Real Weather Conditions Research Articles

Economical microscale predictions of wind over complex terrain from mesoscale simulations using machine learning

The ability to assess detailed wind patterns in real time is increasingly important for a variety of applications, including wind energy generation, urban comfort and environmental health, and drone maneuvering in complex environments. Machine Learning techniques are helping to develop accurate and reliable models for predicting local wind patterns. In this paper, we present a method for obtaining wind predictions with a higher resolution, similar to those from computational fluid dynamics (CFD), from coarser, and therefore less expensive, mesoscale predictions of wind in real weather conditions. This is achieved using supervised learning techniques. Four supervised learning approaches are tested: linear regression (SGD), support vector machine (SVM), k-nearest neighbors (KNn) and random forest (RFR). Among the four tested approaches, SVM slightly outperforms the others, with a mean absolute error of 1.81 m/s for wind speed and 40.6∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{\\circ }$$\\end{document} for wind direction. KNn however achieves the best results in predicting wind direction. Speedup factors of about 290 are achieved by the model with respect to using CFD.

Efficiency of satellite data in the agro-ecological monitoring system

The article discusses the ecological value of the normalized vegetation index (NDVI). Generalization of scientific data on the possibility of use in forestry, agriculture, ecological research, modeling of ecosystems and monitoring of the earth’s surface has been carried out. It was found that, unlike the surveyor, the operational/satellite monitoring of crops makes it possible to automatically generate reports, control the condition of crops, forecast yields and plan agricultural operations taking into account the real ecological state and weather conditions. In particular, you can create electronic vegetation maps; develop images and field relief for a specific region. It has been established that the use of data from remote sensing of the Earth (RSE) ensures the determination of the objective state of crops (density, quantitative and qualitative changes in crops, obtaining information on chemical treatments) on large areas. The factors that influence the calculation of NDVI are given, and the necessity of using an approach focused on climatic conditions is indicated. It was found that the transformation of multispectral NDVI data into one image layer allows estimating the amount of available vegetation and the development of crops on a field scale. Regular field NDVI mapping helps identify and mitigate any crop problems, increase yields, and make agribusiness more profitable. NDVI has become one of the most important and frequently used indicators in precision agriculture, so it deserves further practical research. This is a numerical indicator of the quality and quantity of plants in the field. It is emphasized that NDVI has become one of the most important and frequently used indicators in precision agriculture. Therefore, deserves further practical investigation. Ecosystem service is a means of identifying threats to ecosystems in order to develop socially acceptable and effective solutions to environmental problems. The ecosystem approach allows predicting changes, which is extremely important for spatial planning and land use management. This approach is especially important when assessing and resolving conflict situations in nature management, when the economic benefit from the use of one or another natural resource becomes a strong argument. From the point of view of human benefit, operational monitoring becomes an ecosystem service. The use of spectral indices contributes to the production of high-quality «environmentally friendly» products, the preservation of environmental components, the reproduction of soil fertility, obtaining the maximum profit, along with the transition from a linear economy to a circular one (economic effect), saving resources, optimizing and diversifying agricultural production.

A high-fidelity approach to modeling weather-dependent fuel consumption on ship routes with speed optimization

In this paper, we present the scheduling problem on a given route where speed optimization under various weather conditions is to be performed. Different approaches for calculating fuel consumption for vessels are introduced with a discussion of how this might influence the speed optimization strategies on predetermined multi-stop routes in a short sea shipping service within offshore logistics. Due to both spatial and temporal changes in weather conditions, fuel consumption as a function of speed becomes time-dependent as a vessel performs its route in varying weather. In our novel approach, the weather impact on fuel consumption for the considered vessels is modeled with a higher level of detail than in previously conducted studies, including both wave direction and wave period as input together with the wave height. We test our approach for optimizing schedules on a large set of routes of different lengths and number of stops, as well as for a set of different weather samples based on historical observations. When comparing the new approach to current industry practice, the computational study reveals on average a 4.5% reduction in fuel consumption across the different routes and weather scenarios. The magnitude of the reduction potential increases for worsening weather conditions. Furthermore, it is demonstrated how the approach commonly used for modeling weather impacts in the literature tends to greatly miscalculate the true cost of performing a voyage in realistic weather conditions. Finally, we discuss how the model fidelity is likely to affect the outcome of the routing decisions at a higher planning level, representing a potential for even further reductions of fuel consumption in various weather conditions.

A new coupling of a GPU‐resident large‐eddy simulation code with a multiphysics wind turbine simulation tool

AbstractThe development of new wind farm control strategies can benefit from combined analysis of flow dynamics in the farm and the behavior of individual turbines within one simulation environment. In this work, we present such an environment by developing a new coupling between the large‐eddy simulation (LES) code GRASP and the multiphysics wind turbine simulation tool OpenFAST via an actuator line model (ALM). In addition, the implementation of the recently proposed filtered actuator line model (FALM) within the coupling is described. The new ALM implementation is cross‐verified with results from four other commonly used research LES codes. The results for the blade loads and the near wake obtained with the new coupling are consistent with the other codes. Deviations are observed in the far wake. The results further indicate that the FALM is able to reduce the lift and power overprediction from which the traditional ALM suffers on coarse LES grids. This new simulation environment paves the way for future wind farm simulations under realistic weather conditions by leveraging GRASP's ability to impose data from large‐scale meteorological models as boundary conditions.

The impacts of the wind on GPS of quadrotors

PurposeThe Global Positioning System (GPS) is crucial for determining the positions of quadrotors, enabling safe flight and maintaining stability against environmental conditions. This study aims to investigate the effect of wind on the GPS of quadrotors experimentally.Design/methodology/approachThis experimental study was conducted using an F450 frame, 980 kV motors and a Pixhawk flight controller to manage the quadrotor’s flight. To investigate the effects of wind on the quadrotor’s GPS during flight, a Pixhawk 4 Holybro flight controller was used. The experimental tests were performed on a predetermined route at different wind speeds.FindingsAnalysis of the data obtained from the flight tests showed that GPS signals were more affected as the wind speed increased. The percentage of GPS jamming levels reached 18% at high wind speeds.Practical implicationsPositioning services will be even more critical for quadrotors, which are expected to be used more frequently in public areas. This study is expected to be a reference for GPS-related research.Originality/valueWinds pose a significant threat to the safe flight of quadrotors in many ways. This study experimentally investigates the effects of wind on the GPSs of quadrotors and to what extent it affects them at different wind speeds under real weather conditions. The obtained data shows that wind has a significant impact on GPS jamming.

Machine Learning Method for Road Vehicle Collected Data Analysis

Abstract A major challenge encountered in the development of systems exposed to weather stressors, such as autonomous vehicles and unstaffed aerial vehicles, is to ensure their proper functioning under adverse rain or snow conditions. Since the sensing of the surroundings by these vehicles relies on optical sensors such as lidars and cameras, it is essential to ensure the robustness of these systems from the early stages of the project. In this respect, experiments in climatic wind tunnels provide a solution for simulating the operating conditions that the autonomous vehicles will confront. This work proposes a method based on field measurements and unsupervised machine learning to faithfully reproduce in controlled environments real weather conditions captured during wintertime in Ontario, Canada. The purpose of this paper is not to investigate correlations between observed weather conditions and the characteristics of the precipitation encountered, but rather to establish a consistent method based on outdoor disdrometer data to identify critical parameters to be simulated in climatic wind tunnels. To achieve this goal, weather data such as temperature, relative humidity, and droplet size distribution were recorded at General Motors’s McLaughlin Advanced Technology Track (MATT) using an FD70 disdrometer and WXT530 weather transmitter, both manufactured by Vaisala, installed on a car provided by the Automotive Center of Excellent (ACE) team of the University of Ontario Institute of Technology. The implementation of the proposed method allowed the identification of precipitation clusters characterized by parameters of a theoretical model for particle size distributions fitted to the collected data.

Investigating energy production and wake losses of multi-gigawatt offshore wind farms with atmospheric large-eddy simulation

Abstract. As a consequence of the rapid growth of the globally installed offshore wind energy capacity, the size of individual wind farms is increasing. This poses a challenge to models that predict energy production. For instance, the current generation of wake models has mostly been calibrated on existing wind farms of much smaller size. This work analyzes annual energy production and wake losses for future, multi-gigawatt wind farms with atmospheric large-eddy simulation. To that end, 1 year of actual weather has been simulated for a suite of hypothetical 4 GW offshore wind farm scenarios. The scenarios differ in terms of applied turbine type, installed capacity density, and layout. The results suggest that production numbers increase significantly when the rated power of the individual turbines is larger while keeping the total installed capacity the same. Even for turbine types with similar rated power but slightly different power curves, significant differences in production were found. Although wind speed was identified as the most dominant factor determining the aerodynamic losses, a clear impact of atmospheric stability and boundary layer height has been identified. By analyzing losses of the first-row turbines, the yearly average global-blockage effect is estimated to between 2 and 3 %, but it can reach levels over 10 % for stably stratified conditions and wind speeds around 8 m s−1. Using a high-fidelity modeling technique, the present work provides insights into the performance of future, multi-gigawatt wind farms for a full year of realistic weather conditions.

Study on heat and moisture transfer characteristics of HPCMs

Phase change materials (PCMs) could be used in envelopes to moderate indoor temperature while hygroscopic materials could be used in envelopes to moderate indoor humidity. However, it remains unsolved whether these two materials are mixed to generate a better effect than single materials. Therefore, a transient model for coupled heat and moisture transfer through hygroscopic PCMs (HPCMs) was presented. The numerical cases of periodic boundary conditions and realistic weather conditions were conducted to investigate the heat and moisture transfer characteristics of three gypsum-based HPCMs containing different mass ratios of microencapsulated PCMs. Quantitative analyses were conducted to capture the effects of hygrothermal properties on heat and moisture transfer characteristics of HPCMs. The numerical results show that the mixing of PCMs and hygroscopic materials could generate a better temperature-humidity controlling effect than pure hygroscopic material, and the condensation risks inside the envelopes could also be reduced. Both the studied cases indicate that the HPCMs could be applied in building envelopes to passively moderate the indoor temperature and humidity simultaneously, reducing the building energy consumption and condensation risks inside the envelopes. The effects of hygroscopic and moisture transfer properties on temperature-control performance of HPCMs are relatively small, while the thermal properties play an important role in the improvement of temperature-humidity controlling performance of HPCMs with the increase of PCM concentration.

Prediction of the output power of photovoltaic module using artificial neural networks model with optimizing the neurons number

Artificial neural networks (ANNs) is an adaptive system that has the ability to predict the relationship between the input and output parameters without defining the physical and operation conditions. In this study, some queries about using ANN methodology are simply clarified especially about the neurons number and their relationship with input and output parameters. In addition, two ANN models are developed using MATLAB code to predict the power production of a polycrystalline PV module in the real weather conditions of Iraq. The ANN models are then used to optimize the neurons number in the hidden layers. The capability of ANN models has been tested under the impact of several weather and operational parameters. In this regard, six variables are used as input parameters including ambient temperature, solar irradiance and wind speed (the weather conditions), and module temperature, short circuit current and open circuit voltage (the characteristics of PV module). According to the performance analysis of ANN models, the optimal neurons number is 15 neurons in single hidden layer with minimum Root Mean Squared Error (RMSE) of 2.76% and 10 neurons in double hidden layers with RMSE of 1.97%. Accordingly, it can be concluded that the double hidden layers introduce a higher accuracy than the single hidden layer. Moreover, the ANN model has proven its accuracy in predicting the current and voltage of PV module.

Thermal Performance of Horizontal Fixed Sun Shading Device

Earlier investigations on passive cooling methods applied software modelling, and the findings were not confirmed through field measurement. Hence, this study applied a stationary experiment on a real structure and weather conditions employing horizontal sun shading (SDH). The purpose of this study was to compare the performance of fixed passive sun-shading devices put on to the bare façade of three-story terrace shophouses in Malaysia. The experiment findings revealed that SDH significantly improved the internal thermal environment by lowering the average monthly indoor air temperature (Ta) by 0.98 K and the peak temperature by 2.11 K. SDH is also effective during the warmest sunny days, lowering 1.23 K on average for the day. Meanwhile, SDH reduced the temperature in the control room by 5.40 K during the warmest peak time.When it came to indoor mean radiant temperature (Tmrt), SDH performed better than the control room in the very hot peakover a month (2.38 K) and on the highest temperature of the day (7.70 K). Finally, it can be inferred that SDH worked better from late at night until early in the morning, cooling the room temperature faster. This quiescent choice is one of the best for enhancing a building's internal thermal performance while also possibly contributing to a decrease in operational energy consumption.

Research on solar dish/Stirling engine driven adsorption-based desalination system for simultaneous co-generation of electricity and freshwater: Numerical investigation

Poly-production green systems are recently promising alternatives that could produce various useful energy outputs such as electricity, heat, and distilled water with higher efficiencies, lower costs, and eco-friendly benefits. Considering the superior advantages of the dish/Stirling power cycle and adsorption-based distillation system. This study investigates a detailed theoretical dynamic modeling and performance analysis of an adsorption-based distillation system powered by a solar dish/Stirling engine (ADS-SDSE) for combined electricity and freshwater dual-production. Numerical lumped models for the hybrid system components are developed using MATLAB to evaluate the electrical performance and freshwater production of the proposed ADS-SDSE. The models are considered based on opt-geometric approaches, energy balance analyses, and isotherm adsorption simulation to dynamically simulate the ADS-SDSE operation to analyze its performance under real weather conditions in Tianjin, China, for one complete year. The daily, monthly, and yearly performances of the ADS-SDSE are comprehensively evaluated in terms of net electric power, electrical efficiency, specific distilled freshwater productivity, specific cooling power, and the gained output ratio (GOR) of the hybrid system. It is found that the role of the Stirling engine rejected heat recovery remarkably enhanced the inlet feed hot water temperature feeding the adsorptions beds and became uniformly at (82.6−95 °C) throughout the day. Moreover, the proposed ADS-SDSE can produce an electrical power output of about 23.42 kW with solar to electricity efficiency of 23.40%, specific daily freshwater production (SDWP) of about 11.53 m3 per ton of silica gel, 320 W/kg of silica gel specific cooling power, and 0.62 GOR. Conclusively, it can be inferred that the proposed ADS can be powered efficiently by the waste heat of the solar dish/Stirling engine.

Hybridizing solar dish Stirling power system with single-effect desalination for sustainable electricity and freshwater co-generation: Mathematical modeling and performance evaluation

At present, poly-generation sustainable systems are highly promising pathways that could produce several beneficial energy outputs, such as electricity, heat, and freshwater, that have the potential to fulfill financial competitiveness and higher efficiencies. Considering the great advantages of the solar dish/Stirling cycle, this study introduces comprehensive theoretical modeling and performance analysis of a solar dish/Stirling-powered single effect distillation system (SDSPSEDS) for combined electricity, heat, and freshwater tri-production. A detailed mathematical model executed in MATLAB software based on energy balance and opt-geometric approaches was established to simulate the SDSPSEDS operation dynamically. In order to analyze its performance under real weather conditions of Tabuk, KSA, for four seasonal scenarios. The energetic performance of the hybrid SDSPSEDS is comprehensively evaluated in terms of net electric power, solar-to-electricity conversion efficiency, Stirling engine rejected heat, distilled freshwater productivity, and overall co-generation efficiency of the hybrid system. The simulation results show that the daily electrical energy produced by the SDSPSEDS is 234.7, 194.6, 159.8, and 190.0 kWh/day. In contrast, the daily freshwater production is obtained as 787.4, 657.3, 545.0, and 650.0 kg/day in June, September, January, and March, respectively. Moreover, it is also found that the overall daily co-generation efficiency of the hybrid SDSPSEDS is increased to 62.60%, 53.50%, 47.40%, and 52.96% compared to only daily average electrical efficiencies of 20.92%, 17.82%, 15.50%, and 17.60% attained; in the same examined seasonal days, respectively when utilizing only standalone solar dish/Stirling power system. Thus, the findings of this study proved that the hybrid SDSPSEDS is an efficient system to produce power and water in rural areas with no water piping network or electrical grid.

Development of Lightweight Geopolymer Composites by Combining Various CDW Streams

This study regards the development of lightweight geopolymer composites through the valorization of various construction and demolition wastes. Brick waste was utilized as the sole aluminosilicate precursor for the geopolymerization reactions, expanded polystyrene and polyurethane wastes were used as artificial lightweight aggregates, and short polyethylene fibers developed from CDWs reinforced the geopolymer matrix. The curing conditions of the geopolymer synthesis were optimized to deliver a robust geopolymer matrix (T = 25–80 °C, t = 24–72 h). Both raw materials and products were appropriately characterized with XRD and SEM, while the mechanical performance was tested through compressive strength, flexural strength, Poisson’s ratio and Young’s modulus measurements. Then, a comprehensive durability investigation was performed (sorptivity, wet/dry cycles, freeze/thaw cycles, and exposure to real weather conditions). In contrast to polyurethane waste, the introduction of expanded polystyrene (0.5–3.0% wt.) effectively reduced the final density of the products (from 2.1 to 1.0 g/cm3) by keeping sufficient compressive strength (6.5–22.8 MPa). The PE fibers could enhance the bending behavior of lightweight geopolymers by 24%; however, a geopolymer matrix–fiber debonding was clearly visible through SEM analysis. Finally, the durability performance of CDW-based geopolymers was significantly improved after the incorporation of expanded polystyrene aggregates and polyethylene fibers mainly concerning freeze/thaw testing. The composite containing 1.5% wt. expanded polystyrene and 2.0% v/v PE fibers held the best combination of properties: Compr. Str. 13.1 MPa, Flex. Str. 3.2 MPa, density 1.4 g/cm3, Young’s modulus 1.3 GPa, and sorptivity 0.179 mm/min0.5.

Innovative PCM-incorporated foamed concrete panels for walls’ exterior cladding: An experimental assessment in real-weather conditions

This study aims to develop innovative exterior cladding panels capable of improving the walls’ thermal performance for new and existing buildings. A phase change material (PCM) was incorporated into foamed concrete (FC) to develop innovative PCM-incorporated FC (PCM-FC) cladding panels, which were assessed as an exterior finishing of cement brick wall and compared to the conventional cement rendering. The test was conducted using reduced-scale testing cells in real-weather conditions and for four cardinal orientations. The developed PCM-FC cladding panels yielded remarkable reductions in the wall’s internal surface temperature and the cell’s internal air temperature, reaching 6.75 ℃ and 5.50 ℃, respectively. Moreover, the developed cladding panels performed effectively for the four cardinal orientations, yet their effectiveness varied according to the intensity and the time of receiving direct solar radiation. Furthermore, a low decrement factor of 0.49 and a 32.1% reduction in the intensity of overheating were obtained when using PCM-FC cladding panels compared to Ref-CR. The developed PCM-FC cladding panels substantiated superior thermal performance in reducing external heat gain, which results from the combined effects of PCMs’ high thermal energy storage and FC’s low thermal conductivity. Therefore, these PCM-FC cladding panels can potentially contribute to reducing buildings’ high energy consumption.

Experimental Electrical Assessment Evaluation of a Vertical n-PERT Half-Size Bifacial Solar Cell String Receiver on a Parabolic Trough Solar Collector

A two-trough parabolic-shaped concentrating photovoltaic solar collector with a vertical half-size ‘phosphorus-passivated emitter rear totally diffused’ bifacial cell string receiver was designed and built for household applications, with the aim of smooth the electrical ‘duck curve’. The study consisted in testing the concentrating photovoltaic solar collector outdoors, under real weather conditions, for its daily electrical peak power and efficiency, as well as for its electrical transversal and longitudinal Incidence Angle Modifier direction. The outdoor testing measurements were conducted in a parabolic trough with low concentration coupled with a central vertical half-size ‘phosphorus-passivated emitter rear totally diffused’ bifacial cell string receiver. Furthermore, the electrical transversal Incidence Angle Modifier showed to be very delicate due to the position and outline of the receiver, which led to an electrical peak efficiency close to 10% at ±25° (i.e., for an electrical power output of around 49.3 W/m2). To validate the measured parameters, a ray-tracing software has been used, where the measured Incidence Angle Modifiers have a very good agreement with the simulated Incidence Angle Modifiers (e.g., deviation of <4%). Consequently, the concentrating solar collector met the objective of lowering the Photovoltaic cell stress and high radiation intensity, by shifting the electrical peak power at normal (e.g., at 0°) to higher incidence angles (e.g., ±25°); this aids the electrical demand peak shaving, by having the highest electrical power production displaced from the highest intensity solar radiation during the day.

Effect of operating conditions and air filters maintenance on the performance and efficiency of gas turbine power plant

The purpose of this study was to evaluate the thermal performance of a gas turbine unit under real weather conditions by applying the first law of thermodynamics and studying the effect of the cleanliness of the air filters. The unit operated with a design power of 265 MW under standard conditions (15 °C, 1 bar pressure, and 60 % relative humidity). The current study also included analyzing the power unit using the MATLAB simulation program to know the effect of external factors (temperature, relative humidity, and compression ratio) for a whole year (2019) on the performance of the turbine unit. The results showed that the highest efficiency was obtained during the month of November (34 %) at a temperature of 19 °C and the lowest efficiency was achieved in August (23 %) at the highest recorded temperature of 46 °C. The results also showed that when filters were replaced in November, the efficiency and air mass flow rate increased by 21 % and 40 %, respectively.

Dynamic response-based crack resistance analysis of fibre reinforced concrete specimens under different temperatures and crack depths

Steel fibre-reinforced concrete has been used extensively because of its excellent mechanical properties. Academic researchers have comprehensively discussed the impact and challenges of fibre reinforcement to obtain optimal properties in the resultant concrete. Most researchers reported the mechanical performance of fibre-reinforced concrete (FRC) under static loads. A few studies did conclude the mentioned performance on dynamic loads. However, a comprehensive analysis is still missing that can explain the crack resistance performance of FRC under dynamic loads at relatively high temperatures. In this study, the efficacy of FRC beams for crack resistance is analyzed under coupled loads, i.e., dynamic load at relatively high temperatures as compared to room temperature. Various researchers found that concrete's qualities may change at different temperatures due to moisture content, physical and chemical changes to the ingredients, differences in cooling and heating schedules, water-to-cement ratio, and aggregate. The rate of reduction in moisture content is quite possible even in relatively high temperatures as compared to standard room temperature. Therefore, we selected a range of temperature that demonstrate tests on more realistic weather conditions for most of the concrete applications. As per theory, a slight change in modulus or strength shall definitely effect the dynamic response. Therefore, we tested cantilever FRC beams on a modal excitor in a band heater to expose the beams to bending loads at different temperature values. The variation in the beam's dynamic response parameters, including modal amplitude and frequency, is discussed, and compared with experimental results for regular and reinforced concrete beams. The SIF of plain concrete decreased as concrete temperature increased. Compared to conventional concrete, using SFRC-1 enhanced fracture resistance by 10–20% at various crack depths (2 mm, 4 mm, 6 mm) and temperatures (20 °C, 40 °C, 60 °C).

Retrofitting WASP to a RoPax Vessel—Design, Performance and Uncertainties

Wind-assisted propulsion (WASP) is one of the most promising ship propulsion alternatives that radically reduce greenhouse gas emissions and are available today. Using the example of a RoPax ferry, this study presents the performance potential of WASP systems under realistic weather conditions. Different design alternatives and system layouts are discussed. Further, uncertainties in the performance prediction of WASP systems are analyzed. Included in the analysis are the sail forces as well as the aero- and hydrodynamic interaction effects, i.e., the sail–sail and sail–deck interaction as well as the drift and yaw of the ship. As a result, this study provides guidelines on the most important parameters when designing and modeling a WASP ship. Finally, the study presents an analysis of the expected accuracy of the employed empirical/analytical performance prediction model ShipCLEAN.

Biodegradation properties of natural fibers for agro textile nonwovens production

The aim of this paper is to investigate biodegradation properties of PLA (as a bio-based polymer), Hemp, Jute (as natural bast fibers) and Viscose (as a cellulose regenerates) for agrotextile nonwovens production. For the purpose of those investigations, an analysis of the biodegradation time of samples were performed by soil burial test (ISO 11721 – Textiles – Determination of resistance of cellulose-containing textiles to microorganisms – Soil burial test) conducted under controlled conditions in laboratory and under real weather conditions. The samples were exposed in the soil for 4, 7, 9 and 11 days. An analysis of mass loss and changes in their mechanical properties, compared to unexposed samples, were determined.

Assessment of Ship Fuel Consumption for Different Hull Roughness in Realistic Weather Conditions

This paper presents the effect of hull roughness over 10 years of operation on ship performance. The numerical model is developed by coupling NavCad and Matlab to perform the computation and the data processing. On the basis of a given hull, an engine, and an optimized propeller, the performance of the ship is computed for eight cases of hull roughness according to the ITTC recommendations in both calm waters and different weather conditions along the ship route. The effect of both wind and waves is considered for computing the added ship resistance along the route, thus requiring more power than just only the added resistance in waves. This provides a more accurate estimation of the ship’s performance along the different sea states. Lastly, a weighted average of the main ship parameters is estimated to evaluate better the ship’s performance. According to this study, the fuel consumption in calm water can be increased by around 20% after 10 years of ship operation based on the level of hull roughness. However, in the same weather conditions along the ship route, the ship’s fuel consumption can be increased by 10% compared to the same trip with a clean hull.