Stuart R. Mead

Prediction of industrial, biophysical and extreme geophysical flows using particle methods

Purpose – The purpose of this paper is to show how simulation of the flow of particulates and fluids using discrete element modelling (DEM) and smoothed particle dynamics (SPH) particle methods, offer opportunities for better understanding the dynamics of flow processes.Design/methodology/approach – DEM and SPH methods are demonstrated in a broad range of computationally‐demanding applications including comminution, biomedical, geophysical extreme flow events (risk/disaster modelling), eating of food by humans and elite water‐based sports.Findings – DEM is ideally suited to predicting industrial and geophysical applications where collisions between particles are the dominant physics. SPH is highly suited to multi‐physics fluid flow applications in industrial, biophysical and geophysical applications. The advantages and disadvantages of these particle methods are discussed.Research limitations/implications – Research results are limited by the numerical resolution that can currently be afforded.Practical i...

Dynamic simulation of dam-break scenarios for risk analysis and disaster management

We explore the effect of dam wall collapse scenarios on the extent and speed of inundation resulting from a dam-break by taking advantage of the easy inclusion of dynamic moving objects in the smoothed particle hydrodynamics (SPH) method. Insight into the degree of practical variation in the flood behaviours that can be generated by both the presence of dam wall fragments and the collapse sequence is investigated via a case study using key locations downstream of the Geheyan Dam, Hubei, China. Scenarios considered include ones initiated by seismic fracture, overtopping and foundation failure. The nature of the scenario determines the rate of increase of area of the breach and therefore the discharge flow rate, which in turn strongly influences the extent and timing of inundation for timescales of up to 1 h and distances of up to 10 km from the dam wall. Beyond this, the influence of the specific scenario declines. The presence of the dam wall fragments in the flow strongly influences the pattern of flooding and can protect some locations and lead to increased flooding in others. The flow in all cases has a complex three-dimensional structure, with multiple hydraulic jumps due to variations in the valley floor gradient and width. The SPH method therefore provides the ability to include realistic variations in the dam-break mechanism, thereby leading to more informed risk analysis planning before a dam-break occurs. The methodology for including these SPH flood predictions into a geographical information system (GIS) is also described. One of the collapse scenarios is used to demonstrate the ability of the GIS to then make predictions of expected flood area and the extent of flooding of villages, towns and key infrastructure. The inclusion of SPH into a GIS framework will allow the modelling to be used for disaster management following a dam-break event.

A scenario-based risk framework for determining consequences of different failure modes of earth dams

Failure modes for earth dams are extensively reviewed and analysed using a three-pronged approach including a literature review, physical observations of a representative earth dam site and finite element structural analysis of the dam wall. Several failure scenarios are used for predicting consequences in terms of downstream inundation and damage. The fluid flow component is performed using the mesh-free smoothed particle hydrodynamics method. For a representative earthen dam, piping and landslip are identified as key failure modes based on a combination of finite element analysis, theory and physical observations. Inundation behaviour is very different for the two failure modes. The landslip failure is the most critical one for the dam studied with flood water breaking the river bank and affecting surrounding property and farmland. For the piping failures, water flow from the initial pipes formed for significant periods before they collapse, but the flow rates are small compared with that of the much larger landslip mode. After failure, fragments of the collapsing wall block the breach and can considerably restrict the flood discharge. In some cases, the water pressure is able to push the obstructing material downstream and some minor flooding occurs, but in others cases the breach can remain blocked with little flooding occurring. A prototype risk framework is developed using the small database of the pre-computed flooding scenarios and key variables that affect inundation such as water level in the reservoir. This can be used to estimate inundation maps for as yet non-computed scenarios through interpolation and superposition techniques. The implementation of the risk framework is demonstrated by the estimation of inundation maps for two in-between non-computed reservoir levels. Inundation due to multiple breaches is also estimated by superposition of three single-breach scenarios. Results are compared against the simulated multiple breach. A preliminary implementation of this risk framework into a geographic information system is also described.

Integrating airborne hyperspectral imagery and LiDAR for volcano mapping and monitoring through image classification

Abstract Optical and laser remote sensing provide resources for monitoring volcanic activity and surface hydrothermal alteration. In particular, multispectral and hyperspectral imaging can be used for detecting lithologies and mineral alterations on the surface of actively degassing volcanoes. This paper proposes a novel workflow to integrate existing optical and laser remote sensing data for geological mapping after the 2012 Te Maari eruptions (Tongariro Volcanic Complex, New Zealand). The image classification is based on layer-stacking of image features (optical and textural) generated from high-resolution airborne hyperspectral imagery, Light Detection and Ranging data (LiDAR) derived terrain models, and aerial photography. The images were classified using a Random Forest algorithm where input images were added from multiple sensors. Maximum image classification accuracy (overall accuracy = 85%) was achieved by adding textural information (e.g. mean, homogeneity and entropy) to the hyperspectral and LiDAR data. This workflow returned a total surface alteration area of ∼0.4 km2 at Te Maari, which was confirmed by field work, lab-spectroscopy and backscatter electron imaging. Hydrothermal alteration on volcanoes forms precipitation crusts on the surface that can mislead image classification. Therefore, we also applied spectral matching algorithms to discriminate between fresh, crust altered, and completely altered volcanic rocks. This workflow confidently recognized areas with only surface alteration, establishing a new tool for mapping structurally controlled hydrothermal alteration, evolving debris flow and hydrothermal eruption hazards. We show that data fusion of remotely sensed data can be automated to map volcanoes and significantly benefit the understanding of volcanic processes and their hazards.

A Distributed Computing Workflow for Modelling Environmental Flows in Complex Terrain

Numerical modelling of extreme environmental flows such as flash floods, avalanches and mudflows can be used to understand fundamental processes, predict outcomes and assess the loss potential of future events. These extreme flows can produce complicated and dynamic free surfaces as a result of interactions with the terrain and built environment. In order to resolve these features that may affect flows, high resolution, accurate terrain models are required. However, terrain models can be difficult and costly to acquire, and often lack detail of important flow steering structures such as bridges or debris. To overcome these issues we have developed a photogrammetry workflow for reconstructing high spatial resolution three dimensional terrain models. The workflow utilises parallel and distributed computing to provide inexpensive terrain models that can then be used in numerical simulations of environmental flows. A section of Quebrada San Lazaro within the city of Arequipa, Peru is used as a case study to demonstrate the construction and usage of the terrain models and applicability of the workflow for a flash flood scenario.

Probabilistic hazard modelling of rain-triggered lahars

Probabilistic quantification of lahar hazard is an important component of lahar risk assessment and mitigation. Here we propose a new approach to probabilistic lahar hazard assessment through coupling a lahar susceptibility model with a shallow-layer lahar flow model. Initial lahar volumes and their probabilities are quantified using the lahar susceptibility model which establishes a relationship between the volume of mobilised sediment and exceedance probabilities from rainfall intensity-frequency-duration curves. Rainfall-triggered lahar hazard zones can then be delineated probabilistically by using the mobilised volumes as an input into lahar flow models. While the applicability of this model is limited to rain-triggered lahars, this approach is able to reduce the reliance on historic and empirical estimates of lahar hazard and creates an opportunity for the generation of purely quantitative probabilistic lahar hazard maps. The new approach is demonstrated through the generation of probabilistic hazard maps for lahars originating from the Mangatoetoenui Glacier, Ruapehu volcano, New Zealand.