Benchmark System Research Articles

Experimental analysis of the TRC benchmark system.

The Tribomechadynamics Research Challenge (TRC) was a blind prediction of the vibration behavior of a thin plate clamped on two sides using bolted joints. Specifically, the natural frequency and damping ratio of the fundamental bending mode were requested as function of the amplitude, starting from the linear regime until high levels, where both frictional contact and nonlinear bending-stretching coupling become relevant. The predictions were confronted with experimental results in a companion paper; the present article addresses the experimental analysis of this benchmark system. Amplitude-dependent modal data was obtained from phase resonance and response controlled tests. In the phase resonance test, a resonant phase lag between response and excitation was ensured via feedback control, and the excitation level was step-wise in-/decreased. In the response controlled test, the response level was kept fixed via feedback control. An original variant of response controlled testing is proposed: Instead of a fixed frequency interval, a fixed phase interval is analyzed. This way, the high excitation levels required outside resonance, which could activate unwanted exciter nonlinearity, are avoided. The consistency of the nonlinear modal testing methods, with each other, and with conventional linear tests at low amplitudes, is carefully analyzed. Comparisons of nonlinear-mode based predictions with direct frequency response curve measurements (at fixed excitation level) serve as additional cross-validation. Overall, these measures have enabled a high confidence in the acquired modal data. The different sources of the remaining uncertainty were further analyzed. A low reassembly-variability but a moderate time-variability were identified. The latter is attributed to some thermal sensitivity of the system. Two nominally identical plates were analyzed, which both have an appreciable initial curvature, and a significant effect on the vibration behavior was found depending on whether the plate is aligned/misaligned with the support structure. Further, a 1:2 nonlinear modal interaction with the first torsion mode was observed, which only occurs in the aligned configurations. All data (time series of nonlinear tests; linear modal properties) and post-processing methods are publicly available.

Optimal nonlinear system identification using fractional delay second-order volterra system

The aim of this work is to design a fractional delay second order Volterra filter that takes a discrete time sequence as input and its output is as close as possible to the output of a given nonlinear unknown system which may have higher degree nonlinearities in the least square sense. The basic reason for such a design is that rather than including higher than second degree nonlinearities in the designed system, we use the fractional delay degrees of freedom to approximate the given system. The advantage is in terms of obtaining a better approximation of the given nonlinear system than is possible by using only integer delays ( since we are giving more degrees of freedom via the fractional delays ) and simultaneously it does not require to incorporate higher degree nonlinearities than two. This work hinges around the fact that if the input signal is a decimated version of another signal by a factor of M, then fractional delays can be regarded as delays by integers less than M. Using the well known formula for calculating the discrete time Fourier transform ( TFT ) of a decimated signal, we then arrive at an expression for the DTFT of the output of a fractional delay system in terms of the unknown first and second order Volterra system coefficients and the fractional delays. The final energy function to be minimized is the norm square of the difference between the DTFT of the given output and the DTFT of the output of the fractional delay system. Minimization over the filter coefficients is a linear problem and thus the final problem is to minimize a highly nonlinear function of the fractional delays which is accomplished using search techniques like the gradient-search and nature inspired optimization algorithms. The effectiveness of the proposed method is demonstrated using two nonlinear benchmark systems tested with five different input signals. The accuracy of the stated models using the globally convergent metaheuristic, cuckoo-search algorithm ( CSA ) are observed to be superior when compared with other techniques such as real-coded genetic algorithm ( RGA ), particle swarm optimization ( PSO ) and gradient-search ( GS ) methods. Finally, statistical analysis affirms the potential of the proposed designs for its successful implementation.

Optimal nonlinear system identification using fractional delay second-order volterra system

The aim of this work is to design a fractional delay second order Volterra filter that takes a discrete time sequence as input and its output is as close as possible to the output of a given nonlinear unknown system which may have higher degree nonlinearities in the least square sense. The basic reason for such a design is that rather than including higher than second degree nonlinearities in the designed system, we use the fractional delay degrees of freedom to approximate the given system. The advantage is in terms of obtaining a better approximation of the given nonlinear system than is possible by using only integer delays U+0028 since we are giving more degrees of freedom via the fractional delays U+0029 and simultaneously it does not require to incorporate higher degree nonlinearities than two. This work hinges around the fact that if the input signal is a decimated version of another signal by a factor of M, then fractional delays can be regarded as delays by integers less than M. Using the well known formula for calculating the discrete time Fourier transform U+0028 DTFT U+0029 of a decimated signal, we then arrive at an expression for the DTFT of the output of a fractional delay system in terms of the unknown first and second order Volterra system coefficients and the fractional delays. The final energy function to be minimized is the norm square of the difference between the DTFT of the given output and the DTFT of the output of the fractional delay system. Minimization over the filter coefficients is a linear problem and thus the final problem is to minimize a highly nonlinear function of the fractional delays which is accomplished using search techniques like the gradient-search and nature inspired optimization algorithms. The effectiveness of the proposed method is demonstrated using two nonlinear benchmark systems tested with five different input signals. The accuracy of the stated models using the globally convergent metaheuristic, cuckoo-search algorithm U+0028 CSA U+0029 are observed to be superior when compared with other techniques such as real-coded genetic algorithm U+0028 RGA U+0029, particle swarm optimization U+0028 PSO U+0029 and gradient-search U+0028 GS U+0029 methods. Finally, statistical analysis affirms the potential of the proposed designs for its successful implementation.

Machine learning molecular dynamics simulations of liquid methanol

As the simplest hydrogen-bonded alcohol, liquid methanol has attracted intensive experimental and theoretical interest. However, theoretical investigations on this system have primarily relied on empirical intermolecular force fields or ab initio molecular dynamics with semilocal density functionals. Inspired by recent studies on bulk water using increasingly accurate machine learning force fields, we report a new machine learning force field for liquid methanol with a hybrid functional revPBE0 plus dispersion correction. Molecular dynamics simulations on this machine learning force field are orders of magnitude faster than ab initio molecular dynamics simulations, yielding the radial distribution functions, self-diffusion coefficients, and hydrogen bond network properties with very small statistical errors. The resulting structural and dynamical properties are compared well with the experimental data, demonstrating the superior accuracy of this machine learning force field. This work represents a successful step toward a first-principles description of this benchmark system and showcases the general applicability of the machine learning force field in studying liquid systems.

Correlated proton dynamics in hydrogen bonding networks: the benchmark case of 3-hydroxyglutaric acid.

Proton and hydrogen-bonded networks sustain a broad range of structural and charge transfer processes in supramolecular materials. The modelling of proton dynamics is however challenging and demands insights from prototypical benchmark systems. The intramolecular H-bonding networks induced by either protonation or deprotonation of 3-hydroxyglutaric acid provide intriguing case studies of correlated proton dynamics. The vibrational signatures associated with the fluxional proton bonding and its coupling with the hydroxyglutaric backbone are investigated here with infrared action ion spectroscopy experiments and Born-Oppenheimer molecular dynamics (BOMD) computations. Despite the formally similar symmetry of protonated and deprotonated hydroxyglutaric acid, the relative proton affinities of the oxygen centers of the carboxylic and carboxylate groups with respect to that of the central hydroxyl group lead to distinct proton dynamics. In the protonated acid, a tautomeric arrangement of the type HOCO·[HOH]+·OCOH is preferred with the proton binding tighter to the central hydroxyl moiety and the electronic density being shared between the two nearly symmetric H-bonds with the carboxylic end groups. In the deprotonated acid, the asymmetric [OCO]-·HO·HOCO configuration is more stable, with a stronger H-bonding on the bare carboxylate end. Both systems display active backbone dynamics and concerted Grothuss-like proton motions, leading to diffuse band structures in their vibrational spectra. These features are accurately reproduced by the BOMD computations.

Benchmarking DFT-based excited-state methods for intermolecular charge-transfer excitations.

Intermolecular charge-transfer is a highly important process in biology and energy-conversion applications where generated charges need to be transported over several moieties. However, its theoretical description is challenging since the high accuracy required to describe these excited states must be accessible for calculations on large molecular systems. In this benchmark study, we identify reliable low-scaling computational methods for this task. Our reference results were obtained from highly accurate wavefunction calculations that restrict the size of the benchmark systems. However, the density-functional theory based methods that we identify as accurate can be applied to much larger systems. Since targeting charge-transfer states requires the unambiguous classification of an excited state, we first analyze several charge-transfer descriptors for their reliability concerning intermolecular charge-transfer and single out the charge-transfer distance calculated based on the variation of electron density upon excitation (DCT) as an optimal choice for our purposes. In general, best results are obtained for orbital-optimized methods and among those, the maximum overlap method proved to be the most numerically stable variant when using the initial MOs as reference orbitals. Favorable error cancellation with optimally-tuned range-separated hybrid functionals and a rather small basis set can provide an economical yet reasonable wavefunction when using time-dependent density functional theory, which provides relevant information about the excited-state character to be used in the orbital-optimized methods. The qualitative agreement makes these fast calculations attractive for high-throughput screening applications.

Hierarchical Stochastic Frequency Constrained Micro-Market Model for Isolated Microgrids

With the developments of isolated microgrids (IMGs) and prosumers in remote areas, energy trading has emerged as a critical aspect of IMGs. However, the lack of an upstream network and the low inertia of the system may threaten the secure operation of these networks. This paper proposes a Micro-Market (lM) model for IMGs that includes a precise hierarchical control structure. To address the IMGs low inertia and high intermittency of renewable energy sources (RES), the proposed lM manages the active-reactive power and schedules primary and secondary active reserves to maintain the frequency within in a predefined range. Additionally, a bidirectional linearized AC power flow is established to schedule the reactive reserve and the proposed model is formulated as a two-stage stochastic mixed-integer linear problem (MILP) to maximize social welfare (SW) over the next 24 hours. To validate the effectiveness of the proposed model, the lM is tested on an IMG based on a CIGRE medium-voltage benchmark system, and different operational cases are simulated. The results demonstrate that the proposed model, which takes into account hierarchical control levels and technical issues of the IMG, is a cost-effective way to maximize social welfare while ensuring the secure operation of the IMG.

Synchrophasor-Based Out-of-Step Prediction in Large Grids

Out-of-step (OOS) condition is a potential problem in the power system and uncontrolled islanding is one of the severe consequences of out-of-step condition which leads to cascaded tripping of the system. To avoid this undesired cascaded tripping, early prediction of out-of-step condition is essential before losing the synchronization of generators and between the system areas. Controlled islanding is the last emergency action that can be taken by splitting the system intentionally into coherent islands. Conventionally, OOS condition has been detected with impedance-based measurement techniques which have their own limitations. With the implementation of a wide-area measurement system with synchrophasor measurement units (PMUs) in the power system, it is now possible to measure the bus voltage angle at a much faster rate than with SCADA. In this paper, synchrophasor-based bus voltage angle measurement has been used for early prediction of OOS condition in power systems. A new algorithm has been formulated for both generator and tie lines based on the trajectory of first and second derivatives of the bus voltage phase angle for early detection of OOS condition. The prediction speed of proposed method is found to be between 5% and 70% of time to OOS, after disturbance clearance. The proposed algorithm has been mathematically formulated and evaluated with three benchmark systems in real-time simulation environment with an OPAL-RT real-time simulator and a HYPERSIM platform.

Resampling schemes in population annealing: Numerical and theoretical results.

The population annealing algorithm is a population-based equilibrium version of simulated annealing. It can sample thermodynamic systems with rough free-energy landscapes more efficiently than standard Markov chain Monte Carlo alone. A number of parameters can be fine-tuned to improve the performance of the population annealing algorithm. While there is some numerical and theoretical work on most of these parameters, there appears to be a gap in the literature concerning the role of resampling in population annealing which this work attempts to close. The two-dimensional Ising model is used as a benchmarking system for this study. At first various resampling methods are implemented and numerically compared. In a second part the exact solution of the Ising model is utilized to create an artificial population annealing setting with effectively infinite Monte Carlo updates at each temperature. This limit is first performed on finite population sizes and subsequently extended to infinite populations. This allows us to look at resampling isolated from other parameters. Many results are expected to generalize to other systems.

Formulating a quadratic frequency nadir constraint in unit commitment based on energy conservation law

This paper proposes a quadratic formulation for the frequency nadir constraint (FNC) based on the energy conservation law. Incorporating the formulation into the unit commitment (UC) model, a mixed-integer quadratically constrained programming (MIQCP) model for frequency nadir constrained UC can be obtained, which can be solved efficiently by the MIQCP solver. The distinct feature of the formulation is that it considers the inertia difference among generators, which has a significant effect on the on/off schedule of generators. Besides, the formulation has a clear physical meaning and does not have to be linearized. The test on the WSCC 3-machine 9-bus benchmark system validates the accuracy of the formulation, and the case studies on a New England 10-machine 39-bus system confirm the effectiveness of the proposed formulation.

Electrodeposited Ni-Based Catalysts for the Oxygen Evolution Reaction

Alkaline water electrolysis is one of the most mature technologies for producing green hydrogen. However, there still are possibilities to enhance this process by using better electrocatalysts for the kinetically limited oxygen evolution reaction (OER). While there are several existing methods for catalyst synthesis, such as spray coating, coprecipitation and hydrothermal synthesis, they face challenges of either versatility or scalability.[1,2] In this regard, electrodeposition is a promising catalyst synthesis method, due to its excellent process control and ease of scalability.In this work, electrodeposition is used to prepare nickel-based catalysts as a benchmark system. These catalysts are deposited on expanded Ni-mesh supports. Initially, the deposition parameters are optimized to obtain uniform Ni deposits, which provide reproducible activity measurements. Herein, we observe that the deposited Ni catalysts exhibit better OER activities than the Ni mesh support, most likely due to the evolution of a pyramidal morphology with an increased surface area (Fig. 1). The optimized deposition parameters are further used to deposit different Ni-based alloys such as Ni-Fe and Ni-Co, by adding the respective ionized metal species to the Ni electrolyte. The microstructure and composition of these catalysts is analyzed using material characterization techniques like scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDX). Finally, the OER activity and long-term stability of the deposited catalysts is evaluated in an in-house developed electrochemical beaker cell at elevated concentration, temperature, and current densities (30 wt.% KOH, 80 °C, up to 1 A/cm2). The results obtained for the different catalysts are compared to understand the correlation of the catalyst structure and composition with their electrochemical OER performance under industrial conditions. Bibliography [1] Lu Xunyu et al.; Nature Communications; DOI: 10.1038/ncomms7616[2] Zuraya Angeles-Olvera et al.; Energies; DOI: 10.3390/en15051609 Figure 1

Fast free energy estimates from λ-dynamics with bias-updated Gibbs sampling

Relative binding free energy calculations have become an integral computational tool for lead optimization in structure-based drug design. Classical alchemical methods, including free energy perturbation or thermodynamic integration, compute relative free energy differences by transforming one molecule into another. However, these methods have high operational costs due to the need to perform many pairwise perturbations independently. To reduce costs and accelerate molecular design workflows, we present a method called λ-dynamics with bias-updated Gibbs sampling. This method uses dynamic biases to continuously sample between multiple ligand analogues collectively within a single simulation. We show that many relative binding free energies can be determined quickly with this approach without compromising accuracy. For five benchmark systems, agreement to experiment is high, with root mean square errors near or below 1.0 kcal mol−1. Free energy results are consistent with other computational approaches and within statistical noise of both methods (0.4 kcal mol−1 or less). Notably, large efficiency gains over thermodynamic integration of 18–66-fold for small perturbations and 100–200-fold for whole aromatic ring substitutions are observed. The rapid determination of relative binding free energies will enable larger chemical spaces to be more readily explored and structure-based drug design to be accelerated.

P-Bifurcation Analysis of a Quarter-Car Model With Inerter-Based Pendulum Vibration Absorber: A Wiener Path Integration Approach

Abstract In this theoretical study, a recently developed inerter-based pendulum vibration absorber (IPVA) coupled with energy harvesting capabilities is applied to the quarter car model with class C road conditions (ISO 8608). The impact of varying the pendulum length parameter on power harvesting, ride comfort (sprung mass acceleration), and road handling is investigated. It is discovered that P-bifurcation of the probability density function (PDF), can simultaneously occur with enhanced output power (40% improvements), low sprung mass acceleration (60% improvements), and better road handling (60% improvements) when compared with the linear benchmark system. To predict this bifurcation, a Wiener path integration (WPI) method coupled with curvature checking is developed for the PDF. An efficient bifurcation detection algorithm is developed which leads to the prediction of monomodal, bimodal, and rotation PDF regions in the noise intensity-electrical damping plane. Using Monte Carlo simulations (MCS), the performance metrics were then compared against the optimal linear benchmark for varying driving speed on a class F road while varying the electrical damping so that the system is at or near P-bifurcation. Energy transfer into the electrical domain and power harvested are shown to be up to 43% and 20% higher than for the optimized linear system, respectively. Electrical efficiency considerations show that generator selection is also a factor. Ride comfort and road handling still saw improvements of at least 59%. Finally, the new algorithm effectively reduces an exhaustive MCS for various parameter configurations when qualitative changes in the PDF are linked to performance.

A benchmark white dwarf–ultracool dwarf wide field binary

ABSTRACT We present the discovery and multiwavelength characterization of VVV J1438-6158 AB, a new field wide-binary system consisting of a $4.6^{+5.5}_{-2.4}~{\rm Gyr}$ and $T_{\rm eff} = 9500\pm 125~\mathrm{ K}$ DA white dwarf (WD) and a $T_{\rm eff} = 2400\pm 50~\mathrm{ K}$ M8 ultracool dwarf (UCD). The projected separation of the system is $a = 1236.73~{\rm au}$ ($\sim 13.8\, \mathrm{ arcsec}$), and although along the line of sight towards the Scorpius–Centaurus stellar association, VVV J1438-6158 AB is likely to be a field star, from a kinematic 6D probabilistic analysis. We estimated the physical and dynamical parameters of both components via interpolations with theoretical models and evolutionary tracks, which allowed us to retrieve a mass of $0.62\pm 0.18~\mathrm{ M}_\odot$ for the WD, and a mass of $98.5\pm 6.2~\mathrm{ M}_{\rm Jup}$ ($\sim 0.094\pm 0.006~\mathrm{ M}_\odot$) for the UCD. The radii of the two components were also estimated at $0.01309\pm 0.0003~\mathrm{ R}_{\odot }$ and $1.22\pm 0.05~\mathrm{ R}_{\rm Jup}$, respectively. VVV J1438-6158 AB stands out as a benchmark system for comprehending the evolution of WDs and low-mass companions given its status as one of the most widely separated WD+UCD systems known to date, which likely indicates that both components may have evolved independently of each other, and also being characterized by a large-mass ratio ($q = 0.15\pm 0.04$), which likely indicates a formation pathway similar to that of stellar binary systems.

Design of a decentralized control law for variable area coupled tank systems using H∞ complimentary sensitivity function

AbstractThis paper proposes a novel graphical approach to control the liquid levels of the different variable area coupled tank systems using a decentralized controller. The coupled tank systems are common benchmark systems that consist of two tanks interconnected with each other. The primary goal is to maintain the liquid level in the tank at the desired set point by controlling the flow rate. This is attained with a decentralized method wherein the controller values are obtained from the plane. Besides, the robust criteria is enforced to guarantee the robustness. The proposed controller design approach aims to improve the performance of the system in terms of disturbance rejection and tracking. The decentralized control structure uses a distributed control strategy, thereby reducing the computational load which leads to improving the control performance. The loop interactions are minimized with decouplers. Furthermore, first‐order plus dead‐time (FOPDT) models are derived for each of the decoupled subsystems. Besides, the servo and regulatory responses of the controller are verified with input and output disturbances. Additionally, the response of the controller to system uncertainties and parameter variations is also studied. The simulation results demonstrate the effectiveness and robustness of the proposed approach.

Esg2go: A Method to Reduce Bias, Improve Coherence, and Increase Practicality of ESG Rating and Reporting

Rating agencies that assess a company’s environmental, social, and corporate governance (ESG) impact have been subject to public and academic scrutiny due to divergent and often biased rating outcomes. Concurrently, an evolving regulatory environment mandates publicly listed companies to report on ESG and climate emissions, taking into account supply chain risks as well. As a result, small and medium-sized enterprises (SMEs) are increasingly asked as suppliers to present a credible sustainability certificate. The esg2go rating and reporting system aims at improving the credibility and practicality of corporate sustainability assessment. It was jointly developed with its users and relevant stakeholders and is based on a calibrated benchmarking system from verifiable data. The rating method enables the measurement and comparison of sector- and firm size-specific sustainability performance. Its underlying adaptive parametrization is derived from a coherent and pragmatic definition of SME sustainability as the ‘ability to co-exist’. Our data analyses indicate that our scoring function is able to minimize bias and deliver a fair comparability between SMEs. We conclude that esg2go represents a pragmatic and innovative approach to enhance the fairness and accuracy of corporate sustainability assessment.

A ROBUST AUTONOMOUS VEHICULAR NAVIGATION SYSTEM USING RIMU-BASED INS/GNSS INTEGRATED SCHEME

Abstract. The application of the INS/GNSS integrated system is widespread in vehicle navigation. However, in certain complex urban areas, achieving accurate positioning for autonomous vehicles at level 3 and beyond presents a challenge. Moreover, ensuring the continuous availability of the navigation system is crucial for maintaining vehicle safety under all circumstances. Consequently, the specifications of the Inertial Measurement Unit (IMU), which have a direct correlation with cost, dominate the performance of the navigation system in environments where GNSS signals are denied or challenging. To implement level 3 autonomous vehicles, a strategy based on redundant IMUs (RIMU) is employed to not only enhance accuracy and availability but reduce the overall cost of the navigation system. This research mainly focuses on the development of a robust autonomous vehicular navigation system by designing an integrated algorithm for the low-cost RIMU and GNSS receiver within the INS/GNSS integration scheme. The positioning performance is analyzed by using a reference system and a benchmark system in the open sky, GNSS challenging, and GNSS outage scenarios.

Sustainability performance of rural municipalities in Germany

BackgroundSustainable rural development entails efforts to enhance the well-being of rural communities while safeguarding natural resources for future generations. The thorough examination of sustainable rural development is still scarce but nevertheless crucial, as it enables to reveal the various challenges and remaining potentials in rural areas, to identify key stakeholders and their respective roles in promoting sustainable rural development, and to determine the best practices for attaining set goals along the various sustainability dimensions considered. Germany has implemented a range of policies, initiatives, and programs to foster sustainable development, extending its efforts to also encompass rural areas. This study assesses the sustainability performance of rural municipalities in Germany, proposing a novel and comprehensive sustainability benchmarking system. For this purpose, the performance of selected rural municipalities along the ecological, social, economic, and technological dimensions is examined.ResultsBased on the systematic implementation of methodological stages, a rigorous literature review process, a systematic indicator selection, and stringent filtering criteria, the selected indicators of our study cover environmental, energy, quality of life, economic, and technological aspects. These indicators enable to efficiently and effectively measure, compare, and evaluate the sustainability performance of rural municipalities. After normalization, weighting, and aggregation of the considered indicators, the performance is visualized in radar charts. Radar charts are handy for comparing a larger number of variables and displaying them in compact and comprehensible form in a single chart. Finally, the overall relative sustainability performance of the selected rural municipalities in Germany is compared based on an aggregated single score. The adopted methodology of aggregating indicators enables us to assess the sustainability performance of municipalities as well as to highlight variations among them.ConclusionMost databases and sustainable development reports are updated only every couple of years and often do not report the performance of small rural municipalities but only larger (more urban) ones. By conducting a detailed analysis of these specific cases, we can identify key challenges and opportunities unique to rural communities and develop targeted strategies for a more sustainable development. Adding digitalization as a technological value indicator makes our approach more comprehensive than comparable others, and accounts for the important new sustainability dimension of societal transition. This study contributes to the existing literature by proposing a novel sustainability benchmarking system specifically tailored for rural areas. From a practical standpoint, the developed sustainability benchmarking system offers a practical tool for rural municipalities to assess and monitor their sustainability performance and to reflect on variations among them. The identified dimensions and indicators can guide the development of targeted strategies and interventions aimed at enhancing sustainability in rural communities. Finally, policymakers can utilize the benchmarking results to design policies, (incentive) programs, and initiatives that address the specific sustainability challenges faced by rural municipalities and account for limitations in the local potentials.

A New Productivity Benchmarking System Connected to Well-designed Labour Apprenticeship Framework for Construction Projects

This study primarily identifies the knowledge gaps that must be filled to apply conceptualised methods for rising and benchmarking productivity levels of various construction operational tasks. Accordingly, this study intended to evaluate labour productivity in relation to labour performance using potential apprenticeship instruments and systems. Comprehensive literature analysis and expert consultations were carried out to create a new mechanism with the collection of potential models, methods and systems connected to labour training, performance evaluation and productivity measurements. A total of 23 construction projects in Sri Lanka employed the created approach methodically. The results demonstrate the precise patterns of substantial shifts in labour productivity and performance index values, which have sparked new conceptual mechanisms for construction project planning methods. The outcomes demonstrate that the suggested approach can be used in a way that is reliable, generalisable, productive and sustainable. The study provides project managers, planners and engineers with a new road map and helpful techniques to raise the standard for measuring labour productivity levels across a variety of jobs. The overall study outcomes strengthen the chain relationship among the training elements, labour skills, performance and productivity. Though the study findings were limited to the construction industry and Sri Lankan context, the study outcomes are expected to make a significant impact on the current practices of various industry sectors in many developing countries for achieving higher productivity levels in work operations. This paper discusses some more implications and future scopes of the study elaborately.

Nonpilot directional protection of a microgrid

AbstractProtection of an islanded inverter‐based microgrid is challenging because of variable and small fault current contribution of inverter‐based resources (IBR) and the absence of sequence currents. This paper proposes a fast and robust nonpilot directional protection scheme to address this challenge. This scheme relies on support vector machines (SVM) and the harmonic current injection capability of IBRs. Examining the harmonic currents measured by a relay during a fault shows that harmonic currents have similar magnitudes but different orientation under forward and reverse faults. Additionally, harmonic currents have similar orientation but different magnitudes under forward faults at different locations along the protected line. Using this, six SVMs are trained for each relay, given that there are three main types of faults (three‐phase‐to‐ground, line‐to‐line, and line‐to‐ground): three as directional elements and three as zone detection elements. A fault is detected and classified by the undervoltage element of a relay. Then, the measured harmonic currents are routed to the appropriate directionality and zone detection SVMs to facilitate proper relay coordination. The performance of the proposed method is evaluated on the CIGRE North American MV distribution benchmark system under various types of contingency scenarios using PSCAD/EMTDC software.