Observed Response Characteristics Research Articles

P-Y Lateral Pile Analyses Accounting for Arbitrary Loading Directions and Calibration Uncertainty

A bounding surface plasticity p-y model accommodating pile lateral loading in arbitrary directions with respect to the pile axis is demonstrated via back-analysis of test piles. The demonstration analyses include: planar conditions, three-dimensional conditions with asymmetric cyclic loading, and Monte Carlo investigations of the influence of calibration choices. The p‑y model and its host finite element program are implemented in the MATLAB programing environment. Monte Carlo simulations investigating modelling uncertainty are accomplished efficiently when taking advantage of MATLAB’s parallel processing capability. Analysis results are compared to those observed for nine test piles at the Cowden site with diameters 0.272 m, 0.762 m and 2 m having length-to-diameter ratios between 3 and 10. The implemented p-y model is based upon and is a natural extension of the traditional API methodology. The modelling technique accurately reproduces the observed response characteristics of piles in a challenging soil profile with considerable uncertainty in its strength characteristics. It is robust, theoretically rigorous, efficient and requires the same level of effort as traditional p-y analyses. The results are easily interpreted by designers familiar with the p-y method. The characteristic responses of the p-y model under biaxial loading compare favorably to those from finite element elastic-plastic planar continuum analyses as well as small-scale physical tests on rigid piles.

Shake table testing and computational framework for seismic response of utility-scale bucket foundation offshore wind turbines

Shake table testing was conducted to document the seismic response of a bucket foundation offshore wind turbine (OWT) system. Salient response of the system's soil-structure interaction effects is presented and discussed. Among the observed response characteristics, excess pore pressure fluctuation within and around the soil-bucket domain is thoroughly addressed, including the strong tendency for the soil dilation excursions driven by the induced cyclic strains. The experimental data is used to calibrate a numerical model with dynamic soil response simulated by a coupled solid-fluid formulation. The calibrated model is extended to investigate seismic response of a prototype utility-scale OWT, with and without added wind loading effects. Overall, the research outcomes indicate that: i) excess pore pressure fluctuations in the vicinity of the bucket play an important role in dictating the extent of potential permanent base rotation, ii) consideration should be given to wind loading that might further exacerbate this base rotation, and iii) it is of importance to model the turbine tower as a system of discrete masses rather than the simplified proposed for practice equivalent top mass idealization.

Direct current effects on afferent and hair cell to elicit natural firing patterns

SummaryIn contrast to the conventional pulsatile neuromodulation that excites neurons, galvanic or direct current stimulation can excite, inhibit, or sensitize neurons. The vestibular system presents an excellent system for studying galvanic neural interface due to the spontaneously firing afferent activity that needs to be either suppressed or excited to convey head motion sensation. We determine the cellular mechanisms underlying the beneficial properties of galvanic vestibular stimulation (GVS) by creating a computational model of the vestibular end organ that elicits all experimentally observed response characteristics to GVS simultaneously. When GVS was modeled to affect the axon alone, the complete experimental data could not be replicated. We found that if GVS affects hair cell vesicle release and axonal excitability simultaneously, our modeling results matched all experimental observations. We conclude that contrary to the conventional belief that GVS affects only axons, the hair cells are likely also affected by this stimulation paradigm.

Gas Responsive Nanoswitch: Copper Oxide Composite for Highly Selective H2S Detection

AbstractA nanocomposite material based on copper(II) oxide (CuO) and its utilization as a highly selective and stable gas‐responsive electrical switch for hydrogen sulphide (H2S) detection is presented. The material can be applied as a sensitive layer for H2S monitoring, e.g., in biogas gas plants. CuO nanoparticles are embedded in a rigid, nanoporous silica (SiO2) matrix to form an electrical percolating network of low conducting CuO and, upon exposure to H2S, highly conducting copper(II) sulphide (CuS) particles. By steric hindrance due to the silica pore walls, the structure of the network is maintained even though the reversible reaction of CuO to CuS is accompanied by significant volume expansion. The conducting state of the percolating network can be controlled by a variety of parameters, such as temperature, electrode layout, and network topology of the porous silica matrix. The latter means that this new type of sensing material has a structure‐encoded detection limit for H2S, which offers new application opportunities. The fabrication process of the mesoporous CuO@SiO2composite as well as the sensor design and characteristics are described in detail. In addition, theoretical modeling of the percolation effect by Monte‐Carlo simulations yields deeper insight into the underlying percolation mechanism and the observed response characteristics.

Tunable nanostructured columnar growth of SnO2 for efficient detection of CO gas

The present work is focused on the growth and modification of the columnar nanostructures of SnO2 using a glancing angle deposition (GLAD) assisted rf sputtering technique for low temperature detection of carbon monoxide (CO) gas. The GLAD angle and deposition pressure are optimized to tailor the grow of columnar nanostructures of SnO2, which exhibit an enhanced gas sensing response of 1.50 × 102 towards 500 ppm of CO gas at a comparatively lower operating temperature of 110 °C. The enhanced sensing response at low operating temperature is related to the growth of nanoporous columnar structures of SnO2 thin film under the GLAD configuration, which results in an enhanced interaction of target CO gas molecules with the large surface area of sensing SnO2 thin film. The origin of the sensing mechanism supporting the observed response characteristics towards CO gas is identified and discussed in detail.

Response characteristics of hydrogen gas sensor with porous piezoelectric poly(vinylidene fluoride) film

Previously, we have proposed a new type of organic hydrogen gas sensor in which a β-phase poly(vinylidene fluoride) (PVDF) film is coated with thin films of palladium (Pd) on both sides. Volume expansion of the Pd thin film caused by uptake of hydrogen is monitored by a capacitance change of the piezoelectric PVDF thin film. The β-phase PVDF film was synthesized from α-phase PVDF powder by using a wet process that we developed. In this study, we have examined the microscopic structure of the β-phase PVDF films and investigated the response characteristics of the sensors: response at hydrogen exposure, detection sensitivity, recovery time and effect of humidity. We find that the PVDF film has the porous structure consisting of micro-scaled grains of PVDF and demonstrates that the response characteristics depend on the structure of the PVDF films. We propose a simple simulation model to get insight into the observed response characteristics. In the model, it is assumed that PVDF micro-grains expand and shrink one by one while exposing to hydrogen and air (or oxygen), respectively. The simulation explains the basic response characteristics of the sensor.

Virtual Optimisation of CAI Process Parameters for the Sculptured Surface Inspection

One of the key elements of digital manufacturing (including design-planning-production-inspection value chain) is a simulation i.e. virtual modelling of all processes that belong to the manufacturing chain. Simulations are frequently used to optimise some of the processes of digital manufacturing, in order to improve quality of the process itself and its output. This paper presents simulated, virtual experimentation performed in order to estimate the effect of computer aided inspection (CAI) parameters on quality of the measuring process for a sculptured surface inspection, using response surface methodology (RSM). The virtual experimentation is performed using PLM software (module for CMM programming) based on 3D CAD model of the sculptured surface part. The most important CAI parameters in measuring sculptured surfaces are adopted as control factors: number of control sections, number of measuring points in the control sections, and measuring point's distribution along the control sections. The quality of a measuring process is presented by the measuring accuracy and the measuring time, which are adopted as responses from the experiment. Using RSM, the effects of CAI parameters on the observed response characteristics are assessed; then, the optimal setting of CAI parameters is selected aiming to improve CAI process quality, i.e. to maximise the measuring accuracy and minimise the measuring time.

Rapid Neural Coding in the Retina with Relative Spike Latencies

Natural vision is a highly dynamic process. Frequent body, head, and eye movements constantly bring new images onto the retina for brief periods, challenging our understanding of the neural code for vision. We report that certain retinal ganglion cells encode the spatial structure of a briefly presented image in the relative timing of their first spikes. This code is found to be largely invariant to stimulus contrast and robust to noisy fluctuations in response latencies. Mechanistically, the observed response characteristics result from different kinetics in two retinal pathways ("ON" and "OFF") that converge onto ganglion cells. This mechanism allows the retina to rapidly and reliably transmit new spatial information with the very first spikes emitted by a neural population.

DYNAMIC CHARACTERISTICS OF HIGH-RISE BUILDINGS BASED ON SUCCESSIVE VIBRATION OBSERVATION DURING CONSTRUCTION

By use of a newly developed network connected vibration measuring system which is suitable for continuous observation at construction sites, dynamic characteristics of high-rise buildings and their change during construction are discussed. Hundreds of ambient vibration data and several seismic response records were obtained at two neighboring high-rise buildings in approximately twenty months of construction. Observed response characteristics, estimated natural periods and damping ratios are shown with the change of building height under the same soil and foundation condition. Characteristics of higher modes and soil-structure interaction effect are also discussed. By use of forced and ambient vibration data, amplitude-dependent characteristics are clearly displayed as a relation with the velocity response which is proved to be highly correlated with the average deformation angle of stories.

Dilatancy controlled spatiotemporal slip evolution of a sealed fault with spatial variations of the pore pressure

SUMMARY A range of observations suggest the formation and maintenance of sealed and hence overpressured compartments in fluid-infiltrated fault zones. It is assumed that hydromechanical properties of regions with variable pore pressure states control the fault’s stability and thus its characteristic response, that is, seismic or aseismic slip accumulation. We investigate in a systematic parameter space study the effects of spatial variations in pore pressure on spatiotemporal slip evolution along a hydraulically isolated fault plane. The 3-D continuum model is governed by rate-and-state friction and constitutive laws for porosity reduction. We show that the model response is sensitive to the degree of overpressurization and the efficiency of dilatant hardening mechanisms. Low pore pressures and small dilatancy effects result in unstable response types, whereas high pore pressures and large dilatant effects lead to stable and aseismic creep. Regions with an unstable response are shown to support most of the stresses accumulated during interseismic periods. Accelerated slip nucleates preferably in regions of low pore pressure. Statistical properties of model seismicity produce a wide range of event sizes for moderate and large earthquakes, in the case where dilatant mechanisms are inefficient. In case of efficient slip rate controlled porosity increase, less instabilities grow into large earthquakes. Final slip maps demonstrate the applicability of the chosen method to model seismicity controlled by frictional and hydraulic processes on a planar fault plane. The evolution of governing variables that depend on the pore pressure environment provide a conceptual basis for the interpretation of observed response characteristics.

A computational model for reinforced concrete members confined with fiber reinforced polymer lamina: Implementation and experimental validation

This study presents a computational model to simulate the behavior of confined concrete in column plastic hinge zones. The model describes the distribution of confining stresses within a circular column cross-section and the hysteretic behavior of concrete under passive confinement. Of particular interest is the ability of the model to predict the maximum circumferential strains and thus estimate the limit state of the confining medium rather than relying on empirical limits such as concrete compressive strain or drift ratio. This is performed with fiber-discretized beam column analysis without the computational expenses of a continuum finite element (FE) model. The confined section and material model are implemented in an object-oriented computational platform for structural analysis. New classes are developed and presented for a confined fiber section, a confined concrete material, and associated hysteretic behavior rules. Finally, the results from two experimental programs on columns strengthened using fiber reinforced polymer (FRP) lamina are reproduced using the developed computational model. Comparison of simulation and experiment shows that the computational model can closely match the observed response characteristics and can adequately predict the deformation level leading to FRP rupture.

Hebbian imprinting and retrieval in oscillatory neural networks.

We introduce a model of generalized Hebbian learning and retrieval in oscillatory neural networks modeling cortical areas such as hippocampus and olfactory cortex. Recent experiments have shown that synaptic plasticity depends on spike timing, especially on synapses from excitatory pyramidal cells, in hippocampus, and in sensory and cerebellar cortex. Here we study how such plasticity can be used to form memories and input representations when the neural dynamics are oscillatory, as is common in the brain (particularly in the hippocampus and olfactory cortex). Learning is assumed to occur in a phase of neural plasticity, in which the network is clamped to external teaching signals. By suitable manipulation of the nonlinearity of the neurons or the oscillation frequencies during learning, the model can be made, in a retrieval phase, either to categorize new inputs or to map them, in a continuous fashion, onto the space spanned by the imprinted patterns. We identify the first of these possibilities with the function of olfactory cortex and the second with the observed response characteristics of place cells in hippocampus. We investigate both kinds of networks analytically and by computer simulations, and we link the models with experimental findings, exploring, in particular, how the spike timing dependence of the synaptic plasticity constrains the computational function of the network and vice versa.

Energy partitioning in high speed impact of analogue solid rocket motors

AbstractModelling the response of solid rocket motors to bullet and fragment impacts is a high priority among the military services from standpoints of both safety and mission effectiveness. Considerable effort is being devoted to characterising the bullet and fragment vulnerability of solid rocket motors, and to developing solid rocket motor case technologies for preventing or lessening the violent responses of rocket motors to these impact loadings. Because full-scale tests are costly, fast-running analytical methods are required to characterise the response of solid rocket motors to ballistic impact hazards. In this study, a theoretical first-principles-based model is developed to determine the partitioning of the kinetic energy of an impacting projectile among various solid rocket motor failure modes. Failure modes considered in the analyses include case perforation, case delamination, and fragmentation of the propellant simulant material. Energies involved in material fragmentation are calculated using a fragmentation scheme based on a procedure developed in a previous impact study utilising propellant simulant material. The model is found to be capable of predicting a variety of response characteristics for analogue solid rocket motors under high speed projectile impact that are consistent with observed response characteristics. Suggestions are made for improving the model and extending its applicability to a wider class of impact scenarios.