A physics-based multi-regime approach for estimation of head losses in operating hydropower plants

History shows that countries along the Dead Sea Transform, including Israel, have suffered considerable destruction from strong earthquakes, and thus, a modern approach for damage and loss estimations is essential in mitigating damage from future earthquakes. Yet to date, only preliminary damage scenarios have been developed. The present study uses the Hazus MH 2.1 (2012) software to simulate damage and loss estimation for seven earthquakes that may affect Israel. For the first time, over 2,200 different building construction schemes, including a comprehensive nationwide building inventory of over 900K buildings, were simulated in order to identify the high-risk areas and suggest potential mitigation strategies as well as a financial budget plan that would ultimately alleviate the anticipated catastrophe in Israel. The results show excellent ability of Hazus to resolve the expected levels of damage, including damages for various types of buildings, debris and economic losses. Furthermore, it shows that the most intensive damage is expected to concentrate in northern Israel, mainly in the Haifa and Bet Shean regions, as well as in areas of older building stock and adjacent to the major fault lines. Comparison between the budget required for strengthening structures and the economic loss expected after a strong earthquake shows that strengthening structures will undoubtedly reduce the disaster magnitude dramatically. The loss estimations can provide decision makers a tool for planning post-earthquake emergency actions including rescue, debris clearance, building inspection, sheltering requirements and directing the civil protection authorities in a focused and proper response during an earthquake event. Although local fragility curves have not yet been developed in Israel, the new scenarios presented here demonstrate that the benefits of realizing already now the rough scope of earthquake damage greatly outdo future gains from as yet unavailable exact assessments.

There are several approaches for loss estimation in magnetic cores, and all these approaches highly rely on accurate information about flux density distribution in the cores. It is often assumed that the magnetic flux density evenly distributes throughout the core and the overall core loss is calculated according to an effective flux density value and the macroscopic dimensions of the cores. However, the flux distribution in the core can alter by core shapes and/or operating conditions due to nonlinear material properties. This paper studies the element-wise estimation of the loss in magnetic cores. FEM has been used to investigate the flux density distribution in the core and the loss has been estimated considering this distribution. Finally, comparative results are shown between the classical macroscopic core loss estimation using effective dimensions and the element-wise loss estimation. The presented work in this paper has been carried out for two common excitation waveforms in power electronics applications, sinusoid and square-wave and for two different core shapes, toroid and E-cores. Results show that ±10% discrepancy should be expected in loss estimation of the core using effective dimensions under both excitation waveforms.

Estimating technical losses is fundamental to the planning and economics of electric power networks. This paper surveys the evolution of the ideas behind energy loss estimation and focuses on the development of the concepts of the loss factor and equivalent hours. The paper next identifies difficulties in using maximum demands and the loss factor to estimate energy losses. Based on this analysis, this study proposes an alternative loss estimation approach that relies on the “loss coefficient” as the fundamental parameter for describing load variations in loss estimation. A large load-curve data bank from Brazilian utilities is used to characterize load-curve parameters and provide perspective on the old and new concepts. Practical applications put the proposed ideas into perspective, showing how the use of average demands and loss coefficient can help to make better cable choices, increase accuracy in loss estimation for distribution transformers, and enhance the quality of information in loss estimation analysis.

The requirements for fish protection at hydro power plants have led to a significant decrease of the bar spacing at trash racks as well as the need of an inclined or angled design to improve the guidance effect (fish-friendly trash racks). The flexible fish fence (FFF) is a new developed fish protection and guidance system, created by horizontally arranged steel cables instead of bars. The presented study investigated experimentally the head loss coefficient of an angled horizontal trash rack with circular bars (CBTR) and the FFF with identical cross sections in a flume (scale 1:2). Nine configurations of different bar and cable spacing (blockage ratio) and rack angles were studied for CBTR and FFF considering six different stationary flow conditions. The results demonstrate that head loss coefficient is independent from the studied Bar–Reynolds number range and increases with increasing blockage ratio and angle. At an angle of 30 degrees, a direct comparison between the two different rack options was conducted to investigate the effect of cable vibrations. At the lowest blockage ratio, head loss for both options are in similar very low ranges, while the head loss coefficient of the FFF increases significantly compared to the CBTR with an increase of blockage. Further, the results indicate a moderate overestimation with the predicted head loss by common head loss equations developed for inclined vertical trash racks. Thus, an adaption of the design equation is proposed to improve the estimation of head loss on both rack options.

Electricity theft is a great trouble for power companies. As the means of tampering with smart meters continue to increase, the electricity theft behaviours become more diversified and covert, which are difficult to be identified using the existing electricity theft detection method. In addition, the existing methods usually cannot estimate the economic losses caused by electricity theft. To address these issues, a combined unsupervised learning approach for electricity theft detection and loss estimation is proposed in this study. First, three anomaly measurement indexes including the mean index, fluctuation index, and trend index are proposed to capture different anomalies respectively. Then, based on historical electricity consumption data, we develop two unsupervised learning techniques including the sample‐to‐subsamples decomposition algorithm and clustering algorithm to obtain the typical ranges of index values, and the load samples whose index values are not in the typical ranges will be considered fraudulent. Furthermore, three anomaly measurement indexes are combined to judge whether the load sample is fraudulent, and the user whose most load samples are judged fraudulent will be considered as an electricity thief. Finally, an economic loss estimation method is proposed, which quantifies the losses of electricity theft. Numerical experiments are carried out based on the Irish smart meter dataset, and the results demonstrate the effectiveness and the superior performance of the proposed method compared with a series of electricity theft detection methods.

This paper deals with a new application for a special sort of Rogowski coil (RC) sensor in real-time estimation of diode turn-OFF energy loss. The turn-OFF energy loss of power diode is a key metric in designing power electronics circuits. The estimation accuracy of the diode turn-OFF energy loss significantly depends on the accurate extraction of diode reverse-recovery parameters during the turn-OFF process. By far, many methods have been proposed for offline estimation of diode reverse-recovery parameters. However, online estimation of these parameters can also provide worthwhile information for real-time monitoring of power diode and operating power electronics circuit. Specifically, the online estimated energy loss includes information which can be interpreted to obtain general ideas about the diode junction temperature, health status of snubber circuits, and so on. In this paper, a novel approach for online estimation of turn-OFF energy loss of power diodes using an efficient double-layer printed circuit board RC (DLPCBRC) sensor is proposed. The sensor is designed and utilized to acquire the key reverse-recovery parameters of the diode. Based on the extracted reverse-recovery parameters, a sufficiently good estimation of diode turn-OFF energy loss is obtained in real-time. The simulation and experimental results on a typical diode in a boost DC–DC converter are presented to demonstrate the effectiveness of the proposed approach.

<p>Floods are the most costly natural disasters for European economies and expected to increase in frequency and magnitude within a changing climate. Governmental agencies, as well as the (re-)insurance sector, rely on accurate flood loss estimations on the European scale to support climate change adaptation policies, prepare for economic impacts, for instance, via the EU solidarity fund and calculate premiums.</p><p> Flood loss estimation on the European scale is currently based on deterministic depth-damage functions different for each country. This leads to a fragmented approach in flood loss estimation, greatly simplifying the representation of damage processes without information about associated uncertainties. To overcome these shortcomings we developed the Bayesian Network Flood Loss Estimation MOdel for the private sector (BN-FLEMOps). BN-FLEMOps estimates relative loss to residential buildings depending on flood experience of the population, precautionary measures, building area, building type, return period, duration and water depth (Wagenaar et al. 2018). The structure of this probabilistic multi-variable model is based on empirical data from post-flood surveys and uses consistent continent-wide proxy data for European scale application. BN-FLEMOps was successfully validated in three case studies in Italy, Austria and Germany. The officially reported loss figures of the past flood events were within the 95% quantile range of the probabilistic loss estimation (Lüdtke et al. 2019).</p><p>The probabilistic approach enables the quantification of uncertainties of the loss estimates. Model outputs are generated as loss distributions in high spatial resolution, offering Europe-wide information about risk and uncertainty. Thus, providing support for decision-making processes in flood risk management.</p><p>Easy applicability to the BN-FLEMOps model is ensured by its implementation in the standardized OASIS loss modeling framework (lmf). The OASIS lmf enables a plug and play combination with various input data sets and other models.</p><p>A first application of BN-FLEMOps for a Europe-wide 100 years flood hazard scenario provided by the Joint Research Center resulted in accumulated loss for residential buildings in Europe of 79.0 billion euro (Q20 = 32.3; Q80 = 213.8).</p><p> </p><p><span><strong>References</strong></span></p><p>Lüdtke, S., Schröter, K., Steinhausen, M., Weise, L., Figueiredo, R., Kreibich, H. (2019 online first): A consistent approach for probabilistic residential flood loss modeling in Europe. - Water Resources Research. <span>DOI: http://doi.org/10.1029/2019WR026213</span></p><p>Wagenaar, D., Lüdtke, S., Schröter, K., Bouwer, L. M., Kreibich, H. (2018): Regional and Temporal Transferability of Multivariable Flood Damage Models. - Water Resources Research, 54, 5, pp. 3688-3703. DOI: http://doi.org/10.1029/2017WR022233</p>

This paper offers solutions for drawdowns due to intermittent pumping cycles or cyclic pumping, which are high accuracy approximations of the series of Theis functions superimposed in time. The proposed approximation formulas are an improvement over the earlier works. The earlier approximations are valid only if the number of pumping cycles is greater than 10 and involve gamma functions that are less convenient to evaluate than the rational approximation formulas offered in this paper. The proposed approximations are valid for any number of pumping cycles and involve simple functions that can be computed even using a calculator. The drawdown functions are defined for the drawdowns at the end of pumping or shutoff periods. The proposed expressions for these functions are also suitable for the estimation of aquifer parameters by plotting the observed drawdowns on semilogarithmic paper. Procedures for estimation of storage coefficient and head loss at the well from cyclic pumping drawdowns are not available. This paper also offers procedures for the estimation of transmissivity, storage coefficient, and head loss at the pumped well from the observed intermittent (cyclic) pumping drawdowns.

Accurate estimation of head loss introduced via randomly placed roughness elements found in natural or constructed streams (e.g., fish passages) is essential in order to estimate flow variables in mountain streams, understand formation of niches for aquatic life, and model flow structure. Owing to the complexity of the involved processes and the often missing detailed data regarding the roughness elements, the head loss in such streams is mostly approximated using empirical models. In our study, we utilize flume experiments to analyze the effects of the spatial distribution of roughness elements on water surface levels and head loss and, moreover, use the produced data to test three empirical models estimating head loss. The experiments were performed in a 15 m long, 0.9 m wide flume with a slope of 5% under large Froude numbers (2.5–2.8). Flow velocities and water levels were measured with different flow rates at 58 points within a 3.96 m test section of the flume. We could show that different randomly arranged patterns of roughness elements significantly affected head loss (differences up to 33.6%), whereas water jumps occurred when flow depths were in the same size range as the roughness elements. The roughness element position and its size influenced water surface profiles. None of the three tested empirical models were able to well reproduce the differences in head loss due to the different patterns of roughness elements, with overestimated head loss from 12 to 94.7%, R2 from 41 to 73%, NSE from −21.1 to 0.09, and RRMSE from 18.4 to 93%. This generally indicates that these empirical models are conditionally suitable to consider head loss effects of random patterns of roughness elements.

Estimation of soil loss through water erosion is an essential exercise which can help decision makers and planners determine the severity of soil loss through rill and sheet erosion and also curtail the development of further gullies in an area already ravaged by gully erosion. While Universal Soil Loss Equation (USLE) is the most commonly adopted model because it provides a straight forward approach for qualitative estimation of soil loss, however its rainfall erosivity component is found incompetent in most parts of the world. To overcome this deficiency, the Revised Universal Soil Loss Equation (RUSLE) was implemented using rainfall erosivity (R) values peculiar to tropical environment of the Anambra area of Nigeria. Rainfall erosivity (R-factor), soil erodibility (K-factor), slope factor (LS-factor), and cover management (C-factor) were generated in GIS environment and then integrated based on RUSLE equation to estimate the rate of soil erosion. The study indicated that about 1804.39 km2 (39.49 %) of the study area have slight erosion rate of 0–10 t ha−1 year−1, while the rates of erosion in 746.60 km2 (16.34 %), 1025.38 km2 (22.44 %), 659.55 km2 (14.43 %), 287.08 km2 (6.28 %), and 46.59 km2 (1.02 %) of the study area are 10.6–85.3, 85.4–235.2, 235.3–608, 608.1–2200 and >2200.1 t ha−1 year−1 respectively. The study revealed that high rainfall erosivity combined with moderate to high slope factor and decreasing vegetal cover are the major factors driving soil loss in the area.

It is well known that 2D finite element (FE) estimation of stator losses in machines driven by the pulse width modulated (PWM) supplies may result in highly exaggerated losses. This work presents a new simple analytical approach which can predict the PWM losses in the stator laminations of a concentrated winding permanent magnet synchronous machine. Experimental set-up is used to examin the results of 2D-FE simulation and demonstrate the validity of the analytical method.

The spiral wound gasket, developed after the turn of the 20th century, has been a popular gasket choice in the chemical, petrochemical, power and other industries. Since that time, metal gasket manufacturers have developed various designs for this popular type of gasket, using different metals and fillers in the windings. As a result, some subsequent spiral wound designs have included a metal inner ring inserted inboard of the windings, with the primary objective of preventing inward radial buckling of this gasket as well as to cover more of the flange face and minimize erosion between flange faces. However, the cost of fabricating the spiral wound increases in accordance with the metallurgy of the inner ring, as does the assembly bolt force required to fully compress this now captured spiral winding. Additionally, another recently identified drawback of the inner ring is the head loss due to the contraction of the flow area caused by the inner ring intrusion into the flow for certain nominal pipe sizes (NPS) and pipe schedules. For example, standard ASME B16.20 spiral wound gaskets with inner rings designed for ASME B16.5 Class 150 raised face flanges extend inside the flange and pipe wall to varying degrees for most Schedule 10 pipe between NPS ½” and 6”. Such intrusions can impact the flow in the form of minor head loss resulting from intrusion of the inner ring. Flow equations for an orifice can be used to estimate head loss; such an empirical equation has been applied to estimate head loss associated with an inner ring style spiral wound gasket in various pipe schedules and NPSs. Total head loss for multiple flanges in a pipe network has also been calculated as the head losses from individual “inner ring orifices” are accumulated. Several scenarios were identified to indicate where spiral wound gaskets with an inner ring can not only lead to pipe network head loss but substantial hidden energy costs.

ABSTRACTThe objective of this study is to investigate whether the additional damage to building components caused by vertical ground shaking and its impact on estimated monetary losses warrants the extra computational effort needed to include this feature for standard risk assessment applications. As a case study, we consider a 2D model of a modern nine‐story steel frame building located at a high seismic hazard site in California. The structural and nonstructural demands are assessed via nonlinear dynamic analysis carried out using hazard‐consistent bi‐directional (horizontal & vertical) ground motion records. We estimated the seismic losses with and without the vertical ground motion using a component‐based loss estimation approach based on FEMA‐P58. We also explored the sensitivity of the loss estimates to the characteristics of the input vertical acceleration fragility curves. Analysis results indicate a modest increase in the average annual losses (AAL) when the vertical component is included, consistent with the relatively small fraction of the total building replacement cost assigned to components sensitive to vertical motion. We also investigate the sensitivity of the loss estimates to the conditioning ground motion intensity measure adopted in the risk assessment procedure. Considerable discrepancies are observed in the loss estimates on an intensity basis and, to a lesser degree, on a risk basis. Among the tested intensity measures, average spectral acceleration performs better than single‐period spectral accelerations in two regards: it provides higher efficiency, and it maintains good consistency of the selected records with the site hazard while using lower levels of ground motion amplitude scaling. Whereas single‐period spectral ordinates that will approximate these advantages may exist, finding them requires some investigation.

SUMMARYLoss ratio, which is the ratio of the repair cost to the total replacement cost, is an effective parameter for representing structural and nonstructural damage caused by earthquakes. A probabilistic loss estimation framework is first presented that directly relates hazard to response and hence to losses. A key feature of the loss estimation approach is the determination of losses without need for customary fragility curves. Relationships between intensity measures and engineering demand parameters are used to define the demand model. An empirically calibrated loss model in the form of a power curve with upper and lower cut‐offs is used in conjunction with the demand model to estimate loss ratios. Loss ratios for each of the damage states take into account epistemic uncertainty and an effect on price surge following a major hazardous event. The loss model is calibrated and validated for bridges designed based on the prevailing Caltrans, Japan, and New Zealand standards. The loss model is then transformed to provide a composite seismic hazard–loss relationship that is used to estimate the expected annual loss for structures. The closed‐form four‐step stochastic loss estimation model is applied to the bridges designed for ductility. Results of these ductile designs are compared to a bridge detailed to an emerging damage avoidance design philosophy. Copyright © 2011 John Wiley & Sons, Ltd.

Deteriorating highway bridges in the United States and worldwide have demonstrated susceptibility to damage in earthquake events, with considerable economic consequences due to repair or replacement. Current seismic loss assessment approaches for these critical elements of the transportation network neglect the effects of aging and degradation on the loss estimate. However, the continued aging and deterioration of bridge infrastructure could not only increase susceptibility to seismic damage, but also have a significant impact on these economic losses. Furthermore, the contribution of individual aging components to system‐level losses, correlations between these components, and uncertainty modeling in the risk assessment and repair modeling are all crucial considerations to enhance the accuracy and confidence in bridge loss estimates. In this paper, a new methodology for seismic loss assessment of aging bridges is introduced based on the non‐homogeneous Poisson process. Statistical moments of seismic losses can be efficiently estimated, such as the expected value and variance. The approach is unique in its account for time‐varying seismic vulnerability, uncertainty in component repair, and the contribution of multiple correlated aging components. A representative case study is presented with two fundamentally distinct highway bridges to demonstrate the effects of corrosion deterioration of different bridge components on the seismic losses. Using the proposed model, a sensitivity study is also conducted to assess the effect of parameter variations on the expected seismic losses. The results reveal that the seismic losses estimated by explicitly considering the effects of deterioration of bridge components is significantly higher than that found by assuming time‐invariant structural reliability. Copyright © 2011 John Wiley & Sons, Ltd.