Performance Evaluation Framework Research Articles

A Review on Harnessing Renewable Energy Synergies for Achieving Urban Net-Zero Energy Buildings: Technologies, Performance Evaluation, Policies, Challenges, and Future Direction

As urbanization continues to accelerate globally, energy demand in cities is reaching unprecedented levels, contributing to greenhouse gas emissions. In response, the concept of net-zero energy building (NZEB) is becoming a sustainable solution for urban energy needs. NZEB aims to achieve a net-zero energy footprint by balancing the energy it consumes with the energy it produces, primarily from renewable energy (RE) sources. This comprehensive literature review-based study explores the role of RE synergies in the context of urban NZEBs, including discussions on definition and development of NZEBs, RE-synergies for achieving NZEBs, sustainable trends and clusters of NZEBs, climate change impacts on NZEBs, their performance evaluation, policy and regulatory frameworks, and challenges and possible solutions related to NZEBs. It has been identified that while customizing NZEB definitions to align with regional energy supply and demand is important, the same is highly dependent on building architectural and micro-climate features. The assessment of climate change effects and NZEB practices should involve evaluating building energy equilibrium, occupant comfort, and interactions with the energy grid. There are still some technical, policy, and socio-economic challenges that need more attention to provide comprehensive solutions for further enhancing the sustainable development/performance of NZEBs and achieving their goal.

Developing a Performance Evaluation Framework Structural Model for Educational Metaverse

Developing a Performance Evaluation Framework Structural Model for Educational Metaverse

An integrated climate-based daylight performance evaluation framework for indoor arenas' roof system

Daylight environment plays a crucial role in indoor arenas' comfort and energy performance, characterized by their large spans and large spaces. Design parameters of roof systems in these arenas are essential for enhancing the daylight within competition halls. However, due to the complexity of spatial archetypes in these halls and the unique characteristics of freeform surfaces, more research is needed on the interplay between roof system design parameters and daylight performance. Rapid evaluation of daylight performance in competition halls during the design phase remains a challenge. This study proposes a climate-based evaluation framework for assessing daylight performance in indoor arenas and integrates an efficient practical and research workflow using Rhino + Grasshopper in conjunction with Python.Further, based on this framework and workflow, controlled variable simulation experiments were conducted to explore the relationships between external design conditions, such as climate (represented by three typical climatic zones) and seating capacity, and roof system design parameters, including roof form, redundant height, orientation, skylight form, distribution, and skylight-to-floor ratio (SFR), with time-series, climate-based daylight performance indicators. To integrate the critical factors affecting indoor lighting environments in arenas - illuminance potential, glare evaluation, and uniformity assessment - this study selected Continuous Daylight Autonomy (cDA), Useful Daylight Illuminance (UDI), and Glare Autonomy (GA) as performance indicators, supplemented by two time-series climate indicators specifically for evaluating illuminance uniformity in indoor arenas: “Uniformity Autonomy (UA) “and “Uniformity Variance Autonomy (UVA) ". Statistical analysis of five performance indicators across 860 experimental models in seven groups shows that different design conditions and parameters affect the optimal range of SFR. The significance of the impact of various design parameters varies across different performance indicators. There is a strong correlation between cDA, UDI, and GA, while UA and UVA effectively supplement the evaluation of the first three indicators.

Evaluation of operational efficiency and performance for a water treatment plant

The current study presents a comprehensive analysis of the operational efficiency and performance evaluation of the Hazelmere Water Treatment Plant over the period from 1999 to 2018. By focusing on the removal efficiencies of few parameters including iron (Fe), turbidity, and E. coli, the study provides valuable insights into the plant's ability to treat water effectively and produce high-quality drinking water. Leveraging data analysis techniques and computational tools, the research also explores the forecasting of water quality parameters beyond the study period, enhancing predictive capabilities for monitoring and managing water quality in the future. The Hazelmere Water Treatment Plant (WTP) has a daily capacity of 75 Ml it supplies water to the surroundings. Its intricate treatment process, featuring chemical dosing, clarification, filtration, and disinfection, operates harmoniously. The plant consistently exceeded global standards. Effluent turbidity consistently met stringent World Health Organization/South African National (WHO/SANS) discharge standards at ≤ 1 NTU. The turbidity removal efficiencies ranged from 65.88 to 99.61 % on average over the period from 1999 to 2018. Iron removal also adhered to WHO/SANS criteria, registering ≤ 2 mg/L. The removal efficiencies have ranged from 82 to 99% on average for the same period. Most impressively, E. coli removal efficiency maintained a flawless 100 % for the same period, indicating a pathogen-free effluent throughout the period, with a steady annual average of 0 MPN/100 m, some challenges have occurred including the contamination of the freshwater from the dam, the limited data availability, and issues related to sustainability and compliance. These challenges were overcome by using advanced tools for data analyses such as R package, developing a performance evaluation framework and establishing recommendations for the adoption of innovative technologies, and improvements in operation and maintenance practices. Overall, this study makes significant contributions to the field of wastewater treatment and water quality management, advancing our understanding of sustainable water resource management and environmental protection.

HLPerf: Demystifying the Performance of HLS-based Graph Neural Networks with Dataflow Architectures

The development of FPGA-based applications using HLS is fraught with performance pitfalls and large design space exploration times. These issues are exacerbated when the application is complicated and its performance is dependent on the input data set, as is often the case with graph neural network approaches to machine learning. Here, we introduce HLPerf, an open-source, simulation-based performance evaluation framework for dataflow architectures that both supports early exploration of the design space and shortens the performance evaluation cycle. We apply the methodology to GNNHLS, an HLS-based graph neural network benchmark containing 6 commonly used graph neural network models and 4 datasets with distinct topologies and scales. The results show that HLPerf achieves over 10 000 × average simulation acceleration relative to RTL simulation and over 400 × acceleration relative to state-of-the-art cycle-accurate tools at the cost of 7% mean error rate relative to actual FPGA implementation performance. This acceleration positions HLPerf as a viable component in the design cycle.

A holistic approach for performance evaluation of wastewater treatment plants: integrating grey water footprint and life cycle impact assessment.

Wastewater treatment plants (WWTPs) have positive and negative impacts on the environment. Therefore, life cycle impact assessment (LCIA) can provide a more holistic framework for performance evaluation than the conventional approach. This study added water footprint (WF) to LCIA and defined ϕ index for accounting for the damage ratio of carbon footprint (CF) to WF. The application of these innovations was verified by comparing the performance of 26 WWTPs. These facilities are located in four different climates in Iran, serve between 1,900 and 980,000 people, and have treatment units like activated sludge, aerated lagoon, and stabilization pond. Here, grey water footprint (GWF) calculated the ecological impacts through typical pollutants. Blue water footprint (BWF) included the productive impacts of wastewater reuse, and CF estimated CO2 emissions from WWTPs. Results showed that GWF was the leading factor. ϕ was 4-7.5% and the average WF of WWTPs was 0.6 m3/ca, which reduced 84%, to 0.1 m³/ca, through wastewater reuse. Here, wastewater treatment and reuse in larger WWTPs, particularly with activated sludge had lower cumulative impacts. Since this method takes more items than the conventional approach, it is recommended for integrated evaluation of WWTPs, mainly in areas where the water-energy nexus is a paradigm for sustainable development.

Smart Ports in Industry 4.0: A Systematic Literature Review

Background: Information and communication technologies (ICT) have introduced “smart” concepts across industries, including ports. Smart ports, leveraging IoT, cybersecurity, and cloud computing, are trending in maritime operations. They optimize data for informed decision-making, cutting costs, enhancing efficiency, mitigating risks, and fostering growth. Methods: To consolidate knowledge in this area, we are conducting a systematic literature review and meta-analysis using the PRISMA framework. Our goal is to synthesize existing insights, minimize biases, increase reliability, and effectively communicate our findings. To address the research needs mentioned, the current study focuses on implementing a systematic literature review (SLR). Results: The goals of this review are: (i) to present and describe the main categories and themes within the research topic, and (ii) to identify research gaps that will aid future research. Key findings include the identification and classification of current literature trends in the smart port performance evaluation framework and the examination of fundamental themes discussed within this area of research. Conclusions: In our review, we emphasize the smart port concept, clarifying its common interpretations amid the industry 4.0 revolution. We discuss recent advancements in emerging technologies and identify key challenges driving researchers’ exploration of the evolving smart port landscape.

Enhanced group decision-making framework for financial performance evaluation of high-tech enterprises under interval neutrosophic environment

The financial performance of enterprises has always been the key to their survival and development, especially for high-tech enterprises. Evaluating the financial performance of high-tech enterprises is beneficial for the management department to accurately understand the financial situation of the enterprise, timely identify financial problems, and study solutions based on this; On the other hand, the scientific evaluation of enterprise performance also provides useful assistance for other stakeholders such as the government, creditors, and enterprise employees to exercise their rights. With the development of the times and the progress of society, high-tech enterprises have developed rapidly. Studying the financial performance of high-tech enterprises has important theoretical and practical significance. The financial performance evaluation of high-tech enterprises is a classical MAGDM problems. Recently, the TODIM (TODIM) and (grey relational analysis) GRA technique has been employed to cope with MAGDM issues. The interval neutrosophic sets (INSs) are employed as a tool for characterizing uncertain information during the financial performance evaluation of high-tech enterprises. In this manuscript, the interval neutrosophic number TODIM-GRA (INN-TODIM-GRA) technique is implemented to solve the MAGDM under INSs. In the end, a numerical case study for financial performance evaluation of high-tech enterprises is employed to validate the proposed technique.

A Novel Data Envelopment Analysis Framework for Performance Evaluation of European Road Transport Systems

The role of transportation is becoming increasingly important in the world economy, and road transport in particular plays a very important role in all types of transportation. For this reason, it is extremely important to monitor its performance regularly. Very often, this is done using Data Envelopment Analysis (DEA) performance evaluation models, and consequently, there are numerous articles in the literature on DEA evaluation of road transport systems. In this study, we first summarise these articles and classify them according to different characteristics (environmental, safety, economic, energy). Finally, we use them as a basis for developing a novel DEA framework, which is used for the evaluation of the efficiency and ranking of road transport systems that also takes into account undesirable outputs, i.e. environmental and safety outputs. As a case study, we evaluate 28 European countries from technical, safety and environmental aspects. The CCR and SBM models are used to evaluate the efficiency of these countries for the last two years of published data. The results show that Denmark ranks first and Cyprus last for both years. It was also found that safety efficiency is generally rated lower than other criteria. Finally, the results and reasons for the efficiency and inefficiency of specific decision-making units, i.e. countries, are discussed.

Evaluating the energy-exergy-economy-environment performance of the biomass-photovoltaic-hydrogen integrated energy system based on hybrid multi-criterion decision-making model

Integrating biomass, photovoltaic, and other renewable energy sources for hydrogen production can form a biomass-photovoltaic-hydrogen integrated energy system (BPH-IES). The system features multi-energy storage and joint supply, as well as cascaded utilization, is a promising co-generation way to meet the system's electricity, heat and hydrogen needs, and has significant energy-exergy-economy-environment (4E) performance. Therefore, scientific and effective evaluation of the BPH-IES is an important prerequisite for promoting its development. Firstly, by analyzing the structure of the BPH-IES system, this paper constructs a comprehensive performance evaluation index system of the system from the 4E dimensions. Secondly, a hybrid multi-criterion decision making (MCDM) framework for the 4E comprehensive performance evaluation of the BPH-IES is constructed, in which the anti-entropy weighting method is used to determine the objective weights, the subjective weights are determined by the decision making trial and evaluation laboratory method improved by intuitionistic fuzzy sets, and the final combined weighting results are obtained based on a game-theoretic method that the objective and subjective weights' heterogeneity can be fully minimized. The grey-relation-analysis-based measurement alternatives and ranking according to the compromise solution method is proposed to determine the ranking of alternatives. This paper selected 8 typical BPH-IES cases for 4E evaluation analysis. The results showed that energy performance is the core dimension that reflects the 4E performance of the system, and system's economy indicators such as energy supply income and energy supply cost will also significantly affect the system's 4E performance. Therefore, the 4E performance of BPH-IES can be effectively improved by expanding the system's demand and supply scale and increasing the system's installed proportion of clean energy and hydrogen penetration. Finally, the ranking consistency test, Leave-One-Out analysis and sample separation test demonstrate that the developed hybrid MCDM can ensure robustness meanwhile improve the decision efficiency.

Investigating the spatial effect of operational performance in China’s regional tourism system

For the healthy development of regional tourism systems, performance evaluation is vital for regulators so that they can determine the source of inefficiency to enhance systems’ competitiveness through a series of systematic policy plans. Past research has recognized the importance of network collaboration in the tourism sector but has focused mainly on the separate stages of performance (e.g., hotels), with limited discussion on how sectoral interactions can be distilled into collaborative models. Consequently, this paper intends to construct a more comprehensive performance evaluation framework for the Chinese regional tourism system that not only focuses on network interactions and dynamic features among stages but also considers spatial dependency to enhance the accuracy of performance evaluation. Using the panel data of 30 provincial-administrative regions on China’s tourism industry from 2012 to 2016, the operating performance of each regional tourism system and its tourist stages are measured by the SBM-DNDEA model. Furthermore, the spatial effect of regional tourism system operational performance and its influencing factors are investigated via the Tobit spatial Durbin model. The results showed that the operational performance of the Chinese regional tourism system was still relatively low, with the attraction stage performing the best, and there were significant differences among the four economic zones. The strength of traffic convenience had a significant positive effect on the operational performance of the local tourism system, but fiscal expenditure on environmental management also had a negative spillover effect on the surrounding region. The urbanization level had not only a significant positive effect on local areas but also a positive spillover effect on adjacent areas. Interregional development may also affect the performance of attractions, highlighting the importance of systematic integration and allocation of resources for tourism development.

Spatial performance evaluation and optimization of integrated aboveground and underground spaces in urban commercial complexes

ABSTRACT As urban areas experience economic growth and expansion, the development scale and intensity of urban commercial complexes have notably increased. Integrating aboveground and underground spaces enhances the vitality of the latter, thereby improving land development efficiency. However, these complexes encounter challenges, including disconnections in design, leading to poor underground continuity and suboptimal economic outcomes. Existing research predominantly discusses individual factors influencing aboveground and underground space integration, lacking a comprehensive assessment framework for integrated urban commercial complex development. This study introduces a spatial performance evaluation framework encompassing four key dimensions: functional spaces, transportation systems, public spaces, and landscape environments. Representative cases of three complex types – courtyard-style complexes with inward aggregation, courtyard-style complexes with outward radiation, and inner street-style complexes – are selected for spatial performance evaluation. Findings indicate that public space and transportation system performance exert the most significant impact, while functional space and landscape environment performance have a relatively smaller influence. Considering the distinctive characteristics of integrated aboveground and underground development, we propose prioritizing public spaces and transportation systems, emphasizing functional spaces, and advocating a balanced approach to landscape environments. Specific optimization directions for selected case studies are outlined. The study’s conclusions guide the scientific development of integrated spaces in urban commercial complexes, ultimately enhancing overall efficiency.

An integrated group decision making framework for business performance evaluation of performing arts enterprises with probabilistic hesitant fuzzy IDOCRIW-MOOSRA method

There is a lack of domestic and foreign research on the evaluation and improvement strategies of business performance of performing arts enterprises, especially in the context of the “restructuring” of cultural groups in China. Most of the existing studies are distributed in bulk, not only lacking in theoretical depth, but also lacking in systematization to a certain extent, which shows that the existing studies have not fully formed a mature and valuable theoretical system. The business performance evaluation of performing arts enterprises is a multiple attributes group decision making (MAGDM). This paper constructs a novel probabilistic hesitant fuzzy Multi-Objective Optimization Simple Ratio Analysis (PHF-MOOSRA) model based on the integrated determination of objective criteria weights (IDOCRIW) under the probabilistic hesitant fuzzy sets (PHFSs) for this issue. The PHFSs provides an evaluation circumstance containing more information which make the final decision-making results more accurately. Additionally, the IDOCRIW method separately and the MOOSRA method based on the MOORA method is proposed in PHFSs circumstance in this model. In the end, this model is then applied in a numerical case study for business performance evaluation of performing arts enterprises and compare this model with other existing methods.

Understanding university students’ perceptions of classroom environment: A synergistic approach integrating grounded theory (GT) and analytic hierarchy process (AHP)

University classrooms play a crucial role in students' educational experience, as they spend a significant amount of time in these spaces. Understanding students' perceptions of the classroom environment is essential for improving classroom design and management. Adopting a user-centric approach, a novel research design combining both qualitative and quantitative research methods is employed to develop and validate an evaluation framework for classroom environment evaluation. Specifically, this study utilises grounded theory (GT) methodology to identify and prioritises the indoor environment parameters that students consider important. A classroom environment performance evaluation framework for the classrooms within a Hong Kong university was then developed based on the qualitative findings using the Analytic Hierarchy Process (AHP) method. The framework was then used to examine students' perceived importance of the university classroom performance among different sub-groups. The findings reveal that “facilities and services” emerged as the most critical parameter, emphasizing the importance of effective post-occupancy management. Intriguingly, there are minor differences in importance rankings between genders and education levels, with males emphasizing “indoor air quality” and females prioritizing “thermal comfort”. Moreover, distinct priorities are observed between various classroom types; students in lecture theatres focus on “seating plans” and “temperature”, while those in general classrooms prioritise “seating layout” and “fire safety”. These findings emphasise the need for effective post-occupancy management, while also highlight nuanced preferences based on gender, education levels, and classroom types, thereby offer crucial insights for designers to tailor indoor environments that better align with diverse student needs and preferences. Furthermore, a human-built environment interaction model is developed to summarise the research findings and provide insights for future research directions. This comprehensive approach enhances understanding of students’ preferences and experiences in university classrooms.

A DEA-based decision framework for performance evaluation and ranking of workers in a real case from food industries

A DEA-based decision framework for performance evaluation and ranking of workers in a real case from food industries

Framework for performance evaluation of public sector enterprises A multi-criteria decision-making approach

Framework for performance evaluation of public sector enterprises A multi-criteria decision-making approach

Multi-criteria assessment framework for evaluation of Green Deal performance.

The European Green Deal (EGD) is a long-term and important policy to combat climate change. It contains comprehensive regulations that concern the European continent beyond individuals, companies, and cities. Moreover, achieving environmental sustainability depends on the whole world taking responsibility and concrete steps quickly. Although successful and rapid change requires collective effort and high performance across all topics, involving all countries, communities, and sectors, leaving no one behind, since the economic conditions and infrastructures of countries are different, the process of adaptation to green transformation varies. In this study, the multi-criteria decision-making approach has been used to evaluate the performance of the EU member states in terms of many different criteria under the protecting, reducing, and enabling dimensions in an integrated and comprehensive manner. In this context, the data of the EU member states obtained from Eurostat on 3 main and 15 sub-criteria were used, criterion weights were determined by the MEREC method, and then the EGD performances of the countries were revealed by the MAIRCA method. According to the results, "the primary energy consumption" and "freight transport by mode" were selected as the most significant criteria in terms of EGD compliance performance. As a result of the evaluation of the performances of the alternatives, the Netherlands had the best EGD performance which was followed by Sweden while Ireland had the worst ranking and Cyprus was the other underperforming member. Comparative analyses were conducted with the aim of testing the consistency of the proposed methodology.

Multi-criteria decision support framework for climate change-sensitive thermal comfort evaluation in European buildings

This paper proposes a novel multi-criteria decision support framework for climate change-sensitive evaluation of building thermal comfort performance in European buildings. The proposed framework considers various comfort categories based on building use and condition, comfort models based on building operation, sensitivity to climate change, key performance indicators, and their thresholds. The proposed framework is then implemented using a passive house-certified high-performance timber dwelling near Brussels as a case study. The thermal comfort in the free-running reference timber dwelling is assessed using a whole-building energy performance simulation model with a static threshold of 26°C for the bedrooms and an adaptive threshold for the other occupied zones. The analysis found an increase in indoor overheating degree by 1.7°C and ambient warmness degree by 6.5°C during heat waves from the current scenario to the end of the century scenario. However, the reference timber dwelling effectively suppressed the impacts of climate change with varying degrees of success towards the end of the century. The proposed framework is intended to support decision-makers in effectively evaluating performance during the early stages of building design. The study highlights the need for further research on building performance assessment techniques and guidelines in a changing climate.

Thermo-electrochemical modeling of thermally regenerative flow batteries

Thermally regenerative flow batteries are promising for harvesting the ubiquitous low-grade heat energy. Efforts have been made to improve the performance of this type of battery by focusing mainly on thermodynamics perspectives, but ignoring the mass transfer and electrochemical kinetics of the battery. In this work, a thermo-electrochemical model is developed for analyzing effects of the heat transfer irreversibility, overpotential losses, mass transfer, and temperature-dependent resistances on the energy conversion, based on which a five-dimensional performance evaluation framework is proposed for the first time. Results show that the Nernstian loss, concentration loss, and ohmic loss are the main limiting steps for thermo-electricity conversion, and a trade-off between different performance indices exists. To realize the synergistic improvement of the thermo-electrochemical performance, a multi-objective optimization scheme based on a genetic algorithm is developed, and a power density of 13.22 μW cm−2, thermal efficiency of 8.17%, output-voltage efficiency of 48.17%, exergy efficiency of 46.47% and ecological coefficient of performance of 1.23 is achieved, which is among the highest performance in the open literature. The methods and results reported here pave a new way for the design and optimization of thermally regenerative flow batteries.

Field testing and performance evaluation of AMD-controlled high-rise building structures with real-world validation

In recent decades, structural control of civil infrastructures, especially high-rise buildings, has been broadly investigated and developed to mitigate disaster-induced structural responses. The traditional tuned mass damper (TMD) has been exploited to the active mass damper (AMD) system, which leads to the necessary field testing and performance evaluation. Accordingly, a comprehensive dynamic testing and performance evaluation method is proposed in this paper for high-rise structures with AMD systems. Four testing scenarios are firstly adopted and investigated at the field testing stage, including ambient vibration, free vibration, forced vibration, and dynamic loading vibration. Correspondingly, a multi-level performance evaluation framework, sequentially containing direct response data analysis, modal characteristic identification, AMD excitation performance validation, and vibration control efficiency evaluation, is designed and presented for the control performance evaluation and confirmation. To illustrate the presented multi-scenario dynamic testing and multi-level performance evaluation framework, a field dynamic testing was systematically conducted on a real-world tall tower with an AMD system. In the first testing part, the tower's critical dynamic characteristics, such as natural frequency, damping ratio, and modal mass, are accurately identified. Subsequently, the control performance of the AMD system is evaluated by analysis of the excitation and actuation capacity and the structural vibration control efficiency. Furthermore, the amplitude dependency of the damping ratio is identified, and the potential mechanism is discussed.