Impact of sewer condition on urban flooding: an uncertainty analysis based on field observations and Monte Carlo simulations on full hydrodynamic models.

In-sewer defects are directly responsible for affecting the performance of sewer systems. Notwithstanding the impact of the condition of the assets on serviceability, sewer performance is usually assessed assuming the absence of in-sewer defects. This leads to an overestimation of serviceability. This paper presents the results of a study in two research catchments on the impact of in-sewer defects on urban pluvial flooding at network level. Impacts are assessed using Monte Carlo simulations with a full hydrodynamic model of the sewer system. The studied defects include root intrusion, surface damage, attached and settled deposits, and sedimentation. These defects are based on field observations and translated to two model parameters (roughness and sedimentation). The calculation results demonstrate that the return period of flooding, number of flooded locations and flooded volumes are substantially affected by in-sewer defects. Irrespective of the type of sewer system, the impact of sedimentation is much larger than the impact of roughness. Further research will focus on comparing calculated and measured behaviour in one of the research catchments.

Designing pain visualisation for caregivers of people with special needs: A co-creation approach.

Recognizing pain in people with communicative disabilities is challenging. A support system detecting pain signals provides caregivers with information to intervene adequately. This study aims to develop a design for a user interface visualizing pain experiences for a signalling system intended for caregivers. Caregivers receive alerts, indicating the presence or absence of pain experienced by a disabled individual. The design process included the use of value proposition, a brainstorm, a mood board with basic design elements, and multiple questionnaires and focus groups. During the multi-disciplinary design process end-users were extensively involved. The final design was deemed intuitive, clear and recognizable, and useable in daily caregiving. This article describes the creation process for a non-hedonistic visualization for this niche end-user group.

Physiological Measures of Acute and Chronic Pain within Different Subject Groups: A Systematic Review.

Results: The methods' heart rate variability and electroencephalogram show clear and consistent results as acute pain assessment. Magnetic resonance imaging can measure chronic pain. Ordered by invasiveness and vulnerability, a trend shows that the invasive methods are used more with less vulnerable subjects. Only instruments used for skin conductance and automatic facial recognition have a lower-than-average technological maturity. Conclusions: Some pain assessment methods show good and consistent results and have high technological maturity; however, using them as pain assessment for persons with ID is uncommon. Since this addition can ameliorate caregiving, more research of assessment methods should occur.

Analysis of the causes of pump failure and differences of failure characteristics.

It is generally accepted that sewage pumping stations are directly responsible for affecting sewer system performance in terms of combined sewer overflows and flooding. However, the specific causes of pump failure are unknown. This paper presents the analysis of pump failure data provided by four sewer management authorities in The Netherlands. Pump failures have been studied accounting for the nature of failures, operation and maintenance procedures of the management authority, ageing of the pumps and changes in the environment of pumps. Pumps have been clustered on the basis of specific characteristics of their 'environment', including pump age, operating time, pump capacity and degree of pollution of the sewage. The analysis shows that the well known 'bathtub' type failure rate curve can describe failures of sewage pumps. The impact of the degree of pollution of the sewage, however, is less clear. Operating time and total pumping capacity show no correlation with failure rate. Consequently, further research using data mining techniques is needed to separate the impact of the different aspects of the environment of a pump.

Failure of sewage pumps: statistical modelling and impact assessment.

Sewage pumping stations are directly responsible for affecting performance, i.e. failing pumps may result in combined sewer overflows or flooding. However, failures of sewage pumps are not yet incorporated in sewer assessments due to lack of knowledge and data. This paper presents the analysis of pump failure data provided by two sewer management authorities in The Netherlands. Pump failures have been studied accounting for the nature of the failures, the operation and maintenance procedures of the management authority, the ageing of the pumps and the changes in the environment of pumps. The analysis shows that sewage pumps fail relatively often due to the composition of sewage and the discontinuous operation of the pumps. The interarrival time and the duration of failures are highly variable and independent of the pump type and the specific function of the pump. The results also indicate that the serviceability of sewer systems is significantly affected by failing pumps. As a consequence, part of the environmental damage due to CSOs (combined sewer overflows) can be avoided by improving maintenance of pumping stations.

Impact of dimension uncertainty and model calibration on sewer system assessment.

Assessments of sewer performance are usually based on a single computation of CSO (combined sewer overflow) volumes using a time series of rainfall as system loads. A shortcoming of this method is that uncertainties in knowledge of sewer system dimensions are not taken into account. Moreover, sewer models are rarely calibrated. This paper presents the impacts of database errors and model calibration on return periods of calculated CSO volumes. The impact of uncertainties is illustrated with two examples. Variability of calculated CSO volumes is estimated using Monte Carlo simulations. The results show that calculated CSO volumes vary considerably due to database errors, especially uncertain dimensions of the catchment area. Furthermore, event-based calibration of a sewer model does not result in more reliable predictions because the calibrated parameters have low portability. However, it enables removal of database errors harmonising model predictions and 'reality'.

Diurnal differences between morning-type and evening-type subjects in self-rated alertness, body temperature and the visual and auditory evoked potential.

On the basis of their score on a morningness/eveningness questionnaire 9 extreme morning-type (M-type) and 9 extreme evening-type (E-type) subjects were selected. During a morning and an evening session both groups performed a reaction-time task with a visual and an auditory warning signal. The results showed that (i) M-types have a higher self-rated activation level in the morning than in the evening, while E-types show the reverse; (ii) M-types do not differ in oral temperature between the two sessions, while E-types show an increased temperature in the evening; (iii) M-types have a larger N1-P2 amplitude of the visual and auditory AEP in the morning than in the evening, while E-types show the reverse.

Bayesian decision analysis as a tool for defining monitoring needs in the field of effects of CSOs on receiving waters.

In recent years, decision analysis has become an important technique in many disciplines. It provides a methodology for rational decision-making allowing for uncertainties in the outcome of several possible actions to be undertaken. An example in urban drainage is the situation in which an engineer has to decide upon a major reconstruction of a system in order to prevent pollution of receiving waters due to CSOs. This paper describes the possibilities of Bayesian decision-making in urban drainage. In particular, the utility of monitoring prior to deciding on the reconstruction of a sewer system to reduce CSO emissions is studied. Our concern is with deciding whether a price should be paid for new information and which source of information is the best choice given the expected uncertainties in the outcome. The influence of specific uncertainties (sewer system data and model parameters) on the probability of CSO volumes is shown to be significant. Using Bayes' rule, to combine prior impressions with new observations, reduces the risks linked with the planning of sewer system reconstructions.