DAM BREACH ANALYSIS AND PARAMETER SENSITIVITY ANALYSIS ALONG A RIVER REACH USING HECRAS

Current methods of dam breach analyses adopt a deterministic approach. Applying these methods to Concrete Faced Rockfill Dams (CFRD) is fraught with huge levels of uncertainty, especially in the context of natural hazards. The frequency and magnitude of rainfall and earthquakes are higher in today's world. In the literature, the complete collapse of dams is modelled on dam breach parameters that define the dam break outflow but are not related to the return periods of natural hazards. As more new dams are constructed to control the floods in intra-plate seismic regions, this study presents a novel approach to the derivation of generalized dam break parameters for CFRD based on the structural analysis of Finite Element Model (FEM) simulations for peak ground accelerations corresponding to 475 and 2475 year return periods. Furthermore, the occurrence of rainfall and earthquake for different return periods are modelled using 2D hydrodynamic simulations. Results show the significance of generalized dam breach parameters for planning and managing CFRDs during earthquakes. The study emphasizes the utilization of structural analysis outputs for the hydraulic modeling of dam breaks, which will result in more specific and accurate dam break parameters. Additionally, the study has shown that the flood risk and the severity will increase with the intensity of earthquake and rainfall magnitudes. Disaster mitigation strategies can be optimized by considering the integrated occurrence of rainfall and earthquakes based on the probability of occurrence, demonstrated using a case-study dam. Another significant outcome of the study is the effect of soil saturation condition during a dam break, which reveals that areas within 40 km of the dam breach location might be worst affected.

Dam is built for various functions such as water supply, flood and sediment control, electricity generation and irrigation. Floods due to dam breaches create higher peak flows than floods produced by heavy rainfall. When a dam collapses, the stored water may cause devastating catastrophe towards downstream areas by causing fatalities and property damages. The aim of this study is to perform a two-dimensional dam break modelling of Beris Dam due to probable maximum flood (PMF). The HEC-RAS software was used to predict the breach outflow’s hydrograph and produce the flood inundation and velocity map. Dam breach parameters were calculated using Froehlich and MacDonald and Langridge-Monopolis (MDLM) equations. A 4-day simulation conducted showed that a breach was initiated at almost 10.35 am, 34 hours and 35 minutes after the PMF scenario. Peak discharge during the PMF failure is 10,745.12 m3/s at 12.45 pm the next day which is after 2 hours and 10 minutes of dam breach initiation. Felda Lubuk Merbau, Kampung Betong, Jeniang, Padang Serai and Kota Kuala Muda are among the areas affected by the simulated Beris Dam break. Information obtained on flood velocity, depth and arrival time are useful to local authorities in order to respond effectively and immediately in the event of dam break.

Dam breach analyses for tailings dams currently rely heavily on relationships and methods derived for water retaining dams, despite significant differences in design, construction, dam materials, and geometry; particularly, the upstream face of the dam. Conventional tailings slurry deposition from the dam crest typically forms low angle upstream beaches (1–2 % inclination) within the impoundment. In this paper, we isolate the effect of tailings dam beach geometry at the time of overtopping on breach characteristics using physical and numerical modeling. Five 1 m high homogeneous fine sand dams with beach heights of 0.5 to 0.9 m and a beach slope of 5 % were brought to failure by v-notch overtopping. The laboratory data revealed that a threshold beach height existed above which the peak discharge was progressively limited by the geometry of the reservoir. Numerical simulations, performed in XBeach, captured this effect in the outflow hydrographs, with differences between physical and numerical model peak outflow generally within 25 %. Another key model parameter in tailings dam breach analysis is the volume of tailings solids lost through erosion during breach. Comparison of terrestrial laser scanning elevation profiles, cut through the centreline of the physical model, with XBeach simulations indicate XBeach can replicate the bulk characteristics of erosion when a tailings-style beach is present. These findings show that hazard analysis for overtopping failure in tailings dams should consider the effect of tailings dam beach geometry on the outflow hydrograph, and forms a growing case of evidence to support the use of XBeach for simulation of dam breach.

Analytical techniques for the estimation of dam breach parameters were evaluated and compared. The development of potential flooding from a dam failure requires several elements; the hydrologic scenario, the possible dam failure modes, breach parameters that are associated with the failure modes, and the routing and mapping of the consequent discharge hydrograph. This paper presents recent research into the use and application of several dam breach parameter estimators to describe the physical characteristics of a dam breach, use of those parameters within the unsteady flow routing model HEC-RAS, and the computation and display of the resulting downstream impacts. The breach parameter estimators that were used include both empirical and embankment erosion process models.

Economic risk criteria for dams considering the relative level of economy and industrial economic contribution

9106 Background: Most patients with advanced cancer want an idea of typical, best case, and worst case scenarios for overall survival (OS). Specific percentiles from OS curves of comparable patients are a reasonable starting point for estimating these scenarios. We summarized recent randomized trials to determine if simple multiples of the median OS from each curve provided reasonable estimates of these scenarios, and to determine the ratio of median OS to median PFS from corresponding curves. Methods: We searched the Cochrane register and major journals from 1999 to 2009 for randomized trials of first-line chemotherapy for MBC with ≥90 patients/arm. We recorded the median and following percentiles (represented scenario) from each OS curve: 90th (worst case), 75th (lower typical), 25th (upper typical) and 10th (best case). We estimated these percentiles for each OS curve by multiplying its median by the following simple multiples: 0.25 for the 90th, 0.5 for the 75th, 2 for the 25th, and 3 for the 10th. Each estimate was deemed accurate if within 0.75 to 1.33 times the actual value. Associations between trial characteristics and median OS were assessed with linear regression. Results: We analyzed 74 OS curves from 34 trials including 12,714 women followed for a median of 3 years. The average value (interquartile range, IQR) of the median OS was 22 months (18-24), of the median PFS was 7 months (6-9), and of the ratio of median OS to PFS was 3.0 (2.4-3.5). The average value (IQR) in months from all OS curves for each scenario was: worst case 6 (5-7), lower typical 12 (10-13), upper typical 36 (31-41) and best case 56 (47-60). Simple multiples of the median OS provided accurate estimates of the worst case in 75% of curves, lower typical in 97%, upper typical in 96% and best case in 96%. OS was longer in trials with a higher proportion of ER+ tumors (p=0.0018) and in trials of HER2+ women treated with trastuzumab (p=0.004). Conclusions: Worst, typical, and best case scenarios were remarkably consistent in a wide range of contemporary trials. Simple multiples of the median provided accurate estimates of these scenarios for most OS curves and are a good basis for discussing prognosis. No significant financial relationships to disclose.

BackgroundActive magnetic resonance imaging implants, for example stents, stent grafts or vena cava filters, are constructed as wireless inductively coupled transmit and receive coils. They are built as a resonator tuned to the Larmor frequency of a magnetic resonance system. The resonator can be added to or incorporated within the implant. This technology can counteract the shielding caused by eddy currents inside the metallic implant structure. This may allow getting diagnostic information of the implant lumen (in stent stenosis or thrombosis for example). The electro magnetic rf-pulses during magnetic resonance imaging induce a current in the circuit path of the resonator. A by material fatigue provoked partial rupture of the circuit path or a broken wire with touching surfaces can set up a relatively high resistance on a very short distance, which may behave as a point-like power source, a hot spot, inside the body part the resonator is implanted to. This local power loss inside a small volume can reach ¼ of the total power loss of the intact resonating circuit, which itself is proportional to the product of the resonator volume and the quality factor and depends as well from the orientation of the resonator with respect to the main magnetic field and the imaging sequence the resonator is exposed to.MethodsFirst an analytical solution of a hot spot for thermal equilibrium is described. This analytical solution with a definite hot spot power loss represents the worst case scenario for thermal equilibrium inside a homogeneous medium without cooling effects. Starting with this worst case assumptions additional conditions are considered in a numerical simulation, which are more realistic and may make the results less critical. The analytical solution as well as the numerical simulations use the experimental experience of the maximum hot spot power loss of implanted resonators with a definite volume during magnetic resonance imaging investigations. The finite volume analysis calculates the time developing temperature maps for the model of a broken linear metallic wire embedded in tissue. Half of the total hot spot power loss is assumed to diffuse into both wire parts at the location of a defect. The energy is distributed from there by heat conduction. Additionally the effect of blood perfusion and blood flow is respected in some simulations because the simultaneous appearance of all worst case conditions, especially the absence of blood perfusion and blood flow near the hot spot, is very unlikely for vessel implants.ResultsThe analytical solution as worst case scenario as well as the finite volume analysis for near worst case situations show not negligible volumes with critical temperature increases for part of the modeled hot spot situations. MR investigations with a high rf-pulse density lasting below a minute can establish volumes of several cubic millimeters with temperature increases high enough to start cell destruction. Longer exposure times can involve volumes larger than 100 mm3. Even temperature increases in the range of thermal ablation are reached for substantial volumes. MR sequence exposure time and hot spot power loss are the primary factors influencing the volume with critical temperature increases. Wire radius, wire material as well as the physiological parameters blood perfusion and blood flow inside larger vessels reduce the volume with critical temperature increases, but do not exclude a volume with critical tissue heating for resonators with a large product of resonator volume and quality factor.ConclusionThe worst case scenario assumes thermal equilibrium for a hot spot embedded in homogeneous tissue without any cooling due to blood perfusion or flow. The finite volume analysis can calculate the results for near and not close to worst case conditions. For both cases a substantial volume can reach a critical temperature increase in a short time. The analytical solution, as absolute worst case, points out that resonators with a small product of inductance volume and quality factor (Q Vind < 2 cm3) are definitely save. Stents for coronary vessels or resonators used as tracking devices for interventional procedures therefore have no risk of high temperature increases. The finite volume analysis shows for sure that also conditions not close to the worst case reach physiologically critical temperature increases for implants with a large product of inductance volume and quality factor (Q Vind > 10 cm3). Such resonators exclude patients from exactly the MRI investigation these devices are made for.

The breach risk of reservoir dam exists objectively while exerting benefits. There is great uncertainty in the overtopping breach process of embankment dam and the dam break flood routing which affects the accuracy of dam risk analysis and may cause unnecessary waste in emergency scheduling. However, the uncertainty analysis of the breach process and its consequence is currently inadequate. Therefore, a stratified sampling Monte Carlo method is proposed to simulate uncertain overtopping breach flood of embankment dams. The main sources of uncertainty are analyzed and determined as uncertain dam breach and flood routing processes. The uncertain breach process of dam is studied by presenting a sensitive study between 3 mechanism breach models and 5 parametric breach models. The random dam breach process is restored using HEC-RAS semi-empirical breach model by estimating breach characteristics through multiple common breach models. The random flood routing is carried out through 1D–2D coupled unsteady flow analysis in which the random breach process is adopted as an upper inflow boundary condition. According to the case study results, though parameters have been controlled in a limited range, the flood routing results in the early stage of dam overtopping failure present greater uncertainty. As the flood progresses further downstream, the uncertainty will gradually decrease. This study could serve as a reference for dam breach risk map making.

The aim of this study is to analyze the effects of a possible dam failure under various scenarios and to generate a flood hazard map for two consecutive dams located in a study area with a dense-residential region and a heavy-traffic highway. Two consecutive dams consist of Elmalı 2, a concrete-buttress dam and Elmalı 1, an earth-fill gravity dam in the upstream and downstream, respectively. Hydrologic Engineering Center-River Analysis System (HEC-RAS) was used to develop a dam failure model. Dam failure scenarios were examined regarding three main criteria: the Breach Formation Time (BFT), the Number of Failed Buttresses (NFB) of Elmalı 2, and the Reservoir Volume Ratio (RVR) of Elmalı 1. Accordingly, flood peak depth (Hp), peak flow rate (Qp), peak velocity (vp), and time to reach the peak (tp) are discussed. The results showed that BFT and NFB of Elmalı 2 were highly effective on these values, whereas RVR of Elmalı 1 had no significant effect. Moreover, the total area affected by potential floods was calculated with a comparative areal change analysis using flood inundation and flood hazard maps obtained. Estimated damage costs indicate that in the worst-case scenario, more than 500 buildings will be affected in the region.

Cauwels and Sornette present a novel methodology to determine the fundamental value of firms in the social networking sector, motivated by recent realized IPOs and by reports that suggest sky-high valuations of firms such as Facebook, Groupon, LinkedIn Corp., Pandora Media, Inc., Twitter, and Zynga. The authors’ valuation of these firms is based on two assumptions:1) revenues and profits of a social networking firm are inherently linked to its user base through a direct channel that has no equivalent in other sectors, and 2) the growth in the number of users can be calibrated with standard logistic growth models, which allows for reliable extrapolations of the size of the business at long time horizons. Cauwels and Sornette illustrate the methodology with a detailed analysis of Facebook, one of the biggest of the social media giants. A clear signature of a change of regime, occurring in 2010 in the growth of the number of users, is observed. The change of regime is a move from a pure exponential behavior (a paradigm for unlimited growth) to a logistic function with asymptotic plateau (a paradigm for growth in competition). The authors consider three different scenarios: a base case, high-growth, and extreme-growth scenario. Using a discount factor of 5%, a profit margin of 29% and $3.50 of revenues per user per year yields a value of Facebook of $15.3 billion in the base case scenario, $20.2 billion in the high-growth scenario, and $32.9 billion in the extreme-growth scenario. According to the authors’ methodology, this implies that Facebook needs to increase its profit per user before the IPO by a factor of 3 to 6 in the base case scenario, 2.5 to 5 in the high-growth scenario, and 1.5 to 3 in the extreme-growth scenario in order to meet the current, widespread high expectations. To prove the wider applicability of their methodology, the analysis is repeated for Groupon, the well-known deal-of-the-day website, that went public in November 2011.The results are in line with the Facebook analysis. Customer growth will plateau. By not taking this fundamental property of the growth process into consideration, estimates of the Facebook IPO are wildly overpriced. <b>TOPICS:</b>Legal/regulatory/public policy, accounting and ratio analysis, statistical methods

Incorporating adjuvant cyclin-dependent kinase (CDK) 4/6 inhibitors abemaciclib and ribociclib along with endocrine therapy has been shown to improve invasive disease-free survival (iDFS) for hormone receptor-positive (HR+) human epidermal receptor 2-negative (HER2-) early breast cancer (EBC). This study assesses the cost-effectiveness of this strategy, along with adjuvant aromatase inhibitors from an Indian perspective. A Markov chain model evaluated the cost-effectiveness of abemaciclib and ribociclib with letrozole compared with letrozole alone for HR+/HER2- EBC from a payer perspective in India. Key measures included lifetime quality-adjusted life-years (QALY), life-years (LY), and total costs. This study explores two scenarios for effectiveness: a best-case (BC) scenario, where the benefit of CDK4/6 inhibitors in improving iDFS lasts a lifetime, and a worst-case (WC) scenario, where benefits disappear after 5 years. Probabilistic sensitivity analyses (PSA) were used to account for simulation uncertainty. In the BC scenario, abemaciclib added 2.17 QALY and 4.96 LY, incurring ₹2,317,957.7 ($27,756.65 in US dollars [USD]) in additional costs. However, the incremental cost-effectiveness ratio (ICER) for abemaciclib exceeded India's willingness-to-pay threshold in the BC and WC scenarios. In the BC scenario, ribociclib added 0.98 QALY and 2.58 LY with added costs of ₹1,711,504.32 ($20,494.6 USD). The ICER for ribociclib also surpassed India's threshold in both scenarios. PSA showed that neither drug was cost-effective at the current market prices in either BC/WC scenario. The cost of abemaciclib and ribociclib needs to be reduced by at least 78.61% and 87.19%, respectively, to be cost-effective in the BC scenario. The combination of adjuvant abemaciclib or ribociclib with letrozole is not cost-effective for HR+/HER2- EBC in India in either the BC or WC scenario.

As the advance of memory technologies, multiple types of memory such as different kinds of non-volatile memory (NVM), SRAM, DRAM, etc. provide a flexible configuration considering performance, energy and cost. For improving the performance of systems with multiple types of memory, data allocation is one of the most important tasks. The previous studies on data allocation problem assume the worst (fixed) case of data-access frequencies. However, the data allocation produced by employing worst case usually leads to an inferior performance for most of time. In this paper, we model this problem by probabilities and design efficient algorithms that can give optimal-cost data allocation with a guaranteed probability. The proposed DAGP algorithm produces a set of feasible data allocation solutions which generates the minimum access time or cost guaranteed by a given probability. The experiments show that our technique can significantly reduce the access time or cost compared with the technique considering worst case scenario. For example, comparing with the optimal result generated by employing the worst cases, our technique can reduce memory access time by 10.35% on average when guaranteed probability is set to be 0.8. Moreover, for 80 percents of cases, memory access time is reduced by 23.98% on average.

Experimental investigation on the longitudinal evolution of landslide dam breaching and outburst floods

Large-scale field model tests of landslide dam breaching

This paper investigates trends of historical and projected future South African coal-fired power station criteria (total primary Particulate Matter (PM), Sulphur Dioxide (SO2) and Nitrogen Oxides (NOx)) and Carbon Dioxide (CO2) emissions. It was found that an energy restricted environment has an increasing effect on emissions, as emissions per energy unit increased from the onset of the South African energy crisis. PM emissions particularly, increased during the energy crisis period, due to increased pressure on PM abatement and lowered maintenance opportunity. Projections of future coal-fired power station criteria and CO2 emissions are made for four different future scenarios for the period 2015 to 2030. Three of the four scenarios are based on the lower projected energy demand baseline case as published in the updated Integrated Development Plan (IRP). The difference between these three scenarios is different retrofit rates of power stations with emissions abatement technologies. The fourth scenario is a worst case scenario and assumes high energy demand (and therefore no decommissioning of power stations), high emission rates (similar to worst past emission rates during the period 1999-2012) and no further abatement of emissions above and beyond current mitigation efforts. This scenario gives an indication of what South African coal-fired power station emissions could look like if the energy crisis persists. There is a marked difference between projected best and worst case PM emissions during the entire projected period, but especially during 2030 when worst case PM emissions compared to a 2015 baseline value are expected to rise by 40% and best case PM emissions are projected to decline by 40%. Worst case NOx emissions are expected to increase by 40% in 2030 from a 2015 baseline value whereas best case emissions are expected to decline 10% from the same level in 2030. Worst case SO2 emissions are predicted to increase by around 38% in 2030 and best case emissions are expected to decrease by around 20% in 2030 from a 2015 baseline value. Relative emissions used in the projection of future CO2 emissions in this paper differ from that used in the energy demand and energy mix modelling done for the updated IRP baseline case. The reason for this is that the modelling for the updated IRP assumed relative CO2 emission factors for supercritical boilers, whereas only Kusile and Medupi fall in this category and relative emissions from all other stations are, in fact, between 5% and 16% higher. For this reason, it seems unlikely that the South African climate commitment target for 2030 will be made.