Software Design Research Articles

Improving the enzymatic activity and stability of N-carbamoyl hydrolase using deep learning approach

BackgroundOptically active D-amino acids are widely used as intermediates in the synthesis of antibiotics, insecticides, and peptide hormones. Currently, the two-enzyme cascade reaction is the most efficient way to produce D-amino acids using enzymes DHdt and DCase, but DCase is susceptible to heat inactivation. Here, to enhance the enzymatic activity and thermal stability of DCase, a rational design software “Feitian” was developed based on kcat prediction using the deep learning approach.ResultsAccording to empirical design and prediction of “Feitian” software, six single-point mutants with high kcat value were selected and successfully constructed by site-directed mutagenesis. Out of six, three mutants (Q4C, T212S, and A302C) showed higher enzymatic activity than the wild-type. Furthermore, the combined triple-point mutant DCase-M3 (Q4C/T212S/A302C) exhibited a 4.25-fold increase in activity (29.77 ± 4.52 U) and a 2.25-fold increase in thermal stability as compared to the wild-type, respectively. Through the whole-cell reaction, the high titer of D-HPG (2.57 ± 0.43 mM) was produced by the mutant Q4C/T212S/A302C, which was about 2.04-fold of the wild-type. Molecular dynamics simulation results showed that DCase-M3 significantly enhances the rigidity of the catalytic site and thus increases the activity of DCase-M3.ConclusionsIn this study, an efficient rational design software “Feitian” was successfully developed with a prediction accuracy of about 50% in enzymatic activity. A triple-point mutant DCase-M3 (Q4C/T212S/A302C) with enhanced enzymatic activity and thermostability was successfully obtained, which could be applied to the development of a fully enzymatic process for the industrial production of D-HPG.

Efficiency Analysis of a Passive Daylighting System Based on Northern Malaysia’s Climate

Daylighting design strategy is important in order to have adequate lighting source in a room and necessary to decrease energy consumption for artificial lighting. Passive daylighting system utilizes daylight by collecting, reflecting and diffusing the natural light throughout a given area. The purpose for this study is to monitor, compare and analyse an optimum light pipe system design that can scatter daylight into a room based on three case studies. Lighting analysis was conducted using Autodesk 3ds Max Design software throughout the project based on the actual geographical parameters of Universiti Malaysia Perlis, Malaysia and also using the real sun azimuth on working hours. The results were compared according to the respective designs in order to observe the maximum internal illuminance and the average internal illuminance. The results show that the straight geometry with low aspect ratio produces the highest interior light intensity among other light pipe systems and the average internal illuminance values in the room was able to reach the minimum requirement of a small room which is 200 – 500 lux.

Problem Faced During the Software Development Cycle

The software development cycle cover a series of stages , each compelling to the successful design of software products. Though each stage illustrates eccentric challenges that can block progress and impact the final product’s quality. This paper examines the common problems faced during the software development cycle , including issues in requirements gathering , design , implementation , testing , and maintenance. Through a precise analysis of these stages , we recognize basic interference such as unclear requirements , scope creep , inappropriate structure , coding errors , integration challenges , insufficient testing ,and technical liability. The paper also proposes methods to ease these concern , aiming to enhance the efficiency and effectiveness of software development processes. By understanding and addressing these problems , software development teams can enhance the project outcomes and deliver higher-quality software products. Keywords— Software development , requirements gathering , software design , coding errors , integration challenges , software testing , scope creep , inappropriate structure , technical liability , software cycle .

Hardware and Software Design of Programmable Medium and High-Speed Data Acquisition (DAQ) Board of Fiber Optic Signal for Partial Discharge Acquisition

The anti-electromagnetic interference capability of partial discharge (PD) acoustic signal conversion and collection circuits severely restrict the sensitivity of PD detection. The data acquisition (DAQ) systems available in the current market are costly and have limited functionality, making it difficult to satisfy the acquisition requirements for PD detection. This paper proposes a medium to high-speed fiber optic signal acquisition board with an adjustably controlled sampling rate and filter cutoff frequency. The circuit achieves a higher signal-to-noise (SNR) ratio by distributing the noise in each part of the signal acquisition chain reasonably. The temperature characteristics of the acquisition module are improved by utilizing the programmable T-type structure for transimpedance amplification of photocurrent. The DAQ card performs data acquisition and processing using STM32H743 internal ADC and caches data in bulk with an SRAM and SD card. A data uploading method based on time reference has been proposed, which enables full, effective information signal upload through a low-cost transmission interface. The research ultimately achieves a stable sampling of three channels at 1 MSps, SNR of 63 dB, and programmable gain amplification of the photocurrent with 0–60 dB. Finally, the system is used for PD acoustic signal acquisition in the frequency range of 20 Hz to 100 kHz.

Savonius-Magnus Hybrid Turbine Design Performance Based on Computational Fluid Dynamics

Savonius turbine is a vertical-axis wind turbine (VAWT), which has the advantage of being able to capture wind from different directions. This turbine is suitable for high turbulent wind areas. The blade on the Savonius turbine used in this study is equipped with a Magnus rotor with dimensions of 120 mm in diameter and 720 mm in height. The main purpose of this study is to determine the torque and pressure generated by turbines with three and four blades. The design was then tested numerically with variations in wind velocity. The simulation model was created using computer-aided design software, namely Autodesk Inventor 2023, and then inputted into computational fluid dynamics (CFD) software, namely Ansys Workbench 2022 R2. Wind velocities were varied by 3, 5, 7, 9, and 11 m/s and simulated using transient time with constant wind velocity. The result of this study is that the largest pressure is generated by a hybrid turbine with four blades at a wind velocity of 11 m/s. The results show that the torque and wind pressure that occurs in three- and four-blade hybrid turbines tend to rise; the faster the wind, the higher the torque and pressure of both hybrid turbines

A Novel 3D-Printed Gravity-Independent Air-Eliminating Filter for Rapid Intravenous Infusions.

INTRODUCTION: The absence of a consistent downward G vector can make separation of gases from liquids challenging, such as in field medicine without stable upright equipment or during spaceflight. This limits the use of medical equipment and procedures like administration of intravenous (IV) fluids in microgravity and can make field medicine hazardous. Administering IV fluids and medications in microgravity requires a technique to separate air from the liquid phase. Current commercial filters for separation of gases are incompatible with high flow and blood. We present a novel filter designed to provide adequate air clearance without a consistent downward G vector.METHODS: Inline air-eliminating filters were designed for use with IV fluid tubing in microgravity using computer-aided design software and printed using nylon 12 on an EOS Selective Laser Sintering 3D printer. A 0.2-μm membrane filter was adhered around a central, hollow pillar with external spiral baffles allowing separation and venting of air from the fluid. Results were compared against commercially available inline air-eliminating filters.RESULTS: The 3D-printed filters outperformed the commercial filters in both percentage of air removed and flow rates. The centrifugal, baffled filter had flow rates that far exceeded the commercial filters during rapid transfusion.DISCUSSION: IV fluid administration is an often underappreciated and a necessary basic requirement for medical treatment. An air-eliminating filter compatible with blood and rapid transfusion was developed and validated with crystalloid solutions to allow the successful administration of IV fluid and medication without a consistent downward G vector.Formanek A, Townsend J, Ottensmeyer MP, Kamine TH. A novel 3D-printed gravity-independent air-eliminating filter for rapid intravenous infusions. Aerosp Med Hum Perform. 2024; 95(6):327-332.

Behavioural Study of Beam-Column Joint for Seismic Loading

Abstract: The seismic performance of Reinforced Concrete (RC) structures is a critical aspect of structural engineering, particularly in regions prone to seismic activity. This project presents a detailed study focusing on the behaviour of joints in RC structures following seismic events, utilizing the powerful computational tool ETABS. The primary objectives include understanding the response of joints under seismic loading, assessing their vulnerability, and proposing strategies for enhancing their seismic resilience. The study employs ETABS, a widely used software package for structural analysis and design, to simulate seismic actions on RC structures. Various types of joints, including beam-column joints and slab-column connections, are meticulously analysed under different seismic intensities and structural configurations. Through comprehensive analysis, the project aims to identify critical failure modes, such as shear failure, flexural failure, and joint sliding, and evaluate their impact on overall structural performance. Findings from this study contribute to the advancement of seismic design and retrofitting practices, offering insights into effective strategies for enhancing the seismic resistance of RC structures. The outcomes are valuable for engineers, researchers, and practitioners involved in earthquake engineering, providing essential knowledge for designing resilient structures capable of withstanding seismic hazards. This project underscores the importance of understanding joint behaviours in RC structures subjected to seismic loading, offering practical implications for improving structural safety and mitigating the impact of earthquakes on the built environment.

Synergy of Real and Digital Worlds - Promising Insights for the Future Generations of Fashion

Digital transformation (DT) is reshaping the fashion industry, revolutionizing the way brands, retailers, and consumers interact. It is not a fad but a necessary step towards innovation and survival in today's business context. Implementing digital transformation requires a bespoke approach that addresses specific challenges and goals within the existing framework of each brand or retailer. Fashion brands are leveraging digital technologies throughout their value chain, from product design and production to marketing and distribution. Computer-aided design (CAD) software, predictive analytics, and 3D printing are streamlining the design and prototyping phases, reducing time-to market and improving product quality. Technologies like 3D body scanning, seamless garments and digitized looms are also being adopted. Brands like Hugo Boss are using smart factories that incorporate robotics, artificial intelligence (AI), analytics, and the Internet of Things (IoT) to increase efficiency. Moreover, digital integrated supply chain platforms, such as blockchain, are enabling faster and more efficient production by connecting brands with manufacturers and suppliers globally. The adoption of digital solutions extends to the production of futuristic textiles, digital clothing and virtual model / digital show stoppers. Retailers are also embracing DT to enhance the customer experience and expand their reach. E-commerce has become a crucial channel, allowing retailers to sell products online and reach a wider customer base. Many retailers are investing in robust online platforms and incorporating augmented reality (AR) and virtual reality (VR) technologies to offer immersive in-store shopping experiences. Data analytics and AI are being used to personalize recommendations and offers, enhancing customer engagement and loyalty. In-store virtual assistants or kiosks are worth mentioning in light of digital clientele. Social media platforms play a vital role in the fashion industry's digital transformation. Fashion brands are partnering with social media influencers to promote their products and reach a larger audience. Additionally, collaborative consumption models are emerging through digital apps, supporting sustainability efforts such as zero waste, recycling, and sharing goods or services. Consumers are benefiting from greater convenience, choice, and personalized experiences in the digital fashion landscape. They have access to a wide array of products from around the world and can find inspiration and style ideas on social media platforms. User generated content and reviews facilitate informed purchase decisions. Mobile technology advancements have blurred the lines between online and offline retail experiences, enabling consumers to shop anytime and anywhere. Adaptability, inclusivity, diversity, authenticity and traceability of product life cycle (Blockchain) have become driving instincts of Gen Zers and Millennials at purchase points. However, traditional industry players and small independent retailers face increased competition from e-commerce giants, necessitating their adaptation to digital technologies to remain relevant. The COVID 19 pandemic has accelerated this shift and normalized the idea of going digital. This paper presents an in-depth review of how digital transformations have various players within the fashion Industry with special reference to the brands, designers and enterprises implementing these for their evolution and progression to thrive in this rapidly evolving landscape.

Artificial intelligence enhanced environmental detection system

This paper presents a novel approach to improve the accuracy of environmental detection and prediction by incorporating artificial intelligence (AI) technology into existing detection systems. At the heart of our approach lies the combination of a complex AI model with the hardware and software components of the inspection system. This combined approach can significantly improve the accuracy of detection systems through greater ability to predict environmental changes and events, underscoring the superior performance of hardware and software combined with AI technology. This paper delves into the details of hardware and software design, and discusses measurement implementation methods using a build-down machine. We also explore the practical application of AI models within the framework described above. In addition, this paper also describes the implementation of communication protocols to ensure the effective data exchange between the system network and the artificial intelligence model. These protocols are essential for the real-time processing and analysis of environmental data, enabling systems to respond quickly to detected changes.

Design and evaluation of a colon cancer mobile application

BackgroundColorectal cancer (CRC) is the third leading cause of cancer and the second cause of cancer-related deaths in the world. Despite the infrastructure and the availability of organized screening programs, participation in their screening programs is less than the set goals. Considering the importance of informing the society about the prevention and early detection of colorectal cancer symptoms and the positive impact of mobile health technologies, the present research was conducted with the aim of designing and evaluating a colon cancer mobile application.MethodsThe present research was conducted in two phases: software design and evaluation. In the first phase, the software was prepared using the cascade method. First, all the educational content related to colorectal cancer was collected through an expert panel with the participation of 10 specialists. Then the software was evaluated with alpha and beta testing, and the initial version was approved by users in terms of simplicity and usability. In the second phase, a parallel clinical randomized trial study was conducted with the aim of investigating the effect of a colon cancer mobile application on the early detection of colorectal cancer. In this stage, 204 volunteers participated; inclusion criteria were age 18–85 years, owning a smartphone and the ability to read and write. Participants were randomized into control and intervention groups. The intervention group was educated with the colon cancer application for education about colorectal cancer, and the control group was educated with a pamphlet. After education, both groups were screened for colorectal cancer symptoms, and the results were compared.ResultsIn the software evaluation phase, the application was used by 204 users. In this stage, 84 (41.2%) women and 120 (58.8%) men, with an average (Standard Deviation) age of 47.53 (13.68) participated. Participants were randomized in two groups, 103 people with an average (Standard Deviation) age of 47.62 (14.65) in intervention group and 101 people with an average (Standard Deviation) age of 47.44 (12.70) in control group. There were no significant differences between the demographic characteristics of age, gender, marriage, occupation, instruction level, digestive disease history, cancer history, cancer risk factors, and family history of cancer between the two groups (P > 0.05). The Mann-Whitney U test indicated that there is a significant difference between the two groups of participants in self-assessment, willingness to do the screening, and the results of the assessment of colorectal cancer (P < 0.05).ConclusionThe results of the research indicated the positive impact of the Colon Cancer Application on the abilities of the users of self-assessment of colon cancer. Therefore, based on the findings, it can be concluded that the use of the colon cancer mobile application is effective for colon cancer prevention and self-care.Trial registrationThis study was registered in the Iranian Registry of Clinical Trials (https://irct.behdasht.gov.ir) on 13/2/2024, with the IRCT ID: IRCT20210131050189N9.

Development of a PAK4-targeting PROTAC for renal carcinoma therapy: concurrent inhibition of cancer cell proliferation and enhancement of immune cell response

Finding the oncogene, which was able to inhibit tumor cells intrinsically and improve the immune answers, will be the future direction for renal cancer combined treatment. Following patient sample analysis and signaling pathway examination, we propose p21-activated kinase 4 (PAK4) as a potential target drug for kidney cancer. PAK4 exhibits high expression levels in patient samples and plays a regulatory role in the immune microenvironment. Utilizing AI software for peptide drug design, we have engineered a specialized peptide proteolysis targeting chimera (PROTAC) drug with selectivity for PAK4. To address challenges related to drug delivery, we developed a nano-selenium delivery system for efficient transport of the peptide PROTAC drug, termed PpD (PAK4 peptide degrader). We successfully designed a peptide PROTAC drug targeting PAK4. PpD effectively degraded PAK4 with high selectivity, avoiding interference with other homologous proteins. PpD significantly attenuated renal carcinoma proliferation invitro and invivo. Notably, PpD demonstrated a significant inhibitory effect on tumor proliferation in a fully immunocompetent mouse model, concomitantly enhancing the immune cell response. Moreover, PpD demonstrated promising tumor growth inhibitory effects in mini-PDX and PDO models, further underscoring its potential for clinical application. This PAK4-targeting peptide PROTAC drug not only curtails renal cancer cell proliferation but also improves the immune microenvironment and enhances immune response. Our study paves the way for innovative targeted therapies in the management of renal cancer. This work is supported by Research grants from non-profit organizations, as stated in the Acknowledgments.

Investigating the Higher Education Students’ Perception of an Interactive DC Motor Simulator

This study investigates the perceptions of higher education students regarding an interactive DC (Direct Current) motor simulator, shedding light on the evolving landscape of virtual education. By utilizing five aspects of learning dimension, visual elements, software functionality, usability, and portability of a four-point Likert scale questionnaire, the research uncovers a generally positive reception of the simulator among students, who view it as a valuable complement to traditional hands-on laboratories, enabling self-paced learning and offering repeatable experiments in a safe environment. Nevertheless, our research highlights notable concerns, such as challenges related to user interface design and pre-installation software. These findings offer crucial insights into the strengths and limitations of a DC motor simulator in higher education, providing guidance for educators and instructional designers striving to optimize digital learning experiences.

Smart Gas Leakage Detector Using Arduino Gas Sensor

This project is carried out using the Methane Quality (MQ-2) sensor to detect Liquefied Petroleum Gas LPG, smoke and Carbon Monoxide (CO) leakage in the environment. The microcontroller used was an Arduino Uno for controlling the environmental temperature monitoring system. The results obtained from the sensor would be displayed on the 16x2 i2c Liquid Crystal Display (LCD). The new system with an Arduino microcontroller and MQ2 consists of the hardware design which includes the device design, as well as the software design which consist of the Arduino source code. They also consist of Internet of Things (IoT) enabled sensors, which work as a real-time indicator. After testing, we have 17.7% failure and 82.3% accuracy.

Computer-Assisted Surgery in Mandible Reconstruction

AbstractComputer-assisted surgery is the most significant recent advancement in osseous head and neck reconstruction. Computer-aided design (CAD) software allows computerized planning of resection and reconstruction. Computer-aided manufacturing (CAM) can be used to create models, cutting guides, and patient-specific plates. Several studies have shown that these techniques are more accurate and result in decreased flap ischemia times compared with conventional techniques. CAD also facilitates the immediate placement of dental implants. The most useful application of computer-assisted surgery is delayed reconstruction, in which soft tissue contraction and the absence of a specimen as a reference make accurate estimation of the defect challenging. The drawbacks of CAD/CAM are lack of intraoperative flexibility and cost. Some centers have created in-house CAD/CAM processes using open-source software and commercially available three-dimensional printers.

Structural Optimization of Trusses in Building Information Modeling (BIM) Projects Using Visual Programming, Evolutionary Algorithms, and Life Cycle Assessment (LCA) Tools

The optimal structural design is imperative in order to minimize material consumption and reduce the environmental impacts of construction. Given the complexity in the formulation of structural design problems, the process of optimization is commonly performed using artificial intelligence (AI) global optimization, such as the genetic algorithm (GA). However, the integration of AI-based optimization, together with visual programming (VP), in building information modeling (BIM) projects warrants further investigation. This study proposes a workflow by combining structure analysis, VP, BIM, and GA to optimize trusses. The methodology encompasses several steps, including the following: (i) generation of parametric trusses in Dynamo VP; (ii) performing finite element modeling (FEM) using Robot Structural Analysis (RSA); (iii) retrieving and evaluating the FEM results interchangeably between Dynamo and RSA; (iv) finding the best solution using GA; and (v) importing the optimized model into Revit, enabling the user to perform simulations and engineering analysis, such as life cycle assessment (LCA) and quantity surveying. This methodology provides a new interoperable framework with minimal interference with existing supply-chain processes, and it will be flexible to technology literacy and allow architectural, engineering and construction (AEC) professionals to employ VP, global optimization, and FEM in BIM-based projects by leveraging open-sourced software and tools, together with commonly used design software. The feasibility of the proposed workflow was tested on benchmark problems and compared with the open literature. The outcomes of this study offer insight into the opportunities and limitations of combining VP, GA, FEA, and BIM for structural optimization applications, particularly to enhance structural efficiency and sustainability in construction. Despite the success of this study in developing a workable, user-friendly, and interoperable framework for the utilization of VP, GA, FEM, and BIM for structural optimization, the results obtained could be improved by (i) increasing the callback function speed between Dynamo and RSA through specialized application programming interface (API); and (ii) fine-tuning the GA parameters or utilizing other advanced global optimization and supervised learning techniques for the optimization.

Piping layout integrated in ship design and stability evaluation

Damage stability assessment in ship design is a well-established area of our trade. However, where originally only a limited number of aspects were involved, gradually more details are included. Notably compartment connections by pipes and ducts etcetera. Combined with a high number of damage cases, in practice this results in a set of computations which is not complex as such, yet complicated by its sheer size. Although in the PIAS ship design software suite quite some dedicated tools are available, those have never been designed to support the requirements from today. In this light the software has been extended with a new system to fully define shape and topology of compartments and their connections. This paper reports on the system design, its application in damage scenarios, and on complications.

Design and Implementation of a Car’s Black Box System using Arduino

A black box system (BBS) in a car is crucial for recording and analyzing critical data to enhance safety, investigate accidents, and improve vehicle performance. This research presents a BBS developed using Arduino for cars, aimed at using the power of modern technology for comprehensive data capture and analysis in vehicular contexts. The BBS, or Event Data Recorder (EDR), is an essential component for enhancing road safety, accident analysis, and overall vehicle performance evaluation. The proposed system uses Arduino, a versatile and cost-effective microcontroller platform, to create a robust and customizable solution. It integrates various sensors and data acquisition modules to collect critical data points, including speed, acceleration, GPS coordinates, engine performance, and vehicle diagnostics. The architecture of the system and its smooth integration into automobiles are described in this article through detailed hardware and software design. Data retrieval and analysis are made possible by the system's user-friendly interface, which helps with fleet management, driver behaviour analysis, and accident investigation. This paper addresses the importance of data privacy and security while highlighting technological improvements. It proposes measures to ensure that personal data is managed responsibly and in accordance with legal requirements. In conclusion, a major advancement in improving road safety and vehicle monitoring has been made with the integration of Arduino technology into the car's BBS. Considering data security and privacy, this system provides users with an extensive set of facts to enable them to make well-informed decisions.

High accuracy graphene-based refractive index sensor: Analytical approach

A high-precision graphene-based refractive index (RI) sensor is suggested in this article. Because resonances represent a specific field distribution, optical sensors show a very high sensitivity to environment RI changes. These optical sensors' sensitivity is profoundly subordinate to the materials used in the sensor as well as the sensor structure. The structure of the proposed sensor consists of the following layers, respectively: gold layer, SiO2, graphene and the substance under test (analyte). The transmission line model (TLM) was also fully investigated for this absorber and the inductor and capacitor values related to the simulation were obtained. There was a suitable agreement between the simulation results and TLM. This sensor has nearly perfect absorption and the absorption peak of this sensor in the absorption curve is 99.99 % at 3.24 THz with an average quality factor of 11.39. This absorber-based sensor sensitivity to changing the test medium (analyte) RI is so high that with a very small change in the RI of the analyte, the absorption peak is shifted, and its frequency changes. This sensor sensitivity and figure of merit (FOM) to variation of the analyte RI 726 GHz/RIU 2.69 RIU-1 were acquired, respectively. The characteristics of this sensor can be adjusted by variating the bias voltage exerted on the graphene layer. The Computer Simulation Technology (CST) and Advanced Design System (ADS) software have been used to analyze this structure. This proposed sensor can be used as a good sensor in biomedical applications and early diagnosis of diseases such as leukemia and types of cancer and influenza.

Investigating parameters affecting the real and virtual drapability of silk fabrics for traditional Hanbok

This paper presents research into the parameters affecting the real and virtual drapability of silk fabrics for traditional Hanbok. The KES-FB (Kawabata evaluation system of fabric) and the CLO (3D fashion design software) fabric kit system were used to evaluate the physical properties. The relationships between physical properties and the drape coefficient of silk fabrics were statistically analyzed. It was determined whether the objectified real fabric data could be used and applied as a database when implementing virtual clothing using a 3D virtual clothing program. The KES-FB properties and CLO fabric kit results indicated that the bending property and weight were significantly correlated with the drape coefficient. The bending rigidity and weight per unit area were influential parameters of the drape coefficient. The regression analysis results of both the KES-FB and the CLO fabric kit revealed that bending rigidity and thickness were statistically significantly correlated with the drape coefficient. The bending property was the most determining parameter for the drape coefficient of silk fabrics. A statistically significant difference between the real and virtual drape coefficients of stiffer silk fabrics was found. In the CLO 7.1 program, the accuracy of drape implementation of virtual fabrics was found to be useful when the bending stiffness of the actual fabric was less than 0.089 gf·cm2/cm and the elasticity was more than 1.03%. The results revealed that more research on the program modeling method considering the mechanical and physical properties of the real fabric and its structure is needed.

Generic modelling to develop thermal yield nomograms for coaxial deep borehole heat exchangers (DBHE)

Numerical modelling of coaxial deep borehole heat exchangers (DBHE) can be resource-intensive. Simpler, transparent analytical models and nomograms would be valuable to developers and geologists for evaluating thermal output. An analytical computational model by Beier (2020) was used to produce nomograms of geothermal heat yield by systematically varying DBHE depth and rock thermal conductivity, while assuming two generic simplified DBHE designs, a geothermal gradient of 25°C/km and a fluid circulation rate of 5 L/s. Continuous 25-year heat yields from a 1000 m DBHE range from 27.3 to 54.8 kW for thermal conductivities of 1.6 to 3.6 W/m/K. For a 3000 m DBHE, they range from 165 kW to 281 kW. Effective borehole thermal resistance ( R b,eff ) increases strongly as DBHE depth increases, due to internal heat transfer between upflow and downflow elements. Simulations correspond well with results from industry-standard Earth Energy Designer software for shallow 200 m coaxial BHE. They modestly underestimate OpenGeoSys numerical modelled thermal yields by 2-4% for DBHE in the range 1000 to 3000 m depth. Modelled temperature evolution closely approximates an analytical “line heat source” approach, implying that simpler analytical approaches are plausible for DBHE simulation. Future research should focus on methods for forward quantification of R b,eff . Supplementary material: https://doi.org/10.6084/m9.figshare.c.7237887