Software Design Research Articles

NUMERICAL MODELLING OF RADIATOR SYSTEM PERFORMANCE UNDER BAUCHI CLIMATIC CONDITIONS

The cooling system of the car plays a crucial role in managing the excess heat generated by the engine during its operation. Among its components, the radiator is pivotal for efficiently dissipating heat. However, the effectiveness of a radiator is influenced by various factors, including external conditions such as atmospheric temperature, humidity, and wind speed. This research aimed to understand the impact of Bauchi climatic conditions on automotive radiators. A comprehensive approach was employed, utilizing reverse engineering techniques to create a detailed model of a car radiator using SolidWorks, a computer-aided design (CAD) software. This model underwent simulations using ANSYS software with water as the coolant fluid. Environmental temperature, humidity, and wind speed data for Bauchi North and Bauchi South were sourced from the Nigerian Meteorological Agency (NiMet). The simulation timeframe spanned from January to December. The study shows the effects of environmental temperature, humidity, and wind speed on radiator performance. The highest outlet temperature recorded was 43.50°C at a flow rate of 2500 kg/h in April, and the lowest outlet temperature was 40.01°C at a flow rate of 500 kg/h in Bauchi North. For Bauchi South, the highest outlet temperature was 40.98°C at a flow rate of 2500 kg/h in April, and the lowest was 37.12°C at a flow rate of 500 kg/h. This study highlights the pivotal role of Bauchi's atmospheric conditions in influencing radiator performance, emphasizing the interplay between environmental factors and engineering design in automotive cooling systems.

Numerical investigation and software design for internally finned helically coiled tubes heat exchangers with single-stream and multi-stream

To enhance the heat transfer inside the helically coiled tubes, a kind of internally finned helically coiled tubes is proposed. Compared to the smooth helically coiled tubes, the heat transfer and flow resistance characteristics of internally finned helically coiled tubes are investigated numerically. Influence of fin number, pitch and coil diameter on the performance is analyzed. Empirical correlations to calculate the Nusselt number and friction factor of internally finned helically coiled tubes are summarized. The helically coiled tubes heat exchangers are divided equally into several cells and the theoretical analysis of energy flow in each cell is carried out. According to the established equations of heat transfer, the calculation method for single-stream helically coiled tubes heat exchangers and multi-stream helically coiled tubes heat exchangers is proposed. The geometric model and thermohydraulic model are built up, and the design software for internally finned helically coiled tubes heat exchangers is developed based on Python. Take two cases of helically coiled tubes heat exchangers as examples, smooth helically coiled tubes and internally finned helically coiled tubes (fin number is six) are applied to validate the accuracy of calculations results obtained by design software. The results show that the deviation of outlet temperature and pressure drop is less than 7 % and 11 %, respectively. When applying internally finned helically coiled tubes, the heat transfer coefficient of the tube side is increased by approximately 30 %. The corresponding pressure drop and heat load is higher. The outlet temperature proves that the heat transfer is more insufficient in the case of internally finned helically coiled tubes (fin number is six).

Sustainable Design of Pavements: Predicting Pavement Service Life

Pavement service life is an important factor that affects both the whole life cost and carbon footprint of a pavement. The service life of a pavement is affected by several different parameters which can be broadly classified into climate conditions, binder and mixture properties, pavement design, workmanship, and maintenance strategies. The current practice for determining service life of pavements involves the use of pavement design tools, which are used while constructing a new pavement or performing a reconstruction/resurfacing or pavement maintenance. In addition, field measurements using ground penetration radar, falling weight deflectometer, traffic speed deflectometer, and other techniques are also used to assess the condition of an existing pavement. The information from these measurements is then combined with pavement design software to predict potential pavement service life. The accuracy of the predicted pavement service life is affected by the associated uncertainties in the parameters that affect pavement life. The following paper presents various approaches that could be potentially used to determine the associated uncertainties in the estimation of pavement service life. The various uncertainty quantification techniques have been applied to a specific design, and the outcomes are discussed in this paper. The Monte Carlo simulation method, a system-level uncertainty quantification technique, can estimate a probabilistic pavement service life. The other uncertainty quantification schemes are software specific and provide probabilistic life factors by assumed statistical distributions. Hence, the Monte Carlo simulation technique could be one potential method that can be used for estimating a generalized pavement service utilizing predictions from various design software.

Three-dimensional secondary reconstruction of mistreated zygomatic fractures using patient specific surgical guides and implants.

The zygomatic bone has a great impact on the anterior and lateral projection of the midface as well as the proper position of the globe. Primary alignment of zygomatic fractures is very important as secondary reconstruction is far more challenging. Treatment of misaligned zygoma requires refracturing of the bone to allow for repositioning. Due to the great impact of the zygoma on the projection of the midface, a precise 3D realignment is of great importance. Technology nowadays develops rapidly and allows for superior results in many surgical fields. The use of patient specific surgical guides and fixation plates is becoming more abundant. Using 3D segmentation and design software, we developed a sequence for using 3D planning and printing both for the refracturing stage, avoiding a coronal approach, and for precise repositioning and fixation of the zygoma in the new position. The method is described as well as a unique advanced 3D analysis, allowing for objectively assessing the results. Two cases are presented, including the design and post operative changes. Pre-op, planned and final positions were compared and showed exceptional accuracy allowing for the elimination of human errors which are common in a 3D sensitive procedure such as refracturing of the zygoma. This method can easily be applied to other secondary reconstruction procedures requiring realignment.

Robust and computationally efficient design for run-of-river hydropower

This paper introduces innovative approaches for robust and computationally efficient optimal design of run-of-river hydropower plants. Compared with existing design software, it (1) integrates optimized turbine operations into design optimization instead of following predefined operational rules, and (2) combines this with a regular sampling of the flow duration curve to significantly reduce data inputs. Our rigorous benchmarking demonstrates that (1) operation optimization improves design performance at low computational cost, whilst (2) data input reduction slashes computational costs by over 92% with minimal impact on design recommendations and key robustness analysis insights. Taken together, these innovations make integrated design and operation optimization, complete with in-depth robustness analysis, laptop-accessible. They also reinforce sustainability efforts by minimizing the need for high-performance computing and large associated embodied greenhouse gas emissions.

Proven Distributed Memory Parallelization of Particle Methods

We provide a mathematically proven parallelization scheme for particle methods on distributed-memory computer systems. Particle methods are a versatile and widely used class of algorithms for computer simulations and numerical predictions in various applications, ranging from continuum fluid dynamics to discrete granular flows and molecular dynamics simulations. Particle methods naturally lend themselves to implementation on parallel computing systems. So far, however, a mathematical proof of correctness and equivalence to sequential implementations was only available for shared-memory parallelism. Here, we leverage a formal definition of the algorithmic class of particle methods to provide a proven parallelization scheme for distributed-memory computers. We prove that thus parallelized particle methods on distributed-memory computers are formally equivalent to their sequential counterpart for a well-defined class of particle methods, and we provide analytical expressions for the speed-up and scalability bounds of this class of algorithms in function of their parameters. The parallelization scheme analyzed here is the basis of many real-world software designs for parallel particle methods. The present analysis is, therefore, of direct relevance to existing and new parallel implementations of particle methods and places them on solid theoretical grounds, rationalizing best practices and providing useful scalability and speedup bounds for benchmarking.

Comparative Study on the Interest in Non-Uniform Rational B-Splines Representation versus Polynomial Surface Description in a Freeform Three-Mirror Anastigmat

Novel freeform optical design methods can be classified in two categories, depending on whether they focus on the generation of a starting point or the development of new optimization tools. In this paper, we design a freeform three-mirror anastigmat (TMA) and compare different surface representations using either a differential ray tracer as a new optimization tool or a commercial ray tracer (ANSYS-ZEMAX OpticStudio). For differential ray tracing, we used FORMIDABLE (Freeform Optics Raytracer with Manufacturable Imaging Design cApaBiLitiEs), an optical design library with differential ray tracing and Non-Uniform Rational B-Splines (NURBS) optimization capabilities, available under the European Software Community License (ESCL). NURBS allow a freeform surface to be represented without needing any prior knowledge of the surface, such as the polynomial degree in polynomial descriptions. OpticStudio and other commercial optical design software are designed to optimize polynomial surfaces but are not well-suited to optimize NURBS surfaces, requiring a custom optical design library. In order to demonstrate the interest in using NURBS representation, we designed and independently optimized two freeform telescopes over different iteration cycles; with NURBS using FORMIDABLE or with XY polynomials using OpticStudio. We then compared the resulting systems using their root mean square field maps to assess the optimization quality of each surface representation. We also provided a full-system comparison, including mirror freeform departures. This study shows that NURBS can be a relevant alternative to XY polynomials for the freeform optimization of reflective three-mirror telescopes as it achieves more a uniform imaging quality in the field of view.

Establishing a CAD-CAM workflow for stabilization appliances (Michigan splints).

Stabilization appliances (Michigan splints) are considered well-studied and widely adopted for managing bruxism and temporomandibular disorders (TMDs). Traditionally, these appliances have been fabricated by wax modeling and pressing resin onto casts made from irreversible hydrocolloid or silicone impressions. This article provides a detailed description of an all-digital workflow that uses intraoral scanning and computer-aided design (CAD) software to design a stabilization splint on a digital cast that can be manufactured autonomously by a computer-aided manufacturing (CAM) grinding machine in a subtractive procedure. The workflow is applicable to both dentists and technicians. Special attention is given to aspects and procedures that are important for the successful fabrication of the splint. Working without a cast can save time and money, and the use of CAD-CAM technology provides a homogeneous splint material quality.

The design of LLRF system for STCF storage ring

The Super Tau Charm Facility (STCF) is a new generation of high brightness electron–positron collider planned by China, designed to achieve a center of mass collision energy is 2–7[Formula: see text]GeV and a peak brightness is 0.5–[Formula: see text][Formula: see text]cm[Formula: see text]s[Formula: see text]. The digital low-level RF control system (LLRF), as the essential equipment of the storage ring RF system, is usually responsible for maintaining the stability of the cavity field. This paper presents the design scheme of LLRF for cavity in STCF storage ring, which mainly includes the hardware structure and software design of the system. We perform simulation analysis on the STCF RF system to evaluate the influence of delay and control parameters on the stability of the system and the influence of control parameters on the suppression of two kinds of noise. Desktop testing on the existing prototype demonstrates that the adopted direct-sampling architecture introduces less phase drift compared to the down-conversion architecture. Under the direct-sampling architecture, non-IQ demodulation offers better SNR and stability in both amplitude and phase. Specifically, direct-sampling in non-IQ mode achieves open-loop RMS short-term stability of 0.019% for amplitude and 0.021∘ for phase. Long-term stability in the closed-loop setting measures 0.027% for amplitude and 0.024∘ for phase.

Movement and positioning of a virtual cuboid in 3d space in an augmented reality environment

Human-virtual object interaction is common in both entertainment and work settings. This study investigated the movement time (MT) and subjective rating of difficulty (SRD) for moving a virtual cuboid in a 3D space. The participants wore an augmented reality (AR) headset, picked up a virtual cuboid, and placed it on an assigned target. They rated the SRD of the task on a five-point scale. The effects of the 3D coordinate of the target, sex, and handedness on the MT were analysed. The error placement rate was also recorded. Significant effects of spatial coordinates were found on both MT and SRD. Both single- and two-stage MT modelling were conducted using segmented and unsegmented MT data, respectively. The insignificant prediction error between the models indicates that the two-stage MT model is not superior to the single-stage one. The findings of this study are beneficial to software designers in designing user-friendly AR applications.

Text-to-Model Transformation: Natural Language-Based Model Generation Framework

System modeling language (SysML) diagrams generated manually by system modelers can sometimes be prone to errors, which are time-consuming and introduce subjectivity. Natural language processing (NLP) techniques and tools to create SysML diagrams can aid in improving software and systems design processes. Though NLP effectively extracts and analyzes raw text data, such as text-based requirement documents, to assist in design specification, natural language, inherent complexity, and variability pose challenges in accurately interpreting the data. In this paper, we explore the integration of NLP with SysML to automate the generation of system models from input textual requirements. We propose a model generation framework leveraging Python and the spaCy NLP library to process text input and generate class/block definition diagrams using PlantUML for visual representation. The intent of this framework is to aid in reducing the manual effort in creating SysML v1.6 diagrams—class/block definition diagrams in this case. We evaluate the effectiveness of the framework using precision and recall measures. The contribution of this paper to the systems modeling domain is two-fold. First, a review and analysis of natural language processing techniques for the automated generation of SysML diagrams are provided. Second, a framework to automatically extract textual relationships tailored for generating a class diagram/block diagram that contains the classes/blocks, their relationships, methods, and attributes is presented.

Dynamic Measurement Method for Steering Wheel Angle of Autonomous Agricultural Vehicles

Steering wheel angle is an important and essential parameter of the navigation control of autonomous wheeled vehicles. At present, the combination of rotary angle sensors and four-link mechanisms is the main sensing approach for steering wheel angle with high measurement accuracy, which is widely adopted in autonomous agriculture vehicles. However, in a complex and challenging farmland environment, there are a series of prominent problems such as complicated installation and debugging, spattered mud blocking the parallel four-bar mechanism, breakage of the sensor wire during operation, and separate calibrations for different vehicles. To avoid the above problems, a novel dynamic measurement method for steering wheel angle is presented based on vehicle attitude information and a non-contact attitude sensor. First, the working principle of the proposed measurement method and the effect of zero position error on measurement accuracy and path tracking are analyzed. Then, an optimization algorithm for zero position error of steering wheel angle is proposed. The experimental platform is assembled based on a 2ZG-6DM rice transplanter by software design and hardware modification. Finally, comparative tests are conducted to demonstrate the effectiveness and priority of the proposed dynamic sensing method. Experimental results show that the average absolute error of the straight path is 0.057° and the corresponding standard deviation of the error is 0.483°. The average absolute error of the turning path is 0.686° and the standard deviation of the error is 0.931°. This implies the proposed dynamic sensing method can accurately realize the collection of the steering wheel angle. Compared to the traditional measurement method, the proposed dynamic sensing method greatly improves the measurement reliability of the steering wheel angle and avoids complicated installation and debugging of different vehicles. The separate calibrations for different vehicles are not needed since the proposed measurement method is not dependent on the kinematic models of the vehicles. Given that the attitude sensor can be installed at a higher position on the wheel, sensor damage from mud blocking and the sensor wire breaking is also avoided.

Quantum computing intelligence algorithm for structural topology optimization

Structural topology optimization methods that are driven by the geometric features of components, such as the Moving Morphable Component (MMC), are widely explored due to their convenient interaction with design software. However, these methods exhibit significant sensitivity to the initial positioning of components, limiting their suitability for applications involving complex geometric boundaries. This study addresses these challenges by introducing a novel dual-layer optimization framework that employs a quantum computing-based intelligent optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). The potential drawbacks of the MMC method in engineering applications, particularly its sensitivity to initial conditions, are critically examined, leading to the proposal of a global-gradient hybrid framework for geometry feature-driven topology optimization. This proposed method demonstrates superior capability in optimizing material arrangements compared to the original MMC framework and enhances engineering applicability, making it more suitable for real-world applications. Through three representative examples, the limitations of the original MMC method are illustrated, and the advantages of the proposed dual-layer framework are highlighted. The results indicate that this method not only overcomes sensitivity issues but also stably identifies superior configurations, particularly for structures with complex geometric boundaries, providing models that facilitate interaction with CAD systems. This method offers a robust and precise approach for optimizing designs in various engineering fields.

Novel algae-chitosan/alginate beads for efficient basic Fuchsin removal: Synthesis, characterization, adsorption study, mechanism, and optimization

In this study, utilized algae activated with citric acid and lime juice to develop a novel bioadsorbent, The Algae@CS/Alginate beads were formed by encapsulating the activated algae with chitosan and alginate, producing a nanocomposite that is efficient in removing Basic Fuchsin (BF) dye from water. The beads were characterized by means of a diversity of techniques, such as FTIR, XRD, XPS, SEM and determination the surface area via N2 adsorption/desorption isotherm that permitted that the adsorbent has high surface area 124.43 m2/g. The electrical properties of the BF, including its structure and reactivity, were determined by density functional theory (DFT). The MEP data and the molecular orbitals (HOMO and LUMO), as well as the sites of the electrophilic besides nucleophilic attack places, correspond fairly well, according to DFT. The adsorption process was fitted to Langmuir isothermally, and kinetically to pseudo-second-order (PSOE) model. The adsorption mechanism was identified as chemisorption with an adsorption energy of 32.6 kJ/mol. Thermodynamic research shows that the BF adsorption process by Algae@CS/Alginate beads is spontaneous and endothermic because of the positive ΔHo and negative ΔGo. Through numerical optimization of the programmed, the ideal conditions for adsorption were strongminded to be a pH of 8, a dosage of 0.02 g/25 mL for Algae@CS/Alginate beads, and a concentration of 367.27 mg/g of BF. Using the least amount of intended experiments, the adsorption procedure was optimized by the request of Box-Behnken design (BBD) and answer surface methodology (RSM) in Design-Expert software. Adsorbent reusability test results showed that, following eight successive cycles of adsorption and desorption, the adsorbent was stable and that removal efficacy had not decreased. It additionally demonstrated good efficacy, no alteration in chemical conformation, and the same XRD and FTIR data before and after recycle. Analyze the interaction between the Algae@CS/Alginate beads and the BF.

Detecting refactoring type of software commit messages based on ensemble machine learning algorithms

Refactoring is a well-established topic in contemporary software engineering, focusing on enhancing software's structural design without altering its external behavior. Commit messages play a vital role in tracking changes to the codebase. However, determining the exact refactoring required in the code can be challenging due to various refactoring types. Prior studies have attempted to classify refactoring documentation by type, achieving acceptable results in accuracy, precision, recall, F1-Score, and other performance metrics. Nevertheless, there is room for improvement. To address this, we propose a novel approach using four ensemble Machine Learning algorithms to detect refactoring types. Our experimentation utilized a dataset containing 573 commits, with text cleaning and preprocessing applied to address data imbalances. Various techniques, including hyperparameter optimization, feature engineering with TF-IDF and bag-of-words, and binary transformation using one-vs-one and one-vs-rest classifiers, were employed to enhance accuracy. Results indicate that the experiment involving feature engineering using the TF-IDF technique outperformed other methods. Notably, the XGBoost algorithm with the same technique achieved superior performance across all metrics, attaining 100% accuracy. Moreover, our results surpass the current state-of-the-art performance using the same dataset. Our proposed approach bears significant implications for software engineering, particularly in enhancing the internal quality of software.

Development and implementation of a method for checking the integrity of the design of an object-oriented system

Creating modern software products is a complex and long process consisting of many parts. To achieve quality, it is necessary to carry out various measures for testing and verifying software at all stages of development. This article discusses the software design stage, which is integral and one of the most important. In most software development life cycle (SDLC) models, this stage is one of the first, so design mistakes will lead to problems in all subsequent stages. Thus, due to the high cost of error, it is very important to check the integrity of the developed design at the design stage. The article examines the problem of finding contradictions in object-oriented design. The authors present a set of contradictions that can arise in such a design and aim to develop methods and algorithms for detecting and searching for these contradictions in order to improve the quality of the design, as well as writing software that will implement these algorithms and methods. The program "diagrams.net" was chosen as a tool for creating object-oriented design, the main useful feature of which is the ability to present the created diagrams in the form of an XML file in the popular drawio format. The authors of the study propose a method for parsing the XML file of the diagram and presenting it as a set of objects, such as dependency arrows, classes, methods, etc. These objects must interact according to the established rules.The violation of these rules is a contradiction of the object-oriented design. As a result of the study, a method of finding contradictions was presented and implemented in the Java programming language.

Development of Fruit Based Flavored White Cheese

Cheese is important food constituents among the processing dairy product. Nowadays flavored white cheese is alternatively provided as food product in order to increase consumer acceptance throughout the world. However, flavored cheeses not familiar to consume in Ethiopia. Hence the aim of this study was to develop and evaluate the nutritional and sensory appeal of fruit flavored white cheese. A total of 20 liters of fresh milk were brought from Holeta dairy research livestock farm so as to process the cheese. The fruits (Lemon & Orange) were purchased from Holeta fruit juice shops. The experiment was conducted in five treatments such as 3% fruit flavored cheese, 6% fruit flavored cheese, 9% fruit flavored cheese, 12% fruit flavored cheese and the control (cheese without fruit flavored) using mixture expert design software. Physicochemical of pH, titratable acidity, moisture content, ash content, crude protein, crude fat, mineral and sensory evaluation were done following standard procedures. All the samples were analyzed in duplicate. The sensory attributes were done using five hedonic scale by 15 semi-trained panelists. In this study the result showed that the highest mean score of pH value (6.04) for 12% fruit flavored cheese, Moisture content (3.76%) for 6% flavored cheese and Crude Fat (17.85%) for 3% flavored cheese respectively. Although the highest mean value of Ash (11.55%) and Crude Protein (53.72%) shown in the control. A significant difference (P<0.05) was shown by only Mg among Ca, Fe, Zn and K. Moreover, Color, flavor, odor, texture and overall acceptance shown no significant difference (P>0.05) from Sensory attributes. In conclusion, using fruit flavored cheese may enhance the nutritional quality and sensory acceptance of the cheese. This research study will provide good information for those working on fruit juice shops as well as juice industries to use as alternative product.

BioSense: An automated sensing node for organismal and environmental biology

Automated remote sensing has revolutionized the fields of wildlife ecology and environmental science. Yet, a cost-effective and flexible approach for large scale monitoring has not been fully developed, resulting in a limited collection of high-resolution data. Here, we describe BioSense, a low-cost and fully programmable automated sensing platform for applications in bioacoustics and environmental studies. Our design offers customization and flexibility to address a broad array of research goals and field conditions. Each BioSense is programmed through an integrated Raspberry Pi computer board and designed to collect and analyze avian vocalizations while simultaneously collecting temperature, humidity, and soil moisture data. We illustrate the different steps involved in manufacturing this sensor including hardware and software design and present the results of our laboratory and field testing in southwestern United States.

A Wireless Ad Hoc Network Communication Platform and Data Transmission Strategies for Multi-Bus Instruments

As automatic test technology advances, the number of programmable instruments in a single test system increases. Traditional wired communication methods have a limited range and involve complex cable layouts. Single-function wireless converters provide a viable alternative, but they have limitations. These include complicated configuration, issues with multi-system collaboration, and data blocking. This paper proposes a wireless ad hoc network platform for multi-bus instruments based on a low-cost ESP-12H WiFi module. The platform supports GPIB, RS232, RS485, and CAN bus interface instrument access. It features easy configuration, ad hoc networking, and self-repairing capabilities. A relay multi-hop network with a tree topology expands capacity and coverage. Additionally, a dynamic window-receiving mode and an improved multi-priority queue ensure data transmission integrity. The experimental results show that the platform’s networking time is less than 10 s, and the coverage range reaches 50 m in complex indoor environments. It also shows good stability when running for a long time. However, due to hardware and software design limitations, the actual upload speeds fall short of the theoretical values. For example, RS232 and RS485 are about 10% slower than the theoretical values, and GPIB is about 80% slower. Further optimization is required in the future.

Design of a 2R Open-Chain Plug Seedling-Picking Mechanism and Control System Constrained by a Differential Non-Circular Planetary Gear Train

With a focus on the problems of complex structure and accumulated lateral clearance in the single degree of freedom non-circular wheel system seedling-picking mechanism, which leads to poor motion accuracy, trajectory, and attitude, this study developed a 2R open-chain chili plug seedling-picking mechanism (SPM) constrained by a differential non-circular wheel system. The picking arm was driven by a single-stage non-uniform speed transmission mechanism to reproduce the seedling-picking trajectory and attitude. A protruding seedling-picking device, SPM control system, and test bench were designed. A kinematic model of a differential non-circular gear system was established, and an optimization design software for the SPM was developed based on kinematic analysis. The kinematic characteristics of the SPM were analyzed under optimal parameters. This study completed the seedling-picking performance test of the SPM on the control panel. The test showed that the designed chili SPM can sequentially complete the processes of seedling picking, conveying, retracting, pushing, and returning under the automatic control of the test bench without damaging the main root. The lateral root damage rate was 15.7%, effectively ensuring the integrity of the seedling bowl substrate.