.

Application of the effective crack length method to model delamination of unidirectional composite laminates under Mode II shear loadings

Damage modelling of composite material delamination is an intense field of research to understand the complex composite failure behaviour and predict the residual strength of damaged structures. One of the widely employed methods to simulate delamination is the cohesive zone modelling (CZM) technique. To successfully utilize this approach, accurate characterisation of the interlaminar fracture toughness is crucial, while the composite delamination is dominated by Mode I and Mode II fracture in most cases. Numerous studies have been conducted on composite materials delamination under Mode I loadings using double cantilever beam (DCB) tests. Accordingly, the ASTM standard testing procedure and data reduction scheme to obtain Mode I fracture toughness (GIc) have been well established and widely accepted. However, it is still challenging to characterize the composite Mode II delamination resistance due to the susceptibility problems inherent to the existing testing methods and the lack of robust data reduction schemes to accurately identify the initial crack tip and monitor the crack growth. This study attempts to find a reliable solution to obtain the Mode II fracture toughness (GIIC) and an effective modelling strategy to simulate Mode II delamination in laminated composites. First, we reviewed the existing testing set-ups and surveyed the data reduction schemes conventionally used to obtain GIIC. The advantages and drawbacks of the three most used test methods, and particularly the standard end-notched flexure (ENF) test (ASTM D7905/D7905M) and the end-loaded split (ELS) test (ISO 15114:2014) were examined. Second, the advantages of the effective-crack-length-based data reduction schemes against the classical data reduction schemes were empirically studied with the ENF tests conducted on G40-800/5276-1 carbon-fibre reinforced composite laminate coupons. Although many studies have studied the accuracy of the effective-crack-length-based approaches from different aspects, there is a lack of direct comparison between the numerical results and experimental data. Our modelling study demonstrates that among the five data reduction schemes that are examined, the compliance calibration method (CCM) required by ASTM D7905 yields the most conservative GIIC values, which is suitable for establishing material property for a design purpose. The compliance-based beam method (CBBM) may generate the least conservative GIIC values, which are deemed to be the most accurate ones for modelling and simulation validation purposes. Finite element (FE) modelling of the ENF tests using the CZM technique was carried out and comprehensive parametric studies were conducted to achieve an efficient and robust strategy for delamination modelling of composite laminates under Mode II shear loadings.

A Centralized Multi-Criteria Method for Scheduling Tasks in a Cloud Computing Environment

Task scheduling determines the order of mapping tasks to virtual machines to meet objectives. In this paper, a batch mode heuristic method that is centralized, dynamic, and multi-objective has been presented for scheduling independent tasks with a deadline and belonging to several user levels, using the cloud elasticity in the public cloud environment. In this method, it has been intended to improve the objectives of makespan, deadline violation, total execution cost, and load balancing by considering the tasks’ prioritization based on the criteria of user level, deadline, task length, and selection of heterogeneous virtual machines according to processing power, workload and usage cost. The proposed method was simulated using the CloudSim tool. Besides, the method’s ability to achieve the mentioned goals has been evaluated in comparison with similar methods. The evaluation results, established on standard test data, show that the proposed method has a good performance in improving its objectives.

Estimating of Post-liquefaction Settlement Based on SPT Data in Klaten Regency, Central Java

A strong earthquake with Mw 6.3 occurred in Yogyakarta on May 27, 2006, causes of damage to DI Yogyakarta Province and Central Java Province, including Klaten Regency. The geological stratigraphy consists of volcanic breccias, lava and tuff in this area and generally shallow groundwater levels, which can trigger liquefaction. The potential liquefaction analysis in this study uses Standard Penetration Test (SPT) data carried out in 3 districts, namely Delanggu, Polanharjo, and Karanganom District uses Idriss-Boulanger method. The peak ground acceleration was calculated by Next Generation Attenuation (NGA) method using data obtained from the Pacific Earthquake Engineering Research (PEER) Center database. The peak ground acceleration that causes liquefaction in this study is at least 0.29 g in bedrock. All areas indicated potential liquefaction with varying depths. Polanharjo District is the most susceptible to potential liquefaction. The method proposed by Zhang estimates post-liquefaction settlement in this study from 3.3 – 42.4 cm (light to extensive damage) in Klaten Regency. Based on the results, further mitigation studies are needed in Klaten Regency to minimize settlement that will occur due to liquefaction. This study is required in planning the construction of toll road in Klaten Regency.

Probabilistic and deterministic-based approach for liquefaction potential assessment of layered soil

In the present study, deterministic and probabilistic approaches have been used for the assessment of liquefaction potential of ground during an earthquake. The deterministic approach was used to analyze and assess the liquefaction of loose saturated river bed deposit with emphasis on two benchmark locations. A wide range of earthquake data in the form of peak ground acceleration (PGA) values of 0.18 g, 0.37 g, 0.6 g and 0.75 g was used as input motions. The dynamic properties of soil were evaluated using standard penetration test (SPT) data obtained from the bore logs. The shear stress induced within soil deposit due to the seismic excitation was calculated in the form of cyclic stress ratio (CSR) and cyclic resistance ratio (CRR) in order to calculate the factor of safety (FOS) against liquefaction. In addition, liquefaction potential index (LPI) and probability of liquefaction (PL) were also calculated using input motion. It was observed, based on the probability analysis and liquefaction indices, that the shallow layer soil profile is safe against liquefaction, whereas deep layer soil profile is unsafe.