Performance Analysis Of Process Research Articles

Parametric analysis and optimization of the combustion process and pollutant performance for ammonia-diesel dual-fuel engines

As a low-cost, carbon-free, and widely available hydrogen carrier fuel, ammonia has now regained peoples’ attention in the future development of the carbon-neutral engine. To evaluate the feasibility of ammonia as a carbon-reducing fuel for a high-power diesel engine, a computational fluid dynamics simulation model of a Caterpillar 3401 diesel engine has been established and validated. Initially, an analysis was conducted to examine the effects of different ammonia energy fractions on combustion and the generation of emissions. Subsequently, to address issues related to incomplete ammonia combustion and a decline in engine power performance, a novel fuel injection strategy was developed. This strategy optimizes the distribution of diesel within the combustion chamber and the combustion process of ammonia-diesel dual-fuel by coordinating the injection timing of diesel fuel with the injection angle. The results indicate that an ammonia energy fraction of 40% is deemed to be an optimal mixing ratio for ammonia addition. Compared with pure diesel mode, greenhouse gas emissions are reduced by 34.3%, and the indicated mean effective pressure is only reduced by 4% when the ammonia energy fraction is 40%. Collaborative optimization of fuel injection timing and angle can achieve multi-point pilot ignition, shorten the combustion duration, and thus approach the effect of premixed combustion. This leads to a substantial decrease in unburned ammonia emissions, with the optimal unburned ammonia emission injection scheme registering only 0.279 g/kW·h, a mere 1.63% of the emissions under the original injection scheme with a 40% ammonia energy fraction. Additionally, the rapid combustion contributes to an increase in in-cylinder temperature, resulting in a significant reduction in N2O and CO emissions.

Energy Performance Analysis of the Renovation Process in an Italian Cultural Heritage Building

Renovating buildings with cultural heritage significance is an important step toward achieving sustainability in our cities. The benefits are not only energy-related but also encompass social aspects that make these renovations a high apriority. The present work investigates the renovation process of a cultural heritage building in the Municipality of Trento in Italy, specifically focusing on achieving energy savings and renewable energy integration by implementing various renovation actions. These renovation actions include improvements to the building envelope, such as roof insulation and window replacements. Additionally, the renovation actions for active systems involve the installation of a ground-source heat pump for heating/cooling coupled with a borehole thermal energy storage system, which is an innovative technology for the renovation of cultural heritage buildings. The electrical systems of the building are upgraded through the addition of standard rooftop photovoltaics, innovative building-integrated photovoltaics (shingles), and the installation of an LED lighting system. The baseline and the renovation scenarios are studied using the dynamic simulation tool INTEMA.building, written in the programming language Modelica. This tool simulates both the building envelope and the energy systems with a high level of detail, using advanced control systems and adjustable time steps. According to the simulation analysis, the primary energy demand is reduced by 30.49%, the final energy demand by 36.74%, and the net electricity demand by 8.72%. Results from this study can be useful to interested stakeholders (e.g., building owners, architects, construction companies, public agents, and urban planners) dealing with the renovation of cultural heritage and protected buildings. Also, the results can be exploited for estimating energy savings by applying advanced renovation strategies for cultural heritage buildings.

An aircraft assembly process formalism and verification method based on semantic modeling and MBSE

The aircraft assembly system is highly complex involving different stakeholders from multiple domains. The design of such a system requires comprehensive consideration of various industrial scenarios aiming to optimize key performance indicators. Traditional design methods heavily rely on domain expert knowledge using documents to define assembly solutions which are later verified through simulations. However, these document-centric approaches cannot provide graphical notations for engineers to efficiently understand the entire assembly process. Moreover, it is difficult to analyze the performance of the designed assembly processes using simulations since the simulation models have to be developed based on the documents manually rather than be generated automatically from the design models. In this paper, a semantic-driven approach is proposed to support aircraft assembly process formalism and performance analysis. First, meta-models of aircraft assembly processes are developed based on SysML and discrete-event simulation models using a semantic modeling language named KARMA. Then an application ontology is defined for generating semantic models from KARMA architecture models to capture domain knowledge, system requirements and simulation model information of the aircraft assembly process. A model transformer is developed to transform the KARMA models to discrete-event simulation models based on the application ontology. Then the generated simulation models are executed to obtain the simulation results for verifying the designed assembly process. Finally, the obtained simulation results are used to support decision-making of selecting the optimal aircraft assembly process. A case study is conducted to verify the proposed method.

Comparative study on process simulation and performance analysis in two pressurized oxy-fuel combustion power plants for carbon capture

Process simulation and analysis are demonstrated to provide significant benefits for pressurized oxy-fuel combustion systems. This study compares the performance of pressurized oxy-fuel combustion systems and a first-generation oxy-combustion system under the same standard conditions. On this basis, the increase in efficiency of pressurized oxy-fuel combustion systems is evaluated. Process simulation and analysis are carried out for the first-generation oxy-combustion system in a 600 MW supercritical primary intermediate reheat power plant without heat integration (Base Case) and with heat integration (Case A). The validity of the simulation results is then verified. Considering Case A as a benchmark model, the process simulations of a pressurized oxy-coal combustion system and a staged pressurized oxy-combustion system are performed. The simulation results are compared with results in other literature studies. Compared with the benchmark model, the results indicate that the gross generation efficiency of the pressurized oxy-coal combustion system is improved by 1.12 % (LHV), and the net generation efficiency is improved by 0.47 % (LHV). In addition, the gross generation efficiency of the staged pressurized oxy-combustion system is enhanced by 1.78 % (LHV), and the net generation efficiency is improved by 2.4 % (LHV) compared with the benchmark model.

Modelling and performance analysis of the COVID-19 emergency collaborative process based on a stochastic Petri net

Modelling and performance analysis of the COVID-19 emergency collaborative process based on a stochastic Petri net

Modeling and performance analysis of emergency response process for hydrogen leakage and explosion accidents

To address concerns associated with the initial response process following hydrogen refueling station leakage and explosion accidents, this research introduces the utilization of stochastic colored Petri nets for dynamic modeling of the emergency response procedure. Through the construction of a process model for responding to hydrogen leakage and explosion accidents at refueling stations, the model's effectiveness is assessed using an Isomorphic Markov chain (MC) analysis approach, followed by simulation and analysis of the emergency response procedure. Furthermore, the performance of the emergency process in managing hydrogen leakage and explosion accidents at refueling stations is evaluated, considering place occupancy probabilities and transition utilization probabilities. By optimizing the timing of transitions, critical stages in the process for handling hydrogen leakage and explosion accidents at hydrogen refueling stations are identified, and recommendations for process enhancement are proposed. The findings reveal that continuous hydrogen leakage conditions and the phase involving the summoning of rescue personnel are prone to information congestion. The timely arrival of the on-site manager and the prompt reporting of incident details emerge as pivotal actions within the emergency response process for hydrogen refueling station leakage and combustion incidents. These actions wield substantial influence over the efficacy of emergency response and mitigation, underscoring their significance as primary areas for improvement.

Decision making in operator-machine assignment problems: an optimization approach in U-shaped production lines

Decision-making is a complex problem in all fields of production, because decision makers have to find the most suitable solution alternative among the numerous, while the solution of the problem is limited by multiple, usually conflicting constraints. In the Industry 4.0 era, one of the most widely used production lines are the U-shaped production lines, which focus on the elimination of waste through a high utilization of workers. It means, that worker-machine assignment plays a significant role in the optimization of production processes in a U-shaped production line. The current investigation proposes a novel absorbing Markov chain (AMC) optimization approach to support the decision making regarding worker selection and assignment. The proposed approach integrates the AMC and the performance analysis of the production process. The numerical results validated the decision making model and showed that optimal worker-machine assignment can lead to about 20% production cost reduction, while the key performance indicators (KPI) of the U-shaped production line are significantly increased. The sensitivity analysis of influencing factors made it possible to identify the critical factors of this decision making problem, such as the qualification of operators, time of technological and logistics operations, and maintenance policy.

A holistic analysis of chemical process performance using pinch technology

ABSTRACT The chemical industry is acquiring new advancement day by day. Previously, quite massive equipment had been used to do heat transferring tasks, but now the industry has been modernised. Heat Integration is a trending area of study that might be applied in several sectors to redesign processes. Heat Integration alludes to any technique in chemical engineering that results in considerably smaller, greener, and more energy-efficient appliances. Heat Integration aims to improve energy transfer, lowering the equipment’s capacity for heat transfer. This paper uses pinch analysis to optimize heat integration and find the best heat-exchange network through case studies. Pinch Technology offers a systematic approach to reducing energy use across all sites and activities. It is feasible to determine the proper alterations to the fundamental process parameters that can result in energy savings by using pinch technology. The Aspen Energy Analyzer tool has been used to compute the heat integration of the case studies. After obtaining the data from the software, they were used in pinch analysis to determine the optimal alternative for the heat exchanger network.

Implementation Process Simulation and Performance Analysis for the Multi-Timescale Lookup-Table-Based Maximum Power Point Tracking under Variable Irregular Waves

The efficacy of the multi-timescale lookup-table-based maximum power point tracking (MLTB MPPT) in capturing energy at various fixed sea states has already been demonstrated. However, it remains imperative to conduct a more comprehensive evaluation of the MPPT tracking performance under varying sea states in practical scenarios. Additionally, it is crucial to engage in an in-depth analysis of the dynamic process and energy loss/consumption associated with MLTB MPPT implementations. This paper focuses on the implementation process simulation and performance analysis for the MLTB MPPT under variable irregular waves. Firstly, the structure of the wave power controller based on a MLTB MPPT algorithm is described in detail, as well as that of a controlled plant, known as a novel inverse-pendulum wave energy converter (NIPWEC). Secondly, mathematical models for the MLTB MPPT are developed, taking into account the efficiency of each link. In this paper, we present simplified modelling methods for both permanent magnet synchronous generator (PMSG) vector control and permanent magnet synchronous motor (PMSM) servo control. Finally, the tracking performance of the MLTB MPPT in the presence of variable irregular waves is comprehensively analyzed by simulating the implementation process and comparing it with two other MPPT algorithms, i.e., the frequency- and amplitude-control-based MPPT and the lookup-table-based internal mass position adjustment combined with the optimal fixed damping search. Results show that the MLTB MPPT (Method 2) is a competitive algorithm. Besides, a significant portion (>12%) of the time-averaged absorbed power is actually lost during the power generation process. On the other hand, the power required for a mass-position-adjusting mechanism is relatively small (approximately 0.2 kW, <1.5%). The research findings can offer theoretical guidance for optimizing the operation of NIPWEC engineering prototypes under actual sea conditions.

Simulation Model for Sustainable Management of the Air Cargo Screening Process

This article presents a novel model for the management of air cargo shipment screening. Previous research has focused solely on making the air cargo screening process as efficient as possible. These scientific papers did not look at the costs generated by the improper selection of technical equipment for the cargo handled. The challenge is to be able to complete the entire screening process in the expected time with the lowest possible energy consumption. This article presents a discrete-event simulation model for the balanced planning of air cargo screening. The innovation of this solution is the parallel analysis of process performance and energy consumption. The user receives two variables (energy consumption and process execution time) in relation to the number of cargo shipments handled. The user can therefore control the process by taking these variables into account. This will allow the user to find the right system configuration for the preferences desired. It is possible to strike a balance between achieved process efficiency and energy consumption. This approach has not been considered so far. Given that energy consumption constitutes 15% of operating costs at airports, this is an important issue that needs to be addressed.

A model-based approach towards accelerated process development: A case study on chromatography

Process development is typically associated with lengthy wet-lab experiments for the identification of good candidate setups and operating conditions. In this paper, we present the key features of a model-based approach for the identification and assessment of process design space (DSp), integrating the analysis of process performance and flexibility. The presented approach comprises three main steps: (1) model development & problem formulation, (2) DSp identification, and (3) DSp analysis. We demonstrate how such an approach can be used for the identification of acceptable operating spaces that enable the assessment of different operating points and quantification of process flexibility. The above steps are demonstrated on Protein A chromatographic purification of antibody-based therapeutics used in biopharmaceutical manufacturing.

Nitrogen Removal Performance and Microbial Community Analysis of Anoxic and Oxic Process in Electrolytic Manganese Residue Leachate

Nitrogen Removal Performance and Microbial Community Analysis of Anoxic and Oxic Process in Electrolytic Manganese Residue Leachate

Everything at the proper time: Repairing identical timestamp errors in event logs with Generative Adversarial Networks

Process mining generates valuable insights into business processes through the analysis of event logs. However, event logs are commonly subject to various data quality issues which hinder the success of process mining initiatives in organizations. Identical timestamp errors, for example, occur when multiple events of a process instance mistakenly share the same timestamp. This error causes discovered process models to be unrepresentative and process performance analysis results to be misleading. To address this problem, we propose a method for automatically repairing identical timestamp errors in event logs. To that end, we combine existing method components for error detection and reordering of erroneous events with a novel approach for repairing timestamps based on Generative Adversarial Networks. To allow for a rigorous evaluation, we instantiate our approach as a software prototype, and use it to repair a total of six real-life and artificial event logs with overall 30 variations. Thereby, we show that the proposed method shows improved results compared to alternative approaches for repairing identical timestamp errors in event logs.

Techno-economic assessment and exergy analysis of iron and steel plant coupled MEA-CO2 capture process

In the interest of mitigating global warming and climate change, the steel industry urgently needs to take measures to reduce CO2 emissions. In the context, this study is to evaluate the application value and feasibility through the techno-economic assessment and exergy analysis of the iron and steel industry coupled MEA-CO2 capture process. The integrated process, successfully implemented in Aspen Plus v12®. Considering the influence of heat integration and capture scale, scenarios 1–4 are designed: 1. Full-flow carbon capture, using outsourced steam; 2. Full-flow carbon capture with heat recovery and outsourced steam mixed use; 3. Partial-flow carbon capture only using surplus steam; 4.100,000 tons of CO2/year of capture scale, using outsourced steam. The process can achieve an effective gas capture rate of 90% and a CO2 product purity of 98.3%. The maximum annual CO2 emission reduction is about 7.65 million tons in scenarios 1 and 2. Compared with scenario 1, the CO2 capture cost of scenario 3 decreased by 22.1%, 29.0%, 23.9% and 21.2%, while that of scenario 4 increased by 44.1%, 39.5%, 25.3% and 18.0%. Through exergy analysis, the total exergy efficiency is calculated to be 38.04%, and the components that need attention and improvement in the process are diagnosed. TTAShis provides a reference for the performance analysis and application feasibility of the coupling process of CO2 capture and waste heat utilization from steel plant.

Performance Analysis of 3D Concrete Printing Processes through Discrete-Event Simulation

Three-dimensional concrete printing is a technique that has been growing constantly, presenting advantages such as reduced completion times and a decreased environmental impact by eliminating the use of formworks. To carry out the process, the printing path of the extruded material and the movement of a robot must be programmed. Thus, the present research simulated these 3D concrete printing processes in a small 2-floor building of 309.06 m2 and then in a 12-floor building of 10,920 m2. To analyze the 3D printing process, discrete-event simulation was used while considering different variables such as extrusion speed and the locations of a robot mounted on tracks. The results show that when comparing the time taken for a conventional construction system to construct concrete walls and the maximum duration for 3D-printed walls, this method is 45% faster than traditional construction for a small building, but for a big building, there is a difference of 40% in favor of conventional construction; however, this was when using only 1 robot for the whole building. After running the same analyses but using 3 robots instead of 1, the total 3D concrete printing time for the big building was 80% faster in favor of the 3D concrete printing process.

MCDM-Based Ranking and Prioritization of Fisheries’ Risks: A Case Study of Sindh, Pakistan

The fisheries sector in developing countries, including Pakistan, faces various risks that have not been comprehensively studied and addressed through policy measures. This study aims to analyze fisheries’ risks in Pakistan by following a risk management process and using statistical analysis. The data was collected through structured questionnaire surveys, and subsequently, fuzzy analytic hierarchy process (fuzzy AHP) and importance performance analysis (IPA) were utilized to analyze the data. The study ranked the top five risks in order of importance as management, technical, economic, environmental, and occupational risks. The study also identified high-importance, low-performance sub-factors, including inadequate legislative implementation, overexploitation, and infrastructure shortages. It was found that there is low risk perception and inadequate management regulations in the sector. The findings suggest that risk management strategies, such as risk avoidance and risk transfer, can be used to mitigate fisheries’ risks. The study highlights the need for policy measures to revitalize the fisheries sector in Pakistan and provides recommendations for further research.

Performance analysis of a boil-off gas re-liquefaction process for LNG carriers

With the growth of LNG demand and rapid rise in natural gas prices, it is of great significance to develop an efficient boil-off gas (BOG) re-liquefaction process for LNG carriers. This paper proposes a BOG re-liquefaction process using the single mixed refrigerant (SMR) cycle, and comprehensively compares it with the typical Mark III process. The processes were rigorously simulated with Aspen HYSYS, and performed process optimization in terms of specific energy consumption (SEC) as the objective function using the genetic algorithm method. Sensitivity and exergy analysis were also conducted to assess process variables and irreversibility. Furthermore, the processes were performed economic analysis including the total capital cost (TCC), total operating cost and total annualized cost (TAC). The results show that the SEC and major equipment exergy loss of the proposed process have 529.4 kWh/ton and 465 kW, which are 50.34% and 40.88% lower than the Mark III process. Additionally, the TAC for proposed process presents 4.07 million USD/year, compared to 6.62 million USD/year for the Mark III, resulting in a 38.55% annual savings.

A Pilot-Scale Nanofiltration–Ultrafiltration Integrated System for Advanced Drinking Water Treatment: Process Performance and Economic Analysis

In this pilot study, the performance of an “ultrafiltration (UF) + nanofiltration (NF)” advanced treatment process in improving drinking water quality was investigated. The membrane performance and effluent qualities of three commercial NF membranes (Dow Filmtec NF270-400, VONTRON TAPU-LS, and GE Osmonics-HL8040F 400) were evaluated, and the reasons for the difference in effluent quality of these three NF membranes were analyzed. The results showed that UF as a pretreatment process could provide NF with stable and qualified influent. After passing through the UF unit, the turbidity of raw water decreased by 88.6%, and the SDI value was less than 3. Due to the small pore size of NF membranes, organics and polyvalent ions in raw water were further removed. With a water recovery of 90%, the conductivity, chemical oxygen demand (CODMn), and hardness of NF effluent are significantly improved. The three commercial NF membranes showed different performance advantages. Among them, Dow Filmtec NF270-400 had the best desalting performance, VONTRON TAPU-LS had the highest retention rate of organic matter, and GE Osmonics-HL8040F 400 had significantly advanced softening performance. Thanks to the combination of the UF membrane and NF membrane, membrane fouling was effectively inhibited, and drug consumption was within an acceptable range. The operation costs of these three NF membranes were 0.165, 0.179, and 0.171 USD per ton of produced water, respectively. The results showed that the UF + NF process is an ideal technology for advanced treatment in water plants.

DAILY ProM SOFTWARE

The importance of project management in the modern world was analyzed. The problem of using softwaretools in project management was substantiated. A review of scientific works on the subject of the study was carried out.Four features that describe the need in project management tools were analyzed. A list of 10 alternative tools to MicrosoftProject was described. SWOT analysis of Microsoft Project was conducted too. Creation steps of the new softwareproduct “Daily ProM Software” were described. All buttons and their functions were justified. SWOT analysis of thedeveloped product was conducted too. The advantages of the program were described in the research.DAILY ProM is a process mining software tool that is used to analyze, visualize and improve business processes. It isan open-source software developed at Eindhoven University of Technology, and is available for free download from theProM website.With DAILY ProM, users can import event logs from various sources, such as ERP systems, workflow managementsystems, and databases. The software then uses process mining techniques to extract useful insights from the event logs,such as process flow, performance metrics, bottlenecks, and compliance issues.DAILY ProM supports a wide range of process mining techniques, including process discovery, conformancechecking, performance analysis, and social network analysis. It also provides a user-friendly interface that allows usersto easily visualize the extracted process models and analyze them using various interactive tools.Overall, DAILY ProM is a powerful tool for process mining, and is widely used by researchers, practitioners, andstudents in the field of business process management.

Kinetics studies and performance analysis of algae hydrothermal liquefaction process

Kinetics studies and performance analysis of algae hydrothermal liquefaction process