Recent coe items

Quantifying the Current and Future Greenhouse Gas Emissions from Road Infrastructure in Africa

Tue, 27 Jan 2026 00:00:00 +0000

This paper uses a newly developed framework for quantifying current and future greenhouse gas (GHG) emissions from Africa’s road transportation sector. It provides first-order estimates for road infrastructure projects (new road construction and existing road maintenance and rehabilitation) and vehicle-related emissions through 2050. Africa's current road network was estimated from available data, and its future growth (2021-2050) was modeled using three approaches. Road construction makes up the majority of GHG emissions from infrastructure built before 2021, with culverts and bridges contributing smaller but still significant amounts. By 2050, vehicle operation is projected to account for 85% of total transportation emissions, followed by vehicle manufacturing (7%), new road construction (4%), and road maintenance/rehabilitation and road roughness (approximately 2% each). While infrastructure-related emissions are relatively small compared to vehicle-related emissions, their...

Towards Universal Performance Modeling for Machine Learning Training on Multi-GPU Platforms

Tue, 10 Jun 2025 00:00:00 +0000

Characterizing and predicting the training performance of modern machine learning (ML) workloads on compute systems with compute and communication spread between CPUs, GPUs, and network devices is not only the key to optimization and planning but also a complex goal to achieve. The primary challenges include the complexity of synchronization and load balancing between CPUs and GPUs, the variance in input data distribution, and the use of different communication devices and topologies (e.g., NVLink, PCIe, network cards) that connect multiple compute devices, coupled with the desire for flexible training configurations. Built on top of our prior work for single-GPU platforms, we address these challenges and enable multi-GPU performance modeling by incorporating (1) data-distribution-aware performance models for embedding table lookup, and (2) data movement prediction of communication collectives, into our upgraded performance modeling pipeline equipped with inter-and intra-rank...

Thermal fluctuations and bending rigidities of graphane and fluorographene at different temperatures

Tue, 11 Jun 2024 00:00:00 +0000

Little research has been conducted to determine the thermal properties and phenomena of graphane and fluorographene. A clear understanding of the thermal problems involved is needed, which may provide a basis for further research on other material properties. In the present study, molecular dynamics simulations were performed to investigate the thermal properties of graphane and fluorographene and especially the phenomena involved, including thermal fluctuations and bending rigidities. Furthermore, comparisons of thermal properties and the phenomena involved were made computationally between pristine and functionalised graphene. The thermal fluctuations and bending rigidities were determined at different temperatures. The present study aims to provide a clear understanding of the thermal problems involved in hydrogenated and fluorinated graphene. The results indicated that while thermally excited ripples spontaneously appear in graphene, fully hydrogenated or fluorinated graphene...

Computational study of transport phenomena in microchannel reactors for hydrogen production by steam reforming

Tue, 11 Jun 2024 00:00:00 +0000

The potential of methanol reforming systems to greatly improve productivity in chemical reactors has been limited, due in part, to the effect of mass transfer limitations on the production of hydrogen. There is a need to determine whether or not a microchannel reforming reactor system is operated in a mass transfer-controlled regime, and provide the necessary criteria so that mass transfer limitations can be effectively eliminated in the reactor. Three-dimensional numerical simulations were carried out using computational fluid dynamics to investigate the essential characteristics of mass transport processes in a microchannel reforming reactor and to develop criteria for determining mass transfer limitations. The reactor was designed for thermochemically producing hydrogen from methanol by steam reforming. The mass transfer effects involved in the reforming process were evaluated, and the role of various design parameters was determined for the thermally integrated reactor. In...

Continuous and efficient production of hydrogen from methanol in protruded millisecond microchannel reactors for fuel cell applications

Mon, 10 Jun 2024 00:00:00 +0000

Protrusions can be used to improve the transport processes involved, but the causes of the phenomena are still incompletely understood. Computational fluid dynamics analyses are performed under different sets of circumstances to gain insights into the physics of heat and mass transfer processes in a protruded millisecond microchannel reactor, wherein a steam reforming reaction is proceeding and protrusions are used to improve the transport processes involved. Recommendations are made on how to optimize design for better reactor performance. Particular emphasis is placed on delineating the role of methanol-air equivalence ratio and channel length in reactor performance. The results indicate that the equivalence ratio and channel length must be adjusted as needed to minimize pressure drops and maximize production of hydrogen. Necessary adjustments to the equivalence ratio of methanol to air can be made to control the maximum reactor temperature within certain needed limits. The...

Effects of inlet velocity and steam-to-methanol ratio on the phenomena of process intensification in protruded millisecond microchannel reactors

Mon, 10 Jun 2024 00:00:00 +0000

The present study focuses upon the physics of heat and mass transfer processes in a protruded millisecond microchannel reactor, wherein a steam reforming reaction is proceeding and protrusions are used to improve the transport processes involved. Parametric analysis of the reactor system is carried out using a three-dimensional numerical model that is sufficiently detailed to delineate the role of geometric features and operation conditions in reactor performance. Computational fluid dynamics analyses are performed under different sets of circumstances. In analysing the mechanisms involved in the intensified processes, account is taken of the factors that may influence the reactor performance. New insights into the physics of the processes are presented, with recommendations on how to optimize reactor design for better performance. The results indicate that the flow rates and feed compositions must be adjusted as needed to maximize production of hydrogen and minimize pressure...

Molecular dynamics study of the thermal properties and phenomena of graphane and fluorographene

Mon, 10 Jun 2024 00:00:00 +0000

In spite of significant efforts to investigate the ability of hydrogenated and fluorinated graphene to conduct heat, little research has focused particularly upon their other thermal properties, such as thermal contraction and heat capacity, which have implications for the development of thermal nanotechnology. In an attempt to determine these thermal properties, a few experiments have been carried out, with rather conflicting results. In the present study, calculations were performed using molecular dynamics to investigate the thermal properties of graphane and fluorographene and especially the phenomena involved. The thermal expansion coefficients and heat capacities of the two-dimensional materials were determined at different temperatures. The results indicated that graphane is thermally contracted more significantly than graphene. The calculated molar heat capacity at constant volume is about 25.00 J/(mol·K) for graphene and about 29.26 J/(mol·K)...

Fundamental characteristics of flow past an array of hemispherical protrusions in millisecond microchannel reactors

Fri, 7 Jun 2024 00:00:00 +0000

Flow of a fluid past a body is a very complicated phenomenon. Computational fluid dynamics is used for studying the characteristics of flow past an array of hemispherical protrusions that is disposed on the wall surfaces of a millisecond microchannel reactor. Protrusions can be used to improve the transport processes involved, but the causes of the phenomena are still incompletely understood. Parametric analyses are performed under different sets of circumstances to delineate the role of geometric features and operation conditions in reactor performance. Dimensionless quantities are used to simplify the characterization of the reactor system with multiple interacting transport phenomena. The mechanisms involved in the intensified processes are analysed, and performance improvement recommendations are presented. The results indicate that the protruded reactor behaves effectively and good yields can be obtained with only milliseconds residence of the mixtures within the channels....

Effects of pressure and flow rate on the efficiency and performance of autothermal reforming systems for hydrogen production

Thu, 6 Jun 2024 00:00:00 +0000

Computational modelling for microchannel reactor design was conducted in the attempt to fully understand autothermal reforming phenomena in continuous flow reactors. The effects of pressure and flow rate on the efficiency and performance were evaluated by performing computational fluid dynamics under different design conditions. The reactor efficiency and performance were assessed by means of the reactant conversion, product yield, reaction rate, hydrogen productivity, and output power. Recommendations for designing an autothermal reforming system were made and strategies for performing efficient operation were set forth. The results indicated that the pressure and flow rate set strict limits on operation, and there is a trade-off between high productivity and low conversion. The pressure and flow rate play competing roles in the reactor efficiency and performance. Lower pressures and flow rates can increase the conversion and yield, but higher pressures and flow rates can significantly...

Computational fluid dynamics and thermodynamic analysis of transport and reaction phenomena in autothermal reforming reactors for hydrogen production

Thu, 6 Jun 2024 00:00:00 +0000

Computational fluid dynamics uses numerical methods and algorithms to solve and analyse problems that involve fluid flows. Computers may be used to perform the calculations required to simulate the interaction of liquids and gasses with a surface defined by boundary conditions. Thermodynamics is the science of the relationship between heat, work, temperature, and energy. Computational modelling for microchannel reactor design was performed to investigate the effects of various factors on the efficiency and performance of an autothermal reforming system. The yield and productivity from the chemical process were determined by performing computational fluid dynamics and thermodynamic analysis. Strength and weakness were assessed under different reaction conditions. Design recommendations were provided and operation strategies were mapped out. The results indicated that operation at millisecond contact times is feasible, but optimisation of reaction conditions is necessary to balance...

Optimized GPU Implementation of Grid Refinement in Lattice Boltzmann Method

Tue, 2 Apr 2024 00:00:00 +0000

Optimized GPU Implementation of Grid Refinement in Lattice Boltzmann Method

Effect of Anisotropic Consolidation on Cyclic Liquefaction Resistance of Granular Materials via 3D-DEM Modeling

Mon, 4 Mar 2024 00:00:00 +0000

Effect of Anisotropic Consolidation on Cyclic Liquefaction Resistance of Granular Materials via 3D-DEM Modeling

Evolution of granular media under constant-volume multidirectional cyclic shearing

Mon, 29 Jan 2024 00:00:00 +0000

Evolution of granular media under constant-volume multidirectional cyclic shearing

Evolution of granular materials under isochoric cyclic simple shearing

Mon, 29 Jan 2024 00:00:00 +0000

Evolution of granular materials under isochoric cyclic simple shearing

Impact of bidirectional seismic shearing on the volumetric response of sand deposits

Mon, 29 Jan 2024 00:00:00 +0000

Impact of bidirectional seismic shearing on the volumetric response of sand deposits

Liquefaction of granular materials in constant-volume cyclic shearing: Transition between solid-like and fluid-like states

Mon, 29 Jan 2024 00:00:00 +0000

Liquefaction of granular materials in constant-volume cyclic shearing: Transition between solid-like and fluid-like states

Convergence of rotational hardening with bounds in clay plasticity

Mon, 29 Jan 2024 00:00:00 +0000

Convergence of rotational hardening with bounds in clay plasticity

Numerical modeling of soil liquefaction and lateral spreading using the SANISAND-Sf model in the LEAP experiments

Mon, 29 Jan 2024 00:00:00 +0000

Numerical modeling of soil liquefaction and lateral spreading using the SANISAND-Sf model in the LEAP experiments

Multidirectional cyclic shearing of clays and sands: Evaluation of two bounding surface plasticity models

Mon, 29 Jan 2024 00:00:00 +0000

Multidirectional cyclic shearing of clays and sands: Evaluation of two bounding surface plasticity models

Strategies for numerical simulation of cast-in-place piles under axial loading

Mon, 29 Jan 2024 00:00:00 +0000

Strategies for numerical simulation of cast-in-place piles under axial loading

Characteristic limitations of advanced plasticity and hypoplasticity models for cyclic loading of sands

Mon, 29 Jan 2024 00:00:00 +0000

Characteristic limitations of advanced plasticity and hypoplasticity models for cyclic loading of sands

Dynamic Mesh Processing on the GPU

Mon, 29 Jan 2024 00:00:00 +0000

We propose a system for dynamic triangle mesh processing entirely on the GPU. Our system offers an efficient data structure that allows fast updates of the underlying mesh connectivity and attributes. Our data structure partitions the mesh into small patches which allows processing all dynamic updates for each patch within the GPU's fast shared memory. This allows us to rely on speculative processing for conflict handling, which has low rollback cost while maximizing parallelism and reducing the cost of locking. Our system also introduces a new programming model for dynamic mesh processing. The programming model offers concise semantics for dynamic updates, relieving the user from having to worry about conflicting updates in the context of parallel execution. Our programming model relies on the cavity operator, which is a general mesh update operator that formulates any dynamic operation as an element reinsertion by removing a set of mesh elements and inserting...

Roles of pre- and post-liquefaction stages in dynamic system response of liquefiable sand retained by a sheet-pile wall

Mon, 29 Jan 2024 00:00:00 +0000

Roles of pre- and post-liquefaction stages in dynamic system response of liquefiable sand retained by a sheet-pile wall

Modeling cyclic shearing of sands in the semifluidized state

Mon, 29 Jan 2024 00:00:00 +0000

Modeling cyclic shearing of sands in the semifluidized state

Effect of particle shape on cyclic liquefaction resistance of granular materials

Mon, 29 Jan 2024 00:00:00 +0000

Effect of particle shape on cyclic liquefaction resistance of granular materials

Effects of size polydispersity on random close-packed configurations of spherical particles

Mon, 29 Jan 2024 00:00:00 +0000

Effects of size polydispersity on random close-packed configurations of spherical particles

Effect of coefficient of uniformity on cyclic liquefaction resistance of granular materials

Mon, 29 Jan 2024 00:00:00 +0000

Effect of coefficient of uniformity on cyclic liquefaction resistance of granular materials

SANISAND-MSf: a sand plasticity model with memory surface and semifluidised state

Mon, 29 Jan 2024 00:00:00 +0000

SANISAND-MSf: a sand plasticity model with memory surface and semifluidised state

Reply to the discussion by Dimitrios Kolymbas of the article entitled âCharacteristic limitations of advanced plasticity and hypoplasticity models for cyclic loading of sandsâ

Mon, 29 Jan 2024 00:00:00 +0000

Reply to the discussion by Dimitrios Kolymbas of the article entitled âCharacteristic limitations of advanced plasticity and hypoplasticity models for cyclic loading of sandsâ

Methods and mechanisms for improving combustion stability by fluid recirculation structures in micro-structured burners

Thu, 9 Nov 2023 00:00:00 +0000

A combustion air stream is introduced tangentially into the interior of a premix burner by means of a swirl producer, and is mixed with fuel. At the burner outlet, the vortex flow which arises bursts open at a sudden change of cross section, with the initiation of a back-flow zone which serves to stabilize a flame in the operation of the burner. Although premix burners make possible an operation with very low pollutant emissions, they often operate dangerously near to the extinction limit of the flame. Cavity structures have been designed for the purpose of improving flame stability. However, the precise mechanism by which the cavity method provides increased flame stability remains unclear. This study relates to the combustion characteristics and flame stability of a micro-structured cavity-stabilized burner. Computational fluid dynamics simulations are conducted to gain insights into burner performance such as reaction rates, species concentrations, temperatures, and flames....

Transport phenomena in microchannel reactors for proton-exchange membrane fuel cell applications

Mon, 6 Nov 2023 00:00:00 +0000

Direct oxidation of fuels such as methanol in proton-exchange membrane fuel cells at practical current densities with acceptable catalyst loadings is not as economically attractive as conversion of methanol fuel to a hydrogen-rich mixture of gases via steam reforming and subsequent electrochemical conversion of the hydrogen-rich fuel stream to direct current in the fuel cell. The potential of methanol reforming systems to greatly improve productivity in chemical reactors has been limited, due in part, to the effect of mass transfer limitations on the production of hydrogen. There is a need to determine whether or not a microchannel reforming reactor system is operated in a mass transfer-controlled regime, and provide the necessary criteria so that mass transfer limitations can be effectively eliminated in the reactor. Three-dimensional numerical simulations were carried out using computational fluid dynamics to investigate the essential characteristics of mass transport processes...

Improvements of efficiency and performance for steam reforming reactors with optimum conditions of wall thermal conductivities and channel dimensions

Fri, 3 Nov 2023 00:00:00 +0000

The most important industrial method for the production of hydrogen is the catalytic steam reforming process. Many attempts have been made to improve heat transfer for thermally integrated microchannel steam reforming reactors. However, the mechanisms for the effects of design factors on heat transfer characteristics are still not fully understood. This study relates to a thermochemical process for producing hydrogen by the catalytic endothermic reaction of methanol with steam in a thermally integrated microchannel reforming reactor. Computational fluid dynamics simulations are conducted to better understand the consumption, generation, and exchange of thermal energy between endothermic and exothermic processes in the reactor. The effects of wall heat conduction properties and channel dimensions on heat transfer characteristics and reactor performance are investigated. Thermodynamic analysis is performed based on specific enthalpy to better understand the evolution of thermal...

Maximum Clique Enumeration on the GPU

Fri, 3 Nov 2023 00:00:00 +0000

We present an iterative breadth-first approach to maximum clique enumeration on the GPU. The memory required to store all of the intermediate clique candidates poses a significant challenge. To mitigate this issue, we employ a variety of strategies to prune away non-maximum candidates and present a thorough examination of the performance and memory benefits of each of these options. We also explore a windowing strategy as a middle-ground between breadth-first and depth-first approaches, and investigate the resulting tradeoff between parallel efficiency and memory usage. Our results demonstrate that when we are able to manage the memory requirements, our approach achieves high throughput for large graphs indicating this approach is a good choice for GPU performance. We demonstrate an average speedup of 1.9x over previous parallel work, and obtain our best performance on graphs with low average degree.

Thermal conductivity of carbon nanotube films and fibers with different structures and purities at different temperatures

Fri, 3 Nov 2023 00:00:00 +0000

The unique one-dimensional structure and concomitant properties endow carbon nanotubes with special natures, rendering them with unlimited potential in nanotechnology-associated applications. The increasing popularity of carbon nanotubes has created a demand for greater scientific understanding of the characteristics of thermal transport in nanostructured materials. However, the effects of impurities, misalignments, and structure factors on the thermal conductivity of carbon nanotube films and fibers are still poorly understood. Carbon nanotube films and fibers were produced, and the parallel thermal conductance technique was employed to determine the thermal conductivity. The effects of carbon nanotube structure, purity, and alignment on the thermal conductivity of carbon films and fibers were investigated to understand the characteristics of thermal transport in the nanostructured material. The importance of bulk density and cross-sectional area was determined experimentally....

Homogeneous charge compression ignition of fuel-lean methane-air mixtures over alumina-supported platinum catalysts in small-scale free-piston engines

Thu, 2 Nov 2023 00:00:00 +0000

The heterogeneous and homogeneous combustion-based homogeneous charge compression ignition of fuel-lean methane-air mixtures over alumina-supported platinum catalysts was investigated experimentally and numerically in free-piston micro-engines without ignition sources. Single-shot experiments were carried out in the purely homogeneous and coupled heterogeneous and homogeneous combustion modes, involved temperature measurements, capturing the visible combustion image sequences, exhaust gas analysis, and the physicochemical characterization of catalysts. Simulations were performed with a two-dimensional transient model that includes detailed heterogeneous and homogeneous chemistry and transport, leakage, and free-piston motion to gain physical insight and to explore the heterogeneous and homogeneous combustion characteristics. The micro-engine performance concerning combustion efficiency, mass loss, energy density, and free-piston dynamics was investigated. The results reveal that...

Catalytically stabilized combustion of propane in heat-recirculating continuous flow reactors for improved flame stabilization and energy efficiency

Wed, 1 Nov 2023 00:00:00 +0000

Flame stabilization is a common problem in small-scale combustion systems. However, the fuel-air mixture flow pattern, including any recirculation, is critical to achieving flame stability. In the present study, numerical simulations are conducted to understand the mechanisms of flame stabilization in heat-recirculating continuous flow reactors. The essential factors affecting combustion characteristics and flame stability are determined in order to obtain design insights. The results indicate that the wall thermal conductivity, flow velocity, equivalence ratio, and exterior heat losses are important factors in determining the energy efficiency of the reactor. There is an optimum wall thermal conductivity in terms of flame stability. The system with a moderate wall thermal conductivity will be most robust against the surrounding conditions. Excess enthalpy combustion can occur in an efficient and rapid manner, resulting from the injection of free radicals and heat produced by...

Heat transfer and thermodynamic analysis of synthesis gas production processes in chemical reactors with integrated heat exchangers by steam reforming

Tue, 26 Sep 2023 00:00:00 +0000

Heat transfer and thermodynamic analysis are performed using computational fluid dynamics and chemical kinetics to investigate the synthesis gas production processes in chemical reactors with integrated heat exchangers by steam reforming. The change of thermal energy in the reactor is fully described in order to analyze the influences of fluid velocity, solid thermal properties, and flow arrangement on the thermal behavior of the reactor. The evolution of energy is discussed in terms of reaction heat flux, and thermodynamic analysis of the oxidation and reforming processes is performed in terms of enthalpy changes. The results indicate that while the net sensible enthalpy change is always positive in the reactor, the net enthalpy change for the endothermic and exothermic reactions is positive and negative, respectively. The wall thermal conductivity plays a significant role in determining the efficiency and operation of the autothermal system. The parallel flow design is advantageous...

Computational fluid dynamics studies of catalytically stabilized combustion of propane in flow tube reactors

Tue, 26 Sep 2023 00:00:00 +0000

The most efficient and stable combustion occurs in a catalytic reactor when the burning mixture is in contact with the catalyst for a sufficiently long period. When the contract period is too short, insufficient energy is generated adjacent to the catalyst surface to sustain combustion in the main or free stream. This study is focused mainly upon the essential combustion characteristics of propane-air mixtures in flow tube reactors with a heat-recirculating structure. Computational fluid dynamics simulations are performed to gain a greater understanding of the mechanisms of flame stabilization. The essential factors affecting flame stability and combustion characteristics are determined in order to obtain design insights. The results indicate that in order to meet the emission level requirements, for industrial low emission gas turbine engines, staged combustion is required in order to minimise the quantity of the oxides of nitrogen produced. The combustion catalyst has several...

The simplified thermal modeling approach used in CalME

Tue, 29 Nov 2022 00:00:00 +0000

This paper details the development of a new 1‑D combined finite difference and finite element procedure for calculating in-depth pavement temperatures, which has been implemented in the CalME design method. The model is driven by a database of known surface temperatures rather than raw climatic inputs and an energy balance at the surface, since it was noted that the pavement structure had little impact on the surface temperature (if the surface properties remain constant). The model runs quickly, enabling direct simulation of in-depth temperatures while performing Monte Carlo based simulation of pavement reliability. The disadvantages to this approach are that it requires the surface temperatures to be developed independently and that it does not have a coupled moisture model for the prediction of freeze/thaw conditions. The paper also details some anomalies in the output of the Enhance Integrated Climatic Model (used in the new AASHTO mechanistic-empirical...

Building a Performance Model for Deep Learning Recommendation Model Training on GPUs

Tue, 29 Nov 2022 00:00:00 +0000

We devise a performance model for GPU training of Deep Learning Recommendation Models (DLRM), whose GPU utilization is low compared to other well-optimized CV and NLP models. We show that both the device active time (the sum of kernel runtimes) but also the device idle time are important components of the overall device time. We therefore tackle them separately by (1) flexibly adopting heuristic-based and ML-based kernel performance models for operators that dominate the device active time, and (2) categorizing operator overheads into five types to determine quantitatively their contribution to the device active time. Combining these two parts, we propose a critical-path-based algorithm to predict the per-batch training time of DLRM by traversing its execution graph. We achieve less than 10% geometric mean average error (GMAE) in all kernel performance modeling, and 4.61% and 7.96% geomean errors for GPU active time and overall E2E per-batch training time prediction with overheads...

Using Cameras for Measuring Displacements in Model Tests

Tue, 29 Nov 2022 00:00:00 +0000

Using Cameras for Measuring Displacements in Model Tests

SKS03: Centrifuge Test of Liquefaction-Induced Downdrag in Interbedded Soil Deposits

Thu, 14 Jul 2022 00:00:00 +0000

Earthquake shaking can cause significant soil settlements, especially if the shaking causes liquefaction. Soil settlements will induce drag loads that can significantly increase the axial loads in a pile foundation and/or cause significant pile settlement (Figure 1). The liquefaction-induced downdrag on piles is affected by the complex interplay and timing of a variety of processes including the development and dissipation of pore water pressures, soil settlement, sand boils and gaps that provide vents for high excess pore pressures. Since it has not been possible to accurately model all these complex processes, simplifying assumptions are used to account for downdrag in the current design procedures. A series of centrifuge tests were designed to investigate the complex processes and the validity of the simplifying assumptions. This report describes the details of the second (SKS03) of the two model tests performed under this project. Sinha et al. (2021b)describes the previous...

SKS02: Centrifuge Test of Liquefaction-Induced Downdrag in Uniform Liquefiable Deposit

Thu, 14 Jul 2022 00:00:00 +0000

Earthquake-induced liquefaction can cause soil settlement at pile interfaces, which can induce negative skin friction resulting in additional load (known as drag load) and drag the pile downwards (Figure 1). Despite significant research on the effects of liquefaction on structures and the seismic response of piles, there is still a knowledge gap in the evolution and assessment of liquefaction-induced downdrag on piles mainly related to the complex interplay and timing of the different mechanisms during/post liquefaction such as excess pore pressure generation/dissipation patterns, sequencing and timing of settlements, presence of interface gaps and ejecta, location of the initial neutral plane, and settlement around the tip. This has led to simplifying assumptions in current design procedures, which might result in over-conservatism in drag load estimation. Commonly used numerical tools lack the ability to model these mechanisms, while the absence of experimental data hinders...

Modeling of Dry and Saturated Soil-Foundation Interfaces

Thu, 14 Jul 2022 00:00:00 +0000

Modeling and simulation of earthquake soil-structure interaction (ESSI) require a number of sophisticated modeling and simulation approaches to reduce modeling uncertainty and improve the accuracy of results. The superstructure can be supported by either a shallow or deep foundation and in dry, partially saturated, or fully saturated soil. An interface element is thus required to accurately model the interaction of dry as well as partially saturated soil with the foundation. The current modeling techniques mostly assume a hard normal contact behavior i.e. normal contact stiffness is constant with penetration. However, more physical contact stress expected between the soil-foundation interface is non-linear. The normal contact stiffness increases with penetration until the soil surface becomes hard. At this stage, any further penetration can be assumed to be of hard contact. In this thesis, a soft contact formulation is presented to model the non-linear stiffness at the soil-foundation...

Parametric Study of Liquefaction Induced Downdrag on Axially Loaded Piles

Thu, 14 Jul 2022 00:00:00 +0000

Earthquake-induced liquefaction typically causes soil settlement which may lead to downdrag in axially loaded piles. The drag load generated may overstress the pile or cause significant foundation settlements. Despite significant research progress on the effects of liquefaction on structures and the seismic response of piles, there is still a knowledge gap in the assessment of liquefaction-induced downdrag. This paper discusses different factors that govern this mechanism and presents a parametric study performed using the AASHTO-recommended neutral plane method using displacement-based t-z spring analyses on a simplified profile where liquefiable layer depth and thickness, reconsolidation strains in dense and loose sand, tip conditions, and pile types (L/D ratios) are varied. The results obtained from this preliminary analysis draw some important conclusions regarding the performance of large, medium, and slender piles and are used to design centrifuge model tests to further...

Towards Flexible and Compiler-Friendly Layer Fusion for CNNs on Multicore CPUs

Thu, 7 Jul 2022 00:00:00 +0000

Towards Flexible and Compiler-Friendly Layer Fusion for CNNs on Multicore CPUs

Use of Photron Cameras and TEMA Software to Measure 3D Displacements in Centrifuge Tests

Thu, 7 Jul 2022 00:00:00 +0000

Snapshots recorded from multiple cameras viewing the same dynamic event from different angles can be processed and used for the dynamic tracking of 3D displacements of multiple targets placed on the model. This report describes the first combined use of new high-speed Photron cameras and the TEMA Classic 3D software at the Center for Geotechnical Modeling (CGM) at University of California, Davis (UCD). The cameras and their mounting, as well as the target markers, lighting, camera calibration, and camera triggering are described, followed by a discussion on the software options selected for the analysis of videos recorded for a centrifuge model test conducted on the 9 m-radius centrifuge. The results presented show that this method is effective and reliable in obtaining the positions, displacements, velocities, and accelerations of the targets. Recommendations are made for improvements in future applications.

Obtaining the 3D displacements of targets requires multiple...

Centrifuge Study of Downdrag on Axially Loaded Piles in Liquefiable Soils

Thu, 7 Jul 2022 00:00:00 +0000

Piles are designed to transfer superstructure loads using positive skin friction and tip resistance while undergoing acceptable settlements. However, when liquefaction-induced soil settlement occurs, it can drag the pile downward and result in negative skin friction and drag load. In such cases, estimating the drag load and pile settlement becomes important for pile design. A series of centrifuge model tests were performed to study liquefaction-induced downdrag on piles. The tests included four heavily instrumented piles installed in two different soil layered profiles with their tip embedment zero, three and five times their diameterin the dense sand. Loads on the piles were varied to study their effect on drag load and pile settlement. Results are presented describing the mechanism behind the development of liquefaction-induced downdrag, the magnitude of drag load, and pile settlement. Finally, recommendations are made for the design of piles in liquefiable soils

Neon: A Multi-GPU Programming Model for Grid-based Computations

Fri, 11 Feb 2022 00:00:00 +0000

We present Neon, a new programming model for grid-based computation with an intuitive, easy-to-use interface that allows domain experts to take full advantage of single-node multi-GPU systems. Neon decouples data structure from computation and back end configurations, allowing the same user code to operate on a variety of data structures and devices. Neon relies on a set of hierarchical abstractions that allow the user to write their applications as if they were sequential applications, while the runtime handles distribution across multiple GPUs and performs optimizations such as overlapping computation and communication without user intervention. We evaluate our programming model on several applications: a Lattice Boltzmann fluid solver, a finite-difference Poisson solver and a finite-element linear elastic solver. We show that these applications can be implemented concisely and scale well with the number of GPUs—achieving more than 99% of ideal efficiency.

RXMesh: A GPU Mesh Data Structure

Thu, 13 May 2021 00:00:00 +0000

We propose a new static high-performance mesh data structure for triangle surface meshes on the GPU. Our data structure is carefully designed for parallel execution while capturing mesh locality and confining data access, as much as possible, within the GPU's fast shared memory. We achieve this by subdividing the mesh into patches and representing these patches compactly using a matrix-based representation. Our patching technique is decorated with ribbons, thin mesh strips around patches that eliminate the need to communicate between different computation thread blocks, resulting in consistent high throughput. We call our data structure RXMesh: Ribbon-matriX Mesh. We hide the complexity of our data structure behind a flexible but powerful programming model that helps deliver high performance by inducing load balance even in highly irregular input meshes. We show the efficacy of our programming model on common geometry processing applications—mesh...

A Hybrid Constrained Coral Reefs Optimization Algorithm with Machine Learning for Optimizing Multi-reservoir Systems Operation

Tue, 4 Aug 2020 00:00:00 +0000

The continuous growing demand for water, prolonged periods of drought, and climatic uncertainties attributed mainly to climate change mean surface water reservoirs more than ever need to be managed efficiently. Several optimization algorithms have been developed to optimize multi-reservoir systems operation, mostly during severe dry/wet seasons, to mitigate extreme-events consequences. Yet, convergence speed, presence of local optimums, and calculation-cost efficiency are challenging while looking for the global optimum. In this paper, the problem of finding an efficient optimal operation policy in multi-reservoir systems is discussed. The complexity of the long-term operating rules and the reservoirs’ upstream and downstream joint-demands projected in recursive constraints make this problem formidable. The original Coral Reefs Optimization (CRO) algorithm, which is a meta-heuristic evolutionary algorithm, and two modified versions have been used to solve this problem. Proposed...

Dynamic Graphs on the GPU

Tue, 11 Feb 2020 00:00:00 +0000

We present a fast dynamic graph data structure for the GPU. Our dynamic graph structure uses one hash table per vertex to store adjacency lists and achieves 3.4–14.8x faster insertion rates over the state of the art across a diverse set of large datasets, as well as deletion speedups up to 7.8x. The data structure supports queries and dynamic updates through both edge and vertex insertion and deletion. In addition, we define a comprehensive evaluation strategy based on operations, workloads, and applications that we believe better characterize and evaluate dynamic graph data structures.

Impact of bidirectional seismic shearing on the volumetric response of sand deposits

Tue, 11 Feb 2020 00:00:00 +0000

Impact of bidirectional seismic shearing on the volumetric response of sand deposits

Benchmarking Deep Learning Frameworks and Investigating FPGA Deployment for Traffic Sign Classification and Detection

Mon, 8 Jul 2019 00:00:00 +0000

We benchmark several widely-used deep learning frameworks and investigate the FPGA deployment for performing traffic sign classification and detection. We evaluate the training speed and inference accuracy of these frameworks on the GPU by training FPGA-deployment-suitable models with various input sizes on GTSRB, a traffic sign classification dataset. Then, selected trained classification models and various object detection models that we train on GTSRB's detection counterpart (i.e., GTSDB) are evaluated with inference speed, accuracy, and FPGA power efficiency by varying different parameters such as floating-point precisions, batch sizes, etc. We discover that Neon and MXNet deliver the best training speed and classification accuracy on the GPU in general for all test cases, while TensorFlow is always among the frameworks with the highest inference accuracies. We observe that with the current OpenVINO release, the performance of lightweight models (e.g., MobileNet-v1-SSD, etc)...

High-Performance Linear Algebra-based Graph Framework on the GPU

Mon, 8 Jul 2019 00:00:00 +0000

High-Performance Linear Algebra-based Graph Framework on the GPU

Graph Coloring on the GPU

Sat, 1 Jun 2019 00:00:00 +0000

We design and implement parallel graph coloring algorithms on the GPU using two different abstractions—one datacentric (Gunrock), the other linear-algebra-based (GraphBLAS). We analyze the impact of variations of a baseline independent-set algorithm on quality and runtime. We study how optimizations such as hashing, avoiding atomics, and a max-min heuristic affect performance. Our Gunrock graph coloring implementation has a peak 2x speed-up, a geomean speed-up of 1.3x and produces 1.6x more colors over previous hardwired state-of-theart implementations on real-world datasets. Our GraphBLAS implementation of Luby’s algorithm produces 1.9x fewer colors than the previous state-of-the-art parallel implementation at the cost of 3x extra runtime, and 1.014x fewer colors than a greedy, sequential algorithm with a geomean speed-up of 2.6x.

Generalizing Tanglegrams

Mon, 30 Jul 2018 00:00:00 +0000

Tanglegrams are a tool to infer joint evolution of species. Tanglegrams are widely used in ecology to study joint evolution history of parasitic or symbiotically linked species. Visually, a tanglegram is a pair of evolutionary trees drawn with the leaves facing at each other. One species at the leaf of one trees is related ecologically to a species at a leaf of another tree. Related species from the two trees are connected by an edge. The number of crossings between the edges joining the leaves indicate the relatedness of the trees. Earlier work on tanglegrams considered the same number of leaves on both the trees and one edge between the leaves of the two trees. In this paper we consider multiple edges from a leaf in the trees. These edges correspond to ecological events like duplication, host switching etc. We generalize the definition of tanglegrams to admit multiple edges between the leaves. We show integer programs for optimizing the number of crossings. The integer...

Applying Machine Learning to Identify NUMA End-System Bottlenecks for Network I/O

Tue, 3 Jul 2018 00:00:00 +0000

Performance bottlenecks across distributed nodes, such as in high performance computing grids or cloud computing, have raised concerns about the use of Non-Uniform Memory Access (NUMA) processors and high-speed commodity interconnects. Performance engineering studies have investigated this with varying degrees of success. However, with continuous evolution in end-system hardware, along with changes in the Linux networking stack, this study has become increasingly complex and difficult due to the many tightly-coupled performance tuning parameters involved. In response to this, we present the Networked End- System Characterization and Adaptive Tuning tool, or NESCAT, a partially automated performance engineering tool that uses machine learning to study high-speed network connectivity within end-systems. NESCAT exploits several novel techniques for systems performance engineering. These include using k-means clustering and Artificial Neural Networks (ANNs) to effectively learn and...

Benchmarking Deep Learning Frameworks with FPGA-suitable Models on a Traffic Sign Dataset

Thu, 10 May 2018 00:00:00 +0000

We benchmark several widely used deep-learning frameworks for performing deep-learning-related automotive tasks (e.g., traffic sign recognition) that need to achieve realtime and high accuracy results with limited resources available on embedded platforms such as FPGAs. In our benchmarks, we use various input image sizes on models that are suitable for FPGA deployment, and investigate the training speed and inference accuracy of selected frameworks for these different sizes on a popular traffic sign recognition dataset. We report results by running the frameworks solely on the CPU as well as by turning on GPU acceleration. We also provide optimizations we apply to fine-tune the performance of the frameworks. We discover that Neon and MXNet deliver the best training speed and inference accuracy in general for all our test cases, while Tensorflow is always among the frameworks with the highest inference accuracies. We also observe that on the particular dataset we tested on (i.e.,...

Scalable Breadth-First Search on a GPU Cluster

Tue, 13 Mar 2018 00:00:00 +0000

On a GPU cluster, the ratio of high computing power to communication bandwidth makes scaling breadth-first search (BFS) on a scale-free graph extremely challenging. By separating high and low out-degree vertices, we present an implementation with scalable computation and a model for scalable communication for BFS and direction-optimized BFS. Our communication model uses global reduction for high-degree vertices, and point-to-point transmission for low-degree vertices. Leveraging the characteristics of degree separation, we reduce the graph size to one third of the conventional edge list representation. With several other optimizations, we observe linear weak scaling as we increase the number of GPUs, and achieve 259.8 GTEPS on a scale-33 Graph500 RMAT graph with 124 GPUs on the latest CORAL early access system.

Parametrization and Effectiveness of Moving Target Defense Security Protections for Industrial Control Systems

Tue, 13 Mar 2018 00:00:00 +0000

Critical infrastructure systems continue to foster predictable communication patterns and static configurations over extended periods of time. The static nature of these systems eases the process of gathering reconnaissance information that can be used to design, develop, and launch attacks by adversaries. In this research effort, the early phases of an attack vector will be disrupted by randomizing application port numbers, IP addresses, and communication paths dynamically through the use of overlay networks within Industrial Control Systems (ICS). These protective measures convert static systems into "moving targets," adding an additional layer of defense. Moving Target Defense (MTD) is an active area of research that periodically changes the attack surface of a system to create uncertainty and increase the workload for an adversary. To assess the effectiveness of MTD strategies within an ICS environment, performance metrics have been captured to quantify the impacts introduced...

Parametrization and Effectiveness of Moving Target Defense Security Protections within Industrial Control Systems

Tue, 13 Mar 2018 00:00:00 +0000

Critical infrastructure systems continue to foster predictable communication patterns and static configurations over extended periods of time. The static nature of these systems ease the process of gathering reconnaissance information that can be used to design, develop and launch attacks by adversaries. In this research effort, the early phases of an attack vector will be disrupted by randomizing port numbers, IP addresses, and communication paths dynamically through the use of overlay networks. These protective measures convert static systems into "moving targets," adding an additional layer of defense. Moving Target Defense (MTD) is an active area of research that periodically changes the attack surface of a system to create uncertainty and increase the workload for an adversary. To assess the effectiveness of MTD strategies within a critical infrastructure environment, performance metrics have been captured to quantify the impacts introduced to the opera- tional network...

GPU LSM: A Dynamic Dictionary Data Structure for the GPU

Tue, 13 Mar 2018 00:00:00 +0000

We develop a dynamic dictionary data structure for the GPU, supporting fast insertions and deletions, based on the Log Structured Merge tree (LSM). Our implementation on an NVIDIA K40c GPU has an average update (insertion or deletion) rate of 225 M elements/s, 13.5x faster than merging items into a sorted array. The GPU LSM supports the retrieval operations of lookup, count, and range query operations with an average rate of 75 M, 32 M and 23 M queries/s respectively. The trade-off for the dynamic updates is that the sorted array isalmost twice as fast on retrievals. We believe that our GPU LSM is the first dynamic general-purpose dictionary data structure for the GPU.

Parallel Algorithms and Dynamic Data Structures on the Graphics Processing Unit: a warp-centric approach

Tue, 13 Mar 2018 00:00:00 +0000

Graphics Processing Units (GPUs) are massively parallel processors with thousands of active threads originally designed for throughput-oriented tasks.In order to get as much performance as possible given the hardware characteristics of GPUs, it is extremely important for programmers to not only design an efficient algorithm with good enough asymptotic complexities, but also to take into account the hardware limitations and preferences.In this work, we focus our design on two high level abstractions: work assignment and processing. The former denotes the assigned task by the programmer to each thread or group of threads. The latter encapsulates the actual execution of assigned tasks.

Previous work conflates work assignment and processing into similar granularities. The most traditional way is to have per-thread work assignment followed by per-thread processing of that assigned work. Each thread sequentially processes a part of input and then the results are combined appropriately....

Quotient Filters: Approximate Membership Queries on the GPU

Tue, 13 Mar 2018 00:00:00 +0000

In this paper, we present our GPU implementation of the quotient filter, a compact data structure designed to implement approximate membership queries. The quotient filter is similar to the more well-known Bloom filter; however, in addition to set insertion and membership queries, the quotient filter also supports deletions and merging filters without requiring rehashing of the data set. Furthermore, the quotient filter can be extended to include counters without increasing the memory footprint. This paper describes our GPU implementation of two types of quotient filters: the standard quotient filter and the rank-and-select-based quotient filter. We describe the parallelization of all filter operations, including a comparison of the four different methods we devised for parallelizing quotient filter construction. In solving this problem, we found that we needed an operation similar to a parallel scan, but for non-associative operators. One outcome of this work is a variety...

A Dynamic Hash Table for the GPU

Tue, 13 Mar 2018 00:00:00 +0000

A Dynamic Hash Table for the GPU

Modeling Systems Using Side Channel Information

Tue, 13 Mar 2018 00:00:00 +0000

Side channel analysis is the process of examining information leaked by a computing device during use, and leveraging such data to make inferences about various aspects of the system. Historically, side channels have been exploited for malicious purposes, from inferring sensitive data to infringing on the privacy of users. For example, power consumption has been exploited to reveal secret cryptographic keys, and features of wireless network traffic have been leveraged to reveal web browsing activity of a user. The goal of this dissertation is not only to explore the potential of using side channels to determine what types of activity a computing system is engaged in but also study the relationship between the operations performed by the system and the side channel.

In this dissertation we present two key concepts: the application of side channel analysis for security and privacy purposes, particularly for monitoring systems, and the development of a model for defining...

Leveraging Security Metrics to Enhance System and Network Resilience

Fri, 18 Aug 2017 00:00:00 +0000

Resilience is a relatively new concept in computer security that is continuing to evolve. The research community has not settled on an exact definition for resilience, but most agree that this security property should include resistence to attack, damage recovery, and the ability for a system to learn and better resist such an attack in the future. Much of the existing research has focused on resilience solely in terms of availability, or in defining metrics to describe and compare the resilience of systems. The goal of this dissertation is to not only explore the possibility of a more general framework for resilience, but to also analyze the effectiveness of methods and technologies that can be used to measure and provide resilience.

The dissertation begins by covering common elements of computer security, providing exam- ples, addressing vulnerabilities and exploits, and suggesting potential solutions. In later sections, we examine the feasibility of the proposed solutions....

Technology, Training, and Transformation

Thu, 6 Jul 2017 00:00:00 +0000

As advances in technology transform society, so must it transform how people interact with that technology. However, technology advances much faster than do society and people. Most people don't care how the technology works--they care only that it does work. Current models are unsatisfactory because people must understand more of the underlying technology than is needed to perform their jobs. The view of this evolution explored here proposes that the training and maintenance will rest in the hands of the vendors and service personnel and not the average user. Perhaps this is heretical, given the proposals for improved "security awareness" and similar educational programs.

A Clinic for "Secure" Programming

Thu, 6 Jul 2017 00:00:00 +0000

In this paper, the author mentions that despite the reliance on software in everything from televisions and cars to medical equipment, it often doesn't work correctly. Everyone has had problems with software like text editors that freeze, answering machines that won't answer. Others are far more serious, such as the program on a satellite that contains an error, causing the loss of expensive equipment, or Web servers that have bugs enabling an attacker to break in and steal personal data. In the case of medical equipment, poor software could cost lives. To develop a better software, one way is to make good programming as much a part of learning computer science as good writing is a part of studying English and law. To test this idea, a secure-programming clinic was developed. Principles of robust programming are widely taught in beginning and advanced programming courses. They're a large part of good programming style and require the realization that things can go wrong. A user...

Multi-Stage Delivery of Malware

Mon, 3 Jul 2017 00:00:00 +0000

Malware signature detectors use patterns of bytes, or variations of patterns of bytes, to detect malware attempting to enter a systems. This approach assumes the signatures are both or sufficient length to identify the malware, and to distinguish it from non-malware objects entering the system. We describe a technique that can increase the difficulty of both to an arbitrary degree. This technique can exploit an optimization that many anti-virus systems use to make inserting the malware simple; fortunately, this particular exploit is easy to detect, provided the optimization is not present. We describe some experiments to test the effectiveness of this technique in evading existing signature-based malware detectors.

Demythifying Cybersecurity

Mon, 3 Jul 2017 00:00:00 +0000

A large part of computer security education is tackling myths that support much of the practice in the field. By examining these myths and the underlying truths or heuristics they reflect, we learn three things. First, students and practitioners learn to separate what is empirically and theoretically supported from what is supported solely by untested anecdotes or handed-down "best practices." Second, a key part of education is the human dimension of convincing others that stories that sound right aren't proven and might in fact be wrong. They aren't necessarily wrong-but this possibility must be considered. Finally, we can consider myths from the perspective of teaching stories, because many evolve from activities that at one time were true or that have some accurate elements.

Antimalware Software: Do We Measure Resilience?

Tue, 4 Apr 2017 00:00:00 +0000

Antimalware Software: Do We Measure Resilience?

Insider Attack Identification and Prevention Using a Declarative Approach

Tue, 4 Apr 2017 00:00:00 +0000

Insider Attack Identification and Prevention Using a Declarative Approach

Caution: Danger Ahead (with Big Data)

Tue, 4 Apr 2017 00:00:00 +0000

Caution: Danger Ahead (with Big Data)

Map navigation app with social posting

Thu, 17 Nov 2016 00:00:00 +0000

Map navigation app with social posting

NetSage: Open Privacy-Aware Network Measurement, Analysis, And Visualization Service

Fri, 5 Aug 2016 00:00:00 +0000

NetSage is a project to develop a unified open, privacy-aware network measurement, and visualization service to address the needs of today’s international networks. Modern science is increasingly data-driven and collaborative in nature, producing petabytes of data that can be shared by tens to thousands of scientists all over the world. The National Science, Foundation-supported International Research Network Connections (IRNC) links, have been essential to performing these science experiments. Recent deployment of Science DMZs [Dart, E. et al., 2013], both in the US and other countries, is starting to raise expectations for data throughput performance for wide-area data transfers. New capabilities to measure and analyze the capacity of international wide-area networks are essential to ensure end-users are able to take full advantage of such infrastructure.

NetSage will provide the network engineering community, both US domestic and international, with a suite of tools...

Security Analysis of Scantegrity, an Electronic Voting System

Thu, 7 Jul 2016 00:00:00 +0000

Electronic voting machines are becoming an increasingly popular alternative to paper ballots. With this increase in use we must analyze how well these machines adhere to voting requirements, including those relating to security, privacy, and anonymity. This paper includes analysis of the security and auditing mechanisms of the open-source electronic voting system Scantegrity. We focus on Scantegrity, not to single it out as a vulnerable system, but because it is a popular system that has actually been used in practice. It may contain design flaws and vulnerabilities that might exist in other systems of similar designs, current or future. Therefore, it is our hope that the vulnerabilities that we bring to light will be considered by current and future designers of electronic voting systems, and that the solutions that we propose will also be considered as possible remediations.

Distributed Helios - Mitigating Denial of Service Attacks in Online Voting

Wed, 30 Mar 2016 00:00:00 +0000

One of many major issues that plagues Internet voting is the potential for a distributed denial of service attack on the voting servers. These denial of service attacks are harmful because they block voting during the downtime. In addition, most current online voting protocols are centralized with only one voting server, making such an attack likely to disenfranchise some voters. The question is how to combat these attacks. One solution is to distribute the servers in a parallel manner, so in case one server goes down, the others can still provide service to voters. Whereas many online voting systems assume the constant availability of the voting infrastructure, we focus on the event that a server becomes unavailable. We extend a previously established online voting protocol, Helios, by adding multiserver capability. These servers communicate using the Paxos protocol, an algorithm for fault tolerant distributed environments. An analysis of this solution concludes that a multi-server...

High Efficiency Micromachined Sub-THz Channels for Low Cost Interconnect for Planar Integrated Circuits

Tue, 19 Jan 2016 00:00:00 +0000

High Efficiency Micromachined Sub-THz Channels for Low Cost Interconnect for Planar Integrated Circuits

Extension of the Hot-Switching Reliability of RF-MEMS Switches Using A Series ContactProtection Technique

Tue, 19 Jan 2016 00:00:00 +0000

Extension of the Hot-Switching Reliability of RF-MEMS Switches Using A Series ContactProtection Technique

Proceedings of the Symposium on Recent Advances in Geotechnical Centrifuge Modeling

Fri, 15 May 2015 00:00:00 +0000

Cover: Proceedings of the Symposium on Recent Advances in Geotechnical Centrifuge Modeling, National Geotechnical Centrifuge, Department of Civil Engineering, University of California Davis

Introduction: A symposium on Recent Advances in Geotechnical Centrifuge Modeling was held on July 18-20, 1984 at the University of California at Davis. The symposium was sponsored by the National Science Foundation's Geotechnical Engineering Program and the Center for Geotechnical Modeling at the University of California at Davis.

The symposium offered an opportunity for a meeting of the InternationalCommittee on Centrifuges of the International Society for Soil Mechanics and Foundation Engineering. The U.S. participants also met to discuss theadvancement of the centrifuge modeling technique in the U.S. A request is being transmitted to the American Society of Civil Engineers to establish a subcommittee on centrifuges within the Geotechnical Engineering Division.

Editor:...

CENTRIFUGAL MODEL TESTS FOR ULTIMATE BEARING CAPACITY OF FOOTINGS ON STEEP SLOPES IN COHESIONLESS SOIL [abstract]