Installation Schedule Research Articles

Evaluating constraints on offshore wind farm installation across the Taiwan Strait by exploring the influence of El Niño-Southern Oscillation on weather window assessment

The transition to renewable energy sources, such as offshore wind farms, is essential in mitigating climate change. Taiwan has set ambitious targets to harness wind energy from the Taiwan Strait, but offshore wind farm installations are highly dependent on weather conditions, particularly wind speeds. This study examines the relationship between the El Niño-Southern Oscillation (ENSO) and offshore wind farm installation by assessing weather windows—periods with wind speeds below 12 meters per second at a height of 100 meters for at least 12 hours. Our analysis shows that during La Niña years, the number of feasible weather windows decreases by up to 40%, particularly between October and June, compared to neutral and El Niño years. This decrease can be as high as fourfold in December, significantly impacting installation schedules. Seasonal variations are also notable, with wind speeds exceeding 12 m/s in winter 66.4% of the time, compared to 29.4% in spring, making spring and summer the most favorable periods for installation. However, even during these favorable seasons, La Niña years can bring higher wind speeds, necessitating careful planning. These results underscore the importance of integrating ENSO forecasts into project planning to avoid installation delays and optimize installation timelines. By leveraging seasonal and interannual climate variability predictions, decision-makers can improve the resilience of offshore wind farm projects and ensure efficient energy transition strategies.

Analysis Welding Types Pipe Fabrication Process in Missile Fast Attack Boat Construction

The equipment in the piping system consists of pipes, valves, flanges, filters, fittings, pumps, and others. The installation schedule for this piping system begins after the connection between blocks. Pipes as part of a ship's system have several steps in their installation procedure, one of which is welding. Welding on pipes is carried out by professional welders who have met more complex competency requirements than welders in general, such as flat position welders, vertical welders, or overhead welders. The purpose of this study was to determine the welding process and types of welding in pipe fabrication for the construction of the Missile Fast Attack Boat. Result comparison between the diameters of the welded pipes, the greater the value of the welding volume formed. The largest volume is 426 mm3, with a pipe length for the fabrication process of 4,3 m. On the other hand, the shortest fabrication is for welding pipes with a diameter of 2,5 m, which has a volume of 127 mm3. While the welding process using GTAW / Gas Tungsten Arc Welding (TIG) is very appropriate for welding in small areas and thin pipes. The TIG welding process has an average volume of below 150 mm3.

The greenhouse gas performance of selected biodegradable and recalcitrant plastics in U.S. landfills

Biodegradable plastics are often considered to exhibit superior environmental performance compared to conventional recalcitrant plastics. Here, we assess the greenhouse gas (GHG) emissions of selected biodegradable and recalcitrant plastics made from both fossil and biogenic carbon (C) as disposed in a national average U.S. landfill. This average landfill incorporates consideration of size, precipitation, landfill gas management, and gas collection installation schedule. The GHG emissions of an 80% biodegradable polycaprolactone (PCLf) made from fossil C and a 2% biodegradable poly(butylene succinate) (PBSb) made from biogenic C were evaluated to represent the range of anaerobic biodegradabilities. The 2% biodegradable PBSb has lower GHG emissions than the 80% biodegradable PCLf in the national average landfill. In the best case, which includes aggressive gas collection, conversion of gas to energy, and disposal in a large landfill, the PCLf results in 2423 kg CO2e/mt, which is well above PBSb (−1956 kg CO2e/mt), a hypothetical biogenic and 80% biodegradable PCLb (4739 kg CO2e/mt), and recalcitrant fossil plastic (0 kg CO2e/mt). From a disposal perspective, a recalcitrant biogenic plastic is optimal given the long-term storage of carbon. This study informs the direction of materials research to develop materials that minimize their overall environmental footprint at end-of-life.

Collaborative Planning for Stacking and Installation of Prefabricated Building Components Regarding Crane-Collision Avoidance

Site stacking of the prefabricated building components (PBC) should be planned in coordination with installation schedule and other dynamic constraints to improve the overall construction efficiency. This study explores the collaborative planning for stacking and installation of the PBCs (CPSIP) by avoiding collision of the tower cranes that are in the overlapping area and operated simultaneously with the objective of minimizing the prefabricated construction duration. The CPSIP problem, crane-collision cases, collision-avoiding strategy, and multiphase dynamic optimization strategy are analyzed. Then the optimization model for the CPSIP problem subject to the crane-collision avoiding and other dynamic constraints is proposed, and the binary particle swarm optimization (PSO) algorithm is utilized to solve the optimization model for the CPSIP problem. A case study is presented to demonstrate and justify the developed method for obtaining the CPSIP. This study contributes to the knowledge and methodology for achieving the CPSIP by avoiding crane-collision, thus improving efficiency of the prefabricated construction while promoting safety.

Offshore Logistics: Scenario Planning and Installation Modeling of Floating Offshore Wind Projects

AbstractThe offshore installation, logistics, and commissioning activities are currently estimated to make up 20% to 30% of the capital expenditures (CAPEX) of offshore wind projects. Technical and geographical factors affect both the CAPEX during construction and the installation schedule, such as a lack of supporting port infrastructure, the availability of specialized vessels, the distance from the wind farm to shore, accessibility, water depths, and seabed conditions. In addition, there are significant risks during the construction phase, such as uncertain durations due to the sensitivity of marine operations to weather conditions. Identifying supply chain requirements is critical in the early stages of project planning in order to avoid time delays and cost overruns during the transport and installation process. This study explores and analyzes the logistic requirements and installation methods of a floating offshore wind (FOW) technology. Using an advanced forecasting and decision support tool, realistic case scenarios are simulated at a variety of potential sites for FOW deployment across the UK. Technical risks associated with installation strategies are identified and classified. The results provide a comparison of key installation performance indicators of each case scenario (e.g., installation rate per wind turbine, weather downtime). This study is of interest to researchers, offshore wind project developers, service providers, and other key stakeholders seeking to optimize planning and logistics to drive down CAPEX costs, reduce the construction downtime, and minimize risks during marine operations.

Leveraging Quantity Surveying Data and BIM to Automate Mechanical and Electrical (M & E) Construction Planning

Despite the great potential of LPS and BIM to improve construction project productivity, the full integration of these modern production and information management systems at the data processing level is not yet achieved. After matching the literature to empirical studies in a Constructive Research Approach, it emerged that very few studies have investigated how buildings’ data could be preserved and continuously evolve during the project lifecycle. Accordingly, we underline the potential role of data warehousing in rendering operational data as a strategic asset for decision making. These findings motivate the present research, which aims to capitalize on quantity surveying data in order to automate the generation of M & E installation schedules. This paper first introduces the system functional requirements. Then, it proposes a conceptual scheme for the planning data mart (a data warehouse subset dedicated to planning subject area). Furthermore, we shed light on the M & E fragnet standardization procedure and how data have been processed. Finally, we present the current software developments to demonstrate the feasibility of this concept.

Real-time pipe system installation schedule generation and optimization using artificial intelligence and heuristic techniques

Infrastructure systems in the United States are aging and considerable investment is needed to renew and replace a significant proportion of the existing systems. Piping systems, which are used in many infrastructure systems such as the distribution networks for utilities – water, sewage, gas, oil, etc., are very important in this regard. Real time scheduling is an important and necessary task in the planning and execution of construction projects. This is of particular importance in the installation of pipe systems, for which it is time consuming to plan and coordinate between team members the detailed requirements and information for the generation of practical installation schedules. During the installation stage, there can be delays or interference that could lead to the failure of the initial schedule plan. Current approaches are time-consuming, not automated and do not provide real-time schedules. Thus, the process is still fragmented and essentially manual, with inefficient information flow. To effectively improve the installation schedule, current knowledge of the installation site situation is important, with this knowledge being used to generate realistic schedules. Artificial intelligence (AI) maximizes the value of data by learning from previous cases and facilitates decision-making by making the process smarter and automatic. This paper proposes a new AI framework with machine learning (ML) and heuristic optimization techniques for automating practical pipe system installation schedule generation and optimization. A BIM model is used as reference to provide pipe system component information. A hybrid knowledge-based system is developed to integrate data-driven knowledge base and site-driven knowledge base on pipe system installation. K-Nearest Neighbor (KNN) and Graph Neural Network (GNN) ML techniques are adapted to map extracted components with the installation activities and their requirements for installation based on knowledge obtained from industry experts and piping codes. In addition, a heuristic algorithm is adopted to optimize the installation schedule. Finally, an optimal installation schedule that minimizes overlapping activities, time and cost is suggested.

Study of the addition of a chemical mix additive and curing temperature on the setting time and mechanical properties of no‐cement castable

AbstractTight installation schedules and economic pressures are potential drawbacks for castable installation and performance. Many factors influence the setting behavior and the properties of no‐cement castable refractories, including temperature and chemical composition. In this study, the setting behavior and the mechanical properties of a no‐cement castable were analyzed varying the amount of a chemical additive mix and curing temperature. The chemical additive mix concentration was varied from 0 wt% to 1 wt%. The curing temperature was varied from low (4°C/40°F) to high (40°C/104°F). The mechanical properties were characterized by cold crushing strength (CCS). A variance in the pH level drastically increased the setting time of the castable. Mechanical properties on green samples showed lower strength for castables with a higher concentration of the additive mix. This difference in performance is the result of the lower pH preventing the formation of a chain mechanism in the no‐cement castable bonded with colloidal silica.

BIM-Based Approach for Automatic Pipe Systems Installation Coordination and Schedule Optimization

AbstractDetailed planning, sequencing, and scheduling for the installation of multiple pipe systems are greatly needed to efficiently complete a piping project with both reduced cost and duration. ...

A computer tool for optimisation and simulation of marine operations for offshore wind farm installation

The installation process of offshore wind farms is complex and requires a high level of coordination, agile scheduling and systematic methods. High risks and costs are involved and especially weather conditions have an impact on the marine operations. A computer tool for optimisation and simulation of marine operations has been developed in close cooperation with a large actor in the offshore wind industry. The tool has a web-based user interface and an optimisation engine that is based on a version of a genetic algorithm and uses an agent-based simulation process to evaluate installation schedules with respect to weather risks, time and costs. The objective is to provide decision support for the early phase planning of wind farm installation by offering an efficient method for estimation of cost and time for future projects.

Beam dynamics simulation and beam commissioning preparation in the RAON accelerator

The RAON (Rare Isotope Accelerator complex for ON-line experiments) accelerator that can accelerate various kinds of beams from proton to uranium using superconducting radio-frequency (RF) cavities is currently under construction with the goal of completion in 2021 by the Rare Isotope Science Project in Daejeon, Korea. At Sindong site in Daejeon, the accelerator equipment of the low energy linac section consisting of the quarter-wave resonator (QWR) and half-wave resonator (HWR) cavities is being installed in 2020, and the installation of accelerator equipment including single-spoke resonators (SSR1 and SSR2) cavities in the high energy linac section will be completed by the end of 2021. According to the installation schedule, we are preparing the beam commissioning to verify the performance of the accelerator equipment and to achieve the desired beam parameters. For the successful beam commissioning, several physics application tools to be used at the beam commissioning are being developed, and the beam dynamics studies have been also continued. Here we will present ongoing beam dynamics studies and beam commissioning scenarios under planning. In addition, we will introduce the application tools being developed for successful beam commissioning in the RAON accelerator.

Fuzzy Bayesian schedule risk network for offshore wind turbine installation

Offshore Wind Turbine installation schedule risk analysis is a complex task especially in Taiwan due to the fact that involves huge amount of uncertainties such as typhoons, high winds etc. which have high dependency on the project activities. As a result of this, there is insufficient data for analysis and thus leading to a delay in the successful execution of the project. This study developed the Fuzzy Bayesian Network-Monte Carlo Simulation (FBN-MCS) to model uncertainties having impact on the project duration of offshore wind turbine installation and also to find the correlation between the risks and project duration. Fuzzy Sets Theory (FST) were used to define the membership functions for each risk with the help of experts’ survey. The Bayesian Network (BN) was applied to find the dependency relationship between the risk factors affecting the installation identified through literatures and experts. Monte Carlo Simulation (MCS) model then evaluated the dependent posterior probabilities generated from the BN as independent variables to find their correlation and determine the total project. The proposed model was tested on Taipower Offshore Wind Farm Phase 1 Project, Taiwan, to assess its applicability and the results proved to address the study objectives.

CAD 정보를 활용한 해양 배관재 설치 준비율 관리 방법에 관한 연구

In this study, we propose a piping material supply management method using CAD system. The piping materials installed in super large offshore plants have very complicated connection conditions. Therefore, it is very difficult to determine the order of receipt of a large number of installation materials. Therefore, we have developed a system that can automatically check the preparation rate of installation materials prior to the installation process. We have developed an algorithm to obtain connection information among installation items from PDMS system. We have developed an algorithm that can determine the order of installation materials to be installed using the connection information. The order of the installation material is determined by taking into account the constraint conditions for the complete installation of the piping material. We confirm the effectiveness of the developed algorithms in the operating system. This system is also used to manage installation schedules and plan the installation manpower.

Are Groundwater Monitoring Networks Economical? Cost-Benefit Analysis on the Long-Term Groundwater Supply Project of South Korea

Analyses of the relative economic efficiencies of surface-water and groundwater are important for policy-makers in many water-stressed countries. Groundwater is becoming an increasingly attractive and viable option as a supplementary water source, but its economic background must be understood before implementation. Employing the basic frameworks of the British and US Geological Surveys, we examined the economic viability of groundwater monitoring networks in South Korea, based on an analytic hierarchy process (AHP), pairwise comparison, and cost–benefit analysis. The total cost including installation, maintenance and servicing over the next 50 years is estimated to be US$ 0.79 billion, while the benefits are valued at US$ 2.31 billion. The monitoring network should provide benefits worth 292% of the costs, with the monitoring project thus clearly being economically viable. A sensitivity analysis indicates that the monitoring project is still economical, even if the network installation schedule is delayed slightly. As this study combines both economic and scientific perspectives, it might provide a concrete economic background for implementing groundwater utilization projects elsewhere.

Design and Construction of the Full-Length Prototype of the 11-T Dipole Magnet for the High Luminosity LHC Project at CERN

The luminosity upgrade of the Large Hadron Collider (LHC) at CERN requires the installation of additional collimators in the dispersion suppressor regions of the accelerator. The upgrade foresees the installation of one additional collimator on either side of interaction point 7 (IP7) at the location of the existing main dipoles (MBs) that will be replaced by shorter and more powerful dipoles, and of one additional collimator on either side of IP2 at the location of existing empty cryostats. This paper describes the design and the construction status of the full-length prototype of the 11-T dipole magnet, which is needed for IP7. This magnet features a two-in-one structure, like the LHC MB, impregnated coils made of Nb3Sn conductor, an inner bore of 60 mm, and a magnetic length of about 5.3 m. Two 11-T magnets are needed to replace a 15-m long MB. A by-pass cryostat placed in between the two magnets allows creating a room temperature space for the additional collimators. The magnet is designed to provide the same integrated field as the MB at nominal field. However, due to the difference in transfer function at lower field, a correction by means of a trim current has been considered. A full-length prototype is currently under construction at CERN with the goal of developing the manufacturing and inspection procedures prior to launch the series production. For this, new tooling has been developed and optimized during the fabrication of fully representative practice coils. This paper describes the design of the magnet, the main manufacturing steps, and corresponding quality indicators, which will be used to monitor the series production. Finally, the production and installation schedule will be presented.

A mixed-method optimisation and simulation framework for supporting logistical decisions during offshore wind farm installations

With a typical investment in excess of £100 million for each project, the installation phase of offshore wind farms (OWFs) is an area where substantial cost-reductions can be achieved; however, to-date there have been relatively few studies exploring this. In this paper, we develop a mixed-method framework which exploits the complementary strengths of two decision-support methods: discrete-event simulation and robust optimisation. The simulation component allows developers to estimate the impact of user-defined asset selections on the likely cost and duration of the full or partial completion of the installation process. The optimisation component provides developers with an installation schedule that is robust to changes in operation durations due to weather uncertainties. The combined framework provides a decision-support tool which enhances the individual capability of both models by feedback channels between the two, and provides a mechanism to address current OWF installation projects. The combined framework, verified and validated by external experts, was applied to an installation case study to illustrate the application of the combined approach. An installation schedule was identified which accounted for seasonal uncertainties and optimised the ordering of activities.

Automatic as-built modeling for concurrent progress tracking of plant construction based on laser scanning

The application of automatic as-built modeling based on laser scanning can potentially facilitate progress tracking and control in industrial plant construction. Although notable work has been conducted in the as-built modeling field, the level of automation and ability for programs to recognize semantic information is low. Semantic information, such as an installation schedule for industrial components, is vital for identifying actual construction progress. Unfortunately, as the current practices lack the ability to use robust process mapping to turn such information into corresponding as-built models, the current successful rate of recognition remains low. To fill these gaps, this article describes a new as-built modeling process for industrial components by incorporating segmentation and three-dimensional object recognition techniques from computer vision fields. Following the generation of the as-built model, the tracking process is able to identify schedule delays through deviation analysis between the as-built and four-dimensional as-designed models. The modeling process can be integrated in a concurrent construction environment, which provides precise feedback for planners and site managers to simultaneously maintain the quality of construction plans. A case study is conducted, which demonstrates that the developed process enables as-built modeling with semantic information and automatic construction progress tracking. With a certain number of as-built components of a dehydration module being captured, a successful recognition rate of over 90% is achieved. Furthermore, the processing time of the case study lies within an acceptable time period, which supports efficient progress tracking. The results show the feasibility of the developed process, which promises to save time and labor costs during construction.

Bi-objective optimisation model for installation scheduling in offshore wind farms

A bi-objective optimisation using a compromise programming approach is proposed for installation scheduling of an offshore wind farm. As the installation cost and the completion period of the installation are important aspects in the construction of an offshore wind farm, the proposed method is used to deal with those conflicting objectives. We develop a mathematical model using integer linear programming (ILP) to determine the optimal installation schedule considering several constraints such as weather condition and the availability of vessels. We suggest two approaches to deal with the multi-objective installation scheduling problem, namely compromise programming with exact method and with metaheuristic techniques. In the exact method the problem is solved by CPLEX whereas in the metaheuristic approach we propose Variable Neighbourhood Search (VNS) and Simulated Annealing (SA). Moreover, greedy algorithms and a local search for solving the scheduling problem are introduced. Two generated datasets are used for testing our approaches. The computational experiments show that the proposed metaheuristic approaches produce interesting results as the optimal solution for some cases is obtained.

Investigation of Alkaline Hydrolysis in Refractory Linings of Process Plants: A Case Study

In view of the ever-increasing energy needs in the process industry, efficiency enhancements assume critical importance. Refractory linings play a pivotal role in reducing the energy consumption of the process equipment along with ensuring safe and reliable operation of a plant. Owing to the project complexities and installation schedules, refractory-lined equipments are often stored at project sites for prolonged times, leading to non-performance and premature failures. One of the main reasons for such failure, especially for plants in the vicinity of a seacoast, is alkaline hydrolysis or carbonation of refractory linings. In this paper, we have investigated the advent and nature of alkaline hydrolysis in a refinery plant. Innovative remedial measures were successfully implemented to prevent further refractory degradation and salvage already affected linings. We have also developed guidelines and proactive techniques that can be applied to the design, engineering and installation stages of up-coming process plants to prevent this problem.

Design, manufacture and factory testing of the Ion Source and Extraction Power Supplies for the SPIDER experiment

The SPIDER experiment, currently under construction at the Neutral Beam Test Facility in Padua, Italy, is a full-size prototype of the ion source for the ITER Neutral Beam Injectors. The Ion Source and Extraction Power Supplies (ISEPS) for SPIDER are supplied by OCEM Energy Technology s.r.l. (OCEM) under a procurement contract with Fusion for Energy (F4E) covering also the units required for MITICA and ITER injectors. The detailed design of SPIDER ISEPS was finalized in 2011 and manufacture of most components completed by end 2013. The Factory Acceptance Tests took place early 2014. ISEPS, with an overall power rating of 5MVA, form a heterogeneous set of items including solid state power converters and 1MHz radiofrequency generators of 200kW output power. The paper presents the main features of the detailed design developed by OCEM, focusing in particular on the high output voltage pulse step modulators, the high output current resonant converters, the radiofrequency generators by HIMMELWERK GmbH and the architecture and implementation of the complex control system. Details are given on non-standard factory tests verifying the insulation requirements specific to this application. Performance of ISEPS during the factory acceptance tests is described, with emphasis on demonstration of the load protection requirements, a crucial point for all neutral beam power supplies. Finally, key dates of SPIDER ISEPS installation and site testing schedule are provided.