Performance Assessment Method Research Articles

An Assessment Method of Sealing Performance and Stress Intensity Factors at Crack Tip of Subsea Connector Metal Sealing Rings

Subsea connectors are of a critical part for the sealing of subsea production systems. The working environment makes cracks initiate easily on subsea connector sealing rings. In order to ensure the safety and reliability of the sealing rings, it is necessary to study the crack’s influence on them. In this study, the main parameters that may influence stress intensity factors at crack tip are discussed. The sealing requirements of the subsea connector metal sealing rings were conducted. A finite element model was established to obtain the maximum equivalent stress and maximum equivalent plastic strain of crack-free sealing ring. Meanwhile, the influence of crack depths, crack positions, and crack angles on the sealing performance in preload and operating states was simulated through changing XFEM crack’s parameters in ABAQUS software, as well as their influence on stress intensity factors at the crack tip. The research shows that although the cracks have little effect on the sealing performance of sealing rings in the early stage, the stress intensity factors increase with the crack depths. Long-term use leads to crack propagation, structure breakage, and sealing failure. The research results are of some reference value for improving the safety and reliability of subsea connectors in practical engineering applications.

Multi-platform simulation of reinforced concrete structures under impact loading

This study presents a multi-platform simulation method for performance assessment of reinforced concrete (RC) structures subjected to impact loading. The method is demonstrated through the integration of two finite element analysis packages, LS-DYNA and VecTor2, to take advantage of the explicit integration scheme and various contact types in LS-DYNA for impact analysis and the Modified Compression Field Theory (MCFT) in VecTor2 for reliable modelling of concrete structures, especially for shear-related failure. The communication between the two programs is enabled through a standardized communication protocol which allows data exchange during the simulation in a seamless manner. When applying this method to vehicle/ship collision analysis, one major challenge is the modelling of the impact interface between the three-dimensional LS-DYNA model and the two-dimensional VecTor2 model. Therefore, a coupling method for models with different dimensions is proposed and also justified through a few verification examples. The method is also applied to a vehicle-bridge head-on collision problem and it is found that the conventional modelling method based on a single LS-DYNA model could overestimate the crashworthiness of the RC structures.

Performance assessment method for roof-integrated TSSCs

This paper proposes a performance assessment method for roof-integrated two-stage solar concentrators (TSSCs) as thermo-photovoltaic systems using a parametric modeling approach. The productivity of TSSCs does not only depend on system design, but also on building geometries ensuring good solar gains. Further, the integration process of TSSCs with buildings is complex and needs to address concerns from multiple domains. The proposed approach intends to be a rigorous yet adaptable method to inform decision making where multiple stakeholders from building and energy domains are involved, and promote the use of TSSCs as sustainable, building-integrated energy production technology. Our method contributes to engineering the TSSC designs in relation to the building design. The method allows generating various design alternatives by controlling a set of input parameters for buildings (i.e., roof type and slope, and building orientation) and TSCCs (i.e., design type, geometric ratio, and separation distance between mirrors). The method applies a parametric modeling approach that enables the generation of 20,736 design options of building and TSSCs in a collaborative manner, by featuring various combinations of the design inputs. We validated the method in an illustrative case study of a single-family house (California) for a number of performance indicators related to building and TSSCs e.g., the covered roof area, the annual average load match index (av.LMI), and the number of solar cells. We further perform a sensitivity analysis to find the relative importance of design parameters and discuss our results in terms of maximizing av.LMI and minimizing the number of cells and covered roof area. The illustrative application represents that the method enables designers to adopt a performance-based design approach to simultaneously design both; building, and TSSCs that can be integrated with the building, and searches for the most appropriate solutions i.e., building ensuring good solar potential, and TSSC designs offering high av.LMI, covering less building’s (roof) area, and utilizing less solar cells. Hence, the method serves as a foundation for future employing generative design approaches for building-integrated TSSCs in the early design stages to support informed decision making processes with a focus on solar integration, and energy planning and transition for self-sufficient and sustainable buildings.

Improvements of simplified hourly models for the energy assessment of buildings: The application of EN ISO 52016 in Italy

The Italian National Annex (NA) to EN ISO 52016-1 is aimed at improving the simplified hourly calculation method of the building thermal performance assessment by introducing different modelling options. The present work deepens the influence of the Italian NA improved method on the thermal energy needs for heating and cooling of a residential building-type in two different climate zones. In particular, the Italian NA improved options are applied one-at-the-time, and their effect is evaluated in comparison with the EN ISO 52016-1 standard method. The use of solar angle and time dependent correction factors for the total solar energy transmittance of glazing proved to be the most sensitive modelling option, among those analysed. Negligible variations were instead reported for the other tested options.

Psychiatrists Feel the Financial Pinch of MIPS

Psychiatrists Feel the Financial Pinch of MIPS

Multi-platform simulation of infilled shear-critical reinforced concrete frames subjected to earthquake excitations

This paper proposes a multi-platform simulation method for the seismic performance assessment of masonry infilled reinforced concrete (RC) frames, especially for those that, due to inadequate reinforcing details, tend to undergo shear failure during an earthquake. The multi-platform method is based on a micro–macro modeling approach in which a detailed finite element model of the RC frame is incorporated with a strut model of the infill wall. It exploits the strut model to increase its computational efficiency and the finite element model based on the modified compression field theory to capture the nonlinear behaviour of the RC frame. The proposed method is validated against previously tested frames subjected to lateral loads, and its advantages over the conventional strut models are demonstrated through both quasi-static and dynamic analyses.

IMPA versus Cloud Analysis and IDA: Different Methods to Evaluate Structural Seismic Fragility

Well-known methods for seismic performance assessment, such as incremental dynamic analysis (IDA), multi-stripes analysis (MSA) and the cloud method, involve nonlinear response time-history analyses to characterize the relationship between the chosen damage measure versus intensity measure. Over the past two decades, many authors have proposed simplified procedures or nonlinear static approaches to develop fragility. In these procedures, the capacity of the system is evaluated by nonlinear static procedures (i.e., the capacity spectrum method (CSM), the N2 method, modal pushover analysis (MPA)) and the demand is derived by response spectra. In addition to the familiar ones, incremental modal pushover analysis (IMPA) is a novel nonlinear static procedure proposed in recent years, and it is used in this research to present an IM-based fragility estimation. The accuracy and effectiveness of different methods to assess vulnerability are investigated by comparing fragility curves derived by MPA-based cloud analysis, IMPA and cloud analysis against IDA. The comparison gives valuable insights on the influence of scaling on different sets of records; however, a more extended validation is needed to confirm the obtained results and draw more general conclusions. Results arise from two relatively small bins of record motions differing by ranges of Joyner-Boore distance and scattered in a range of magnitude are presented.

Developing methods of evaluating online data for internet business promotion

Rapid development of the information technologies leads to a continuous replenishment of the Internet marketing tools. The problem of introducing a new mechanism for evaluating results for improving the effectiveness of promoting goods and services in the Internet environment can be attributed to the most important ones. Gaps in comprehension of the problem in relation to web analytics in Russia have been indicated. Studying the main theoretical basis for changing the approach to marketing measures was conducted to increase the efficiency of businesses in the Russian Internet market. The direction of web analytics development in Russia has been defined. The Russian researches are found to focus on the practical part. There are considered the methods of obtaining economic data from the web analytics systems. The problems of business development in the Internet environment in Russia have been defined. As a result, it has been inferred that the existing methods of performance assessment are not applicable. The classification of performance evaluation parameters has been developed. The parameters were divided into 3 levels, depending on the metrics. The first level is associated with presentations, clicks, expenses on advertisements, the second level - with conversion and its cost, the third - with return on investment (ROI). The parameters were divided into the status and economic aspects, depending on their impact on the brand and on the financial condition of the business. According to the developed classification, the process of forming a marketing event was arranged; it is based on definition of the effectiveness level, which the company can achieve. There has been created and illustrated the sequence of events to evaluate the effectiveness of business in the Internet environment.

An innovative variable target time method for probabilistic-based seismic performance assessment of multi-storey buildings

Incremental dynamic analysis is one of the most widely used methods to develop fragility curves due to its ability to deal with various inherent uncertainties in the prediction of earthquake recurrence and characteristics. The dependence of the results to the selected ground motion records, uncertainties associated with the selection of appropriate earthquake input records and high computational costs are among the challenges limit the practical applications of this method. In this study, an innovative variable target time (VTT) method is developed based on the concept of endurance time (ET) analysis for structural reliability assessment of 3D multi-storey structures. A novel low-computational cost process is proposed to develop the database of desired statistical population and estimate the probabilities for constant hazard levels (EDP-based method) by taking into account the uncertainties in the frequency content of the input earthquakes. To verify the accuracy of the outcomes, the results are compared with the fragility curves derived based on different damage levels (IM-based method) and Incremental Dynamic Analysis (IDA) for moment-resisting steel and tunnel-from concrete 3D structures with 5- and 10-storeys. The results indicate that the proposed method is capable of providing highly accurate probabilistic models for structural performance under different levels of earthquake intensity. For the selected steel moment-resisting structures, the maximum difference in the reliability results obtained by the two methods of analysis for the Immediate Occupancy (IO), Life Safety (LS), and Collapse Prevention (CP) performance levels under the Design Basis Earthquake (DBE) and the Maximum Considered Earthquake (MCE) are around 2, 7 and 5%, respectively. Similarly, the reliability results for the 3D tunnel-from concrete structures show around 6, 7, and 6% errors between the two analysis methods for the IO, LS and CP performance levels, respectively. The proposed method reduces the computational costs of the IDA-based methods by 80%, and hence, can be considered as a suitable alternative for the conventional methods to develop fragility curves of 3D structures.

Practical control performance assessment method using Hurst exponents and crossover phenomena

This paper proposes a new Hurst exponent-based method to evaluate the performance of control loops by estimating Minimum Variance Index (MVI). Incorrect estimation of time delays dramatically affects MVI-based performance assessment accuracy. The main advantage of the proposed method over existing methods is that it only requires routine operation data, without any need for prior information of the system model parameters and time delays. Hence, this method is more suitable to be applied on various industrial control processes. Recently, crossover phenomena have been reported in the graphs used to estimate the Hurst exponent of different control signals, which complicate deciding the Hurst exponents values. To address this problem, the crossover phenomenon is investigated for control signals, then the Hurst index is modified based on it. The proposed method is successfully used to assess performance of various types of control loops such as the cascade loop and verified through simulation results.

Performance assessment for non-Gaussian systems by minimum entropy control and dynamic data reconciliation

Control performance of the industrial process is inevitably influenced by the measurement noises and non-Gaussian external disturbances. This influence has not been fully considered in the traditional variance-based controller design. To reduce the influence, a novel scheme that can enhance the control performance is developed by integrating dynamic data reconciliation (DDR) into minimum rational entropy control (MREC) in this paper. Firstly, the influence of measurement noise is fully considered, and a novel DDR method is proposed to deal with the minimum entropy control (MEC) process such that the influence of measurement noise can be reduced, and the control performance will be improved. Then, based on the DDR-MREC performance index, a benchmark for evaluating the control performance of non-Gaussian systems is established. Finally, the proposed control performance assessment (CPA) method is applied to the wind energy conversion system and compared with the CPA method based on DDR-minimum variance control. The experimental results have demonstrated that the proposed new method is more effective than existing works.

A bran-new performance evaluation model of coal mill based on GA-IFCM-IDHGF method

Adopting a more scientific and precise assessment method to evaluate the current running performance of coal mills in practice work is essential to maintain the security and reliability of the coal-fired power plant. However, traditional assessment methods have ignored an important problem that the importance among variables varies with the current operation data of coal mill, which has a serious influence on performance evaluation of coal mill. In this paper, a bran-new GA-IFCM-IDHGF assessment method is proposed. Genetic algorithm (GA) is first applied to optimize initial parameters, which is fundamental and significant step to obtain more accurate the number of clusters. Secondly, intuitionistic fuzzy clustering model (IFCM) is adopted to identify the running modes of the coal mill. According to the Delphi, analytic hierarchy process, gray relations analysis and fuzzy integrated evaluation (DHGF), the security range of variables under the normal observed samples from different running modes is acquired, which is helpful to determine whether the current operation data is normal data. Subsequently, an improved Delphi, analytic hierarchy process, gray relations analysis and fuzzy integrated evaluation (IDHGF) method is used to assess the current running performance of coal mill under the abnormal monitoring data. The performance of the proposed performance assessment method is verified through its application in a self-defined step fault system and an actual industrial cases of coal mill. Compared with the traditional methods, the experimental results demonstrate the effectiveness of the proposed method.

Prospective and retrospective performance assessment of Advanced Driver Assistance Systems in imminent collision scenarios: the CMI-Vr approach

Structured abstractIntroductionProspective and retrospective performance assessment of Advanced Driver Assistance Systems (ADASs) is fundamental to pilot future enhancements for active safety devices. In critical road scenarios between two vehicles where ADAS activation enables collision mitigation only, currently available assessment methodologies rely on the reconstruction of the impact phase consequent to the specific intervention on braking and steering: the velocity change sustained by the vehicle in the collision (Delta V) is retrieved, so that IR decrease for the vehicle occupants can be obtained by appropriate Injury Risk (IR) models. However, information regarding the ADAS performance is available only after the impact phase reconstruction and not just as when the criticality occurs in the pre-impact phase: the best braking and steering alternative cannot be immediately envisaged, since a direct correlation lacks between the braking/steering intervention and IR.MethodThis work highlights an ADAS performance assessment method based on the disaggregation of Delta V in the two pre-impact parameters closing velocity at collision (V_r) and impact eccentricity, represented by the Crash Momentum Index (CMI). Such a disaggregation leads to the determination of IR based solely on impact configuration between the vehicles, without directly considering the impact phase. The performance of diverse ADASs in terms of intervention logic are directly comparable based on the resulting impact configuration, associated with a single coordinate in the CMI-V_r plane and a sole IR value as a consequence.ResultsThe CMI-V_r approach is employable for both purposes of prospective and retrospective performance assessment of ADAS devices. To illustrate the advantages of the methodology, a solution for prospective assessment based on the CMI-V_r plane is initially proposed and applied to case studies: this provides direct suggestions regarding the most appropriate interventions on braking and steering for IR minimization, fundamental in the tuning or development phase of an ADAS. A method for retrospective assessment is ultimately contextualized in the EuroNCAP “Car-to-Car Rear moving” test for an Inter-Urban Autonomous Emergency Braking system, a device implemented on a significant portion of the circulating fleet.ConclusionsBased on the evidenced highlights, it is demonstrated that the approach provides complementary information compared to well-established performance assessment methodologies in all stages of an ADAS life cycle, by suggesting a direct physical connection in the pre-impact phase between the possible ADAS interventions and the foreseeable injury outcomes.

Validity of Performance Assessment Methods in Elite Paracanoeists.

The problem of valid and reliable research methods in paralympic sports seems of great significance, thus the aim of this study was to evaluate the validity of the Wingate test (WAnT) in assessment of anaerobic performance in elite paracanoeists competing in 200 m races. Seven paralympic athletes (32.6 ± 7.76 years), medal winners and finalists of the Paralympic Games, World and European Championships, as well as World Cups were examined. The evaluations were conducted during a competition which was held at the paralympic distance of 200 m, and included the WAnT for upper limbs and the anaerobic threshold test (ATT). Correlations of selected indices of mechanical work and power in the WAnT, as well as anaerobic threshold (AT) power, with the time recorded during the competition were used to determine indices which affected paracanoeing performance. The results indicated strong negative correlations with time achieved in the competition between peak power and total work in the WAnT, and AT power (R = -0.796 p = 0.032; R = -0.882 p = 0.009; R = -0.900 p < 0.001, respectively). The research confirmed the validity of the WAnT for the upper limbs to assess the performance level of paracanoeists. It may be concluded that the WAnT and ATT may be used for monitoring performance during the paralympic 200 m race.

Performance assessment method of dynamic process based on SFA-GPR

A dynamic process performance assessment method based on slow feature analysis and Gaussian process regression (SFA-GPR) is proposed to capture more complete feature information from industrial process data with dynamic characteristics, thus improving the accuracy of the assessment model. First, different binary number performance labels are used to categorize data setsin terms of performance grades, and the process feature subspace is extracted using the slow feature analysis algorithm, followed by the establishment of the Gaussian process regression offline model between the feature subspace and the performance labels. During the online assessment, in conjunction with the proposed performance assessment strategy, performance grades and the current process’s operating status are determined based on the performance label of sample data obtained by the assessment model. Finally, the method is used to assess the online performance of the debutanizer and cracking furnace in the ethylene plant. The findings indicate that the method has a higher level of assessment accuracy.

Multi-objective optimization for probabilistic performance-based design of buildings using FEMA P-58 methodology

This research presents an automated performance-based optimal design process by integrating a multi-objective optimization algorithm and a comprehensive probabilistic performance assessment method. This process is used to provide a set of design options that comply with the minimum code requirements and are optimal in terms of both initial cost and mean annual repair cost. The FEMA P-58 methodology is utilized as a modern performance-based methodology to determine the various performance measures such as repair costs, repair time, casualty rates, environmental impacts, and unsafe placarding for the design alternatives. To account for uncertainties in the magnitude and intensity of future earthquakes, the time-based assessment, and to account for inherent uncertainties affecting seismic performance, the Monte Carlo procedure is performed in accordance with FEMA P-58 guideline. The optimization process is carried out using a well-known multi-objective optimization algorithm called NSGA-II for three example office buildings with 3-, 6- and 9-story steel moment frame structures. For each building, a detailed performance model including a set of fragility functions for the structural and non-structural components as well as contents typically present in the building is considered. Three optimal design options are selected from the Pareto front set obtained for each building based on different optimization objectives. They are compared with each other and with the other design alternatives in terms of various performance metrics under different ground motion intensities. The contribution of structural components as well as drift-, acceleration- and velocity-sensitive non-structural components to the repair costs of these optimal designs is investigated. It is shown that drift-sensitive nonstructural components have the largest contribution to the repair costs of optimal structures. The contribution of these components in earthquake events with a 29% probability of exceedance in 50 years (29%/50 yrs) is on average about 71%, which decreases to 55% with increasing seismic intensity to 3%/50 yrs.

Evaluating Ports Environmental Performance based on the Fuzzy Analytic Hierarchy Process (FAHP)

Appropriate environmental performance is considered one of the most important indicators in the sustainable development of organizations and industries. Evaluating the environmental performance in ports as one of the two main parts of the maritime transport system is of particular importance. Therefore, the current study was designed and conducted to develop a method for evaluating the environmental performance of ports based on the fuzzy analytic hierarchy process (FAHP). In the present study, 22 experts in the field of environment and marine sciences were selected in 2020. Firstly, various studies on the factors affecting the environmental performance of ports were reviewed. Secondly, a questionnaire was designed to assess ports’ environmental performance. Thirdly, this questionnaire was developed using the Delphi technique. Finally, by determining the weight of each parameter, the method of environmental performance assessment in ports was developed based on the FAHP. The final normalized weights for six environmental performance factors including reactive and proactive performance, sustainability, socio-cultural, economic, and governance were estimated 0.202, 0.241, 0.226, 0.070, 0.080, and 0.182. Additionally, it was found that each of the parameters had a different weight and impact on these factors. The highest and lowest impact on the environmental performance index belonged to environmental risk assessment (weight=0.217), cultural effects, and justice (weight=0.107). In the current study, a new method was developed for evaluating the environmental performance of ports based on six factors, 32 parameters, and FAHP. Therefore, this method may provide an effective step in reducing environmental impacts and improving the level of environmental performance in ports to achieve the goal of green port.

Generative Adversarial Networks for synthetic wellbore data: Expert perception vs mathematical metrics

We study the applicability of Generative Adversarial Networks (GANs) for generating the synthetic data related to well construction and geological characterisation of the near-wellbore area. We focus on 1D mud logs (time-series) and 2D core images. GANs are known to have difficulties with their quality assessment in general. Moreover, generic GAN’s performance assessment methods cannot be suitable for the petroleum domain. A petroleum engineer expects the GANs to generate data with specific physical and geological properties, not just a colourful picture. We have trained over 40 GAN models and generated synthetic data with them. Then, we have involved several experts to analyse the generated data in order to address the question of whether it is possible to substitute human analysis with a mathematical metric. We found that some quantitative mathematical metrics can represent our experts’ perceptions. In particular, we show that for 2D core images, Mode Score metric with standard inception v3 model is the best proxy for all considered qualitative metrics of expert’s perception according to the Kendall correlation (for two qualitative metrics the correlation is strong, the absolute value is above 0.7, and for other two it is moderate, the absolute value is between 0.5 and 0.7); for mud logs time-series, Mode Score and Frechet Inception Distance with the InceptionTime model provide the strong (above 0.7) correlation with objects reconstruction quality, whereas Inception Score has almost strong correlation (with Kendalls’-tau coefficient 0.69) with experts’ perception of objects generation quality. With these results, experts manual annotation of generated objects during GAN model selection process can be reduced to calculating the corresponding quantitative metrics.

Seismic performance assessment of concrete bridges with traffic-induced fatigue damage

This paper proposes a universal analytical method for the seismic performance assessment of concrete bridges with initial fatigue damage caused by traffic loads. Load modeling is firstly performed, and random models of traffic load and seismic loads are established using stochastic processes. Subsequently, the theoretical approach for deterministic seismic response analysis of concrete bridges with initial traffic-induced fatigue damage is established by a combination of the micro-meso stochastic damage constitutive models and the finite element numerical method. In this manner, the seismic damage and failure mechanism of concrete bridges with initial fatigue damage can be elucidated. Further, considering the randomness of loads, the stochastic seismic analytical framework of concrete bridges damaged by traffic loads is put forward, in accordance with the probability space partition-based random load combination method and the probability density evolution theory. In such a way, the seismic reliability and safety of existing damaged concrete bridges can be well evaluated. Finally, a railway concrete bridge, as a practical engineering application, is investigated to validate the applicability of the proposed method.

Structural performance assessment considering both observed and latent environmental and operational conditions: A Gaussian process and probability principal component analysis method

Structural faults like damage and degradations will cause changes in structure response data. Performance assessment can be conducted by investigating such changes. In real implementations however, structural responses are affected by environmental and operational variations (EOVs) as well. Such variation should be well captured by the assessment model when detecting structural changes. It should be noted that not all EOVs can be measured by the monitoring system. When both observed and latent EOVs have significant effects on the monitored structural responses, these two effects should be considered properly. Furthermore, uncertainties can be significant for the monitoring data since loads and EOVs cannot be directly controlled under working conditions. To address these problems, this work proposes a performance assessment method considering both observed and latent EOVs. A Gaussian process is used to model the functional behaviour between structural response and observed EOVs whilst principal component analysis is used to eliminate the effect of latent EOVs. These two methods are combined using a Bayesian formulation and the effect of both observed and latent EOVs are modelled. The associated model parameters are inferred through probability density functions to account for the uncertainties. A synthetic data example is presented to validate the proposed method. It is also applied to the monitoring data of a long-span cable-stayed bridge with different damage scenarios considered, illustrating its capability of real implementations in structural health monitoring.