Optimum Way Research Articles

Analyzing numerical simulation of ventilation system and filter membrane: The exposure of airborne nanoparticles in health interior Space

Improving air quality in indoor areas or interior spaces is a vital need. High PM 2.5 concentration or excessive air pollution causes severe damage to human health and the respiratory system. Air ventilation systems in health spaces are more necessary as there is a higher human crowd flow in viral-susceptible areas. The recent COVID situation has made us rethink the re-arrangement of hospitals' interior space and air ventilation systems. For that reason, improving high-efficiency particulate air filters is the need of the hour. The main objective of this research is the optimization and redesign of the air filtration system in health centers by integrating a hybrid combination system of HEPA filters based on computer modeling and numerical simulation. To analyze the effectiveness of the hybrid system, first, we simulated the existing air filtration system by using a successful and proven air filtering computational model in COMSOL Multiphysics. After that, we generated comparative numerical results and graphical analysis obtained by COMSOL to demonstrate the competency of the hybrid system over the conventional air filtration system. Finally, we have shown the most optimum and effective way to implement the hybrid system in health centers by analyzing the Computational Fluid Dynamics of different types of opening and ventilation systems. This research will play an essential role in future interior air quality improvement and effective anti-viral design of health spaces.

Protective graphene-based coatings for Zamak: Physical and electrochemical analysis

Concerns surrounding the widespread use of hazardous materials have increased over time and have led numerous states to implement regulations aimed at preserving human and environmental health. In response, industries like metallurgy have gradually transitioned from traditional, hazardous technologies to safer alternatives, such as using polymeric coatings to protect metals from corrosion. This study focuses on evaluating the protective properties of non-functionalized graphene oxide-based coating (GC) and functionalized graphene oxide-based coating (FGC) on the zamak samples. First, the powders were analyzed from structural, morphological, and spectroscopic perspectives. The formation of amino-silica groups on the graphene oxide sheets was confirmed through SEM-EDS, XRD, and FTIR analyses, validating the success of the functionalization process. Granulometric analysis demonstrated a good dispersion of fillers in the mixtures. Cross's theoretical model was applied to the rheological experiments to find the optimum way of coating application on metallic substrates. The corrosion resistance of the coatings was evaluated using OCP, LSV, PS, EIS, and salt spray experiments. The results revealed that the functionalized graphene oxide coating provided superior corrosion protection compared to other coatings on Zamak samples. AFM topographic images, along with roughness measurements, indicated a significantly less corroded surface when using the functionalized graphene oxide coating. Additionally, Raman spectroscopy confirmed the protective effectiveness of the FGC coating against corrosion.

Efficient Domination in Grid Graphs

Let G = ( V , E ) be a graph. A subset S ⊆ V of vertices is an \textit{efficient dominating set} if every vertex v ∈ V is adjacent to exactly one vertex in S , where a vertex u ∈ S is considered to be adjacent to itself. Efficient domination is highly desirable in many real-world applications, and yet, in general, graphs are often not efficient. It is of value, therefore, to determine optimum ways in which inefficient graphs can be changed in order to make them efficient. It is well known, for example, that almost no m × n grid graphs have efficient dominating sets. In this paper, we consider the minimum number of vertices that can be removed from an m × n grid graph so that the remaining graph has an efficient dominating set.

Enhancing University Innovation Through Industrial Symbiosis

In the context of global changes and the transition to a Green Economy, there has been a lack of emphasis in scientific literature to the management of project innovation activities at universities, particularly in collaboration with business and the government. This gap continues despite international experiences that indicate the benefits of industrial symbiosis for regional economic growth, including socioeconomic and environmental issues. The study focuses on the underexplored management of university project innovation activities in collaboration with businesses and the state as the world shifts toward a Green Economy, highlighting the successful use of industrial symbiosis in other countries to boost regional socioeconomic and environmental development. Current engagement channels are insufficient to facilitate the integration of academic ideas into industry throughout the transition to a circular economy. This study intends to establish novel management mechanisms for university innovation activities based on industry symbiosis, as well as optimum collaboration ways for project initiation and implementation. The authors offer successful implementation techniques, such as project formation and realization through partnership with corporations and government bodies, as well as the involvement of bright youngsters. By developing zones of industrial symbiosis and other cooperative ventures, the research hopes to position universities as crucial to building symbiotic chains, eventually boosting university innovation infrastructure efficiency and fostering sustainable regional development. Received: 30 April 2024 | Revised: 19 August 2024 | Accepted: 22 August 2024 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The data generated or analyzed during this study are included in this published article. Author Contribution Statement Daria Y. Mironova: Conceptualization, Methodology, Formal analysis, Writing - original draft, Project administration. Evgeniya A. Pashkova: Validation, Visualization. Alexander G. Budrin: Methodology, Writing - review & editing. Igor V. Baranov: Methodology, Data curation, Writing - review & editing. Vijayakumar Varadarajan: Methodology, Formal analysis, Supervision. Stephen Afrifa: Investigation, Project administration.

The Age Old Question: Studying as a Medical Student

Entering medical school feels like a dream come true. The excitement builds until the first week arrives and reality sets in. Don’t get me wrong, it is an incredible privilege and experience but the sheer content that is thrown at you can be overwhelming at times and never seems to falter. That is why it is very important to have a strategy to keep up and study as you go. The only problem being how to study. Even after completing three years, this is something I still struggle with. Everyone seems to have a different strategy that works for them so it is important to find one that works for you and fast as last-minute cramming can only get you so far. So what is the optimum way to study? There are many resources provided by the medical school; lectures, websites, books, journals, articles, and research papers. It can be daunting having to go through these and pick one that suits your learning style the best. If you would like some personal recommendations, the book Moore’s Clinically Oriented Anatomy is my favorite when it comes to Anatomy learning. Kumar and Clarke is also an excellent book to learn from. Some other resources I recommend include; Osmosis, KenHub, Khan Academy, and Ninja Nerd These are all great when it comes to learning all aspects of medicine however studying is a personalized experience where one size does not fit all so it is important to shop around and find the best one for you, especially in those early weeks.

Spontaneous Intracranial Hypotension: Role of Computed Tomography-guided Cervical Epidural Blood Patch.

Lumbar epidural blood patch (EBP) is not successful in all cases of cerebrospinal fluid (CSF) leak, particularly in the cervicothoracic region. The present study is a retrospective analysis of a cohort of patients who had undergone computed tomography (CT)-guided cervical EBP for spontaneous intracranial hypotension (SIH) due to CSF leak in the cervical region. We retrospectively collected data from March 2009 to 2020. Our inclusion criteria were (1) clinical syndrome associated with CSF leak, (2) headache coming on shortly after assuming the erect position and relief achieved by lying down, (3) CT myelography evidence of CSF leak in the cervical region, and (4) patient not responding to conservative management for 7 days. Exclusion criteria were patients with bleeding diathesis and infection. There were six females and four males. Ages ranged from 32 to 57, with an average of 42 years. On presentation, all patients underwent contrast-enhanced magnetic resonance imaging (MRI) and CT myelography. Cervical EBP was done under CT scan guidance. Assessment of headache was done on a 10-point numerical rating scale (NRS) before and after the procedure. Results are categorized into complete relief, partial relief, and no relief categories. Nine out of 10 patients were completely recovered. One patient was partially recovered. The average NRS scale was 9.6 before treatment, which became 0.4 after EBP. No neurological or vascular complications were seen. Computed tomography-guided cervical EBP is an optimum and effective way of treating SIH due to a leak in the cervical region. It has a higher success rate than lumbar EBP. However, prospective randomized controlled trials of cervical vs lumbar EBP will further validate our observation.

Forward numerical modelling of pleistocene marine strata, North-West of Morocco

Numerical stratigraphic forward modelling is useful to understand and reconstruct the relative sea-level and sediment supply history responsible for particular strata. This analysis uses BARSIM, a simple 2D forward stratigraphic process-response model that simulates wave and storm processes, applied with an inverse modelling optimisation method to better understand the history of Pleistocene strata in the Achakkar basin of the Tangier region, Morocco. Observations of grain size and bed thickness in four outcrop vertical sections are matched with BARSIM model output to estimate the lowest-error best-fit relative sea level and sediment supply histories that may have controlled deposition of the observed strata assuming deposition over a 10 ky period, consistent with available dating from outcrop sections. The best-fit relative sea level history drops from 4.88 to −2.82 m with two lower-amplitude highstands in between, most likely representing interglacial eustatic and tectonic event. The best-fit sediment supply is variable through time and different for each vertical section, with greatest variation from 11.7 to 2.11 m2y-1 over the 10 ky interval in the north-east vertical section. The spatial and temporal variation of sediment supply in the four vertical sections represents typically dynamic depositional conditions in shallow marine nearshore areas. On the other hand, it can indicate high stratigraphic incompleteness caused by periods of non-deposition or erosion with temporal variations in sediment supply. The optimum way for the simple model to reproduce short intervals of high sedimentation rate separated by longer periods of hiatus and deposition followed by erosion results in a discontinuous stratigraphic record.

Research on Active Disturbance Rejection Control of Small Modular Reactor Once-Through Steam Generator Based on Differential Evolution Optimization Algorithm

The pressure control of once-through steam generator (OTSG) is critical for the operation and safety of small modular reactors. However, the dynamics of the OTSG are quite nonlinear, time varying, and uncertain. Classical control methods face significant challenges in keeping the pressure within acceptable limits in an environment with frequent load variations and multiple sources of external disturbances. In this paper, a robust control strategy based on active disturbance rejection control (ADRC) optimized by the differential evolution (DE) algorithm is proposed to satisfy the requirements of steam pressure control in an optimum and efficient way. First, a lumped parameter model for the OTSG is developed based on the notion of moving boundaries and linearized to introduce a transfer function model for control design purposes. Then a feedforward cascade control system based on an ADRC controller and a proportional integral differential (PID) controller is designed, which mainly consists of a pressure ADRC controller, a feedwater PID controller, and a feedforward compensator. To improve the pressure control performance and parameter tuning efficiency of the OTSG control system, a DE algorithm is applied to optimize the ADRC parameters, and the frequency domain and time domain characteristics are compared with particle swarm optimization and the genetic algorithm. Transient simulation experiments were used to evaluate the control performance at 100%, 50%, and 25% power levels, respectively. Moreover, a performance robustness criterion is proposed to demonstrate the robust stability of the ADRC, and the robustness metric is compared with that of the PID control schemes. The simulation results show that DE-ADRC control strategy has better set point tracking, interference rejection, and robust stability than DE-PID control strategy.

Optimized extraction methodology for phenolic compounds in soil and plant tissues: Their implications in plant growth and gall formation

Phenolic compounds, abundant secondary metabolites in plants, profoundly influence soil ecosystems, plant growth, and interactions with herbivores. Phenolic in soil microorganisms have the potential to impact a wide range of activities in plant-soil interactions. However, the existing methods for measuring microbial activity are typically time-consuming, intricate, and expensive. In this study, we propose modifications to the method used for the extraction and quantification of various types of phenolics in soil and plant tissues. There have been substantial advancements in research aimed at extracting, identifying, and quantifying phenolic compounds in the plant and soil samples. This study discusses the use of different methodologies in the analysis of phenolic compounds. In addition, we investigated the effect of phenolics on plant growth and cues in gall-forming under environmental disturbances.•This method is the optimum way to extract phenolic from soil and microbial activity in bulk and rhizosphere soil.•It can be used on any soil type and plant tissue, metabolites extracted from living organisms.

Zinc Nutrition in Rice Based Cropping Systems: A Comprehensive Review

Rice-based cropping systems being the most practiced cropping system in India, it suffers zinc deficiency as majority of the Indian soils are deficient in the Zn micronutrient. Zn is considered the fourth most important yield limiting nutrient of Agricultural crops. Apart from plant nutrition Zn also plays crucial role in human nutrition. Zn plays a vital role in the physiological function of plants and it is associated with phytohormone activity, protein synthesis and carbohydrate metabolism. To understand better zinc nutrition and its associated benefits from optimum nutrition and ways to manage Zn in rice-based cropping systems, the present review critically examines nutrient mobilization and transformation of Zn in rice-based cropping systems of India.

Pragmatic algorithm for management of common bile duct calculi in resource-limited settings in India.

Endoscopic retrograde cholangiopancreatography (ERCP) facilitates the removal of common bile duct (CBD) calculi by endoscopy. When ERCP fails, exploration of CBD is required for the clearance of CBD calculi. The optimum way for the exploration of CBD is by choledochoscopy. Dedicated flexible or rigid choledochoscopes are expensive and available only in few places in India. Since 1991, we subjected patients with suspected CBD calculi to ERCP, followed by laparoscopic cholecystectomy (LC). Patients in whom ERCP failed to clear CBD were subjected to open exploration of CBD using any easily available, suitable, straight rigid scope for choledochoscopy. Since March 1991, out of 8866 patients with cholelithiasis, 862 underwent ERCP. Ninety-six patients in whom ERCP failed to clear CBD underwent open exploration of CBD. In each case of exploration of CBD, choledochoscopy was performed using a straight rigid scope, either a cystoscope, paediatric cystoscope, hysteroscope or 5-mm laparoscopy telescope with a 5-mm cannula. The CBD clearance was complete in 95 patients, and one patient had an impacted calculus at the ampulla. CBD explorations were followed by choledochoduodenostomy, T-tube placement or suturing of choledochotomy. No residual calculi were observed after such exploration. From our results, we advocate the following algorithm for CBD calculi in resource-limited settings. Subject patients with CBD calculi to ERCP followed by LC. In case of failed ERCP, open exploration of CBD with choledochoscopy using any suitable rigid scope. Dedicated flexible or rigid choledochoscope is not essential. This approach is cost-effective and successful.

Effect of Mixing Intensity on Electrochemical Performance of Oxide/Sulfide Composite Electrolytes

Despite the variety of solid electrolytes available, no single solid electrolyte has been found that meets all the requirements of the successor technology of lithium-ion batteries in an optimum way. However, composite hybrid electrolytes that combine the desired properties such as high ionic conductivity or stability against lithium are promising. The addition of conductive oxide fillers to sulfide solid electrolytes has been reported to increase ionic conductivity and improve stability relative to the individual electrolytes, but the influence of the mixing process to create composite electrolytes has not been investigated. Here, we investigate Li3PS4 (LPS) and Li7La3Zr2O12 (LLZO) composite electrolytes using electrochemical impedance spectroscopy and distribution of relaxation times. The distinction between sulfide bulk and grain boundary polarization processes is possible with the methods used at temperatures below 10 °C. We propose lithium transport through the space-charge layer within the sulfide electrolyte, which increases the conductivity. With increasing mixing intensities in a high-energy ball mill, we show an overlay of the enhanced lithium-ion transport with the structural change of the sulfide matrix component, which increases the ionic conductivity of LPS from 4.1 × 10−5 S cm−1 to 1.7 × 10−4 S cm−1.

Active heating of greenhouse integrated semitransparent photovoltaic thermal system with series connected semitransparent photovoltaic thermal air collectors

In order to fulfill the demand for energy and food security, an active heating of a controlled environment greenhouse integrated semitransparent photovoltaic thermal (GiSPVT) system with N-semitransparent photovoltaic thermal (SPVT) air collector for cold climatic conditions has been analyzed in this paper. The proposed SPVT air collectors are connected in series and integrated with GiSPVT. It is used to generate thermal as well as electrical energy to meet the daily requirements of users. Based on the energy balance equation which is a function of design and climatic parameters, an analytical expression for various variable parameters namely plant, room air, and solar cell temperatures have been derived. Numerical computation has been made in Matlab for computing the thermal, electrical, and overall exergy of the proposed system. Based on numerical computation, the following observations have been made: (i) From a thermal point of view, the packing factor (0.5, 0.8) of the semitransparent PV module plays an important role and it must be optimized for maximum thermal heating. (ii) The selection of a number of collector N is an important parameter to generate electrical energy as well as thermal heating of GiSPVT room air in an optimum way.

Rapid Targeted Assembly of the Proteome Reveals Evolutionary Variation of GC Content in Avian Lice.

Nucleotide base composition plays an influential role in the molecular mechanisms involved in gene function, phenotype, and amino acid composition. GC content (proportion of guanine and cytosine in DNA sequences) shows a high level of variation within and among species. Many studies measure GC content in a small number of genes, which may not be representative of genome-wide GC variation. One challenge when assembling extensive genomic data sets for these studies is the significant amount of resources (monetary and computational) associated with data processing, and many bioinformatic tools have not been optimized for resource efficiency. Using a high-performance computing (HPC) cluster, we manipulated resources provided to the targeted gene assembly program, automated target restricted assembly method (aTRAM), to determine an optimum way to run the program to maximize resource use. Using our optimum assembly approach, we assembled and measured GC content of all of the protein-coding genes of a diverse group of parasitic feather lice. Of the 499 426 genes assembled across 57 species, feather lice were GC-poor (mean GC = 42.96%) with a significant amount of variation within and between species (GC range = 19.57%-73.33%). We found a significant correlation between GC content and standard deviation per taxon for overall GC and GC3, which could indicate selection for G and C nucleotides in some species. Phylogenetic signal of GC content was detected in both GC and GC3. This research provides a large-scale investigation of GC content in parasitic lice laying the foundation for understanding the basis of variation in base composition across species.

Artificial Intelligence in Indian Education: Navigating Challenges and Embracing Opportunities

This research paper explores the varied role of Artificial Intelligence in the teaching-learning process in the Indian context, focusing on its potential as an empowering tool in the hands of both teachers as well as students. AI can alleviate administrative and repetitive burden for teachers, allowing them to focus on face-to-face interactions with students. It can be used by a teacher in a variety of ways including personalised learning pathways, curriculum delivery, managing classroom dynamics and assessment design. Policymakers can gain data-driven decision-making capabilities. Students can also benefit from this new technology by experiencing a more individualised and interactive learning. Besides, there is a need for a comprehensive approach to address social and ethical aspects associated with AI. Controversies surrounding AI are discussed and optimum ways for the integration of AI into education are suggested. Instead of viewing it as a threat, the paper advocates for its responsible use and recognises it as a collaborative teaching and learning tool. AI can thus be used as a transformative catalyst to facilitate pedagogy and learning in India.

Power Aware MANET Routing Protocol for Efficient Packet Transmission Using T–Test and Sleep and Awake Strategy

The majority of the suggested routing protocols have not given any attention to energy consumption whatsoever, despite the fact that advances in battery design have not yet reached the point where a device can be able to operate for a longer amount of time. Energy-efficient routing is one of the crucial issues that must be taken into account in MANETs. Numerous scholars have offered highly effective solutions for this problem. Since all nodes in MANETs are connected to and run by low-power battery devices, energy-aware routing is without a doubt the highest design standard The lifespan of the network is eventually shortened when an intermediary node is shut down due to a power outage because it not only impacts the node's own system but also its capacity to relay packets on behalf of others. The untimely shutdown of a node damages the entire network system because packet forwarding on the route will become fully disconnected as soon as a node Electronics 2020, 9, 1129 5 of 64 fails due to a power outage. However, the preceding node continues to wastefully retransmit the same packets up to a specific threshold, wasting both its power and bandwidth in the process. The preceding node then informs the source that the path is severed as a result of this. Finally, route finding is once more carried out by the source node, which uses a lot of energy in the network. This work suggested a new routing method that uses the T-test procedure to discover the most effective path between nodes. This proposed technique recursively identifies the optimum way between nodes for communication, ensuring that each node participating in route discovery has enough energy for transmission. The T-Test procedure defines and supports the criteria for evaluating the nodes that are chosen and rejected during the route discovery process. This technique, in conjunction with T-Test, enables successful packet transmission in MANET packet flows with sleep and awake strategies. It is also developed using network simulation and compared to the present routing system, indicating that it performs better overall.

Biosynthesis and Characterization of Silver Nanoparticles-Synthesized using Extracts of Mangrove Sonneratia caseolaris leaves

The bottom-up method offers the optimum ways to synthesize nanoparticles efficiently and in an environmental friendly way. The phenolic compound contained in plant extract can be used to synthesize nanoparticles. The purpose of this study was to determine the ability of Sonneratia caseolaris mangrove leaf extract to synthesize silver nanoparticles (AgNPs). Further characterization and investigation of the antibacterial activity were also scrutinized. The first stage was the extraction of mangrove Sonneratia caseolaris leaves. The second stage was biosynthesis of the silver nanoparticles using three (1, 5 and 10 mM) concentrations of AgNO3. The third stage was investigating its characteristics and its antibacterial activity. The results showed that mangrove Sonneratia caseolaris leaf extract could produce biosynthesis nanoparticles from AgNO3. The best reaction for silver nanoparticles was 10 min reaction times with a concentration of 5 mM AgNO3. In the characterization with FTIR, the peak results obtained from biosynthesis were 3431.89, 1632.43, 1508.99, 1429.92, 928.46, 706.66 and 579.37. The size of silver nanoparticles ranged from 90-200 nm. The antibacterial activity of AgNPs dominantly inhibited gram-negative bacteria Escherichia coli and Salmonella thyphimurium.

Multi-Objective Optimization of Welding Processes Using Modified Rao Algorithms

The welding community faces a challenging problem in choosing the best welding methods since they are multi-input processes. Modern manufacturing industries have requirements to get fast and optimum process parameters to utilize complete resources in an optimum way. This work attempts to improve the performance of submerged arc welding (SAW), friction welding (FW), and gas tungsten arc welding (GTAW) processes by optimizing their parameters. The newly developed Rao algorithms and their modified versions known as quasi-oppositional Rao (QO Rao), self-adaptive multi-population elite Rao (SAMPE Rao), and improved Rao (I-Rao) are used. This paper contains four multi-objective optimization case studies of SAW, FW, and GTAW processes. A weighted approach is employed to tackle the multi-objective optimization problems effectively. The outcomes achieved using the Rao, QO Rao, SAMPE Rao, and I-Rao algorithms are compared with those obtained by the established optimization algorithms such as accelerated cuckoo optimization algorithm (ACCOA), cuckoo optimization algorithm (COA), plant propagation algorithm (PPA), teaching–learning-based optimization (TLBO) algorithm, Jaya algorithm, quasi-oppositional Jaya (QO Jaya) algorithm, genetic algorithm (GA), particle swarm optimization (PSO) algorithm, and heat transfer search (HTS) algorithm. The effectiveness of the Rao algorithms and their modified versions has been clearly demonstrated as these algorithms have provided superior solutions while requiring fewer generations to achieve them.

ADAPTIVE TRAFFIC SYSTEM CONTROLLERS IN TRAFFIC ENGINEERING : A SURVEY

In today’s era, traffic congestion is the widest spread problem observed all over the world, arising as consequence of exponential rise in vehicle count at the traffic intersections. This growth has largely affected the people as they are experiencing enhanced delay in travelling time and increased fuel consumption which led to wastage of billions of dollars. The current road infrastructure design and traffic signal controlling using a cycle of fixed time phase of green/red/yellow lights are not adequate to tackle the rising demands of traffic in an optimum way. These traditional traffic signal systems cannot handle the dynamics of road traffic at the intersections and hence results in exceeding delays. Also, the volume of traffic at any intersection at different times of the day is uncertain and hence it is hard to get an exact mathematical model for this problem. Many researchers have proposed some solution to this problem and their work is reviewed extensively in this paper. Due to its ability to deal with uncertainty, fuzzy logic is considered as the most appropriate technique to solve this problem and is highly recommended method for implementing automated traffic controllers. Due to its inherent advantages, most of the research in the field of traffic engineering is carried out using fuzzy logic techniques. Hence, this paper presents a systematic review of various techniques that are used for an effective management of traffic, especially focusing on different fuzzy based traffic controllers and their performance comparison to identify the best input output parameter.

Review of discrete fracture network characterization for geothermal energy extraction

Geothermal reservoirs are highly anisotropic and heterogeneous, and thus require a variety of structural geology, geomechanical, remote sensing, geophysical and hydraulic techniques to inform Discrete Fracture Network flow models. Following the Paris Agreement on reduction of carbon emissions, such reservoirs have received more attention and new techniques that support Discrete Fracture Network models were developed. A comprehensive review is therefore needed to merge innovative and traditional technical approaches into a coherent framework to enhance the extraction of geothermal energy from the deep subsurface. Traditionally, statistics extracted from structural scanlines and unmanned aerial vehicle surveys on analogues represent optimum ways to constrain the length of joints, bedding planes, and faults, thereby generating a model of the network of fractures. Combining borehole images with seismic attributes has also proven to be an excellent approach that supports the stochastic generation of Discrete Fracture Network models by detecting the orientation, density, and dominant trends of the fractures in the reservoirs. However, to move forward to flow modelling, computation of transmissivities from pumping tests, and the determination of hydraulically active fractures allow the computation of the hydraulic aperture in permeable sedimentary rocks. The latter parameter is fundamental to simulating flow in a network of discrete fractures. The mechanical aperture can also be estimated based on the characterization of geomechanical parameters (Poisson’s ratio, and Young’s modulus) in Hot Dry Rocks of igneous-metamorphic origin. Compared with previous review studies, this paper will be the first to describe all the geological and hydro-geophysical techniques that inform Discrete Fracture Network development in geothermal frameworks. We therefore envisage that this paper represents a useful and holistic guide for future projects on preparing DFN models.