A tentative determination of upwelling influence on the paleo-surficial marine water reservoir effect in southeastern Brazil.

Previous work has suggested that seasonal and inter-annual upwelling of deep, cold, radiocarbon depleted waters from the South Atlantic has caused variations in the reservoir effect (R) through time along the southern coast of Brazil. This work aims to examine the possible upwelling influence on the paleo-reservoir age of Brazilian surficial coastal waters based on paired terrestrial/marine samples obtained from archaeological remains. On the Brazilian coast there are hundreds of shell-middens built up by an ancient culture that lived between 6500 to 1500 years ago, but there are few located on open coast with a known upwelling influence. Three archaeological sites located in a large headland in Arraial do Cabo and Ilha de Cabo Frio, southeastern coast of Brazil with open ocean conditions and a well-known strong and large upwelling of the Malvinas/Falkland current were chosen for this study. The 14C age differences between carbonized seed and marine samples varied from 281 ± 44 to 1083 ± 51 14C yr. There are also significant age differences between carbonized seed samples (977 14C yr) and marine samples (200 and 228 14C yr) from the same archaeological layer that cannot be explained by a reservoir effect or an old-wood effect for charcoal. Therefore the present data from the southeastern Brazilian coast are inconclusive for identifying an upwelling effect on R. To do so it would be necessary to more precisely define the present-pre-bomb R in upwelling regions and to analyze paired marine/terrestrial samples that are contemporaneous beyond doubt.

Hydraulic Subsurface Measurements and Hydrodynamic Modeling as Indicators for Groundwater Flow Systems in the Rotondo Granite, Central Alps (Switzerland)

Regional groundwater flow in high mountainous terrain is governed by a multitude of factors such as geology, topography, recharge conditions, structural elements such as fracturation and regional fault zones as well as man-made underground structures. By means of a numerical groundwater flow model, we consider the impact of deep underground tunnels and of an idealized major fault zone on the groundwater flow systems within the fractured Rotondo granite. The position of the free groundwater table as response to the above subsurface structures and, in particular, with regard to the influence of spatial distributed groundwater recharge rates is addressed. The model results show significant unsaturated zones below the mountain ridges in the study area with a thickness of up to several hundred metres. The subsurface galleries are shown to have a strong effect on the head distribution in the model domain, causing locally a reversal of natural head gradients. With respect to the position of the catchment areas to the tunnel and the corresponding type of recharge source for the tunnel inflows (i.e. glaciers or recent precipitation), as well as water table elevation, the influence of spatial distributed recharge rates is compared to uniform recharge rates. Water table elevations below the well exposed high-relief mountain ridges are observed to be more sensitive to changes in groundwater recharge rates and permeability than below ridges with less topographic relief. In the conceptual framework of the numerical simulations, the model fault zone has less influence on the groundwater table position, but more importantly acts as fast flow path for recharge from glaciated areas towards the subsurface galleries. This is in agreement with a previous study, where the imprint of glacial recharge was observed in the environmental isotope composition of groundwater sampled in the subsurface galleries. Copyright © 2012 John Wiley & Sons, Ltd.

Fault Diagnosis in Internal Combustion Engines Using Nonlinear Multivariate Statistics

This paper presents a statistical-based fault diagnosis scheme for application to internal combustion engines. The scheme relies on an identified model that describes the relationships between a set of recorded engine variables using principal component analysis (PCA). Since combustion cycles are complex in nature and produce nonlinear relationships between the recorded engine variables, the paper proposes the use of nonlinear PCA (NLPCA). The paper further justifies the use of NLPCA by comparing the model accuracy of the NLPCA model with that of a linear PCA model. A new nonlinear variable reconstruction algorithm and bivariate scatter plots are proposed for fault isolation, following the application of NLPCA. The proposed technique allows the diagnosis of different fault types under steady-state operating conditions. More precisely, nonlinear variable reconstruction can remove the fault signature from the recorded engine data, which allows the identification and isolation of the root cause of abnormal engine behaviour. The paper shows that this can lead to (i) an enhanced identification of potential root causes of abnormal events and (ii) the masking of faulty sensor readings. The effectiveness of the enhanced NLPCA based monitoring scheme is illustrated by its application to a sensor fault and a process fault. The sensor fault relates to a drift in the fuel flow reading, whilst the process fault relates to a partial blockage of the intercooler. These faults are introduced to a Volkswagen TDI 1.9 Litre diesel engine mounted on an experimental engine test bench facility.

Intercepting beats in predesignated target zones

Moving to a rhythm necessitates precise timing between the movement of the chosen limb and the timing imposed by the beats. However, the temporal information specifying the moment when a beat will sound (the moment onto which one must synchronise one's movement) is not continuously provided by the acoustic array. Because of this informational void, the actors need some form of prospective information that will allow them to act sufficiently ahead of time in order to get their hand in the right place at the right time. In this acoustic interception study, where participants were asked to move between two targets in such a way that they arrived and stopped in the target zone at the same time as a beat sounded, we tested a model derived from tau-coupling theory (Lee DN (1998) Ecol Psychol 10:221-250). This model attempts to explain the form of a potential timing guide that specifies the duration of the inter-beat intervals and also describes how this informational guide can be used in the timing and guidance of movements. The results of our first experiment show that, for inter-beat intervals of less than 3 s, a large proportion of the movement (over 70%) can be explained by the proposed model. However, a second experiment, which augments the time between beats so that it surpasses 3 s, shows a marked decline in the percentage of information/movement coupling. A close analysis of the movement kinematics indicates a lack of control and anticipation in the participants' movements. The implications of these findings, in light of other research studies, are discussed.

Statistical Monitoring of Dynamic Multivariate Processes: Part II: Identifying Fault Magnitude and Signature

This paper builds on work presented in the first paper, Part 1 [1] and is of equal significance. The paper proposes a novel compensation method to preserve the integrity of step-fault signatures prevalent in various processes that can be masked during the removal of both auto- and cross correlation. Using industrial data, the paper demonstrates the benefit of the proposed method, which is applicable to chemical, electrical, and mechanical process monitoring. This paper, (and Part 1 [1]), has led to further work supported by EPSRC grant GR/S84354/01 involving kernel PCA methods.

Nonlinear PCA with Local Approach for Diesel Engine Fault Detection and Diagnosis

This brief examines the application of nonlinear statistical process control to the detection and diagnosis of faults in automotive engines. In this statistical framework, the computed score variables may have a complicated nonparametric distri- bution function, which hampers statistical inference, notably for fault detection and diagnosis. This brief shows that introducing the statistical local approach into nonlinear statistical process control produces statistics that follow a normal distribution, thereby enabling a simple statistical inference for fault detection. Further, for fault diagnosis, this brief introduces a compensation scheme that approximates the fault condition signature. Experimental results from a Volkswagen 1.9-L turbo-charged diesel engine are included.