System Design Research Articles

Design considerations for a continuous mussel farm in New England Offshore waters. Part I: Development of environmental conditions for engineering design

Sustainable aquaculture in nearshore waters faces challenges such as stakeholder conflicts, environmental pollution, and spatial constraints. Offshore aquaculture offers a promising solution but requires robust engineering design to withstand extreme weather conditions. This study develops the environmental conditions essential for engineering the design of a continuous mussel dropper system in New England offshore waters. A potential farm location was identified using criteria including water depth, federal boundaries, seafloor suitability, farm size, and proximity to ports, based on bathymetric and sedimentary maps. Historical data from five wave monitoring stations and two current velocity stations were analyzed to model extreme environmental conditions, as waves and currents pose primary threats. The extreme wave and current conditions are modeled using the Weibull distribution, on the annual maximum hourly significant wave height data and the largest 0.3% of current speeds. A newly proposed method combining Spalding’s wall function with a fourth-order polynomial is used to enhance the current profile analysis. Additionally, a joint probability density function was developed for wave height and current velocity at a specific depth, providing insights into wave height, period, and wavelength for various return periods such as 10, 25, 50, and 100 years. The results suggest a 10-yr wave of 8 m significant wave height and a current speed of 1.68 m/s, while a 50-yr values are 9.4 m and 1.96 m/s respectively. These findings offer critical data on extreme wave and current conditions in New England’s offshore waters, providing practical guidance for the engineering design of offshore mussel farms. This research advances offshore mussel farming and benefits the development of all types of offshore aquaculture systems.

Proposal design and thermodynamic optimization of an afterburning-type isothermal compressed air energy storage system integrated with molten salt thermal storage

The isothermal compressed air energy storage is a potential technique for large-scale energy storage. In this study, the molten salt thermal storage is integrated with the afterburning-type isothermal compressed air energy storage system, which uses liquid piston compression technique, to enhance the thermal performances. Thermodynamic models of the hybrid energy storage system were developed, and the genetic algorithm was used to optimize multiple parameters to enhance the energy efficiency. Four operation modes, i.e., the high, medium-high, medium-low, and the low output power modes were proposed, to enhance the operational flexibility of the hybrid energy storage system. When the system operates in the operation mode of medium-low output power, a portion of afterburning heat is stored in the molten salt and used in the operation mode of low output power. Results show that the roundtrip efficiency of high, medium-high, medium-low, and the low output power modes are 63.57 %, 59.33 %, 57.13 %, and 83.28 %, respectively. Exergy analysis was carried out to quantify the irreversibilities of key components. In the three modes of operation with afterburning, the combustion chamber has the highest portion of exergy loss, and in the operation mode without afterburning, the exergy loss of heat exchangers is higher than that of expanders.

Wind-induced response and control criterion of the double-layer cable support photovoltaic module system

The cable support photovoltaic module system has obvious characteristics of wind-induced vibration. In order to study the wind-induced vibration response characteristics and mechanism of the double-cable support photovoltaic module systems, and further discuss the stiffness control criterion. The wind-induced vibration response of a new type of cable-truss support photovoltaic module system with a span of 35m is studied through the aeroelastic wind tunnel test. Firstly, the scaled aeroelastic test model was established to meet the aeroelastic test requirements. Then, the effects of wind direction, PV module inclination angle, and stability cable initial prestress on the wind-induced vibration response characteristics under uniform flow and turbulent field are studied. Finally, the wind-induced vibration response mechanism and stiffness control criterion are discussed. The results show that the increase of inclination angle will lead to a decrease in critical wind speed, the 0° wind direction is the most unfavorable, and the increase of initial prestress can increase the critical wind speed but is inefficient. The critical wind speed under the turbulent flow field is about 30% higher than that of the uniform flow field. The instability vibration is the result of multi-mode coupled vibration of vertical bending and torsion. It is suggested that the stiffness control criterion is more appropriate as 1/100. The research results are of great significance for the design and application of the cable support photovoltaic module system.

Solid-state anaerobic digestion of sweet corn waste: The effect of mixing and recirculation interval

The mixing and sludge recirculation interval is one of the key successes of the solid-state anaerobic digestion process, a promising technology for converting high-solid agro-industrial wastes to renewable energy. This study employed a pilot-scale completely stirred tank reactor to examine biogas production from sweet corn waste, including corn cobs, husks, and seeds. The reactor was operated as solid-state anaerobic digestion at an ambient temperature. The mixing and recirculating intervals were set to non-mixing and mixing for 10 minutes every 3, 6, and 12 hours. The initial total solid of the feedstock was 25%, while the hydraulic retention time was 30 days. The results showed that during the mixing and recirculation every three hours, the highest chemical oxygen demand, total solid, and volatile solid (VS) removal efficiencies were 85.42%, 62.92%, and 64.59%, respectively. The ratio between volatile fatty acid and alkalinity ranged between 0.20 and 0.30 without any sign of system failure. The highest specific methane yield of 766 L/kg VSadded was obtained in the experiment with mixing and recirculating intervals every 3 hours. It was found that the modified Gompertz model could effectively fit the methane yields with an R2 of 0.9667. The modeled methane production potential and the maximum methane production rate were 867.40 NL/kg VSadded and 132.01 NL/kg VSadded-d, respectively. Additionally, the levelized cost of the biogas produced from the solid-state anaerobic digestion of the sweet corn waste was calculated to be 0.61 USD/kg. The findings of this study can serve as a guide for the design and operation of the SS-AD system, which aims to transform various types of lignocellulosic waste into environmentally friendly energy.

Design of IoT-based monitoring system for temperature and dissolved oxygen levels in catfish aquaculture pond water

<span>One of the fish in Indonesian waters that has been successfully bred and cultivated is the catfish (Pangasius sp.). In catfish farming, there are several water quality factors that need to be considered, such as temperature and dissolved oxygen levels. Based on the existing description, it is very important to pay attention to the water quality of aquaculture ponds, especially temperature and dissolved oxygen levels for fish survival. This study aims to create an internet of things (IoT) based monitoring system for temperature and dissolved oxygen levels in catfish aquaculture pond water based on NodeMCU ESP8266. Monitoring system is using SEN0237 gravity analog dissolved oxygen sensor, DS18B20 sensor module, NodeMCU ESP8266, 20×4-character liquid-crystal display (LCD), micro secure digital (SD) card module, internet modem. Data from measurements of temperature and dissolved oxygen levels are stored online in the Adafruit.io database in the .csv format and on a micro secure digital (SD) card in the device in the .txt format. The lowest value of dissolved oxygen levels and temperature are 3.4 mg/L or 3.4 ppm and a temperature of 27.9 °C, respectively. Meanwhile, the highest value of dissolved oxygen levels and temperature are 4.6 mg/L or 4.6 ppm and temperature of 30.9 °C, respectively.</span>

Prediction of building cooling load: an innovative design for GA-SVM and IG-SVM system for the estimation of hourly precision and computational fluctuation range

ABSTRACT Anticipating the loads that buildings will bear is a crucial strategy in the pursuit of energy efficiency and the reduction of emissions. In this paper, we introduce an interactive and comprehensive joint prediction model, specifically crafted to elevate the precision of forecasts related to building loads. The resultant Genetic Algorithm-Support Vector Machine (GA-SVM) prediction model is put into action to provide hourly predictions of cooling loads for buildings. In scenarios where the prediction of building cooling load (BCL) fluctuations becomes imperative, especially in the face of extreme weather conditions, the information granulation (IG) method is employed. The findings of this validation process unveil significant improvements. The coefficient of variation of root mean square error (CV-RMSE) and mean absolute percentage error (MAPE) for the GA-SVM model are reduced by 58.85% and 68.04%, respectively, when compared to the conventional SVM model. Furthermore, in a comparative analysis against three widely utilized prediction models, the SVM model demonstrates a reduction in CV-RMSE and MAPE ranging from 2.04% to 68.04%. The application of the joint prediction model showcases impressive results, with R 2 values ranging from 97.27% to 99.68%, MAPE ranging from 2.59% to 2.84%, and CV-RMSE ranging from only 0.0249 to 0.0319.

Lifetime design, operation, and cost analysis for the energy system of a retrofitted cargo vessel with fuel cells and batteries

Lifetime design, operation, and cost analysis for the energy system of a retrofitted cargo vessel with fuel cells and batteries

Optimal design and experimental testing of EMPI system for plasma disruption mitigation on J-TEXT

Plasma disruptions can cause significant damage to tokamak. Currently, the primary method for mitigating disruptions is the injection of a substantial amount of impurities. The electromagnetic injection method offers a high injection speed and rapid response time, making it a promising technique for impurity injection. The first Electromagnetic Pellet Injection System (EMPI), developed by the J-TEXT team, is capable of launching pellets at high velocities and features a specialized deceleration rail that ensures safe separation of the armature and pellet. However, this system lacks an armature recovery device and a vacuum system. In this work, a second generation EMPI has been developed, which has a vacuum system and a curved recovery rail. The curved recovery rail facilitates the smooth retrieval of the armature, enhancing the safety of the recycling process. Additionally, this new system employs an augmented rail design that improves launch performance. Test results indicate that the maximum current of the new EMPI has been reduced by approximately 60%, while the maximum launch speed has increased by around 20%.

Key Design and Dehumidification Effect Testing of a New Dry Air Protection System for Main Cables

Key Design and Dehumidification Effect Testing of a New Dry Air Protection System for Main Cables

Pasteables: A Flexible and Smart “Stick-and-Peel” Wearable Platform for Fitness and Athletics

Wearable technologies are becoming increasingly popular and transforming our fitness and sports industry. Monitoring health parameters and body activity can help achieve fitness goals, improve sports performance, and aid in physiotherapy. However, state-of-the-art wearable devices are often not flexible, expensive, hard to set up, or have privacy concerns. They are designed and optimized for a specific application with tight hardware-software integration and it is hard or impossible to re-purpose them for diverse use cases. In this paper, we propose a flexible, re-configurable human body movement and health monitoring platform, called "Pasteables". It is a stick-and-peel device (which acts like a band-aid) that attaches to the skin or clothing and can create an on-body network of smart wearables. Given an application, Pasteables can be easily adapted to its requirements while ensuring good performance and privacy. We present the overall architecture, system design steps, and the configuration process. We have designed a set of functional prototypes and configured them for performing a variety of camera-less pose and posture detection tasks, which are important for athletes, professional dancing, physiotherapy, and fitness workouts. We note that the Pasteables can perform pose/posture detection without external stationary reference at low cost and high accuracy.

Stability analysis and multi-objective optimization of methanol steam reforming for on-line hydrogen production

The potential solution to hydrogen storage and transportation challenges is provided by liquid fuel-based on-line hydrogen production. An online hydrogen production device has been constructed and the stable output of hydrogen at 6.8 bar under dynamic conditions of 6–13 Nm3/h has been achieved. To achieve optimal economic and thermodynamic performances, the mathematical models for mass, energy, and techno-economics are constructed based on field test data. The Non-Dominated Sorting Genetic Algorithm is employed to update temperature splitting points between multi-stage heat exchangers, targeting multi-objective optimization of heat exchange area, system energy efficiency, and annual average cost. Pareto optimal solutions indicate that such optimization can improve system energy efficiency by 0.03%–3.76% and decrease the hydrogen production cost from 0.004 $/kg to 0.599 $/kg. This work demonstrates the feasibility and effectiveness of multi-objective optimization for online hydrogen production system design and offers important guidance for decision-making in heat exchange network schemes.

Thermal analysis of packed bed thermal energy storage system with dimpled spherical capsules

The thermal storage potential of a packed bed filled with paraffin wax capsules was examined. Heat transfer fluid (HTF) at 70 °C inlet temperature for dimpled and plain stainless-steel capsules was compared for three different flow rates, 1 L/min, 3 L/min and 5 L/min. In general, dimpled spherical capsules sustain more heat than plain spherical capsules at the same flow rate, according to instantaneous and cumulative heat stored. Spherical capsules with dimples exhibited a 30 % improvement in charging rate compared to smooth spheres, particularly at elevated flow rates. Specifically, at a flow rate of 5 L/min, dimpled capsules achieved faster charging and sustained higher temperature compared to plain capsules. Higher flow rates (3 and 5 L/min) result in steeper temperature increases and an earlier peak temperature phase compared to the lower flow rate (1 L/min). Key dimensionless heat transfer numbers were examined. The Stefan number was found to be 0.1966 for an HTF inlet temperature of 70 °C and a latent heat of fusion (Lm) of 213 kJ/kg. Heat transfer increases when Reynolds numbers increased from laminar (123.8 at 1 L/min) to turbulent (619.1 at 5 L/min). Rayleigh number decreased over time but increased for dimpled capsules, indicating improved convection. Dimpled capsules had higher Nusselt numbers and increases with flow rate, indicating better convective heat transfer. Dimpled capsules absorbed heat faster and stored more energy, giving them a viable and efficient Packed Bed Latent Thermal Energy Storage system design.

Research on the aero-hydro coupling characteristics of the floating twin-rotor wind turbine system

The concept of installing two wind turbines on a floating platform, known as a floating twin-rotor wind turbine system, has recently garnered significant interest. This configuration can harness greater wind energy resources, reduce installation and mooring costs by sharing mooring lines, and minimize losses due to wake effects between turbines through yaw control. However, previous research has not sufficiently addressed the dynamic performance analysis of such systems. This study focuses on a high-capacity floating twin-rotor wind turbine system and develops an aero-hydrodynamic coupled analysis method based on the free vortex wake method and potential flow theory, specifically tailored for the twin-rotor configuration. This method facilitates real-time iterative calculations of wind and wave loads acting on the system and suggests optimization strategies for its design. Our findings indicate that the design of high-capacity floating twin-rotor systems can significantly reduce costs. Furthermore, the twin-rotor floating system design enhances wake recovery and achieves optimal comprehensive performance when the rotor spacing ratio (S/D) is 1.2 for the IEA 15 MW turbine. The coupled interactions induce periodic variations in aerodynamic performance, with the amplitude of these variations increasing with turbulence intensity. This research lays a theoretical foundation for advancing the design, platform optimization, and coupled computational analyses of large-capacity, large-scale floating twin-rotor wind turbine systems.

GPS Tracking and Indoor Navigation System

This project is an idea of developing an application based on a navigation system formed by Graph Data Structure. An indoor positioning system (IPS) can be thought of as a global positioning system (GPS) for indoor venues. While GPS is used outdoors, IPS can detect real-time locations to accurately determine the coordinates of people or assets inside a building. These coordinates are typically represented visually by a blue dot on a digital indoor map to provide additional context to users and features such as wayfinding. The project aims to have certain objectives such as a tracking system, navigation system that is inside a small area of a building. This idea aims to track the location of any particular device within a building and show a navigation to that device in an efficient manner. Not only tracking of devices but also solving a problem of finding a particular room in the building through data of different paths that is stored. This project comes under the intelligent system design and development domain and falls under the sector of analysing and designing hardware, software and operating systems for computers. The main objective of this system design is to navigate through the area and find places to reach with ease and as fast as possible, it is helpful for people who are new at that place and even finding a user in that particular vicinity by live tracking technique.

Arduino performance in control systems for converting air-to-water

Humans are unable to function without water. Water is therefore necessary for living. This study will address the advantages of converting air into drinkable water based on this premise. Regarding the condensation process itself, it is not the best option to use it in remote locations because it needs a lot of energy and equipment. Consequently, thermoelectric technology was used in this study to replace the condensation process. This tool's easier thermoelectric operation makes it suitable for usage in remote locations. The design of an effective Arduino program control system should take into account the effects of temperature and humidity condition parameters on the environment to maximize water production. This will allow the performance between supporting sensors and the main components to be automatically optimized under a variety of environmental conditions and produce water without wasting excessive energy. As a result, the trial where the average temperature was 30°C and the average humidity was 81% produced the highest results for the researchers when they calculated the environmental condition factors that were already known. Within the hour-long study session, 6 milliliters of water were created. In addition to the efficiency with which the Arduino program is commanded, from all sensors to the primary thermoelectric components, it can execute commands automatically and optimally. It can also resolve issues that affect the air-to-water converter controller's performance in a way that ensures proper operation of all controllers by taking into account the relevant factors. to the fullest without squandering too much energy

Pressurization System under Various Operating Conditions for Smoke Control

The importance of smoke control systems has been emphasized for a safe evacuation and efficient firefighting activities during fire situations. To protect stairwells from smoke hazards, ‘Design Guide for Smoke Control System of Special Evacuation Stairwell and Lobby (NFPC501A)’ has been presented. In domestic area, pressurization systems utilize an air supply system consisting of fans, ducts, and dampers for supplying the outdoor air to the lobbies . For a 10-story model building, the design of the pressurization system must consider the leakage/supply flow rate, pressure loss, and fan performance. In this study, the flow field of the pressurization system under various operating conditions was analyzed using CONTAM network model.

Fault Detection in Transmission Line

Abstract: This project focuses on the design and implementation of an advanced fault detection system for overhead transmission lines, utilizing key components such as the ESP 8266 microcontroller, current sensors, a GPS module, and IoT integration. The system is capable of detecting and classifying four major fault types: single line to ground (L-G), line to line (LL), double line to ground (L-L-G), and three-phase faults (L-L-LG). By placing current sensors at the transmission line's sending end, the system identifies faults and accurately determines their location through GPS coordinates .Simulations using protect us software were conducted to verify the system’s performance prior to building a hardware prototype. Upon fault detection, the system provides alerts via an LCD display and a buzzer, while real-time fault data is transmitted to an Android app and web server through the arduino IoT cloud. Testing confirmed the system’s precision in fault identification and location tracking, ensuring timely notifications for control room and remote device operators. This successful implementation highlights the system's potential for improving safety and efficiency in power transmission networks. the project lays the groundwork for further exploration into advanced fault detection and real-time monitoring solutions in electrical engineering.

Analysis of Wind Response of Braced and Unbraced Tall Building

As high-rise buildings become increasingly prevalent worldwide, their complex structural components and the need for high stability pose challenges for safety and design requirements. The present study investigates the influence of bracing systems and plan aspect ratios on the ability of tall buildings to withstand wind loads. The study aims to analyze the effects of these variables on the wind-induced responses of tall buildings and improve bracing system design for structures with high aspect ratios. Numerical simulations using finite element analysis software are conducted, creating various building models with different aspect ratios and bracing systems. The displacement, drift, base shear responses and time period of each model are examined to evaluate the effectiveness of different bracing systems. The results highlight the significant impact of aspect ratio on the response to wind loads, with larger aspect ratios experiencing greater motion and stress. However, well-designed bracing systems prove effective in reducing wind-induced motion and stress. The study provides insights on best bracing system for different aspect ratios, offering valuable insights for creating safer and more resilient high-rise buildings.

Comparison of SEMG-Based Hand Gesture Classifiers

Machine learning techniques have shown success in classifying hand gestures. As the prevalence of prosthetic devices continues to rise, the adoption of non-invasive technologies, such as surface electromyography (sEMG), becomes paramount. This study systematically assesses the isolated influence of classification algorithms within hand gesture recognition (HGR) systems using sEMG data and dynamic time warping (DTW) based features. This approach effectively handles temporal variations in sEMG signals by leveraging DTW, ensuring input features are invariant to gesture speed. Six supervised learning classifiers were evaluated: the multilayer perceptron, support vector machine, logistic regression, linear discriminant analysis, k-nearest neighbors, and decision tree. Cross-validation was employed to fine-tune the segmentation hyperparameters, significantly improving results. To ensure reproducibility, the source code has been made available, the proposed system design has been detailed, and the evaluation protocols have been described. Our findings indicate that logistic regression outperformed other classifiers in this setup, achieving 95.2% accuracy in classifying six hand movements from ten healthy individuals, representing a 1.6% improvement over the best previously reported performance using the same publicly available dataset. Future research will assess the proposed HGR system’s generalization capability on larger datasets suitable for training more complex classifiers, including deep learning models.

Design and Implementation of a Community Waimai Delivery Assistant System Based on Path Optimization Algorithm

With the rapid development of the food delivery industry, how to efficiently complete delivery tasks in complex community environments has become an important challenge for food delivery platforms and delivery personnel. This project focuses on the problem of planning delivery routes for b0oth inside and outside residential areas, and designs and implements a delivery assistant system based on the Internet of Things and path optimization algorithms. The system utilizes the DFRobot IoT platform to achieve real-time communication between Python programs and mobile apps. Through various path optimization algorithms such as genetic algorithm and simulated annealing algorithm, the system automatically generates the optimal delivery path, significantly improving delivery efficiency and reducing delivery costs. The experimental results show that the system has good operability and reliability in practical applications, providing an effective solution for improving the intelligence level of food delivery