Open-source Environment Research Articles

Mining of Data in Real Time to build an Interactive Research Analytics Dashboard

The paper discusses the process of building a web-based interactive platform to assess the research productivity of the individual faculty of an institution. The application harvests the bibliographic data of researchers’ publications from the Scopus database and visualises it in real-time. The open-source environment R with different packages like the shiny, shiny dashboard for building web apps and dashboard designing; httr for data harvesting through API, jsonlite for parsing JSON data, tm for text mining, wordcloud for visualising wordcloud, textstem for lemmatization of text strings, dplyr for data manipulation, etc. were used. The data was harvested at the backend using Scopus API. The user interface of the application’s front end is the default design of the shiny dashboard, with some limited customization using CSS. The system tracks and visualizes the research productivity of the faculty. The application provides the total number of publications, citations, H Index, open access information, number of publications in open access, and closed access, in an assessment year rather than a calendar year, source-wise differentiation of publications, annual distribution of publications, common themes of the research, etc.

An automated geometry generation procedure for CWE applications in OpenFOAM: the case study of a thunderstorm downburst moving over Genoa city

AbstractSince a decade, Computational Fluid Dynamics (CFD) simulations for Wind Engineering (WE) on large-scale environments became a norm. Meso-$$\gamma$$ γ scales and microscale can be characterized by a large number of structures as well as complex terrain topographies. CFD simulations over such an area would commonly imply the involvement of a time-consuming geometry preparation in the pre-processing stage. This is also the innovative goal of the present paper for which an automated geometry generation procedure for Computational Wind Engineering (CWE) applications is developed in open-source environments. This paper further expands on the unsteady Reynolds-averaged Navier–Stokes (URANS) simulation of a thunderstorm downburst immersed in a background Atmospheric Boundary Layer (ABL) wind moving over Genoa city, Italy. Recommendations for geometry and grid generation of the present case study are also proposed. The study considers two simultaneous approaching wind conditions, a background ABL wind and a moving downburst (DB), the latter modeled as an impinging jet. The simulated results are compared with available full-scale LiDAR profiler data in terms of the vertical profiles of outflow velocity, showing relatively good agreement in terms of magnitude and profile shape.

Computational Tool for Aircraft Fuel System Analysis

Fuel level gauging in aircraft presents a significant flight mechanics challenge due to the influence of aircraft movements on measurements. Moreover, it constitutes a multidimensional problem where various sensors distributed within the tank must converge to yield a precise and single measurement, independent of the aircraft’s attitude. Furthermore, fuel distribution across multiple tanks of irregular geometries complicates the readings even further. These issues critically impact safety and economy, as gauging errors may compromise flight security and lead to carrying excess weight. In response to these challenges, this research introduces a multi-stage project in aircraft fuel gauging systems, as a continuum of studies, where this first article presents a computational tool designed to simulate aircraft fuel sensor data readings as a function of fuel level, fuel tank geometry, sensor location, and aircraft attitude. Developed in an open-source environment, the tool aims to support the statistical inference required for accurate modeling in which synthetic data generation becomes a crucial component. A discretization procedure accurately maps fuel tank geometries and their mass properties. The tool, then, intersects these geometries with fuel-level planes and calculates each new volume. It integrates descriptive geometry to intersect these fuel planes with representative capacitive level-sensing probes and computes the sensor readings for the simulated flight conditions. The method is validated against geometries with analytical solutions. This process yields detailed fuel measurement responses for each sensor inside the tank, and for different analyzed fuel levels, providing insights into the sensors’ signals’ non-linear behavior at each analyzed aircraft attitude. The non-linear behavior is also influenced by the sensor saturation readings at 0 when above the fuel level and at 1 when submerged. The synthetic fuel sensor readings lay the baseline for a better understanding on how to compute the true fuel level from multiple sensor readings, and ultimately optimizing the amount of used sensors and their placement. The tool’s design offers significant improvements in aircraft fuel gauging accuracy, directly impacting aerostructures and instrumentation, and it is a key aspect of flight safety, fuel management, and navigation in aerospace technology.

Guardians of the iot realm: a comparative analysis of cryptographic security solutions for bolstering iot device networks

The "Internet of Things" (IoT) is an emerging technology that allows electronic devices and sensors to connect with one another over the Internet. The IoT is a network of smart devices such as sensors that are connected through cables or wirelessly. Today, IoT devices are commonly used in medical science, industrial automation, and smart home automation, among other applications. Easy accessibility and the open-source environment of IoT devices are major threats to privacy and security. In this paper, we comprehensively discuss areas of IoT, including architecture, details of IoT layers with respect to security algorithms, protocols, attacks, and their mitigation. The primary purpose of this research is to provide an efficient and cryptographically proven algorithm scheme with appropriate hardware to improve IoT device network security. The presented research enhances the network security of IoT devices by presenting an algorithmic framework fortified by cryptography and supported by the finest hardware options. After evaluating several cryptographic algorithms and hardware options, a more secure solution for IoT infrastructure is proposed. The article in particular, proposes a detailed strategy that addresses security at every level of the IoT system. This research is an important step towards ensuring the integrity and security of IoT devices in a networked environment, with the primary goal of increasing the protection of sensitive data and interactions.

Interactive RShiny Reports – Independence and Autonomy in Medical Data Visualization

The article discusses the use of the R language, especially the RShiny tool, to create interactive reports in the field of medical data analysis. The authors emphasize the need for an interdisciplinary approach to teaching statistics among medical students. An alternative to traditional static reports was presented, proposing the creation of interactive web applications that enable exploration, analysis and visualization of medical data changing in real time. The use of the R language as an open source tool allows for the development of medical students' competences in the field of data analysis and the adaptation of research tools to individual needs. A draft lesson plan using sample medical data on cervical cancer was also presented, along with a proposal for specific analyzes of these data and their visualization using interactive RShiny reports. The article ends with a discussion on the role of learning the R language in the education of students of Polish medical universities and the need to expand the educational offer for them with courses in data analysis in an open source environment.

The human infertility single-cell testis atlas (HISTA): an interactive molecular scRNA-Seq reference of the human testis.

Single-cell RNA-seq (scRNA-Seq) has been widely adopted to study gene expression of the human testis. Several datasets of scRNA-Seq from human testis have been generated from different groups processed with different informatics pipelines. An integrated atlas of scRNA-Seq expression constructed from multiple donors, developmental ages, and fertility states would be widely useful for the testis research community. To describe the generation and use of the human infertility single-cell testis atlas (HISTA), an interactive web tool for understanding human spermatogenesis through scRNA-Seq analysis. We obtained scRNA-Seq datasets derived from 12 donors, including healthy adult controls, juveniles, and several infertility cases, and reprocessed these data using methods to remove batch effects. Using Shiny, an open-source environment for data visualization, we created numerous interactive tools for exploring the data, some of which support simple statistical hypothesis testing. We used the resulting HISTA browser and its underlying data to demonstrate HISTA's value for testis researchers. A primary application of HISTA is to search by a single gene or a set of genes; thus, we present various analyses that quantify and visualize gene expression across the testis cells and pathology. HISTA also contains machine-learning-derived gene modules ("components") that capture the entire transcriptional landscape of the testis tissue. We show how the use of these components can simplify the highly complex data in HISTA and assist with the interpretation of genes with unknown functions. Finally, we demonstrate the diverse ways HISTA can be used for new data analysis, including hypothesis testing. HISTA is a research environment that can help scientists organize and understand the high-dimensional transcriptional landscape of the human testis. HISTA has already contributed to published testis research and can be updated as needed with input from the research community or downloaded and modified for individual needs.

Cultivating Community Health and Well-being in Open Source: Mitigating Burnout and Prioritizing Mental Health

Purpose: This whitepaper addresses the critical but often overlooked mental health challenges within open-source communities, including stress and burnout. The collaborative spirit of open-source communities has undoubtedly accelerated technological innovation, but the mental well-being of their contributors is frequently neglected. The objective is to uncover the root causes of these mental health issues and evaluate their impact, thereby underscoring the need for supportive and inclusive community practices.
 Methodology: This paper uses the ‘Mixed methods’ research approach, analyzing data from industry surveys and extracting insights from personal narratives and experiences documented by contributors in blogs and forums. This comprehensive strategy allows for a detailed exploration of mental health within the open-source environment, facilitating the identification of key stress factors and mental health challenges associated with community participation.
 Findings: The investigation reveals a direct link between the operational dynamics of open-source projects and the prevalence of mental health problems among participants. Key stressors include high expectations regarding workload, the predominantly volunteer nature of contributions, social isolation, and a lack of formal support structures. Additionally, the study highlights a significant lack of awareness of these issues and the availability of intervention strategies, further increasing the risk of burnout and stress among community members.
 Unique Contribution to Theory, Practice, and Policy: This paper makes a novel contribution to understanding mental health in open-source communities by merging analytical data with qualitative insights from contributor narratives. It offers recommendations for a wide range of stakeholders, from contributors to leaders and policymakers, to cultivate a culture that supports mental well-being, diversity, and sustainability. This paper presents a comprehensive blueprint for nurturing healthier, more resilient open-source communities.

Methodology of Spatial Data Acquisition and Development of High-Definition Map for Autonomous Vehicles – Case Study from Wrocław, Poland

Autonomous drive systems are a dynamically developed sector of the automotive industry. The key problem in such technological solutions is to provide a reliable navigation system, which is typically based on high-definition (HD) maps supporting the identification of the position of a maneuvering vehicle. HD maps should include possibly up-to-date and detailed information on traffic lanes and on the traffic rules and regulations on such lanes. An effective development of an HD map should be based on the geodetic measurement methods, which ensure efficient and accurate acquisition of spatial data. This article presents the results of an experiment consisting in the manipulation of data obtained with the use of the mobile laser scanning method and further in employing this data in the development of an HD map in an open-source environment. The applied measurement technology and the processing method allowed data of high resolution (frequently above 1000 points per m2) and of high accuracy (3D accuracy down to less than 5 cm). The obtained data were processed in the Vector Map Builder environment (which is accessible from the level of an internet browser) and the final product - HD map was created in the Lanelet2 open-source environment. The above-described experiments allowed two main conclusions. Most importantly, they demonstrate the importance of planning and performing in-field mobile laser scanning measurements. They also point to the important role of the human analyst who needs to manually vectorize the key elements of road infrastructure and to define traffic rules.

Bibliometric analysis on cannibalism/infanticide and maternal aggression towards pups in laboratory rodents.

Animal welfare has evolved during the past decades to improve not only the quality of life of laboratory rodents but also the quality and reproducibility of scientific investigations. Bibliometric analysis has become an important tool to complete the current knowledge with academic databases. Our objective was to investigate whether scientific research on cannibalism/infanticide is connected with maternal aggression towards the offspring in laboratory rodents. To carry out our research, we performed a specific search for published articles on each concept. Results were analyzed in the open-source environment RStudio with the package Bibliometrix. We obtained 253 and 134 articles for the first search (cannibalism/infanticide) and the second search (maternal aggression towards the pups) respectively. We observed that the interest in infanticide/cannibalism started in the 1950s, while researchers started showing interest in maternal aggression towards the pups 30 years later. Our analyses indicated that maternal aggression had better citations in scientific literature. In addition, although our results showed some common features (e.g. oxytocin or medial preoptic area in the brain), we observed a gap between cannibalism/infanticide and maternal aggression towards the pups with only 14 published articles in common for both the searches. Therefore, we recommend researchers to combine both concepts in further investigations in the context of cannibalism for better dissemination and higher impact in laboratory rodents' welfare research.

RJDemetra, a promising tool for the seasonal adjustment of official statistics

Seasonal adjustment (SA) is a crucial factor in the process of producing official macroeconomic statistics. The most important SA methods, X-13Arima-Seats and Tramo-Seats, are currently included into JDemetra+, a universal open-source environment, which is available on several platforms and operating systems, as a result of adoption of Java programming language for source codes, and Xml metalanguage for the definition of input specifications. This paper focuses on the potentials of RJDemetra, the R library developed for JDemetra+ suite. Its structure and functionalities will be illustrated with several examples, reporting the associated R scripts. In addition, a new operational practices will be suggested, exposing an alternative procedure to enhance interactive time-series updating in SA revision policies step, and also to ensure consistency checking in input system, in order to improve and to speed up the SA estimation process, providing greater security and efficiency. Finally, the interaction between two very different environments such as SAS-IML, and R will be displayed through a new SAS-R procedure available for estimating Quarterly Accounts SA series.

Performance analysis and gradient-porosity electrode design of vanadium redox flow batteries based on CFD simulations under open-source environment

As a promising large-scale energy storage device, the vanadium redox flow battery (VRFB) has attracted attention due to its excellent safety, the independence between energy capacity and power capacity, the suitable polarization potential, and the ability to avoid cross-contamination. In this work, a 3D model of VRFB is developed based on the open-source computational fluid dynamics (CFD) platform OpenFOAM, which is well-validated. Then, the effect of operating conditions is studied, which shows that a higher electrolyte concentration can reduce the overpotential and increase the discharge voltage. Reducing the current density can increase the deepness of charge and discharge, reduce the electrolyte concentration gradient, the mass transfer loss and the activation loss. In addition, the effect of electrode porosity is studied that the overpotential decreases near the membrane and increases near the current collector with increasing porosity. Finally, the effect of porosity changes in different directions is studied, and an attempt is made to utilize this overpotential distribution by introducing the gradient-porosity electrode to reduce the non-uniformity of overpotential. The gradient-porosity electrode design using higher porosity near the membrane and lower porosity near the current collector can effectively improve the distribution of overpotential and increase battery performance by 1.67 mV.

EXPLANATION OF THE MOLECULAR MECHANISM OF ANTI-DEPRESSION THERAPY USING WEBINARS AS LEARNING COMMUNICATION MEDIA

The Covid-19 Pandemic outbreak has changed various forms of life in society, including restrictions on activities in an open-source environment. The pandemic has also created various kinds of unresolved mental health problems, both in the national dan global area, both those who are directly exposed to the virus and those who are not. Today, the community is still struggling to control the spread of Covid-19, but on the other hand, it has caused the spread of feelings of anxiety, fear and mental pressure due to isolation, physical distancing restrictions, social relations, and other uncertainties. Therefore, these webinar activities were held as one of the online learning communication media, in terms of providing mattery regarding the molecular mechanism of antidepressant therapy, which during the post-Covid-19 pandemic its use increased due to social reasons. This webinar media was very effective without having to gather a crowd and aims to increase knowledge, especially among participants in terms of handling mental health such as depression in terms of its pharmacology therapy. Then, knowing the mechanism of molecular action can improve the optimization of antidepressant therapy according to the patient’s condition. The target participants in this webinar are health workers, students of health study programs, and common people. The webinar activity was conducted by the online system, using the Zoom meeting platform, and was held on April 15th, 2023, then was attended by 241 people, who came from all over Indonesia. From the implementation of the webinar activities, it is known that there has been an increase in understanding of the molecular matter that has been given, this can be seen from the percentage of the correct answers in the post-test evaluation compared to the answers in the pre-test.

HPV and Covid-19 Era: effects of nonpharmaceutical interventions on HPV transmission

ABSTRACT Human papillomavirus (HPV) is considered the commonest viral cause of sexually transmitted infections. The impact of social distance measures due to Covid-19 pandemic on HPV spread is unknown. Therefore, this study has analyzed the seven-year trend of HPV prevalence in all patients tested for HPV DNA at the Microbiology and Virology Unit at Bari Policlinico. Moreover, the HPV prevalence in 2020 has been compared with the previous year ones in order to evaluate the consequences of lockdown and social distancing measures on transmission risks. From 2013 to 2020, we retrospectively analyzed 64 anal swabs, 418 biopsies, 5925 cervical-vaginal swabs, 512 cervical swabs, 104 gland swabs, 154 oral swabs, 21 seminal fluids and 503 urethral swabs. HPV DNA detection was initially performed using nested-polymerase chain reaction (PCR) and subsequently multiplex real-time PCR assay. All statistical tests were carried out by the open-source environment R 4.0.3 (R Core Team). The data were analyzed according to yearly positivity rates, temporal trend and prevalence of HPV genotypes (HPV-6, HPV-11, HPV-16, HPV-18, high risk and low risk) by age category and sex. The number of patients increased steadily from 2016 to 2019 and then decreased in 2020. There were significant differences in prevalence between females and males for HPV-6 (6.16% in females Vs 30.80% in males), HPV-11 (0.82% Vs 7.16%) and HPV-16 (7.77% Vs 5.01%). The prevalence of HPV-6 and HPV-11 significantly increased in 2020 compared to 2013–2019 (15.72% Vs 8.52 and 3.18% Vs 1.44%). On the contrary, the overall prevalence of HPV DNA remained constant in 2020 (52.84% Vs 48.44%). Over time, the prevalence of HPV DNA (Coefficient=-0.020, p-value = 0.036) and particularly high-risk genotypes (Coefficient=-0.030, p-value = 0.005) decreased in females, while low-risk genotypes (Coefficient = 0.141, p-value= < 0.001) and the prevalence of HPV DNA increased in males (Coefficient = 0.068, p-value = 0.008). During the pandemic, the number of screened patients declined, although HPV prevalence compared to 2013–2019 remained constant or increased as in the case of low-risk genotypes. It can be assumed that the reduction of the screening coverage favored the emerging of the more symptomatic low-risk infections. In conclusion, nonpharmaceutical interventions due to Covid-19 pandemic did not reduce the risk of HPV infection but it likely caused a decrease in access to health services resulting in an increased risk of undiagnosed HPV.

Abstract 2093: Introducing InMoose, an integrated open source Python package for multi-omic analyses

Abstract The recent exponential progress of sequencing technologies has dramatically impacted cancer research and paved the way to precision medicine in cancer care. In parallel, light-speed progress in bioinformatics has been essential to allow analysts to embrace the vast amount of data yielded by high-throughput profiling machines, turn this data into cancer biology knowledge, and ultimately develop innovative approaches to cancer care. Still, computational complexity and tools' interoperability remain major challenges for the advancement of -omic data-driven cancer research. Despite the historical prevalence of R, Python is gaining momentum in the bioinformatics landscape. As a general purpose language, it offers numerous advantages: - its overall ecosystem facilitates the integration of bioinformatics tools into large-scale frameworks, increasing their versatility and widening their targeted audience; - its straightforward syntax and user-friendly logic makes it a popular language in education, and explains its wide adoption in various sectors; - its wide adoption favors interdisciplinarity, e.g. it can reduce the learning curve for engineers eager to make an impact in cancer research. These advantages motivate the further development of the Python bioinformatics ecosystem. We thus advocate the necessity to port reference tools from R to Python, with the ambition of shaping a comprehensive ecosystem. Sign of this trend, state-of-the-art tools have been directly developed in Python (e.g. lifelines, a library dedicated to survival analysis) or quickly ported in Python from R (e.g. harmony, an R library for integrating single cell data). We introduce InMoose (Integrated Multi-Omics Open Source Environment), an open source Python unified framework for every -omic data type. It is based on recognized tools and focuses on efficiency and user-friendliness. InMoose is accessible at https://github.com/epigenelabs/inmoose and is released under GPL3 license. The first version of InMoose focuses on bringing to the Python world transcriptomics tools mostly based on the edgeR R package. It features batch-effect correction algorithms, as well as differential expression analysis, for microarray and RNA-seq data. InMoose demonstrates the advantages of our approach: - it is developed with the intent to capitalize on and facilitate interactions with other popular Python data-oriented libraries (e.g. pandas, numpy); - it demonstrates significant computational performance improvements; - our package integrates easily into web-based user-friendly analyses platforms (e.g. Epigene Labs’ proprietary mCUBE platform); - porting existing code from one language to another provides an opportunity window to improve both functionality and performance. We expect that our effort will help foster a larger collaborative effort to build and grow a consistent state-of-the-art Python platform for cancer bioinformatics. Citation Format: Maximilien Colange, Guillaume Appé, Akpéli Nordor, Abdelkader Behdenna. Introducing InMoose, an integrated open source Python package for multi-omic analyses [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2093.

DTUMOS, digital twin for large-scale urban mobility operating system

The advancement of digital twin technology has significantly impacted the utilization of virtual cities in the realm of smart cities and mobility. Digital twins provide a platform for the development and testing of various mobility systems, algorithms, and policies. In this research, we introduce DTUMOS, a digital twin framework for urban mobility operating systems. DTUMOS is a versatile, open-source framework that can be flexibly and adaptably integrated into various urban mobility systems. Its novel architecture, combining an AI-based estimated time of arrival model and vehicle routing algorithm, allows DTUMOS to achieve high-speed performance while maintaining accuracy in the implementation of large-scale mobility systems. DTUMOS exhibits distinct advantages in terms of scalability, simulation speed, and visualization compared to current state-of-the-art mobility digital twins and simulations. The performance and scalability of DTUMOS are validated through the use of real data in large metropolitan cities including Seoul, New York City, and Chicago. DTUMOS’ lightweight and open-source environment present opportunities for the development of various simulation-based algorithms and the quantitative evaluation of policies for future mobility systems.

A Singular Environment: Featuring a Framework for Integrated Project Management

There's always been a need to improve everyone's work process to ease the productivity and effectiveness of project management. However, this task entails many mechanisms, which might take a lot of time and cause the main priorities to be overlooked. That's when open-source environment solutions came. This article explores the need for being able to gather all subject changes in scope, time, cost, and quality, among others. For that were explored open-source environments and selected the one that's most suitable for gathering all characteristics, supported by the eight domains of the most recent version of Project Management Body of Knowledge in its 7th version. Furthermore, this environment also intends to stay updated by supporting future trends such as sustainability, agility, risk, requirements, and benefits management. Thereby, this tool gives a singular way of managing projects in a way that improves performance and increases higher success rates by providing accurate information.

PolyVerif: An Open-Source Environment for Autonomous Vehicle Validation and Verification Research Acceleration

Validation and Verification (V&V) of Artificial Intelligence (AI) based cyber physical systems such as Autonomous Vehicles (AVs) is currently a vexing and unsolved problem. AVs integrate subsystems in areas such as detection, sensor fusion, localization, perception, and path planning. Each of these subsystems contains significant AI content integrated with traditional hardware and software components. The complexity for validating even a subsystem is daunting and the task of validating the whole system is nearly impossible. Fundamental research in advancing the state-of-the-art for AV V&V is required. However, for V&V researchers, it is exceedingly difficult to make progress because of the massive infrastructure requirements to demonstrate the viability of any solution. This paper presents PolyVerif, the world’s first open-source solution focused on V&V researchers with the objective of accelerating the state-of-the-art for AV V&V research. PolyVerif provides an AI design and verification framework consisting of a digital twin creation process, an open-source AV engine, access to several open-source physics based simulators, and open-source symbolic test generation engines. PolyVerif’s objective is to arm V&V researchers with a framework which extends the state-of-the-art on any one of the many major axes of interest and use the remainder of the infrastructure to quickly demonstrate the viability of their solution. Given its open-source nature, researchers can also contribute their innovations to the project. Using this critical property of open-source environments, the innovation rate of the whole research community to solve these vexing issues can be greatly accelerated. Finally, the paper also presents results from several projects which have used PolyVerif.

Sardinia as a 100% renewable power system: A frequency stability study

This paper investigates a real complex power system supplied by a 100% renewable generation, focusing on the primary frequency regulation. The grid and the power production park are represented by means of an electro-mechanical model in a free open-source environment. The lack of synchronous generators in the grid, due to the conventional power plants shutdowns, requires higher performances from renewable power plants (RPPs) in terms of synchronization and inertial response. Doubly fed induction generators (DFIGs) are identified as the promising power plants able to lessen inertial issues. DFIG system control is investigated in the present paper, according to the recent studies in the literature, implementing a new strategy of control in case of avoiding maximum power point tracker (MPPT) operation. The 100% renewable 112-bus Sardinia islanded power system is the case study of this paper. Four scenarios were selected to show the primary frequency response in the most critical under and upper frequency events among the year. The simulations revealed that the most severe frequency nadir in the simulation reached a decrease of 0.37 Hz. DFIGs control system appeared robust in terms of inertial response and capability of reaching new stable operating point.

Investigation of the transient coupling between the dynamic laser beam absorptance and the melt pool - vapor depression morphology in laser powder bed fusion process

A predictive powder-bed model has been developed using open-source environments to investigate the coupling between the optical and the thermo-hydrodynamical phenomena for the laser powder bed fusion process. Firstly, discrete element modeling has been carried out to predict the configuration of powder particles over a substrate. Then, thermo-fluidic simulations for both the stationary and the moving laser irradiation have been carried out to investigate the melt pool dynamics, the vaporization induced keyhole depression instabilities, and the multiple reflections of the laser beam in the powder bed and the keyhole. The local absorptance and the reflectance of the laser beam at the static curvature of the solid powder particles and the dynamic interface of the vaporization-induced keyhole depression have been incorporated using a parallelized ray-tracing algorithm. The influences of laser power, scanning speed, beam spot diameter, and powder layer thickness on the melting mode and the transient beam absorption have been investigated. During the initial phase of melting in the powder bed, it was found that the laser absorption is very high (up to 73%) due to multiple reflections induced beam trapping. The absorption behavior for the conduction mode of melting was found to be dependent on the scanning speed of the laser beam. For the keyhole mode of melting, the temporal variation of the laser beam absorption shows a highly non-linear fluctuating behavior that is directly related to the vapor depression morphology of the melt pool. The numerically predicted attributes such as the initial laser beam absorptance, the transient melt pool-vapor depression morphology for the stationary laser irradiation, and the melt pool dimensions for the single-track deposition matches well with the findings of the published powder calorimetric measurement, published high-speed transmission X-ray imaging and the measured single-track deposited using the in-house laser powder bed fusion setup, respectively.

Verification of TRANSPORT Simulation Environment coupling with PHREEQC for reactive transport modelling

Abstract. Many types of geologic subsurface utilisation are associated with fluid and heat flow as well as simultaneously occurring chemical reactions. For that reason, reactive transport models are required to understand and reproduce the governing processes. In this regard, reactive transport codes must be highly flexible to cover a wide range of applications, while being applicable by users without extensive programming skills at the same time. In this context, we present an extension of the Open Source and Open Access TRANSPORT Simulation Environment, which has been coupled with the geochemical reaction module PHREEQC, and thus provides multiple new features that make it applicable to complex reactive transport problems in various geoscientific fields. Code readability is ensured by the applied high-level programming language Python which is relatively easy to learn compared to low-level programming languages such as C, C++ and FORTRAN. Thus, also users with limited software development knowledge can benefit from the presented simulation environment due to the low entry-level programming skill requirements. In the present study, common geochemical benchmarks are used to verify the numerical code implementation. Currently, the coupled simulator can be used to investigate 3D single-phase fluid and heat flow as well as multicomponent solute transport in porous media. In addition to that, a wide range of equilibrium and nonequilibrium reactions can be considered. Chemical feedback on fluid flow is provided by adapting porosity and permeability of the porous media as well as fluid properties. Thereby, users are in full control of the underlying functions in terms of fluid and rock equations of state, coupled geochemical modules used for reactive transport, dynamic boundary conditions and mass balance calculations. Both, the solution of the system of partial differential equations and the PHREEQC module, can be easily parallelised to increase computational efficiency. The benchmarks used in the present study include density-driven flow as well as advective, diffusive and dispersive reactive transport of solutes. Furthermore, porosity and permeability changes caused by kinetically controlled dissolution-precipitation reactions are considered to verify the main features of our reactive transport code. In future, the code implementation can be used to quantify processes encountered in different types of subsurface utilisation, such as water resource management as well as geothermal energy production, as well as geological energy, CO2 and nuclear waste storage.