3,436 research outputs found
Predicting and validating the load-settlement behavior of large-scale geosynthetic-reinforced soil abutments using hybrid intelligent modeling
Settlement prediction of geosynthetic-reinforced soil (GRS) abutments under service loading conditions is an arduous and challenging task for practicing geotechnical/civil engineers. Hence, in this paper, a novel hybrid artificial intelligence (AI)-based model was developed by the combination of artificial neural network (ANN) and Harris hawks’ optimisation (HHO), that is, ANN-HHO, to predict the settlement of the GRS abutments. Five other robust intelligent models such as support vector regression (SVR), Gaussian process regression (GPR), relevance vector machine (RVM), sequential minimal optimisation regression (SMOR), and least-median square regression (LMSR) were constructed and compared to the ANN-HHO model. The predictive strength, relalibility and robustness of the model were evaluated based on rigorous statistical testing, ranking criteria, multi-criteria approach, uncertainity analysis and sensitivity analysis (SA). Moreover, the predictive veracity of the model was also substantiated against several large-scale independent experimental studies on GRS abutments reported in the scientific literature. The acquired findings demonstrated that the ANN-HHO model predicted the settlement of GRS abutments with reasonable accuracy and yielded superior performance in comparison to counterpart models. Therefore, it becomes one of predictive tools employed by geotechnical/civil engineers in preliminary decision-making when investigating the in-service performance of GRS abutments. Finally, the model has been converted into a simple mathematical formulation for easy hand calculations, and it is proved cost-effective and less time-consuming in comparison to experimental tests and numerical simulations
Inferring the joint demographic history of multiple populations from multidimensional SNP frequency data
Demographic models built from genetic data play important roles in
illuminating prehistorical events and serving as null models in genome scans
for selection. We introduce an inference method based on the joint frequency
spectrum of genetic variants within and between populations. For candidate
models we numerically compute the expected spectrum using a diffusion
approximation to the one-locus two-allele Wright-Fisher process, involving up
to three simultaneous populations. Our approach is a composite likelihood
scheme, since linkage between neutral loci alters the variance but not the
expectation of the frequency spectrum. We thus use bootstraps incorporating
linkage to estimate uncertainties for parameters and significance values for
hypothesis tests. Our method can also incorporate selection on single sites,
predicting the joint distribution of selected alleles among populations
experiencing a bevy of evolutionary forces, including expansions, contractions,
migrations, and admixture. As applications, we model human expansion out of
Africa and the settlement of the New World, using 5 Mb of noncoding DNA
resequenced in 68 individuals from 4 populations (YRI, CHB, CEU, and MXL) by
the Environmental Genome Project. We also combine our demographic model with a
previously estimated distribution of selective effects among newly arising
amino acid mutations to accurately predict the frequency spectrum of
nonsynonymous variants across three continental populations (YRI, CHB, CEU).Comment: 17 pages, 4 figures, supporting information included with sourc
Evaluation of Induced Settlements of Piled Rafts in the Coupled Static-Dynamic Loads Using Neural Networks and Evolutionary Polynomial Regression
Coupled Piled Raft Foundations (CPRFs) are broadly applied to share heavy loads of superstructures between piles and rafts and reduce total and differential settlements. Settlements induced by static/coupled static-dynamic loads are one of the main concerns of engineers in designing CPRFs. Evaluation of induced settlements of CPRFs has been commonly carried out using three-dimensional finite element/finite difference modeling or through expensive real-scale/prototype model tests. Since the analyses, especially in the case of coupled static-dynamic loads, are not simply conducted, this paper presents two practical methods to gain the values of settlement. First, different nonlinear finite difference models under different static and coupled static-dynamic loads are developed to calculate exerted settlements. Analyses are performed with respect to different axial loads and pile’s configurations, numbers, lengths, diameters, and spacing for both loading cases. Based on the results of well-validated three-dimensional finite difference modeling, artificial neural networks and evolutionary polynomial regressions are then applied and introduced as capable methods to accurately present both static and coupled static-dynamic settlements. Also, using a sensitivity analysis based on Cosine Amplitude Method, axial load is introduced as the most influential parameter, while the ratio l/d is reported as the least effective parameter on the settlements of CPRFs
Advanced Theoretical and Computational Methods for Complex Materials and Structures
The broad use of composite materials and shell structural members with complex geometries in technologies related to various branches of engineering has gained increased attention from scientists and engineers for the development of even more refined approaches and investigation of their mechanical behavior. It is well known that composite materials are able to provide higher values of strength stiffness, and thermal properties, together with conferring reduced weight, which can affect the mechanical behavior of beams, plates, and shells, in terms of static response, vibrations, and buckling loads. At the same time, enhanced structures made of composite materials can feature internal length scales and non-local behaviors, with great sensitivity to different staking sequences, ply orientations, agglomeration of nanoparticles, volume fractions of constituents, and porosity levels, among others. In addition to fiber-reinforced composites and laminates, increased attention has been paid in literature to the study of innovative components such as functionally graded materials (FGMs), carbon nanotubes (CNTs), graphene nanoplatelets, and smart constituents. Some examples of smart applications involve large stroke smart actuators, piezoelectric sensors, shape memory alloys, magnetostrictive and electrostrictive materials, as well as auxetic components and angle-tow laminates. These constituents can be included in the lamination schemes of smart structures to control and monitor the vibrational behavior or the static deflection of several composites. The development of advanced theoretical and computational models for composite materials and structures is a subject of active research and this is explored here for different complex systems, including their static, dynamic, and buckling responses; fracture mechanics at different scales; the adhesion, cohesion, and delamination of materials and interfaces
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Local forest structure variability increases resilience to wildfire in dry western U.S. coniferous forests.
A 'resilient' forest endures disturbance and is likely to persist. Resilience to wildfire may arise from feedback between fire behaviour and forest structure in dry forest systems. Frequent fire creates fine-scale variability in forest structure, which may then interrupt fuel continuity and prevent future fires from killing overstorey trees. Testing the generality and scale of this phenomenon is challenging for vast, long-lived forest ecosystems. We quantify forest structural variability and fire severity across >30 years and >1000 wildfires in California's Sierra Nevada. We find that greater variability in forest structure increases resilience by reducing rates of fire-induced tree mortality and that the scale of this effect is local, manifesting at the smallest spatial extent of forest structure tested (90 × 90 m). Resilience of these forests is likely compromised by structural homogenisation from a century of fire suppression, but could be restored with management that increases forest structural variability
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Population History and Gene Divergence in Native Mexicans Inferred from 76 Human Exomes.
Native American genetic variation remains underrepresented in most catalogs of human genome sequencing data. Previous genotyping efforts have revealed that Mexico's Indigenous population is highly differentiated and substructured, thus potentially harboring higher proportions of private genetic variants of functional and biomedical relevance. Here we have targeted the coding fraction of the genome and characterized its full site frequency spectrum by sequencing 76 exomes from five Indigenous populations across Mexico. Using diffusion approximations, we modeled the demographic history of Indigenous populations from Mexico with northern and southern ethnic groups splitting 7.2 KYA and subsequently diverging locally 6.5 and 5.7 KYA, respectively. Selection scans for positive selection revealed BCL2L13 and KBTBD8 genes as potential candidates for adaptive evolution in Rarámuris and Triquis, respectively. BCL2L13 is highly expressed in skeletal muscle and could be related to physical endurance, a well-known phenotype of the northern Mexico Rarámuri. The KBTBD8 gene has been associated with idiopathic short stature and we found it to be highly differentiated in Triqui, a southern Indigenous group from Oaxaca whose height is extremely low compared to other Native populations
Robust Geotechnical Design - Methodology and Applications
This dissertation is aimed at developing a novel robust geotechnical design methodology and demonstrating this methodology for the design of geotechnical systems. The goal of a robust design is to make the response of a system insensitive to, or robust against, the variation of uncertain geotechnical parameters (termed noise factors in the context of robust design) by carefully adjusting design parameters (those that can be controlled by the designer such as geometry of the design). Through an extensive investigation, a robust geotechnical design methodology that considers explicitly safety, robustness, and cost is developed. Various robustness measures are considered in this study, and the developed methodology is implemented with a multi-objective optimization scheme, in which safety is considered as a constraint and cost and robustness are treated as the objectives. Because the cost and the robustness are conflicting objectives, the robust design optimization does not yield a single best solution. Rather, a Pareto front is obtained, which is a collection of non-dominated optimal designs. The Pareto front reveals a trade-off relationship between cost and robustness, which enables the engineer to make an informed design decision according to a target level of cost or robustness. The significance and versatility of the new design methodology are illustrated with multiple geotechnical applications, including the design of drilled shafts, shallow foundations, and braced excavations
Determining Additional Modulus of Subgarde Reaction Based on Tolerable Settlement for the Nailed-slab System Resting on Soft Clay.
Abstract—Nailed-slab System is a proposed alternative
solution for rigid pavement problem on soft soils. Equivalent
modulus of subgrade reaction (k’) can be used in designing of
nailed-slab system. This modular is the cumulative of modulus of
subgrade reaction from plate load test (k) and additional
modulus of subgrade reaction due to pile installing (∆∆∆∆k). A recent
method has used reduction of pile resistance approach in
determining ∆∆∆∆k. The relative displacement between pile and soils,
and reduction of pile resistance has been identified. In fact,
determining of reduction of pile resistance is difficult. This paper
proposes an approach by considering tolerable settlement of rigid
pavement. Validation is carried out with respect to a loading test
of nailed-slab models. The models are presented as strip section
of rigid pavement. The theory of beams on elastic foundation is
used to calculate the slab deflection by using k’. Proposed
approach can results in deflection prediction close to observed
one. In practice, the Nailed-slab System would be constructed by
multiple-row piles. Designing this system based on one-pile row
analysis will give more safety design and will consume less time
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General report of TC103 numerical methods in geomechanics
This paper presents a General Report on 46 contributions, including poster presentations, submitted for the parallel sessions organized by TC 103: Numerical Methods in Geomechanics. The authors come from various regions of the world and the topics of the submitted papers are diverse. These contributions are reviewed from the viewpoint of the current research directions in relation to the numerical schemes and their key results. The overview of the latest work is provided in this general report, dividing the broad paper topics into several important subjects
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