Reliable Performance Assessment Research Articles

Regional seismic ground‐motion simulation and observation with engineering applications

Regional seismic ground‐motion simulation and observation with engineering applications

Tall building performance‐based seismic design using SCEC broadband platform site‐specific ground motion simulations

AbstractThe scarcity of strong ground motion records presents a challenge for making reliable performance assessments of tall buildings whose seismic design is controlled by large‐magnitude and close‐distance earthquakes. This challenge can be addressed using broadband ground‐motion simulation methods to generate records with site‐specific characteristics of large‐magnitude events. In this paper, simulated site‐specific earthquake seismograms, developed through a related project that was organized through the Southern California Earthquake Center (SCEC) Ground Motion Simulation Validation (GMSV) Technical Activity Group, are used for nonlinear response history analyses of two archetype tall buildings for sites in San Francisco, Los Angeles, and San Bernardino. The SCEC GMSV team created the seismograms using the Broadband Platform (BBP) simulations for five site‐specific earthquake scenarios. The two buildings are evaluated using nonlinear dynamic analyses under comparable record suites selected from the simulated BBP catalog and recorded motions from the NGA‐West database. The collapse risks and structural response demands (maximum story drift ratio, peak floor acceleration, and maximum story shear) under the BBP and NGA suites are compared. In general, this study finds that use of the BBP simulations resolves concerns about estimation biases in structural response analysis which are caused by ground motion scaling, unrealistic spectral shapes, and overconservative spectral variations. While there are remaining concerns that strong coherence in some kinematic fault rupture models may lead to an overestimation of velocity pulse effects in the BBP simulations, the simulations are shown to generally yield realistic pulse‐like features of near‐fault ground motion records.

Uplift mechanics of unanchored liquid storage tanks subjected to lateral earthquake loading

Motivated by the seismic response of unanchored liquid storage tanks, their uplift mechanism under strong lateral loading is examined. Using three-dimensional finite element models, nonlinear static analysis is conducted to define the moment-rotation relationship of uplifting tanks resting on rigid foundation and describe the evolution of critical response parameters with increasing level of lateral loading. Meridional and hoop stress, as well as their distribution and evolution with increased uplift are computed. Comparing the numerical results with the corresponding results from anchored tanks, striking differences are observed on the values of compressive meridional stresses and their distribution around the tank circumference. Cyclic analysis, associated with repeated uplift at both sides of the tank, is also performed, to obtain the corresponding hysteretic response and verify the assumption of nonlinear-elastic tank behaviour, used in several previous works. Finally, an analytical solution is developed, capable of describing tank uplift in an efficient manner. The analytical solution accounts for the special features of uplift, obtained from the finite element solution, and can be used for simple and reliable assessment of seismic performance in unanchored liquid storage tanks.

How has it changed? A comparative field evaluation of bioretention infiltration and treatment performance post-construction and at maturity

A conventionally-designed bioretention cell, consisting of very sandy media meant to achieve high infiltration rates, was studied for its hydrologic and treatment performance over two monitoring periods: 2013–2014 (immediately post-construction) and 2017–2018 (4–5 years post-construction). Given the limited literature on mature performance of bioretention, the purpose of this study was to determine how the effluent from the bioretention cell and the hydrology changed over 5 years. The hydrologic performance was maintained 5 years post-construction, with median volume reductions of 100% in both monitoring periods, despite an underutilization of the soil volume. Using censored data analysis and a 95% confidence level, the results revealed that the effluent water quality in 2017–2018 was improved compared to 2013–2014 for some parameters, e.g., dissolved solids and nitrogen species, and was maintained for phosphorus, metals, and suspended solids. These results suggest that for a reliable assessment of bioretention cell treatment performance, it is recommended to wait for soil and plant establishment, e.g., 2 years after construction. Between the inlet and outlet of the bioretention cell (2017–2018 data only), concentration decreased for nitrogen species and suspended solids, but did not significantly increase or decrease for alkalinity, hardness, dissolved solids, phosphorus and metals. Mass removal of all contaminants was very high, largely due to high volume reductions. Despite sustained hydrologic performance up to 5 years post-construction, there is a need for targeted bioretention design for enhanced treatment performance of dissolved contaminants.

Reliability assessment of service-based software under operational profile uncertainty

We address the problem of operational reliability assessment through testing of software services delivered on-demand such as Web Services. Software reliability assessment is typically done for a specific operational profile: the profile is needed in testing to select or generate test cases (operational testing) in a way statistically similar to the anticipated use of software in operation; the observations of success/failure of test executions are used to predict software reliability in actual operation. It is well known that unless the profile is accurate, software reliability predictions obtained via operational testing cannot be trusted.We present a new way of dealing with the uncertainty in the operational profile adopting a two-stage Bayesian inference for reliability assessment. The technique relies on the availability of information about partitions of the input space. The approach is demonstrated on contrived examples and on a case study of real Web Services. We discuss the usefulness of the approach in dealing with two important practical problems: i) the true profile in operation differs from the one used in testing, ii) the profile in operation is changing continuously.

Operational reliability assessment of photovoltaic inverters considering voltage/VAR control function

This paper proposes an operational reliability assessment approach of photovoltaic (PV) inverters considering a voltage/VAR control (VVC) function. The approach aims to quantify the reliability degradation and estimate the lifetime of PV inverters when they are utilized for the VVC function. Firstly, an inverter based VVC model considering uncertain profiles of PV power generation and loads is developed and it is solved by a stochastic optimization method. Then, a long-term reliability assessment procedure of the inverters utilized in the VVC model is proposed. To assess the reliability, a power loss model considering the VVC results is developed and a modified lifetime model based on Coffin-Manson model and manufacturing information is proposed. The proposed VVC model and inverter reliability assessment approach are verified on a 33-bus distribution network. The simulation results reveal the long-term impacts of additional utilization in the VVC function on operational reliability and lifetime of PV inverters.

Assessment of Material Durability of Steam Pipelines Based on Statistical Analysis of Strength Properties—Selected Models

The paper presents a research method concerning the application of statistical prognostic models for assessment of material durability and operational reliability of steel for steam pipelines, whose operation has exceeded the working time of 100,000 h. Decisions on the admission of long-lived materials to work for power industry results from extensive diagnostic examinations are based on the results of tests of mechanical properties, microstructure degradation, and corrosion processes. Considering the economic reasons and available data published in diagnostic reports, the determination of failure-free operating time of steam pipelines is based on the results of static tensile tests—tensile strength (Rm); conventional yield point (Rp); elongation (A) and Vickers hardness (V), correlated with the operating time and the media type (fresh steam and secondarily super-heated steam) for the most sensitive element of a pipeline, namely the elbow. The results of changes in strength properties during operation are presented in the form of graphs of the analyzed material feature vs. operating time in the range from zero hours (for a new material) to 300,000 h, taking into account the impact of random and systematic disturbances within the adopted tolerance limits. It has been found that because of the R2 factor and significance level in the t-Student test for regression and correlation coefficients, exponential, hyperbolic and quadratic models are best fitted to empirical points. Based on the tensile strength results (Rm), it has been found that the forecast time of the steam pipeline ranges from 193,400 to 258,300 h. Taking the yield strength (Rp) into account, it has been ascertained that the time ranges from 225,000 to 293,000 h, and for the working time forecast of steam pipelines based on Vickers hardness results, it ranges from 192,100 to 246,800 h.

Reliability Evaluation of Grid Connected Roof Top Solar Photovoltaic Power Plant Using Markov Model Approach

Reliability of the solar power plant depends on its performance and economics factor compared to the conventional fueled power plants. In this paper, reliability performance assessment of grid connected roof top solar photovoltaic power plant (GCRTSPP) are presented at site location 12.0950° N, 75.5451° E) by considering various operating factors of subcomponents of solar photovoltaic panels, diode, capacitor and controller using Markov model approach. Critical stress factors are identified and are improved upon to enhance the system reliability. The performance of the solar photovoltaic array and the subcomponent of GCRTSPP have been examined with the sensitivity results. Also, sensitivity analysis of failure rate of these components with respect to stress factors is performed and critical stress factors are identified. Pareto analysis as a tool, reliability studies of grid connected solar photovoltaic system have been carried out to compute the highest failure rate of component. It is found that electronic controller and diode is more sensitive item compared to solar photovoltaic panels and capacitor. These components failure rate sensitivity analysis with respect to stress factors is performed. The reliability on standalone and grid connected photovoltaic system also compared. The critical stress factors of the components are identified. Artificial neural network (ANN) and machine learning programme (MLP) proposed for further study.

Probabilistic model of assessment of operational reliability of AIS onshore station as sub-system of vessels in conditions of E-Navigation concept implementation

Probabilistic model of assessment of operational reliability of AIS onshore station as sub-system of vessels in conditions of E-Navigation concept implementation

Assessment of operational reliability of quarry excavator-dump truck complexes

The method proposed in the article is based on the mathematical apparatus for quantitative assessment of the reliability of majority schemes of structural redundancy of transport processes, which provide the availability and usage of several backup delivery channels in the transport process in case of any malfunction. The principle of multi-channel haulage is commonly used in quarries for transportation of overburden and minerals from benches by dump trucks, when excavators and dump trucks performing cyclic operations function as a single excavator-dump truck complex. This pattern of work significantly increases the likelihood of fulfilling the daily plan for transporting rock mass due to the redistribution of dump trucks between mining and overburden excavators in the event of failure of one or more units of mining and handling equipment.The reliability of excavator-dump truck complexes is assessed in three stages: initial data collection for mathematical modeling of excavator-dump truck complex performance; solving the problem of optimizing the distribution of dump trucks between excavators, ensuring maximum productivity of the excavator-dump truck complex; assessment of the reliability of its work depending on the probability of fulfilling the daily plan for the transportation of rock mass.The proposed method is implemented as part of a computer program and makes it possible to automate the operational management of the process of transporting rock mass in a quarry using a mobile application. The developed guidelines can be used for any quarries with automobile transport, regardless of the type of mineral extracted, the mining method, the loading pattern, the capacity of the excavation and loading equipment fleet, and the capacity of operated dump trucks.

Development of Energy Benchmarks for Office Buildings Using the National Energy Consumption Database

In an effort to improve the energy efficiency of existing buildings, it is necessary to first evaluate the energy performance of those buildings. Since it is difficult to obtain detailed information on existing buildings, the challenge is how to conduct reliable energy performance assessments with this limited information. As a result, many countries have adopted evaluation systems based on measured energy consumption data for existing buildings. This study aims to analyze the building energy consumption and characteristics using Korea’s national building database and provide an energy performance benchmark for continuous management of the energy performance of existing buildings. We analyzed the relationship between the basic statistical characteristics of the information collected from the national integrated energy database and energy consumption. The total floor area was found to be closely related to energy consumption, and various regression analysis methods were applied and compared to develop a benchmark to explain the trends of energy consumption according to the increase in total floor area. Finally, the developed benchmarks were used to evaluate energy consumption and examine the feasibility of the benchmarks.

Determining accurate area of vulnerability for reliable voltage sag assessment considering wind turbine ride-through capability

The accurate calculation of area of vulnerability (AOV) and expected sag frequency (ESF), which in turn leads to reliable assessment of voltage sag performance, is very useful in establishing efficient planning for the mitigation of voltage sags at buses where sensitive equipment are installed. This paper proposes a method for accurate determination of AOV for fault induced voltage sags. To do so, different mathematical solvers are used to solve the residual voltage equations in order to find the accurate critical points on lines partially included in AOV. Moreover, a new iteration-based technique is developed to calculate ESF with high degree of accuracy considering low voltage ride-through requirement for wind turbines. The proposed technique can efficiently and accurately assess voltage sag performance at wind turbine connection points and provides reliable long-term performance evaluation of tendency and degree of voltage sag occurrences expected to cause wind turbine disconnection. The proposed method is applied on IEEE 30-bus test system penetrated with eight wind turbines and a practical network of Iran equipped with sensitive loads.

Using convolutional neural networks for hygrothermal predictions to extrapolate to other external climates

When simulating the hygrothermal behaviour of a building component, many uncertainties are involved (e.g. exterior and interior climates, material properties, configuration geometry). In contrast to a deterministic assessment, a probabilistic analysis enables including these uncertainties, and thus allows a more reliable assessment of the hygrothermal performance. This easily involves thousands of simulations, which easily becomes computationally inhibitive. To overcome this time-efficiency issue, a convolutional neural network, a type of metamodel mimicking the original model with a strongly reduced calculation time, can replace the hygrothermal model. This was proven in a previous study for a massive masonry wall, where variability of exterior and interior climate, brick material properties and wall geometry was included. However, the question rises whether it is possible to train the network on a limited number of climates, and afterwards use the network to predict accurately for other climates as well. This paper thus focuses on this aspect, and results show that, as long as the range of the new climate data falls within the range of the climate data the network was trained on, the network is able to predict accurately for new climates as well.

Probability density evolution analysis of stochastic seismic response of structures with dependent random parameters

Performance evaluation and reliability assessment of real-world structures under earthquakes is of paramount importance. Generally, different mechanical property parameters of a structure are usually not independent, nor completely dependent, but partly dependent or correlated. Therefore, how to reasonably characterize such partial dependency and whether such partial dependency real matters in the stochastic response and reliability of structures under earthquakes are crucial issues. For this purpose, in the present paper, a novel physically-guided data-driven methodology of capturing the correlation configuration of basic random variables and the probability density evolution method are synthesized. The physically-guided data-driven methodology is firstly outlined. In this methodology, the underlying physical mechanism between dependent random variables is firstly involved to establish a random function model, and then the available observed data are adopted to identify the parameters in this model. What is more, physical constraints are also revealed for the initial modulus of elasticity and compressive strength of concrete. The probability density evolution method is then adopted, and the point selection by minimizing the GF-discrepancy is adjusted according to the correlation configuration and physical constraints. A reinforced concrete frame structure subjected to earthquake input is studied. It is found that when the structure is in the strongly nonlinear stage, the correlation configuration has considerable effects on the standard deviation of the stochastic responses, by a factor of nearly 2. In addition, whether the mechanical parameters in different floors are independent or not has great effects on the stochastic responses as well. Problems to be further studied are also outlined.

Lifecycle operational reliability assessment of water distribution networks based on the probability density evolution method

In this study, a lifecycle operational reliability assessment framework for water distribution networks (WDNs) is proposed on the basis of the probability density evolution method (PDEM). The occurrence models of daily accidents are fitted using the maintenance data provided by a local water administration sector. For a given accident, two types of accidents (e.g., leaks and bursts) are distinguished in different occurrence probabilities and simulated in various ways. The pipe deterioration process in the lifecycle is reflected by incorporating the time-dependent pipe roughness model. Considering various randomness in the model, PDEM, a newly proposed and developed method for a stochastic system, is used to evaluate the lifecycle operational reliability of WDNs. The framework is demonstrated using an actual WDN, and the nodal reliabilities in the lifecycle are obtained. Comparisons of the operational reliabilities of all nodes calculated via the PDEM and Monte Carlo simulations prove that PDEM is an accurate and highly efficient method.

Skin-conformal, soft material-enabled bioelectronic system with minimized motion artifacts for reliable health and performance monitoring of athletes

Recent advances in biosensors, bioelectronics, and system integration allow the development of wristband-type devices for health and performance monitoring of athletes. Although these devices provide adequate sensing outputs, they suffer from signal loss due to improper contact of a rigid sensor with the skin. In addition, when a rubber band tightly secures the sensor to the skin, the gap between sensor and skin causes inevitable motion artifacts, resulting in corrupted data. Consequently, the rigidity and bulky form factor of the existing devices are not suitable for a practical use since athletes typically go through strenuous activities during training and matches. Here, we introduce a soft, wearable flexible hybrid electronics (WFHE) with integrated flexible sensors and circuits in an ultrathin, low-modulus elastomer. The thin-film bioelectronic system avoids the use of bulky, rigid sensors, while providing negligible mechanical and thermal burdens to the wearer. Enabling conformal contact between sensor and skin minimizes undesired motion artifacts. A set of computational and experimental studies of soft materials, flexible mechanics, and system packaging provides key fundamental design factors for a comfortable, reliable, waterproof bioelectronic system. Skin conformal WFHE with sparse signal reconstruction enables reliable, continuous monitoring of photoplethysmogram, heart rate, and activities of athletes. Development of a quantitative analysis between impact force and impact velocity extracted from motion acceleration provides an objective assessment of an athletic punching force. Collectively, this study shows the first demonstration of a wireless, soft, thin-film electronics for a real-time, reliable assessment of athletic health and performance.

Experimental investigation of single blade loads by captive model tests in pure oblique flow

Maneuvering motion is a critical off-design condition experienced by the propeller during realistic operations. Failures of the propulsive system, loss of efficiency and modification of the propeller side effects (propeller-hull induced pressure and noise) are the undesired consequences of these working conditions. Free running model tests, still representing the primary approach for a reliable performance assessment, requires facilities and devices that are not commonly affordable; alternatively, rectilinear towing tank can be used for maneuvering investigations by static or dynamic tests and can be a valid alternative to investigate propeller performance in off-design. On these basis, in this paper the propeller performance in maneuvering conditions is investigated by means of oblique towing tests in case of a twin screw model equipped with a novel set-up for single blade loads measurements.In the experiments, the drift angle and the advance speed of the model varied systematically, to focus on the relation between propeller operating conditions and loads. Moreover, the averaged and periodic blade loads are compared, in terms of the equivalent drift angle, to the measurements obtained by free running model tests, in order to demonstrate the reliability of pure oblique flow tests for the preliminary quantification of the off-design loads developed by the propeller.

Performance Monitoring via Functional Near Infrared Spectroscopy for Virtual Reality Based Basic Life Support Training.

The use of serious game tools in training of medical professions is steadily growing. However, there is a lack of reliable performance assessment methods to evaluate learner’s outcome. The aim of this study is to determine whether functional near infrared spectroscopy (fNIRS) can be used as an additional tool for assessing the learning outcome of virtual reality (VR) based learning modules. The hypothesis is that together with an improvement in learning outcome there would be a decrease in the participants’ cerebral oxygenation levels measured from the prefrontal cortex (PFC) region and an increase of participants’ serious gaming results. To test this hypothesis, the subjects were recruited and divided into four groups with different combinations of prior virtual reality experience and prior Basic Life Support (BLS) knowledge levels. A VR based serious gaming module for teaching BLS and 16-Channel fNIRS system were used to collect data from the participants. Results of the participants’ scores acquired from the serious gaming module were compared with fNIRS measures on the initial and final training sessions. Kruskal Wallis test was run to determine any significant statistical difference between the groups and Mann–Whitney U test was utilized to obtain pairwise comparisons. BLS training scores of the participants acquired from VR based serious game’s the learning management system and fNIRS measurements revealed decrease in use of resources from the PFC, but increase in behavioral performance. Importantly, brain-based measures can provide an additional quantitative metric for trainee’s expertise development and can assist the medical simulation instructors.

Assessment of Reliability and Quality Performance using the Impact of Shortfall Generation Capacity Index on Power Systems

This paper presents a novel practical technique developed and applied for assessment of reliability and quality in real-life power systems. System-wide integrated performance indices are capable of addressing and revealing areas of deficiencies and bottlenecks as well as shortfalls in the composite generation-transmission-demand structure of large-scale power grids. The new evaluation methodology offers a general and comprehensive framework to assess the harmony and compatibility of generation capacities, transmission and required demand in a power system. The technique used in this paper is evaluated by the shortfall generation capacity index which is based on three dimensions introduced to represent the relationship between certain system generation capacity and demand. Also, practical applications to the Saudi power grid are presented for demonstration purposes.

Reliable long-term performance assessment of commercial photovoltaic modules tested under field conditions over 5 years

Due to their scalability and global abundance of sunlight, photovoltaic panels are a promising option as a renewable energy source. Implementation of photovoltaic technologies on a large scale requires a careful business-case assessment, aimed at the selection of the technological option most appropriate for the local conditions in terms of long-term performance. For this purpose, five types of modules representative of current options on the market were tested under field conditions for five years at a test facility in Germany. The degradation rates of module performance were computed from the obtained photovoltaic power normalized by both recorded and modeled solar irradiance. The results emphasize the relevance of using modeled irradiance data in addition to recorded solar irradiance in order to extract reliable degradation rates. The available methodological tools still have to be adapted to every dataset for the most accurate result. Eventually, robust degradation rates were extracted from experimental power data, based on modeled clear-sky irradiance, and a combination of aggregation and regression strategies. The results show distinctive degradation behaviors of the five available commercial photovoltaic modules in response to the local conditions.