System Design Applications Research Articles

Design and construction of a website-based librarian application system in Bali

This study focuses on the development of a web-based application system related to the functional positions of librarians in Bali. This web-based application is designed as a one-stop service to provide essential functional position information for librarians. The primary research question asked is how to design and construct a web-based librarian application system in Bali. The objective of this study is to design, develop, and evaluate a system that supports librarians in managing their activities and credit scores. The development method used is the linear sequential (waterfall) method, which includes the stages of analysis, design, coding, implementation, testing, and maintenance. This system features a user interface with functions such as Home, Activity Details, Forms, and a List of Librarians, enabling librarians to manage various activities organized into categories of Expert Librarians and Skilled Librarians. Each activity comprises a menu for librarian type, education, library management, services, librarian system development, professional development, and task support, which are further broken down into sub-activities according to their categories. Application testing was carried out using the Black Box Testing method to ensure that all functions operated according to user needs. This system was implemented as a web-based application using PHP and MySQL databases, allowing librarians to access it online. The implementation results show that this application has run well and is able to meet the needs of librarians in managing their functional positions efficiently, simplifying the credit score submission process, and enhancing accuracy and efficiency in reporting.

Technical and economic simulation of a hybrid renewable energy power system design for industrial application

Countries in Africa rank the highest in low energy accessibility and air pollution globally. Presenting the urgent need to explore renewable energy sources to tackle the power challenge and reduce the carbon footprint for a greener atmosphere. A novel hybrid wind and solar renewable energy power system (HREPS) coupled to a battery that is capable of powering industrial appliances in the Basse district of The Gambia has been proposed. The HREPS size was estimated automatically with the PVsyst software taking into account the PV power and battery capacity based on the load profile and loss of load probability, with all the necessary meteorological, technical, and economic factors. The optimal size was possible with 20 photovoltaic modules (250 W) and 1 Wind generator (1 KW) compatible with the annual load requirement of about 2555 MWh. These results suggested that the HREPS is reliable for the user’s load demand in all the tested meteorological conditions of the study area. When the HREPS is linked to any other renewable source, it shows the potential of gaining about 8395 kWh annually in the battery. The continuous operation of the hybrid system for 21 years presents a net gain of > 400% for the standalone systems with a projected gain of > 600% when linked to a small smart grid system. Since high taxes may scuttle these gains, it is recommended that the Government encourage investment in renewable energy power systems by subsidizing the taxes on the purchase of items to make them more affordable.

Capacitance-based mass flow rate measurement of two-phase hydrogen in a 0.5 in. tube

Mass flow rate is a critical measurement parameter when designing cryogenic hydrogen fluid systems. It is important in custody transfer applications for calculating financial obligations, fundamental fluid property research/modeling, and fluid system design applications to optimize chill down performance, maintain thermal equilibriums, and provide feedback control for pumps and valves. However, due to the large temperature differential between cryogenic fluids and the environment, there is often multiphase flow during system chilldown and steady state operation. Current available cryogenic flow measurement techniques are not equipped to deal with the complex multiphase flow inherent in cryogenic fluid systems, resulting in significant measurement errors. This mass flow measurement inaccuracy can cause financial loss, system instability, and even component failure, resulting in a strong market demand for a multiphase cryogenic mass flow meter to optimize and control sophisticated and costly cryogenic systems. This paper presents a solution in the form of a novel capacitance-based technique for measuring the multiphase mass flow rate of cryogenic hydrogen in a terrestrial environment. The device was calibrated and tested on a ½” tube multiphase hydrogen flow loop at a cryogenic hydrogen test facility. An error of ± 2 % full scale was achieved across a range of flow conditions, including transient and steady states.

AI and Machine Learning Solutions for Real-Time Fault-Tolerant System Design in Critical Applications

This study presents an innovative framework for implementing real-time fault-tolerant systems using artificial intelligence (AI) and machine learning (ML) to enhance reliability and resilience in critical applications. Addressing the needs of sectors such as aerospace, healthcare, automotive, and industrial automation, the proposed system integrates fault detection, isolation, and recovery mechanisms into a multi-layered architecture. Through the use of deep learning for accurate anomaly detection and reinforcement learning for rapid fault isolation, the system achieves high fault tolerance with minimal latency. The framework leverages edge computing for real-time data processing, ensuring timely responses to faults without excessive computational demands. Results from multiple case studies demonstrate significant improvements in fault detection accuracy, isolation speed, and recovery rates, affirming the framework’s adaptability and effectiveness in high-stakes environments. These findings highlight the potential of AI-driven fault-tolerant systems to elevate operational safety and reliability standards across diverse critical industries.

R744 Refrigeration Solution for Small Supermarkets

Application based technology solution is nowadays preferred to achieve the performance of the cooling system configuration at its best. Therefore, benchmarking is an essential criterion which would add value to the optimum system design for various applications. In this study, a case study is carried out for a Milk Bar (small supermarket) to evaluate the potential of R744 cooling system for the similar cooling demand and tropical conditions. Field data collected during a particular time and temperature zone is further used to develop a yearly round performance of the HFC plug-in cabinets for MT and LT applications. The data is further used to develop a centralized R744 booster system that would meet the similar cooling load and demand of all the cabinets in the shop. Based on the cooling loads for the HFC unit, the yearly performance of the R774 booster system is calculated and compared to the existing plug-in solution. It is observed that the yearly electric energy consumption for the R744 centralized refrigeration system is 3.3 M W·h, 24% lower than with the existing solution based on HFCs. Moreover, the economic prospective of the R744 is further discussed to alternative material for the components and centralized unit structure which could empower the system with more reliability and an effective substitute to the synthetic technology for smaller supermarkets. This article is a translation of the article by Singh S, Pardiñas ÁÁ, Hafner A, Schlemminger C, Banasiak K. R744 Refrigeration Solution for Small Supermarkets. In: Proceedings of the 9th IIR Conference on the Ammonia and CO2 Refrigeration Technologies. Ohrid: IIF/IIR, 2021. DOI: 10.18462/iir.nh3-co2.2021.0030 Published with the permission of the copyright holder.

Design Of Simulation Application System For Corporate Income Tax

The design of the corporate income tax simulation application system aims to provide an effective and efficient tool for companies in calculating income tax liabilities in accordance with applicable tax regulations. The research method used is to start identifying problems through literature studies related to corporate taxes and interviews with users. Then analyze the needs related to the required features, security, performance and ease of use. The development system used is the waterfall model method. The waterfall model method is one of the software development models in the SDLC (Sequencial Development Life Cycle) model. Waterfall models are often also called linear sequence models or classic life flows. Key features developed include an intuitive user interface, flexibility in handling companies of various sizes, and strict data security to protect sensitive financial information. With a comprehensive design and focusing on user needs, this application is expected to be a reliable solution in supporting corporate income tax management.

System Design, Modelling, Energy Analysis, and Industrial Applications of Ohmic Heating Technology

AbstractThe food and drink industry is gradually gaining sustainability pressure due to the high carbon emissions rate and limited availability of traditional energy supplies. Thus, it is essential to consider energy efficiency and decarbonisation of the ever-expanding food and drink industry. Ohmic heating technology is a highly energy-efficient and quick method of electrically heating food products. It uses the resistance of the food material to convert electrical energy into heat. However, the heating rate of ohmic heating depends on several process variables, such as electrical conductivity, voltage gradient, and voltage frequency. Therefore, it is important to study and understand the effects of these process variables to optimise the modelling and control of ohmic heating systems to obtain desirable output from food products. Hence, this study presents a review of the effects of process parameters on nutritional and organoleptic qualities, product yields, and energy efficiency of ohmic heating, along with its various industrial applications. The technology shows promising advancements in colour and nutritional quality, increasing energy efficiency, shorter processing times, and higher product yields compared to conventional heating processes.

Integration of extended reality and CAE in the context of industry 4.0

ABSTRACT Simulation plays a major role in the development of new products and is considered one of the nine technological pillars of Industry 4.0. By encapsulating a plethora of digital tools, simulation has transitioned towards what is known as Computer Aided Engineering (CAE), which further enables engineers to validate the design and ensure product performance. The development of cutting-edge digital technologies, such as Extended Reality (XR), has also gained attention aiming at the facilitation of human-machine interface (HMI) and the creation of communication channels for improved remote collaboration. The contribution of this study lies in the design and development of a cloud-based framework for the integration of CAE tools with Mixed Reality (MR), specifically, Computational Fluid Dynamics (CFD), focusing on industrial refrigeration systems design and editing applications. Furthermore, the developed solution provides augmented 3D visualizations overlaid on the existing installations. The proposed framework supports the virtual co-existence of engineers during the design phase, thus enabling collaboration and mentoring between experienced and young engineers. Additionally, it can be realized as a Cloud platform, which supports the distribution of several services such as storage of CAD files, simulation results, and the XR application for the setup and visualization of simulation results.

Pemodelan Sistem Pakar Identifikasi Tingkat Stres Karyawan dengan Metode Certainty Factor

Expert systems work by collecting knowledge from experts in the form of rules or knowledge bases, then using an inference engine to analyze situations and produce decisions or suggestions. Apart from that, it is often used in the fields of medicine, engineering, finance, etc., related to this, especially the process of identifying the level of stress experienced by employees in the company so that they can find out more, therefore an expert system application design is needed for identification using the method. certainty factor, based on the certainty factor which has a concept based on symptoms and diagnoses from the weight of an expert's value and the user's value, calculated using the formula in CF, the final result is the creation of an expert system application for identifying employee stress levels based on a website.

Experimental investigation on the thermal enhancement of spherical macro-encapsulated phase change material assisted soil heat accumulators

Reserved cavities during construction have the potential to serve as the space to efficiently harness shallow geothermal energy resources in light of the underground spaces' rapid expansion. Earth-air heat exchanger technology is an effective way among all the technologies. However, as the heat storage capacity of the surrounding soil gradually diminishes due to the long-term operation of the system, it is recommended to incorporate phase change materials (PCMs) with a stabilized heat storage capacity to improve the overall thermal performance of the system. This research specifically recommends back-filling macro-encapsulated PCMs measuring 15–25 mm in order to prevent backfill contamination caused by PCM leakage. The shells and cores of the PCMs are polypropylene spheres and n-heptadecane. Different volume proportions of macro-encapsulated PCMs are used in the design of modified soil accumulators. 27 groups of orthogonal array experimental tables were made using the Taguchi method to test the improved heat accumulator's performance with different heating sources. According to the results, adding PCMs causes the peak temperature to change and increases overall energy storage by 7.2 %. The most significant factor is the soil moisture content, which accounts for 62.47 % of the overall impact of the PCM's heat storage ratio and total heat storage capacity. With a contribution of 20.41 %, the PCM ratio is ranked second. Furthermore, optimization options for the primary parameters that impact the total heat storage and heat storage ratio of the PCM are offered. This paper offers references for the potential use of the PCM-assisted EAHE system design in real-world engineering applications.

Electrical conductivity based algorithm for precise application of liquid nitrogenous fertilizers

Precise application of nitrogenous fertilizers mainly urea ammonium nitrate (UAN) and granular urea (both pure and neem-coated) in aqueous form, is critically important for basal and foliar applications. The physicochemical properties of aqueous solution of these nitrogenous fertilizers plays important role in design of any liquid fertilizer application system. The study was carried out during 2019–20 at ICAR-Indian Agricultural Research Institute, New Delhi with an aim to develop algorithms for use in sensors-based systems for real time monitoring of available N concentration in the fertilizer solution before its application. The physicochemical properties like pH, electrical conductivity (EC), specific gravity (SG), dynamic viscosity (DV), surface tension (ST) and percentage light absorbance (LA) of urea ammonium nitrate (UAN-28%), pure urea, and neem coated urea in diluted form (pre-selected N-concentrations i.e. 0.78, 0.9, 1.08, 1.33, 1.75, 2.54 and 4.67% corresponding to the dilution ratios of 1:35, 1:30, 1:25, 1:20, 1:15, 1:10 and 1:05) were measured and analyzed for their significance with N-concentration. Electrical conductivity (EC) alone showed a significant relationship with N-concentrations. Prediction models were developed for diluted UAN and granular urea fertilizers based on the EC and N-concentrations. The regression models in terms of EC to predict N-concentration had coefficients of determination (R2) of 0.998, 0.998, and 0.999 for diluted UAN, pure urea, and neem coated urea with water, respectively showed a great potential for their sensor based precise application. The controlled application of diluted liquid fertilizers with water can be achieved through sensing relevant physicochemical property.

Impedance matching in optically induced dielectrophoresis: Effect of medium conductivity on trapping force.

An impedance analysis for optically induced dielectrophoresis is presented. A circuit model is developed for this purpose. The model parameters are fully defined in terms of the geometrical and material properties of the system. It is shown that trapping force can only be generated when the material properties follow certain impedance matching conditions. The impedance match factor is introduced to succinctly quantify the phenomenon. It is used to calculate bounds on the allowed electrical conductivity of the suspension medium. Results from the proposed model are found to be in good agreement with full-wave numerical simulations. By computing the acceptable set of material parameters with little computational cost, the presented analysis can streamline ODEP system design for various applications.

Implementation of the Multimedia Development Life Cycle (MDLC) in Solar System Application Design

Augmented Reality (AR) technology has had an impact on changes in the world of education, especially improving the quality of education which has positively influenced the learning and teaching process, with the use of tools in education it has proven effective in improving the learning and teaching environment in the classroom and even changing the way we view education. This research aims to design a solar system application as an alternative AR-based learning media by integrating 3D models, animation and video to improve the learning experience of students, especially students of SDN Larangan 5 Tangerang. This is based on the lack of student learning experience, especially regarding the solar system material which is still lacking and not yet varied because so far SDN Larangan 5 has not used technology, especially AR technology in the learning process and still uses book texts and videos. This research used the Multimedia Development Life Cycle (MDLC) method and usability testing was carried out using the System Usability Scale (SUS) method with a total of 33 respondents with a test result of 78 which indicates the level of user satisfaction with the solar system application that has been tested on the respondents.

Photon counting CT clinical adoption, integration, and workflow.

Photon counting CT was recently introduced into clinical practice [Rajendran K, Petersilka M, Henning A, Shanblatt ER, Schmidt B, Flohr TG, Ferrero A, Baffour F, Diehn FE, Yu L, Rajiah P, Fletcher JG, Leng S, McCollough CH. First Clinical Photon-counting Detector CT System: Technical Evaluation. Radiology 2022;303(1):130-138. doi: https://doi.org/10.1148/radiol.212579 ]. Photon counting detectors (PCD) afford better spatial resolution, radiation dose efficiency, and iodine contrast-to-noise than EID-CT [Leng S, Bruesewitz M, Tao S, Rajendran K, Halaweish AF, Campeau NG, Fletcher JG, McCollough CH. Photon-counting Detector CT: System Design and Clinical Applications of an Emerging Technology. Radiographics 2019;39(3):729-743. doi: https://doi.org/10.1148/rg.2019180115 ); (Leng S, Rajendran K, Gong H, Zhou W, Halaweish AF, Henning A, Kappler S, Baer M, Fletcher JG, McCollough CH. 150-mum Spatial Resolution Using Photon-Counting Detector Computed Tomography Technology: Technical Performance and First Patient Images. Invest Radiol 2018;53(11):655-662. doi: https://doi.org/10.1097/RLI.0000000000000488 )(Booij R, van der Werf NR, Dijkshoorn ML, van der Lugt A, van Straten M. Assessment of Iodine Contrast-To-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data. Diagnostics (Basel) 2022;12(6). doi: https://doi.org/10.3390/diagnostics12061467 ); (Sawall S, Klein L, Amato C, Wehrse E, Dorn S, Maier J, Heinze S, Schlemmer HP, Ziener CH, Uhrig M, Kachelriess M. Iodine contrast-to-noise ratio improvement at unit dose and contrast media volume reduction in whole-body photon-counting CT. Eur J Radiol 2020;126:108909. doi: https://doi.org/10.1016/j.ejrad.2020.108909 ] while also maintaining multienergy CT (MECT) capabilities[Flohr T, Petersilka M, Henning A, Ulzheimer S, Ferda J, Schmidt B. Photon-counting CT review. Phys Med 2020;79:126-136. doi: https://doi.org/10.1016/j.ejmp.2020.10.030 ]. This article will review the clinical adoption of PCD-CT including protocol development, clinical applications, clinical integration and workflow considerations. Protocol development is institution specific and involves collaborative decision-making among radiologists, physicists, and technologists. Key PCD clinical applications include radiation exposure reduction, intravenous contrast volume reduction, and improved lesion conspicuity. Patients who would most benefit from these improvements may preferentially be scanned with PCD CT. With numerous available reconstructions, radiologists should be strategic in the series sent to PACS for interpretation and routinely sending spectral series to PACS can facilitate integration with clinical workflow. The Society of Abdominal Radiology PCD Emerging Technology Commission endorsed this article.

The Actuating Characteristics of Magnetorheological Fluids Subjected to Particle Sedimentation and Temperature Variation

Magnetorheological (MR) fluids are known for their controllable characteristics under the influence of magnetic fields and, hence, widely used as semi-active actuators for vibration control. Regardless of advantages such as fast response time and reversible property, MR fluids inevitably experience sedimentation caused by significant density mismatches between magnetic particles and carrier liquids. Moreover, the effect of the temperature on actuating characteristics is also one of the problems to be resolved for practical implementation. This study experimentally investigates the sedimentation behavior under various temperatures ranging from 25 to 70 °C using a multiguide-arm magnetic device that generates a uniform magnetic flux density across MR fluids. The sedimentation stability is then observed after 168 h at current inputs of 0, 1, and 2 A, respectively. Subsequently, the field-dependent rheological properties of MR fluids are evaluated using a rheometer and discussed, showing actuating capability, which depends on the viscosity, shear stress, and yield stress before (initial state) and after the sedimentation (sedimentation state). The field-dependent yield stresses, which directly represent the actuating force of the semi-active actuator, are specifically evaluated. Under the on-state condition (2 A) at a temperature of 70 °C, the yield stress decreased from 2.747 kPa (initial state) to 2.352 kPa (sedimentation state). By using this yield stress, the field-dependent damping force was evaluated, showing a decrement from 1672 N (initial state) to 1623 N (sedimentation state) at a velocity of 0.8 m/s. It is shown that the temperature causes the reduction of the actuating properties after the long-term operation. The insightful findings achieved in this work will provide useful information for the evaluation of actuating characteristics of smart MR fluids and the design of MR application systems subjected to particle sedimentation and temperature variation.

3D network-on-chip data acquisition system mapping based on reinforcement learning and improved attention mechanism

The three-dimensional Network-on-Chip (NoC) data acquisition system is designed to create a time-interleaved data acquisition system using NoC technology. In the design of NoC application systems, optimizing the mapping algorithm can effectively reduce network communication latency. Aiming at the mapping challenge of a large number of functional IP nodes in 3D NoC data acquisition system, the reinforcement learning and improved attention mechanism mapping algorithm (RA-Map) is proposed. The RA-Map mapping algorithm employs node function encoding and node position encoding to express the properties of an IP node in the task graph preprocessing. The local attention mechanism is used in the mapping network encoder, and the fusion of dynamic key node information is proposed in the decoder. The mapping result evaluation network achieves unsupervised training of the mapping network. These targeted improvements improve the quality of the mapping. Experimental results show that the RA-Map mapping algorithm can effectively model the IP core mapping. Compared with the DPSO algorithm and SA algorithm, the average communication cost of RA-Map mapping algorithm is reduced by 6.5 % and 8.5 %, respectively.

A direct and analytical method for inverse problems under uncertainty in energy system design: combining inverse simulation and Polynomial Chaos theory

This article introduces and formalizes a novel stochastic method that combines inverse simulation with the theory of generalized Polynomial Chaos (gPC) to solve and study inverse problems under uncertainty in energy system design applications. The method is particularly relevant to design tasks where only a deterministic forward model of a physical system is available, in which a target design quantity is an input to the model that cannot be obtained directly, but can be quantified reversely via the outputs of the model. In this scenario, the proposed method offers an analytical and direct approach to invert such system models. The method puts emphasis on user-friendliness, as it enables its users to conduct the inverse simulation under uncertainty directly in the gPC domain by redefining basic algebra operations for computations. Moreover, the method incorporates an optimization-based approach to integrate supplementary constraints on stochastic quantities. This feature enables the solution of inverse problems bounding the statistical moments of stochastic system variables. The authors exemplify the application of the proposed method with proof-of-concept tests in energy system design, specifically performing uncertainty quantification and sensitivity analysis for a Multi-Energy System (MES). The findings demonstrate the high accuracy of the method as well as clear advantages over conventional sampling-based methods when dealing with a small number of stochastic variables in a system or model. However, the case studies also highlight the current limitations of the proposed method such as slow execution speed due to the optimization-based approach and the challenges associated with, for example, the curse of dimensionality in gPC.

Augmented Reality Applications in Mechanical System Design and Prototyping

With the integration of computer-generated images and data into the real world, augmented reality (AR) is a game-changing technology that improves users' perceptions and interactions with their surroundings. This technology, which can overlay digital data on real-world environments, has great potential for use in several fields, such as mechanical system design and prototyping. The use of AR in this industry is not just a theoretical idea; rather, it is a rapidly developing reality with enormous potential for creativity, effectiveness, and accuracy. Augmented Reality (AR) is a technology that combines the physical and digital worlds to provide a composite vision that improves the user's sense of reality. Augmented Reality (AR) superimposes digital data in real-time over the actual world, in contrast to Virtual Reality (VR), which submerges users in a fully digital environment. Usually, gadgets like tablets, smartphones, AR glasses, and head-mounted displays (HMDs) help with this integration. The term "mechanical system design" describes the entire process of imagining, creating, and perfecting mechanical parts and systems; it includes everything from rough concept drawings to intricate engineering models and simulations. Before moving on with full-scale manufacturing, prototyping entails building early models or samples of a product to test and verify design concepts.

Development and Application of Substation Grounding Grid Topology Detection and Recognition System

Abstract To solve the problem of substation grounding grid faults difficult to diagnose in the case of non-power non-excavation, based on the inductive apparent magnetic resistance method developed a set of grounding grid topology detection and identification systems, to achieve non-destructive detection and real-time imaging of the grounding grid location, structure, breakpoints, and other information to identify and rebuild the topology of the grounding grid. The paper introduces the system design and practical experiments and applications in a substation in Guangzhou City, the system has achieved good application results, reaching the level of engineering prototype, the development of the system device has a good practical significance, and has a broad application prospect.

Predictive control method for mode transition process of multi-mode turbine engine based on onboard adaptive composite model

In order to achieve precise control of thrust and flow during the mode transition(MT) process of multi-mode turbine engine(MMTE) within the switching envelope and under the condition of engine performance degradation, research on multi-mode model predictive control method is conducted. A mode transition trajectory optimization method based on SQP is explored, and a small range of adjustable parameters that ensure the continuous thrust and flow is obtained. Based on this, a multi-mode onboard modeling approach based on the directional adjustment law scheduling of the variable geometry adjustment mechanism is proposed. Furthermore, an investigation into a predictive control method for MT process based on onboard adaptive composite model is conducted. The simulation results demonstrate that the proposed method exhibits a maximum thrust fluctuation of less than 0.66 % during MT process, under both normal and degraded engine component performance conditions, which is significantly superior to the conventional PID control of 2.8 %. Compared to the average single step calculation time of 7.24 ms using the SQP optimization method, the proposed approach only requires 0.204 ms. The methodology presented takes into consideration of control accuracy and computing efficiency, thereby offering promising prospects for engineering applications in MMTE MT control system design.