Search results for: simulated soil

Authors: U. S. Putro, L. Mayangsari, M. Siallagan, N. P. Tjahyani

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National Collective Management Institute (LKMN) in Indonesia stated that legal music products were about 77.552.008 unit while illegal music products were about 22.0688.225 unit in 1996 and this number keeps getting worse every year. Consequently, Indonesia named as one of the countries with high piracy levels in 2005. This study models people decision toward unlawful behavior, music content piracy in particular, using agent-based modeling and simulation (ABMS). The classification of actors in the model constructed in this study are legal consumer, illegal consumer, and neutral consumer. The decision toward piracy among the actors is a manifestation of the social norm which attributes are social pressure, peer pressure, social approval, and perceived prevalence of piracy. The influencing attributes fluctuate depending on the majority of surrounding behavior called social network. There are two main interventions undertaken in the model, campaign and peer influence, which leads to scenarios in the simulation: positively-framed descriptive norm message, negatively-framed descriptive norm message, positively-framed injunctive norm with benefits message, and negatively-framed injunctive norm with costs message. Using NetLogo, the model is simulated in 30 runs with 10.000 iteration for each run. The initial number of agent was set 100 proportion of 95:5 for illegal consumption. The assumption of proportion is based on the data stated that 95% sales of music industry are pirated. The finding of this study is that negatively-framed descriptive norm message has a worse reversed effect toward music piracy. The study discovers that selecting the context-based campaign is the key process to reduce the level of intention toward music piracy as unlawful behavior by increasing the compliance awareness. The context of Indonesia reveals that that majority of people has actively engaged in music piracy as unlawful behavior, so that people think that this illegal act is common behavior. Therefore, providing the information about how widespread and big this problem is could make people do the illegal consumption behavior instead. The positively-framed descriptive norm message scenario works best to reduce music piracy numbers as it focuses on supporting positive behavior and subject to the right perception on this phenomenon. Music piracy is not merely economical, but rather social phenomenon due to the underlying motivation of the actors which has shifted toward community sharing. The indication of misconception of value co-creation in the context of music piracy in Indonesia is also discussed. This study contributes theoretically that understanding how social norm configures the behavior of decision-making process is essential to breakdown the phenomenon of unlawful behavior in music industry. In practice, this study proposes that reward-based and context-based strategy is the most relevant strategy for stakeholders in music industry. Furthermore, this study provides an opportunity that findings may generalize well beyond music piracy context. As an emerging body of work that systematically constructs the backstage of law and social affect decision-making process, it is interesting to see how the model is implemented in other decision-behavior related situation.

Keywords: music piracy, social norm, behavioral decision-making, agent-based model, value co-creation

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Authors: Galatee Levadoux, Trevor Benson, Chris Worrall

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With the rise of public awareness on climate change comes an increasing demand for renewable sources of energy. As a result, the wind power sector is striving to manufacture longer, more efficient and reliable wind turbine blades. Currently, one of the leading causes of blade failure in service is improper cure of the resin during manufacture. The infusion process creating the main part of the composite blade structure remains a critical step that is yet to be monitored in real time. This stage consists of a viscous resin being drawn into a mould under vacuum, then undergoing a curing reaction until solidification. Successful infusion assumes the resin fills all the voids and cures completely. Given that the electrical properties of the resin change significantly during its solidification, both the filling of the mould and the curing reaction are susceptible to be followed using dieletrometry. However, industrially available dielectrics sensors are currently too small to monitor the entire surface of a wind turbine blade. The aim of the present research project is to scale up the dielectric sensor technology and develop a device able to monitor the manufacturing process of large composite structures, assessing the conformity of the blade before it even comes out of the mould. An array of flat copper wires acting as electrodes are embedded in a polymer matrix fixed in an infusion mould. A multi-frequency analysis from 1 Hz to 10 kHz is performed during the filling of the mould with an epoxy resin and the hardening of the said resin. By following the variations of the complex admittance Y*, the filling of the mould and curing process are monitored. Results are compared to numerical simulations of the sensor in order to validate a virtual cure-monitoring system. The results obtained by drawing glycerol on top of the copper sensor displayed a linear relation between the wetted length of the sensor and the complex admittance measured. Drawing epoxy resin on top of the sensor and letting it cure at room temperature for 24 hours has provided characteristic curves obtained when conventional interdigitated sensor are used to follow the same reaction. The response from the developed sensor has shown the different stages of the polymerization of the resin, validating the geometry of the prototype. The model created and analysed using COMSOL has shown that the dielectric cure process can be simulated, so long as a sufficient time and temperature dependent material properties can be determined. The model can be used to help design larger sensors suitable for use with full-sized blades. The preliminary results obtained with the sensor prototype indicate that the infusion and curing process of an epoxy resin can be followed with the chosen configuration on a scale of several decimeters. Further work is to be devoted to studying the influence of the sensor geometry and the infusion parameters on the results obtained. Ultimately, the aim is to develop a larger scale sensor able to monitor the flow and cure of large composite panels industrially.

Keywords: composite manufacture, dieletrometry, epoxy, resin infusion, wind turbine blades

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Authors: Ankit Tyagi, Reet Kamal Tiwari, Naveen James

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Landslide is the major geo-environmental problem of Himalaya because of high ridges, steep slopes, deep valleys, and complex system of streams. They are mainly triggered by rainfall and earthquake and causing severe damage to life and property. In Uttarakhand, the Tehri reservoir rim area, which is situated in the lesser Himalaya of Garhwal hills, was selected for landslide hazard zonation (LHZ). The study utilized different types of data, including geological maps, topographic maps from the survey of India, Landsat 8, and Cartosat DEM data. This paper presents the use of a weighted overlay method in LHZ using fourteen causative factors. The various data layers generated and co-registered were slope, aspect, relative relief, soil cover, intensity of rainfall, seismic ground shaking, seismic amplification at surface level, lithology, land use/land cover (LULC), normalized difference vegetation index (NDVI), topographic wetness index (TWI), stream power index (SPI), drainage buffer and reservoir buffer. Seismic analysis is performed using peak horizontal acceleration (PHA) intensity and amplification factors in the evaluation of the landslide hazard index (LHI). Several digital image processing techniques such as topographic correction, NDVI, and supervised classification were widely used in the process of terrain factor extraction. Lithological features, LULC, drainage pattern, lineaments, and structural features are extracted using digital image processing techniques. Colour, tones, topography, and stream drainage pattern from the imageries are used to analyse geological features. Slope map, aspect map, relative relief are created by using Cartosat DEM data. DEM data is also used for the detailed drainage analysis, which includes TWI, SPI, drainage buffer, and reservoir buffer. In the weighted overlay method, the comparative importance of several causative factors obtained from experience. In this method, after multiplying the influence factor with the corresponding rating of a particular class, it is reclassified, and the LHZ map is prepared. Further, based on the land-use map developed from remote sensing images, a landslide vulnerability study for the study area is carried out and presented in this paper.

Keywords: weighted overlay method, GIS, landslide hazard zonation, remote sensing

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Authors: I. M. L. Nadeesha Jayaweera, Adao Alex Trindade

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In choosing a candidate model in likelihood-based modeling via an information criterion, the practitioner is often faced with the difficult task of deciding just how far up the ranked list to look. Motivated by this pragmatic necessity, we construct an uncertainty band for a generalized (model selection) information criterion (GIC), defined as a criterion for which the limit in probability is identical to that of the normalized log-likelihood. This includes common special cases such as AIC & BIC. The method starts from the asymptotic normality of the GIC for the joint distribution of the candidate models in an independent and identically distributed (IID) data framework and proceeds by deriving the (asymptotically) exact distribution of the minimum. The calculation of an upper quantile for its distribution then involves the computation of multivariate Gaussian integrals, which is amenable to efficient implementation via the R package "mvtnorm". The performance of the methodology is tested on simulated data by checking the coverage probability of nominal upper quantiles and compared to the bootstrap. Both methods give coverages close to nominal for large samples, but the bootstrap is two orders of magnitude slower. The methodology is subsequently extended to two other commonly used model structures: regression and time series. In the regression case, we derive the corresponding asymptotically exact distribution of the minimum GIC invoking Lindeberg-Feller type conditions for triangular arrays and are thus able to similarly calculate upper quantiles for its distribution via multivariate Gaussian integration. The bootstrap once again provides a default competing procedure, and we find that similar comparison performance metrics hold as for the IID case. The time series case is complicated by far more intricate asymptotic regime for the joint distribution of the model GIC statistics. Under a Gaussian likelihood, the default in most packages, one needs to derive the limiting distribution of a normalized quadratic form for a realization from a stationary series. Under conditions on the process satisfied by ARMA models, a multivariate normal limit is once again achieved. The bootstrap can, however, be employed for its computation, whence we are once again in the multivariate Gaussian integration paradigm for upper quantile evaluation. Comparisons of this bootstrap-aided semi-exact method with the full-blown bootstrap once again reveal a similar performance but faster computation speeds. One of the most difficult problems in contemporary statistical methodological research is to be able to account for the extra variability introduced by model selection uncertainty, the so-called post-model selection inference (PMSI). We explore ways in which the GIC uncertainty band can be inverted to make inferences on the parameters. This is being attempted in the IID case by pivoting the CDF of the asymptotically exact distribution of the minimum GIC. For inference one parameter at a time and a small number of candidate models, this works well, whence the attained PMSI confidence intervals are wider than the MLE-based Wald, as expected.

Keywords: model selection inference, generalized information criteria, post model selection, Asymptotic Theory

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Authors: Maria De Albuquerque Bercot, Caio Gustavo Mesquita Angelo, Daniela Maria Moreira Siqueira, Augusto Assucena De Vasconcellos, Rodrigo Studart Correa

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Mining is an important socioeconomic activity in Brazil although it negatively impacts the environment. Mineral operations cause irreversible changes in topography, removal of vegetation and topsoil, habitat destruction, displacement of fauna, loss of biodiversity, soil erosion, siltation of watercourses and have potential to enhance climate change. Due to the impacts and its pollution potential, mining activity in Brazil is legally subjected to environmental licensing. Unlicensed mining operations or operations that not abide to the terms of an obtained license are taken as environmental crimes in the country. This work reports a case analyzed in the Forensic Institute of the Brazilian Federal District Civil Police. The case consisted of detecting illegal aspects of sand exploitation from a licensed mine in Federal District, nearby Brasilia city. The fieldwork covered an area of roughly 6 ha, which was surveyed with an unmanned aerial vehicle (UAV) (PHANTOM 3 ADVANCED). The overflight with UAV took about 20 min, with maximum flight height of 100 m. 592 UAV georeferenced images were obtained and processed in a photogrammetric software (AGISOFT PHOTOSCAN 1.1.4), which generated a mosaic of geo-referenced images and a 3D model in less than six working hours. The 3D model was analyzed in a forensic software for accurate modeling and volumetric analysis. (MAPTEK I-SITE FORENSIC 2.2). To ensure the 3D model was a true representation of the mine site, coordinates of ten control points and reference measures were taken during fieldwork and compared to respective spatial data in the model. Finally, these spatial data were used for measuring mining area, excavation depth and volume of exploited sand. Results showed that mine holder had not complied with some terms and conditions stated in the granted license, such as sand exploration beyond authorized extension, depth and volume. Easiness, the accuracy and expedition of procedures used in this case highlight the employment of UAV imagery and computational photogrammetry as efficient tools for outdoor forensic exams, especially on environmental issues.

Keywords: computational photogrammetry, environmental monitoring, mining, UAV

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Authors: Aleksander Ejsmont, Aleksandra Galarda, Joanna Goscianska

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Smart porous carriers with defined structure and physicochemical properties are required for releasing the therapeutic drug with precise control of delivery time and location in the body. Due to their non-toxicity, ordered structure, chemical, and thermal stability, mesoporous carbons can be considered as modern carriers for active pharmaceutical ingredients (APIs) whose effectiveness needs frequent dosing algorithms. Such an API-carrier system, if programmed precisely, may stabilize the pharmaceutical and increase its dissolution leading to enhanced bioavailability. The substance conjugated with the material, through its prior adsorption, can later be successfully applied internally to the organism, as well as externally if the API release is feasible under these conditions. In the present study, ordered mesoporous carbons of different morphologies and structures, prepared by hard template method, were applied as carriers in the adsorption and controlled release of active pharmaceutical ingredients. In the first stage, the carbon materials were synthesized and functionalized with carboxylic groups by chemical oxidation using ammonium persulfate solution and then with amine groups. Materials obtained were thoroughly characterized with respect to morphology (scanning electron microscopy), structure (X-ray diffraction, transmission electron microscopy), characteristic functional groups (FT-IR spectroscopy), acid-base nature of surface groups (Boehm titration), parameters of the porous structure (low-temperature nitrogen adsorption) and thermal stability (TG analysis). This was followed by a series of tests of adsorption and release of paracetamol, benzocaine, and losartan potassium. Drug release experiments were performed in the simulated gastric fluid of pH 1.2 and phosphate buffer of pH 7.2 or 6.8 at 37.0 °C. The XRD patterns in the small-angle range and TEM images revealed that functionalization of mesoporous carbons with carboxylic or amine groups leads to the decreased ordering of their structure. Moreover, the modification caused a considerable reduction of the carbon-specific surface area and pore volume, but it simultaneously resulted in changing their acid-base properties. Mesoporous carbon materials exhibit different morphologies, which affect the host-guest interactions during the adsorption process of active pharmaceutical ingredients. All mesoporous carbons show high adsorption capacity towards drugs. The sorption capacity of materials is mainly affected by BET surface area and the structure/size matching between adsorbent and adsorbate. Selected APIs are linked to the surface of carbon materials mainly by hydrogen bonds, van der Waals forces, and electrostatic interactions. The release behavior of API is highly dependent on the physicochemical properties of mesoporous carbons. The release rate of APIs could be regulated by the introduction of functional groups and by changing the pH of the receptor medium. Acknowledgments—This research was supported by the National Science Centre, Poland (project SONATA-12 no: 2016/23/D/NZ7/01347).

Keywords: ordered mesoporous carbons, sorption capacity, drug delivery, carbon nanocarriers

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Authors: Aamir Shahzad, Mao-Gang He

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Currently, dusty plasmas motivated the researchers' widespread interest. Since the last two decades, substantial efforts have been made by the scientific and technological community to investigate the transport properties and their nonlinear behavior of three-dimensional and two-dimensional nonideal complex (dusty plasma) liquids (NICDPLs). Different calculations have been made to sustain and utilize strongly coupled NICDPLs because of their remarkable scientific and industrial applications. Understanding of the thermophysical properties of complex liquids under various conditions is of practical interest in the field of science and technology. The determination of thermal conductivity is also a demanding question for thermophysical researchers, due to some reasons; very few results are offered for this significant property. Lack of information of the thermal conductivity of dense and complex liquids at different parameters related to the industrial developments is a major barrier to quantitative knowledge of the heat flux flow from one medium to another medium or surface. The exact numerical investigation of transport properties of complex liquids is a fundamental research task in the field of thermophysics, as various transport data are closely related with the setup and confirmation of equations of state. A reliable knowledge of transport data is also important for an optimized design of processes and apparatus in various engineering and science fields (thermoelectric devices), and, in particular, the provision of precise data for the parameters of heat, mass, and momentum transport is required. One of the promising computational techniques, the homogenous nonequilibrium molecular dynamics (HNEMD) simulation, is over viewed with a special importance on the application to transport problems of complex liquids. This proposed work is particularly motivated by the FIRST TIME to modify the problem of heat conduction equations leads to polynomial velocity and temperature profiles algorithm for the investigation of transport properties with their nonlinear behaviors in the NICDPLs. The aim of proposed work is to implement a NEMDS algorithm (Poiseuille flow) and to delve the understanding of thermal conductivity behaviors in Yukawa liquids. The Yukawa system is equilibrated through the Gaussian thermostat in order to maintain the constant system temperature (canonical ensemble ≡ NVT)). The output steps will be developed between 3.0×105/ωp and 1.5×105/ωp simulation time steps for the computation of λ data. The HNEMD algorithm shows that the thermal conductivity is dependent on plasma parameters and the minimum value of lmin shifts toward higher G with an increase in k, as expected. New investigations give more reliable simulated data for the plasma conductivity than earlier known simulation data and generally the plasma λ0 by 2%-20%, depending on Γ and κ. It has been shown that the obtained results at normalized force field are in satisfactory agreement with various earlier simulation results. This algorithm shows that the new technique provides more accurate results with fast convergence and small size effects over a wide range of plasma states.

Keywords: molecular dynamics simulation, thermal conductivity, nonideal complex plasma, Poiseuille flow

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Authors: Andres Nieto-Leal, Victor N. Kaliakin, Tania P. Molina

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The nature of most engineering materials is quite complex. It is, therefore, difficult to devise a general mathematical model that will cover all possible ranges and types of excitation and behavior of a given material. As a result, the development of mathematical models is based upon simplifying assumptions regarding material behavior. Such simplifications result in some material idealization; for example, one of the simplest material idealization is to assume that the material behavior obeys the elasticity. However, soils are nonhomogeneous, anisotropic, path-dependent materials that exhibit nonlinear stress-strain relationships, changes in volume under shear, dilatancy, as well as time-, rate- and temperature-dependent behavior. Over the years, many constitutive models, possessing different levels of sophistication, have been developed to simulate the behavior geomaterials, particularly cohesive soils. Early in the development of constitutive models, it became evident that elastic or standard elastoplastic formulations, employing purely isotropic hardening and predicated in the existence of a yield surface surrounding a purely elastic domain, were incapable of realistically simulating the behavior of geomaterials. Accordingly, more sophisticated constitutive models have been developed; for example, the bounding surface elastoplasticity. The essence of the bounding surface concept is the hypothesis that plastic deformations can occur for stress states either within or on the bounding surface. Thus, unlike classical yield surface elastoplasticity, the plastic states are not restricted only to those lying on a surface. Elastoplastic bounding surface models have been improved; however, there is still need to improve their capabilities in simulating the response of anisotropically consolidated cohesive soils, especially the response in extension tests. Thus, in this work an improved constitutive model that can more accurately predict diverse stress-strain phenomena exhibited by cohesive soils was developed. Particularly, an improved rotational hardening rule that better simulate the response of cohesive soils in extension. The generalized definition of the bounding surface model provides a convenient and elegant framework for unifying various previous versions of the model for anisotropically consolidated cohesive soils. The Generalized Bounding Surface Model for cohesive soils is a fully three-dimensional, time-dependent model that accounts for both inherent and stress induced anisotropy employing a non-associative flow rule. The model numerical implementation in a computer code followed an adaptive multistep integration scheme in conjunction with local iteration and radial return. The one-step trapezoidal rule was used to get the stiffness matrix that defines the relationship between the stress increment and the strain increment. After testing the model in simulating the response of cohesive soils through extensive comparisons of model simulations to experimental data, it has been shown to give quite good simulations. The new model successfully simulates the response of different cohesive soils; for example, Cardiff Kaolin, Spestone Kaolin, and Lower Cromer Till. The simulated undrained stress paths, stress-strain response, and excess pore pressures are in very good agreement with the experimental values, especially in extension.

Keywords: bounding surface elastoplasticity, cohesive soils, constitutive model, modeling of geomaterials

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Authors: Iris Vogeler, Rogerio Cichota, Armin Werner

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Dairy farms are under pressure to increase productivity while reducing environmental impacts. Effective fertiliser management practices are critical to achieve this. Determination of optimum nitrogen (N) fertilisation rates which maximise pasture growth and minimise N losses is challenging due to variability in plant requirements and likely near-future supply of N by the soil. Remote sensing can be used for mapping N nutrition status of plants and to rapidly assess the spatial variability within a field. An algorithm is, however, lacking which relates the N status of the plants to the expected yield response to additions of N. The aim of this simulation study was to develop a multi-variate model for determining N fertilisation rate for a target percentage of the maximum achievable yield based on the pasture N concentration (ii) use of an algorithm for guiding fertilisation rates, and (iii) evaluation of the model regarding pasture yield and N losses, including N leaching, denitrification and volatilisation. A simulation study was carried out using the Agricultural Production Systems Simulator (APSIM). The simulations were done for an irrigated ryegrass pasture in the Canterbury region of New Zealand. A multi-variate model was developed and used to determine monthly required N fertilisation rates based on pasture N content prior to fertilisation and targets of 50, 75, 90 and 100% of the potential monthly yield. These monthly optimised fertilisation rules were evaluated by running APSIM for a ten-year period to provide yield and N loss estimates from both nonurine and urine affected areas. Comparison with typical fertilisation rates of 150 and 400 kg N/ha/year was also done. Assessment of pasture yield and leaching from fertiliser and urine patches indicated a large reduction in N losses when N fertilisation rates were controlled by the multi-variate model. However, the reduction in leaching losses was much smaller when taking into account the effects of urine patches. The proposed approach based on biophysical modelling to develop a multi-variate model for determining optimum N fertilisation rates dependent on pasture N content is very promising. Further analysis, under different environmental conditions and validation is required before the approach can be used to help adjust fertiliser management practices to temporal and spatial N demand based on the nitrogen status of the pasture.

Keywords: APSIM modelling, optimum N fertilization rate, pasture N content, ryegrass pasture, three dimensional surface response function.

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Authors: Samita Sondhi, Sachin Kumar, Chirag Chopra

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The increase in population has resulted in an excessive feedstock production, which has in return lead to the accumulation of a large amount of waste from different resources as crop residues, industrial waste and solid municipal waste. This situation has raised the problem of waste disposal in present days. A parallel problem of depletion of natural fossil fuel resources has led to the formation of alternative sources of energy from the waste of different industries to concurrently resolve the two issues. The biogas is a carbon neutral fuel which has applications in transportation, heating and power generation. India is a nation that has an agriculture-based economy and agro-residues are a significant source of organic waste. Taking into account, the second largest agro-based industry that is sugarcane industry producing a high quantity of sugar and sugarcane waste byproducts such as Bagasse, Press Mud, Vinasse and Wastewater. Currently, there are not such efficient disposal methods adopted at large scales. According to manageability objectives, anaerobic digestion can be considered as a method to treat organic wastes. Press mud is lignocellulosic biomass and cannot be accumulated for Mono digestion because of its complexity. Prior investigations indicated that it has a potential for production of biogas. But because of its biological and elemental complexity, Mono-digestion was not successful. Due to the imbalance in the C/N ratio and presence of wax in it can be utilized with any other fibrous material hence will be digested properly under suitable conditions. In the first batch of Mono-digestion of Pressmud biogas production was low. Now, co-digestion of Pressmud with Bagasse which has desired C/N ratio will be performed to optimize the ratio for maximum biogas from Press mud. In addition, with respect to supportability, the main considerations are the monetary estimation of item result and ecological concerns. The work is designed in such a way that the waste from the sugar industry will be digested for maximum biogas generation and digestive after digestion will be characterized for its use as a bio-fertilizer for soil conditioning. Due to effectiveness demonstrated by studied setups of Mono-digestion and Co-digestion, this approach can be considered as a viable alternative for lignocellulosic waste disposal and in agricultural applications. Biogas produced from the Pressmud either can be used for Powerhouses or transportation. In addition, the work initiated towards the development of waste disposal for energy production will demonstrate balanced economy sustainability of the process development.

Keywords: anaerobic digestion, carbon neutral fuel, press mud, lignocellulosic biomass

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Authors: Nick Toossi, Joseph Hartland

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Background: Malawi is an example of a low resource setting which faces a chronic shortage of doctors and other medical staff. This shortfall is made up for by clinical officers (COs), who are para-medicals trained for 4 years. The literature suggests to improve outcomes surgical skills training specifically should be promoted for COs in district and mission hospitals. Accordingly, the primary author was tasked with developing a basic surgical skills teaching package for COs of Mulanje Mission Hospital (MMH), Malawi, as part of a 4th year medical student External Student Selected Component field trip. MMH is a hospital based in the South of Malawi near the base of Mulanje Mountain and works in an extremely isolated environment with some of the poorest communities in the country. Traveling to Malawi the medical student author performed an educational needs assessment to develop and deliver a bespoke basic surgical skills teaching package. Methodology: An initial needs assessment identified the following domains: basic surgical skills (instrument naming & handling, knot tying, suturing principles and suturing techniques) and perineal repair. Five COs took part in a teaching package involving an interactive group simulation session, overseen by senior clinical officers and surgical trainees from the UK. Non-organic and animal models were used for simulation practice. This included the use of surgical skills boards to practice knot tying and ox tongue to simulate perineal repair. All participants spoke and read English. The impact of the session was analysed in two different ways. The first was via a pre and post Single Best Answer test and the second a questionnaire including likert’s scales and free text response questions. Results: There was a positive trend in pre and post test scores on competition of the course. There was increase in the mean confidence of learners before and after the delivery of teaching in basic surgical skills and simulated perineal repair, especially in ‘instrument naming and handling’. Whilst positively received it was discovered that learners desire more frequent surgical skills teaching sessions in order to improve and revise skills. Feedback suggests that the learners were not confident in retaining the skills without regular input. Discussion: Skills and confidence were improved as a result of the teaching provided. Learner's written feedback suggested there was an overall appetite for regular surgical skills teaching in the clinical environment and further opportunities to allow for deliberate self-practice. Surgical mentorship schemes facilitating supervised theatre time among trainees and lead surgeons along with improving access to surgical models/textbooks were some of the simple suggestions to improve surgical skills and confidence among COs. Although, this study is limited by population size it is reflective of the small, isolated and low resource environment in which this healthcare is delivered. This project does suggest that current surgical skills packages used in the UK could be adapted for employment in low resource settings, but it is consistency and sustainability that staff seek above all in their on-going education.

Keywords: clinical officers, education, Malawi, surgical skills

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Authors: Hellen L. De Castro e Silva, Ana A. Robles Aguilar, Erik Meers

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Digestates are residual by-products, rich in nutrients and trace elements, which can be used as organic fertilisers on soils. However, due to the non-digestibility of these elements and reduced dry matter during the anaerobic digestion process, metal concentrations are higher in digestates than in feedstocks, which might hamper their use as fertilisers according to the threshold values of some country policies. Furthermore, there is uncertainty regarding the required assimilated amount of these elements by some crops, which might result in their bioaccumulation. Therefore, further processing of the digestate to obtain safe fertilizing products has been recommended. This research aims to analyze the effect of applying the hydrothermal carbonization process to manure-derived digestates as a thermal treatment to reduce the bioavailability of heavy metals in mono and co-digestates derived from pig manure and maize from contaminated land in France. This study examined pig manure collected from a novel stable system (VeDoWs, province of East Flanders, Belgium) that separates the collection of pig urine and feces, resulting in a solid fraction of manure with high up-concentration of heavy metals and nutrients. Mono-digestion and co-digestion processes were conducted in semi-continuous reactors for 45 days at mesophilic conditions, in which the digestates were dried at 105 °C for 24 hours. Then, hydrothermal carbonization was applied to a 1:10 solid/water ratio to guarantee controlled experimental conditions in different temperatures (180, 200, and 220 °C) and residence times (2 h and 4 h). During the process, the pressure was generated autogenously, and the reactor was cooled down after completing the treatments. The solid and liquid phases were separated through vacuum filtration, in which the solid phase of each treatment -hydrochar- was dried and ground for chemical characterization. Different fractions (exchangeable / adsorbed fraction - F1, carbonates-bound fraction - F2, organic matter-bound fraction - F3, and residual fraction – F4) of some heavy metals (Cd, Cr, Ni, and Cr) have been determined in digestates and derived hydrochars using the modified Community Bureau of Reference (BCR) sequential extraction procedure. The main results indicated a difference in the heavy metals fractionation between digestates and their derived hydrochars; however, the hydrothermal carbonization operating conditions didn’t have remarkable effects on heavy metals partitioning between the hydrochars of the proposed treatments. Based on the estimated potential ecological risk assessment, there was one level decrease (considerate to moderate) when comparing the HMs partitioning in digestates and derived hydrochars.

Keywords: heavy metals, bioavailability, hydrothermal treatment, bio-based fertilisers, agriculture

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Model assessment, in the Bayesian context, involves evaluation of the goodness-of-fit and the comparison of several alternative candidate models for predictive accuracy and improvements. In posterior predictive checks, the data simulated under the fitted model is compared with the actual data. Predictive model accuracy is estimated using information criteria such as the Akaike information criterion (AIC), the Bayesian information criterion (BIC), the Deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). The goal of an information criterion is to obtain an unbiased measure of out-of-sample prediction error. Since posterior checks use the data twice; once for model estimation and once for testing, a bias correction which penalises the model complexity is incorporated in these criteria. Cross-validation (CV) is another method used for examining out-of-sample prediction accuracy. Leave-one-out cross-validation (LOO-CV) is the most computationally expensive variant among the other CV methods, as it fits as many models as the number of observations. Importance sampling (IS), truncated importance sampling (TIS) and Pareto-smoothed importance sampling (PSIS) are generally used as approximations to the exact LOO-CV and utilise the existing MCMC results avoiding expensive computational issues. The reciprocals of the predictive densities calculated over posterior draws for each observation are treated as the raw importance weights. These are in turn used to calculate the approximate LOO-CV of the observation as a weighted average of posterior densities. In IS-LOO, the raw weights are directly used. In contrast, the larger weights are replaced by their modified truncated weights in calculating TIS-LOO and PSIS-LOO. Although, information criteria and LOO-CV are unable to reflect the goodness-of-fit in absolute sense, the differences can be used to measure the relative performance of the models of interest. However, the use of these measures is only valid under specific circumstances. This study has developed 11 models using normal, log-normal, gamma, and student’s t distributions to improve the PCR stutter prediction with forensic data. These models are comprised of four with profile-wide variances, four with locus specific variances, and three which are two-component mixture models. The mean stutter ratio in each model is modeled as a locus specific simple linear regression against a feature of the alleles under study known as the longest uninterrupted sequence (LUS). The use of AIC, BIC, DIC, and WAIC in model comparison has some practical limitations. Even though, IS-LOO, TIS-LOO, and PSIS-LOO are considered to be approximations of the exact LOO-CV, the study observed some drastic deviations in the results. However, there are some interesting relationships among the logarithms of pointwise predictive densities (lppd) calculated under WAIC and the LOO approximation methods. The estimated overall lppd is a relative measure that reflects the overall goodness-of-fit of the model. Parallel log-likelihood profiles for the models conditional on equal posterior variances in lppds were observed. This study illustrates the limitations of the information criteria in practical model comparison problems. In addition, the relationships among LOO-CV approximation methods and WAIC with their limitations are discussed. Finally, useful recommendations that may help in practical model comparisons with these methods are provided.

Keywords: cross-validation, importance sampling, information criteria, predictive accuracy

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Authors: Márcia Afonso, Marisa Dinis-Almeida, Cristina Fael

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Climate change, namely precipitation patterns alteration, has led to extreme conditions such as floods and droughts. In turn, excessive construction has led to the waterproofing of the soil, increasing the surface runoff and decreasing the groundwater recharge capacity. The permeable pavements used in areas with low traffic lead to a decrease in the probability of floods peaks occurrence and the sediments reduction and pollutants transport, ensuring rainwater quality improvement. This study aims to evaluate the porous asphalt performance, developed in the laboratory, with addition of cellulosic fibres. One of the main objectives of cellulosic fibres use is to stop binder drainage, preventing its loss during storage and transport. Comparing to the conventional porous asphalt the cellulosic fibres addition improved the porous asphalt performance. The cellulosic fibres allowed the bitumen content increase, enabling retention and better aggregates coating and, consequently, a greater mixture durability. With this solution, it is intended to develop better practices of resilience and adaptation to the extreme climate changes and respond to the sustainability current demands, through the eco-friendly materials use. The mix design was performed for different size aggregates (with fine aggregates – PA1 and with coarse aggregates – PA2). The percentage influence of the fibres to be used was studied. It was observed that overall, the binder drainage decreases as the cellulose fibres percentage increases. It was found that the PA2 mixture obtained most binder drainage relative to PA1 mixture, irrespective of the fibres percentage used. Subsequently, the performance was evaluated through laboratory tests of indirect tensile stiffness modulus, water sensitivity, permeability and permanent deformation. The stiffness modulus for the two mixtures groups (with and without cellulosic fibres) presented very similar values between them. For the water sensitivity test it was observed that porous asphalt containing more fine aggregates are more susceptible to the water presence than mixtures with coarse aggregates. The porous asphalt with coarse aggregates have more air voids which allow water to pass easily leading to ITSR higher values. In the permeability test was observed that asphalt porous without cellulosic fibres presented had lower permeability than asphalt porous with cellulosic fibres. The resistance to permanent deformation results indicates better behaviour of porous asphalt with cellulosic fibres, verifying a bigger rut depth in porous asphalt without cellulosic fibres. In this study, it was observed that porous asphalt with bitumen higher percentages improve the performance to permanent deformation. This fact was only possible due to the bitumen retention by the cellulosic fibres.

Keywords: binder drainage, cellulosic fibres, permanent deformation, porous asphalt

Procedia PDF Downloads 198

Authors: Naohiro Nakamura, Takuya Kinoshita, Hiroshi Fukuyama

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The 2011 off The Pacific Coast of Tohoku Earthquake caused considerable damage to wide areas of eastern Japan. A large number of earthquake observation records were obtained at various places. To design more earthquake-resistant buildings and improve earthquake disaster prevention, it is necessary to utilize these data to analyze and evaluate the behavior of a building during an earthquake. This paper presents an earthquake response simulation analysis (hereafter a seismic response analysis) that was conducted using data recorded during the main earthquake (hereafter the main shock) as well as the earthquakes before and after it. The data were obtained at a high-rise steel-reinforced concrete (SRC) building in the bay area of Tokyo. We first give an overview of the building, along with the characteristics of the earthquake motion and the building during the main shock. The data indicate that there was a change in the natural period before and after the earthquake. Next, we present the results of our seismic response analysis. First, the analysis model and conditions are shown, and then, the analysis result is compared with the observational records. Using the analysis result, we then study the effect of soil-structure interaction on the response of the building. By identifying the characteristics of the building during the earthquake (i.e., the 1st natural period and the 1st damping ratio) by the Auto-Regressive eXogenous (ARX) model, we compare the analysis result with the observational records so as to evaluate the accuracy of the response analysis. In this study, a lumped-mass system SR model was used to conduct a seismic response analysis using observational data as input waves. The main results of this study are as follows: 1) The observational records of the 3/11 main shock put it between a level 1 and level 2 earthquake. The result of the ground response analysis showed that the maximum shear strain in the ground was about 0.1% and that the possibility of liquefaction occurring was low. 2) During the 3/11 main shock, the observed wave showed that the eigenperiod of the building became longer; this behavior could be generally reproduced in the response analysis. This prolonged eigenperiod was due to the nonlinearity of the superstructure, and the effect of the nonlinearity of the ground seems to have been small. 3) As for the 4/11 aftershock, a continuous analysis in which the subject seismic wave was input after the 3/11 main shock was input was conducted. The analyzed values generally corresponded well with the observed values. This means that the effect of the nonlinearity of the main shock was retained by the building. It is important to consider this when conducting the response evaluation. 4) The first period and the damping ratio during a vibration were evaluated by an ARX model. Our results show that the response analysis model in this study is generally good at estimating a change in the response of the building during a vibration.

Keywords: ARX model, response analysis, SRC building, the 2011 off the Pacific Coast of Tohoku Earthquake

Procedia PDF Downloads 142

Authors: Weili Jiang, Simon Cadavid Lopera, Klaus Drechsler

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Fuel cell vehicle has become the most competitive solution for the transportation sector in the hydrogen economy. Type IV pressure vessel is currently the most popular and widely developed technology for the on-board storage, based on their high reliability and relatively low cost. Due to the stringent requirement on mechanical performance, the pressure vessel is subject to great amount of composite material, a major cost driver for the hydrogen tanks. Evidently, the optimization of composite layup design shows great potential in reducing the overall material usage, yet requires comprehensive understanding on underlying mechanisms as well as the influence of different design parameters on mechanical performance. Given the type of materials and manufacturing processes by which the type IV pressure vessels are manufactured, the design and optimization are a nuanced subject. The manifold of stacking sequence and fiber orientation variation possibilities have an out-standing effect on vessel strength due to the anisotropic property of carbon fiber composites, which make the design space high dimensional. Each variation of design parameters requires computational resources. Using finite element analysis to evaluate different designs is the most common method, however, the model-ing, setup and simulation process can be very time consuming and result in high computational cost. For this reason, it is necessary to build a reliable automation scheme to set up and analyze the di-verse composite layups. In this research, the simulation process of different tank designs regarding various parameters is conducted and automatized in a commercial finite element analysis framework Abaqus. Worth mentioning, the modeling of the composite overwrap is automatically generated using an Abaqus-Python scripting interface. The prediction of the winding angle of each layer and corresponding thickness variation on dome region is the most crucial step of the modeling, which is calculated and implemented using analytical methods. Subsequently, these different composites layups are simulated as axisymmetric models to facilitate the computational complexity and reduce the calculation time. Finally, the results are evaluated and compared regarding the ultimate tank strength. By automatically modeling, evaluating and comparing various composites layups, this system is applicable for the optimization of the tanks structures. As mentioned above, the mechanical property of the pressure vessel is highly dependent on composites layup, which requires big amount of simulations. Consequently, to automatize the simulation process gains a rapid way to compare the various designs and provide an indication of the optimum one. Moreover, this automation process can also be operated for creating a data bank of layups and corresponding mechanical properties with few preliminary configuration steps for the further case analysis. Subsequently, using e.g. machine learning to gather the optimum by the data pool directly without the simulation process.

Keywords: type IV pressure vessels, carbon composites, finite element analy-sis, automation of simulation process

Procedia PDF Downloads 100

Authors: Anna Mucha, Ewa Wojtyna, Anita Pollak

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The environment in which an individual resides and observes may play a meaningful role in well-being and related constructs. Contact with nature may have a positive influence of natural environments on individuals, impacting mood and psychophysical sensations, such as pain relief. Conversely, urban settings, dominated by concrete elements, might lead to mood decline and heightened stress levels. Similarly, the situation may appear in the case of the perception of virtual environments. However, this is a topic that requires further exploration, especially in the context of relationships with pain. The aforementioned matters served as the basis for formulating and executing the outlined experimental research within the realm of environmental psychology, leveraging new technologies, notably virtual reality (VR), which is progressively gaining prominence in the domain of mental health. The primary objective was to investigate the impact of a simulated virtual environment, mirroring a natural setting abundant in greenery, on the perception of acute pain induced by thermal stimuli (high temperature) – encompassing intensity, unpleasantness, and pain tolerance. Comparative analyses were conducted between the virtual natural environment (intentionally constructed in the likeness of a therapeutic garden), virtual urban environment, and a control group devoid of virtual projections. Secondary objectives aimed to determine the mutual relationships among variables such as positive and negative emotions, preferences regarding virtual environments, sense of presence, and restorative experience in the context of the perception of presented virtual environments and induced thermal pain. The study encompassed 126 physically healthy Polish adults, distributing 42 individuals across each of the three comparative groups. Oculus Rift VR technology and the TSA-II neurosensory analyzer facilitated the experiment. Alongside demographic data, participants' subjective feelings concerning virtual reality and pain were evaluated using the Visual Analogue Scale (VAS), the original Restorative Experience in the Virtual World questionnaire (Doświadczenie Regeneracji w Wirtualnym Świecie), and an adapted Slater-Usoh-Steed (SUS) questionnaire. Results of statistical and psychometric analyses, such as Kruskal-Wallis tests, Wilcoxon tests, and contrast analyses, underscored the positive impact of the virtual natural environment on individual pain perception and mood. The virtual natural environment outperformed the virtual urban environment and the control group without virtual projection, particularly in subjective pain components like intensity and unpleasantness. Variables such as restorative experience, sense of presence and virtual environment preference also proved pivotal in pain perception and pain tolerance threshold alterations, contingent on specific conditions. This implies considerable application potential for virtual natural environments across diverse realms of psychology and related fields, among others as a supportive analgesic approach and a form of relaxation following psychotherapeutic sessions.

Keywords: environmental psychology, nature, acute pain, emotions, vitrual reality, virtual environments

Procedia PDF Downloads 40

Authors: Laura Micheli, Majd Hijazi, Mahmoud Faytarouni

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The damage reported by oil and gas industrial facilities revealed the utmost vulnerability of steel liquid storage tanks to seismic events. The failure of steel storage tanks may yield devastating and long-lasting consequences on built and natural environments, including the release of hazardous substances, uncontrolled fires, and soil contamination with hazardous materials. It is, therefore, fundamental to reliably predict the damage that steel liquid storage tanks will likely experience under future seismic hazard events. The seismic performance of steel liquid storage tanks is usually assessed using vulnerability curves obtained from the numerical simulation of a tank under different hazard scenarios. However, the computational demand of high-fidelity numerical simulation models, such as finite element models, makes the vulnerability assessment of liquid storage tanks time-consuming and often impractical. As a solution, this paper presents a surrogate model-based strategy for predicting seismic-induced damage in steel liquid storage tanks. In the proposed strategy, the surrogate model is leveraged to reduce the computational demand of time-consuming numerical simulations. To create the data set for training the surrogate model, field damage data from past earthquakes reconnaissance surveys and reports are collected. Features representative of steel liquid storage tank characteristics (e.g., diameter, height, liquid level, yielding stress) and seismic excitation parameters (e.g., peak ground acceleration, magnitude) are extracted from the field damage data. The collected data are then utilized to train a surrogate model that maps the relationship between tank characteristics, seismic hazard parameters, and seismic-induced damage via a data-driven surrogate model. Different types of surrogate algorithms, including naïve Bayes, k-nearest neighbors, decision tree, and random forest, are investigated, and results in terms of accuracy are reported. The model that yields the most accurate predictions is employed to predict future damage as a function of tank characteristics and seismic hazard intensity level. Results show that the proposed approach can be used to estimate the extent of damage in steel liquid storage tanks, where the use of data-driven surrogates represents a viable alternative to computationally expensive numerical simulation models.

Keywords: damage prediction , data-driven model, seismic performance, steel liquid storage tanks, surrogate model

Procedia PDF Downloads 124

Authors: Mathuravech Thanaphon, Thephasit Nat

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The Electricity Generating Authority of Thailand (EGAT) is focusing on expanding its pumped storage hydropower (PSH) capacity to increase the reliability of the system during peak demand and allow for greater integration of renewables. To achieve this requirement, Thailand will have to double its current renewable electricity production. To address the challenges of balancing supply and demand in the grid with increasing levels of RE penetration, as well as rising peak demand, EGAT has already been studying the potential for additional PSH capacity for several years to enable an increased share of RE and replace existing fossil fuel-fired generation. In addition, the role that pumped-storage hydropower would play in fulfilling multiple grid functions and renewable integration. The proposed sites for new PSH would help increase the reliability of power generation in Thailand. However, most of the electricity generation will come from RE, chiefly wind and photovoltaic, and significant additional Energy Storage capacity will be needed. In this paper, the impact of integrating the PSH system on the adequacy of renewable rich power generating systems to reduce the thermal power generating units is investigated. The variations of system adequacy indices are analyzed for different PSH-renewables capacities and storage levels. Power Development Plan 2018 rev.1 (PDP2018 rev.1), which is modified by integrating a six-new PSH system and RE planning and development aftermath in 2030, is the very challenge. The system adequacy indices through power generation are obtained using Multi-Objective Genetic Algorithm (MOGA) Optimization. MOGA is a probabilistic heuristic and stochastic algorithm that is able to find the global minima, which have the advantage that the fitness function does not necessarily require the gradient. In this sense, the method is more flexible in solving reliability optimization problems for a composite power system. The optimization with hourly time step takes years of planning horizon much larger than the weekly horizon that usually sets the scheduling studies. The objective function is to be optimized to maximize RE energy generation, minimize energy imbalances, and minimize thermal power generation using MATLAB. The PDP2018 rev.1 was set to be simulated based on its planned capacity stepping into 2030 and 2050. Therefore, the four main scenario analyses are conducted as the target of renewables share: 1) Business-As-Usual (BAU), 2) National Targets (30% RE in 2030), 3) Carbon Neutrality Targets (50% RE in 2050), and 5) 100% RE or full-decarbonization. According to the results, the generating system adequacy is significantly affected by both PSH-RE and Thermal units. When a PSH is integrated, it can provide hourly capacity to the power system as well as better allocate renewable energy generation to reduce thermal generations and improve system reliability. These results show that a significant level of reliability improvement can be obtained by PSH, especially in renewable-rich power systems.

Keywords: pumped storage hydropower, renewable energy integration, system adequacy, power development planning, RE100, multi-objective genetic algorithm

Procedia PDF Downloads 32

Authors: Andreas Lind, Aitor Iriondo Pascual, Dan Hogberg, Lars Hanson

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Factory setup lifecycles are most often described and prepared in CAD environments; the preparation is based on experience and inputs from several cross-disciplinary processes. Early in the factory setup preparation, a so-called block layout is created. The intention is to describe a high-level view of the intended factory setup and to claim area reservations and allocations. Factory areas are then blocked, i.e., targeted to be used for specific intended resources and processes, later redefined with detailed factory setup layouts. Each detailed layout is based on the block layout and inputs from cross-disciplinary preparation processes, such as manufacturing sequence, productivity, workers’ workplace requirements, and resource setup preparation. However, this activity is often not carried out with all variables considered simultaneously, which might entail a risk of sub-optimizing the detailed layout based on manual decisions. Therefore, this work aims to realize a digital method for assembly manufacturing layout planning where productivity, area utilization, and ergonomics can be considered simultaneously in a cross-disciplinary manner. The purpose of the digital method is to support engineers in finding optimized designs of detailed layouts for assembly manufacturing factories, thereby facilitating better decisions regarding setups of future factories. Input datasets are company-specific descriptions of required dimensions for specific area reservations, such as defined dimensions of a worker’s workplace, material façades, aisles, and the sequence to realize the product assembly manufacturing process. To test and iteratively develop the digital method, a demonstrator has been developed with an adaptation of existing software that simulates and proposes optimized designs of detailed layouts. Since the method is to consider productivity, ergonomics, area utilization, and constraints from the automatically generated block layout, a multi-objective optimization approach is utilized. In the demonstrator, the input data are sent to the simulation software industrial path solutions (IPS). Based on the input and Lua scripts, the IPS software generates a block layout in compliance with the company’s defined dimensions of area reservations. Communication is then established between the IPS and the software EPP (Ergonomics in Productivity Platform), including intended resource descriptions, assembly manufacturing process, and manikin (digital human) resources. Using multi-objective optimization approaches, the EPP software then calculates layout proposals that are sent iteratively and simulated and rendered in IPS, following the rules and regulations defined in the block layout as well as productivity and ergonomics constraints and objectives. The software demonstrator is promising. The software can handle several parameters to optimize the detailed layout simultaneously and can put forward several proposals. It can optimize multiple parameters or weight the parameters to fine-tune the optimal result of the detailed layout. The intention of the demonstrator is to make the preparation between cross-disciplinary silos transparent and achieve a common preparation of the assembly manufacturing factory setup, thereby facilitating better decisions.

Keywords: factory setup, multi-objective, optimization, simulation

Procedia PDF Downloads 126

Authors: Saqib Aziz, Brad Alexander, Christoph Gengnagel, Stefan Weinzierl

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This paper explores a generative design, simulation, and optimization workflow for the integration of acoustical diffuser and/or absorber geometry with embedded coupled Helmholtz-resonators for full-scale 3D printed building components. Large-scale additive manufacturing in conjunction with algorithmic CAD design tools enables a vast amount of control when creating geometry. This is advantageous regarding the increasing demands of comfort standards for indoor spaces and the use of more resourceful and sustainable construction methods and materials. The presented methodology highlights these new technological advancements and offers a multimodal and integrative design solution with the potential for an immediate application in the AEC-Industry. In principle, the methodology can be applied to a wide range of structural elements that can be manufactured by additive manufacturing processes. The current paper focuses on a case study of an application for a biaxial load-bearing beam grillage made of reinforced concrete, which allows for a variety of applications through the combination of additive prefabricated semi-finished parts and in-situ concrete supplementation. The semi-prefabricated parts or formwork bodies form the basic framework of the supporting structure and at the same time have acoustic absorption and diffusion properties that are precisely acoustically programmed for the space underneath the structure. To this end, a hybrid validation strategy is being explored using a digital and cross-platform simulation environment, verified with physical prototyping. The iterative workflow starts with the generation of a parametric design model for the acoustical geometry using the algorithmic visual scripting editor Grasshopper3D inside the building information modeling (BIM) software Revit. Various geometric attributes (i.e., bottleneck and cavity dimensions) of the resonator are parameterized and fed to a numerical optimization algorithm which can modify the geometry with the goal of increasing absorption at resonance and increasing the bandwidth of the effective absorption range. Using Rhino.Inside and LiveLink for Revit, the generative model was imported directly into the Multiphysics simulation environment COMSOL. The geometry was further modified and prepared for simulation in a semi-automated process. The incident and scattered pressure fields were simulated from which the surface normal absorption coefficients were calculated. This reciprocal process was repeated to further optimize the geometric parameters. Subsequently the numerical models were compared to a set of 3D concrete printed physical twin models, which were tested in a .25 m x .25 m impedance tube. The empirical results served to improve the starting parameter settings of the initial numerical model. The geometry resulting from the numerical optimization was finally returned to grasshopper for further implementation in an interdisciplinary study.

Keywords: acoustical design, additive manufacturing, computational design, multimodal optimization

Procedia PDF Downloads 136

Authors: Husam Abdulmuttaleb Hashim

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The environmental pollution problems represent a great challenge to the world, threatening to destroy all the evolution that mankind has reached, the organizations and associations that cares about environment are trying to warn the world from the forthcoming danger resulted from excessive use of nature resources and consuming it without looking to the damage happened as a result of unfair use of it. Most of the urban centers suffers from the environmental pollution problems and health, economic, and social dangers resulted from this pollution, and while the land use planning is responsible for distributing different uses in urban centers and controlling the interactions between these uses to reach a homogeneous and perfect state for the different activities in cities, the occurrence of environmental problems in the shade of existing land use planning operation refers to the disorder or insufficiency in this operation which leads to presence of such problems, and this disorder lays in lack of sufficient importance to the environmental considerations during the land use planning operations and setting up the master plan, so the research start to study this problem and finding solutions for it, the research assumes that using accurate and scientific methods in early stages of land use planning operation will prevent occurring of environmental pollution problems in the future, the research aims to study and show the importance of the environmental impact assessment method (EIA) as an important planning tool to investigate and predict the pollution ranges of the land use that has a polluting pattern in land use planning operation. This research encompasses the concept of environmental assessment and its kinds and clarifies environmental impact assessment and its contents, the research also dealt with urban planning concept and land use planning, it also dealt with the current situation of the case study (Al-Garma district) and the land use planning in it and explain the most polluting use on the environment which is the industrial land use represented in the tannery industries and then there was a stating of current situation of this land use and explaining its contents and environmental impacts resulted from it, and then we analyzed the tests applied by the researcher for water and soil, and perform environmental evaluation through applying environmental impact assessment matrix using the direct method to reveal the pollution ranges on the ambient environment of industrial land use, and we also applied the environmental and site limits and standards by using (GIS) and (AUTOCAD) to select the site of the best alternative of the industrial region in Al-Garma district after the research approved the unsuitability of its current site location for the environmental and site limitations, the research conducted some conclusions and recommendations regard clarifying the concluded facts and to set the proper solutions.

Keywords: EIA, pollution, tannery industry, land use planning

Procedia PDF Downloads 432

Authors: Sathwik Sarvadevabhatla Kasyap, Kostas Senetakis

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The mechanical behavior of geological materials is very complex, and this complexity is related to the discrete nature of soils and rocks. Characteristics of a material at the grain scale such as particle size and shape, surface roughness and morphology, and particle contact interface are critical to evaluate and better understand the behavior of discrete materials. This study investigates experimentally the micro-mechanical behavior of quartz sand grains with emphasis on the influence of the presence of microparticles in their contact region. The outputs of the study provide some fundamental insights on the contact mechanics behavior of artificially coated grains and can provide useful input parameters in the discrete element modeling (DEM) of soils. In nature, the contact interfaces between real soil grains are commonly observed with microparticles. This is usually the case of sand-silt and sand-clay mixtures, where the finer particles may create a coating on the surface of the coarser grains, altering in this way the micro-, and thus the macro-scale response of geological materials. In this study, the micro-mechanical behavior of Leighton Buzzard Sand (LBS) quartz grains, with interference of different microparticles at their contact interfaces is studied in the laboratory using an advanced custom-built inter-particle loading apparatus. Special techniques were adopted to develop the coating on the surfaces of the quartz sand grains so that to establish repeatability of the coating technique. The characterization of the microstructure of coated particles on their surfaces was based on element composition analyses, microscopic images, surface roughness measurements, and single particle crushing strength tests. The mechanical responses such as normal and tangential load – displacement behavior, tangential stiffness behavior, and normal contact behavior under cyclic loading were studied. The behavior of coated LBS particles is compared among different classes of them and with pure LBS (i.e. surface cleaned to remove any microparticles). The damage on the surface of the particles was analyzed using microscopic images. Extended displacements in both normal and tangential directions were observed for coated LBS particles due to the plastic nature of the coating material and this varied with the variation of the amount of coating. The tangential displacement required to reach steady state was delayed due to the presence of microparticles in the contact region of grains under shearing. Increased tangential loads and coefficient of friction were observed for the coated grains in comparison to the uncoated quartz grains.

Keywords: contact interface, microparticles, micro-mechanical behavior, quartz sand

Procedia PDF Downloads 173

Authors: Jade V. Rushby, Tony Loughland, Tracy L. Durksen, Hoa Nguyen, Robert M. Klassen

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This paper reports a study investigating the development and implementation of an online multi-session ‘scenario-based learning’ (SBL) program administered to preservice teachers in Australia. The transition from initial teacher education to the teaching profession can present numerous cognitive and psychological challenges for early career teachers. Therefore, the identification of additional supports, such as scenario-based learning, that can supplement existing teacher education programs may help preservice teachers to feel more confident and prepared for the realities and complexities of teaching. Scenario-based learning is grounded in situated learning theory which holds that learning is most powerful when it is embedded within its authentic context. SBL exposes participants to complex and realistic workplace situations in a supportive environment and has been used extensively to help prepare students in other professions, such as legal and medical education. However, comparatively limited attention has been paid to investigating the effects of SBL in teacher education. In the present study, the SBL intervention provided participants with the opportunity to virtually engage with school-based scenarios, reflect on how they might respond to a series of plausible response options, and receive real-time feedback from experienced educators. The development process involved several stages, including collaboration with experienced educators to determine the scenario content based on ‘critical incidents’ they had encountered during their teaching careers, the establishment of the scoring key, the development of the expert feedback, and an extensive review process to refine the program content. The 4-part SBL program focused on areas that can be challenging in the beginning stages of a teaching career, including managing student behaviour and workload, differentiating the curriculum, and building relationships with colleagues, parents, and the community. Results from prior studies implemented by the research group using a similar 4-part format have shown a statistically significant increase in preservice teachers’ self-efficacy and classroom readiness from the pre-test to the final post-test. In the current research, professional teaching identity - incorporating self-efficacy, motivation, self-image, satisfaction, and commitment to teaching - was measured over six weeks at multiple time points: before, during, and after the 4-part scenario-based learning program. Analyses included latent growth curve modelling to assess the trajectory of change in the outcome variables throughout the intervention. The paper outlines (1) the theoretical underpinnings of SBL, (2) the development of the SBL program and methodology, and (3) the results from the study, including the impact of the SBL program on aspects of participating preservice teachers’ professional identity. The study shows how SBL interventions can be implemented alongside the initial teacher education curriculum to help prepare preservice teachers for the transition from student to teacher.

Keywords: classroom simulations, e-learning, initial teacher education, preservice teachers, professional learning, professional teaching identity, scenario-based learning, teacher development

Procedia PDF Downloads 48

Authors: Susan Mwai, Mary Muchane, Peter Wachira, Sheila Okoth, Muchai Muchane, Halima Saado

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Tropical forests harbor a wide range of biodiversity and rich macro-fungi diversity compared to the temperate regions in the World. However, biodiversity is facing the threat of extinction following the rate of forest loss taking place before proper study and documentation of macrofungi is achieved. The present study was undertaken to determine the effect of converting indigenous habitat to plantation forest on macrofungi diversity. To achieve the objective of this study, an inventory focusing on macro-fungi diversity was conducted within Kereita block in Kikuyu Escarpment forest which is on the southern side of Aberdare mountain range. The macrofungi diversity was conducted in the indigenous forest and in more than 15 year old Patula plantation forest , during the wet (long rain season, December 2014) and dry (Short rain season, May, 2015). In each forest type, 15 permanent (20m x 20m) sampling plots distributed across three (3) forest blocks were used. Both field and laboratory methods involved recording abundance of fruiting bodies, taxonomic identity of species and analysis of diversity indices and measures in terms of species richness, density and diversity. R statistical program was used to analyze for species diversity and Canoco 4.5 software for species composition. A total number of 76 genera in 28 families and 224 species were encountered in both forest types. The most represented taxa belonged to the Agaricaceae (16%), Polyporaceae (12%), Marasmiaceae, Mycenaceae (7%) families respectively. Most of the recorded macro-fungi were saprophytic, mostly colonizing the litter 38% and wood 34% based substrates, which was followed by soil organic dwelling species (17%). Ecto-mycorrhiza fungi (5%) and parasitic fungi (2%) were the least encountered. The data established that indigenous forests (native ecosystems) hosts a wide range of macrofungi assemblage in terms of density (2.6 individual fruit bodies / m2), species richness (8.3 species / plot) and species diversity (1.49/ plot level) compared to the plantation forest. The Conversion of native forest to plantation forest also interfered with species composition though did not alter species diversity. Seasonality was also shown to significantly affect the diversity of macro-fungi and 61% of the total species being present during the wet season. Based on the present findings, forested ecosystems in Kenya hold diverse macro-fungi community which warrants conservation measures.

Keywords: diversity, Indigenous forest, macro-fungi, plantation forest, season

Procedia PDF Downloads 195

Authors: Isabel Brás, Artur Figueirinha, Bruno Esteves, Luísa P. Cruz-Lopes

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The agriculture lignocellulosic by-products are receiving increased attention, namely in the search for filter materials that retain contaminants from water. These by-products, specifically almond and hazelnut shells are abundant in Portugal once almond and hazelnuts production is a local important activity. Hazelnut and almond shells have as main constituents lignin, cellulose and hemicelluloses, water soluble extractives and tannins. Along the adsorption of heavy metals from contaminated waters, water soluble compounds can leach from shells and have a negative impact in the environment. Usually, the chemical characterization of treated water by itself may not show environmental impact caused by the discharges when parameters obey to legal quality standards for water. Only biological systems can detect the toxic effects of the water constituents. Therefore, the evaluation of toxicity by biological tests is very important when deciding the suitability for safe water discharge or for irrigation applications. The main purpose of the present work was to assess the potential impacts of waters after been treated for heavy metal removal by hazelnut and almond shells adsorption systems, with short term acute toxicity tests. To conduct the study, water at pH 6 with 25 mg.L-1 of lead, was treated with 10 g of shell per litre of wastewater, for 24 hours. This procedure was followed for each bark. Afterwards the water was collected for toxicological assays; namely bacterial resistance, seed germination, Lemna minor L. test and plant grow. The effect in isolated bacteria strains was determined by disc diffusion method and the germination index of seed was evaluated using lettuce, with temperature and humidity germination control for 7 days. For aquatic higher organism, Lemnas were used with 4 days contact time with shell solutions, in controlled light and temperature. For terrestrial higher plants, biomass production was evaluated after 14 days of tomato germination had occurred in soil, with controlled humidity, light and temperature. Toxicity tests of water treated with shells revealed in some extent effects in the tested organisms, with the test assays showing a close behaviour as the control, leading to the conclusion that its further utilization may not be considered to create a serious risk to the environment.

Keywords: lignocellulosic wastes, adsorption, acute toxicity tests, risk assessment

Procedia PDF Downloads 347

Authors: Margherita Tufarelli, Leonardo Giliberti, Elena Pucci

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The fashion industry's interest in virtuality is linked, on the one hand, to the emotional and immersive possibilities of digital resources and the resulting languages and, on the other, to the greater efficiency that can be achieved throughout the value chain. The interaction between digital innovation and deep-rooted manufacturing traditions today translates into a paradigm shift for the entire fashion industry where, for example, the traditional values of industrial secrecy and know-how give way to experimentation in an open as well as participatory way, and the complete emancipation of virtual reality from actual 'reality'. The contribution aims to investigate the theme of digitisation in the Italian fashion industry, analysing its opportunities and the criticalities that have hindered its diffusion. There are two reasons why the most common approach in the fashion sector is still analogue: (i) the fashion product lives in close contact with the human body, so the sensory perception of materials plays a central role in both the use and the design of the product, but current technology is not able to restore the sense of touch; (ii) volumes are obtained by stitching flat surfaces that once assembled, given the flexibility of the material, can assume almost infinite configurations. Managing the fit and styling of virtual garments involves a wide range of factors, including mechanical simulation, collision detection, and user interface techniques for garment creation. After briefly reviewing some of the salient historical milestones in the resolution of problems related to the digital simulation of deformable materials and the user interface for the procedures for the realisation of the clothing system, the paper will describe the operation and possibilities offered today by the latest generation of specialised software. Parametric avatars and digital sartorial approach; drawing tools optimised for pattern making; materials both from the point of view of simulated physical behaviour and of aesthetic performance, tools for checking wearability, renderings, but also tools and procedures useful to companies both for dialogue with prototyping software and machinery and for managing the archive and the variants to be made. The article demonstrates how developments in technology and digital procedures now make it possible to intervene in different stages of design in the fashion industry. An integrated and additive process in which the constructed 3D models are usable both in the prototyping and communication of physical products and in the possible exclusively digital uses of 3D models in the new generation of virtual spaces. Mastering such tools requires the acquisition of specific digital skills and, at the same time, traditional skills for the design of the clothing system, but the benefits are manifold and applicable to different business dimensions. We are only at the beginning of the global digital transformation: the emergence of new professional figures and design dynamics leaves room for imagination, but in addition to applying digital tools to traditional procedures, traditional fashion know-how needs to be transferred into emerging digital practices to ensure the continuity of the technical-cultural heritage beyond the transformation.

Keywords: digital fashion, digital technology and couture, digital fashion communication, 3D garment simulation

Procedia PDF Downloads 46

Authors: Shilpa Murthy, Hazlina Binti Abu Bakar, Juliet Mathew, Chandrashekhar Thummala Hlly Sreerama Reddy, Pathiyil Ravi Shankar

Abstract:

Simulation is defined as a technique that replaces or expands real experiences with guided experiences that interactively imitate real-world processes or systems. Simulation enables learners to train in a safe and non-threatening environment. For decades, simulation has been considered an integral part of clinical teaching and learning strategy in medical education. The several types of simulation used in medical education and the clinical environment can be applied to several models, including full-body mannequins, task trainers, standardized simulated patients, virtual or computer-generated simulation, or Hybrid simulation that can be used to facilitate learning. Simulation allows healthcare practitioners to acquire skills and experience while taking care of patient safety. The recent COVID pandemic has also led to an increase in simulation use, as there were limitations on medical student placements in hospitals and clinics. The learning is tailored according to the educational needs of students to make the learning experience more valuable. Simulation in the pre-clinical years has challenges with resource constraints, effective curricular integration, student engagement and motivation, and evidence of educational impact, to mention a few. As instructors, we may have more reliance on the use of simulation for pre-clinical students while the students’ confidence levels and perceived competence are to be evaluated. Our research question was whether the implementation of simulation-based learning positively influences preclinical medical students' confidence levels and perceived competence. This study was done to align the teaching activities with the student’s learning experience to introduce more low-fidelity simulation-based teaching sessions for pre-clinical years and to obtain students’ input into the curriculum development as part of inclusivity. The study was carried out at International Medical University, involving pre-clinical year (Medical) students who were started with low-fidelity simulation-based medical education from their first semester and were gradually introduced to medium fidelity, too. The Student Satisfaction and Self-Confidence in Learning Scale questionnaire from the National League of Nursing was employed to collect the responses. The internal consistency reliability for the survey items was tested with Cronbach’s alpha using an Excel file. IBM SPSS for Windows version 28.0 was used to analyze the data. Spearman’s rank correlation was used to analyze the correlation between students’ satisfaction and self-confidence in learning. The significance level was set at p value less than 0.05. The results from this study have prompted the researchers to undertake a larger-scale evaluation, which is currently underway. The current results show that 70% of students agreed that the teaching methods used in the simulation were helpful and effective. The sessions are dependent on the learning materials that are provided and how the facilitators engage the students and make the session more enjoyable. The feedback provided inputs on the following areas to focus on while designing simulations for pre-clinical students. There are quality learning materials, an interactive environment, motivating content, skills and knowledge of the facilitator, and effective feedback.

Keywords: low-fidelity simulation, pre-clinical simulation, students satisfaction, self-confidence

Procedia PDF Downloads 36

Authors: Benukar Biswas, S. Banerjee, P. K. Bandhyopadhyaya, S. K. Patra, S. Sarkar

Abstract:

Jute can be sown as relay crop in between the lines of 15-20 days old green gram for additional pulse yield without reducing the yield of jute. The main problem of this system is water use efficiency (WUE). The increase in water productivity and reduction in production cost were reported in the zero-tilled crop. The hydrogel can hold water up to 400 times of its weight and can release 95 % of the retained water. The present field study was carried out during 2015-16 at BCKV (tropical sub-humid, 1560 mm annual rainfall, 22058/ N, 88051/ E, 9.75 m AMSL, sandy loam soil, aeric Haplaquept, pH 6.75, organic carbon 5.4 g kg-1, available N 85 kg ha-1, P2O5 15.3 kg ha-1 and K2O 40 kg ha-1) with four levels of irrigation regimes: no irrigation - RF, cumulative pan evaporation 250mm (CPE250), CPE125 and CPE83 and three levels of hydrogel: no hydrogel (H0), 2.5 kg ha-1 (H2.5) and 5 kg ha-1 (H5). Throughout the crop growing period a linear positive relationship remained between Leaf Area Index (LAI) and evapotranspiration rate. The strength of the relationship between ETa and LAI started increasing and reached its peak at 7 WAS (R2=0.78) when green gram was at its maturity, and both the crops covered the nearly entire base area. This relation starts weakening from 13 WAS due to jute leaf shading. A linear relationship between system yield and ET was also obtained in the present study. The variation in system yield might be predicted 75% with ET alone. Effective rainfall was reduced with increasing irrigation frequency due to enhanced water supply in contrast to hydrogel application due to the difference in water storage capacity. Irrigation contributed a major source of variability of ET. Higher irrigation frequency resulted in higher ET loss ranging from 574 mm in RF to 764 mm in CPE83. Hydrogel application also increased water storage on a sustained basis and supplied to crops resulting higher ET from 639 mm in H0 to 671mm in H5. WUE ranged between 0.4 kg m-3 (RF) to 0.63 kg m-3 (CPE83 H5). WUE increased with increased application of irrigation water from 0.42 kg m-3 in RF to 0.57 kg m-3 in CPE 83. Hydrogel application significantly improves the WUE from 0.45 kg m-3 in H0 to 0.50 in H2.5 and 0.54 in H5. Under relatively dry root zone (RF), both evaporation and transpiration remain at suboptimal level resulting in lower ET as well as lower system yield. Green gram – jute relay system can be water use efficient with 38% higher yield with application of hydrogel @ 2.5 kg ha-1 under deficit irrigation regime of CPE 125 over rainfed system without application of the gel. Application of gel conditioner improved water storage, checked excess water loss from the system, and mitigated ET demand of the relay system for a longer time. Hence, irrigation frequency was reduced from five times at CPE 83 to only three times in CPE 125.

Keywords: zero tillage, deficit irrigation, hydrogel, relay system

Procedia PDF Downloads 212

Authors: Dhanuj M. Gandikota

Abstract:

Sensor-derived three-dimensional (3D) point clouds of trees are invaluable in remote sensing analysis for the accurate measurement of key structural metrics, bio-inventory values, spatial planning/visualization, and ecological modeling. Machine learning (ML) holds the potential in addressing the restrictive tradeoffs in cost, spatial coverage, resolution, and information gain that exist in current point cloud sensing methods. Terrestrial laser scanning (TLS) remains the highest fidelity source of both canopy and below-canopy structural features, but usage is limited in both coverage and cost, requiring manual deployment to map out large, forested areas. While aerial laser scanning (ALS) remains a reliable avenue of LIDAR active remote sensing, ALS is also cost-restrictive in deployment methods. Space-borne photogrammetry from high-resolution satellite constellations is an avenue of passive remote sensing with promising viability in research for the accurate construction of vegetation 3-D point clouds. It provides both the lowest comparative cost and the largest spatial coverage across remote sensing methods. However, both space-borne photogrammetry and ALS demonstrate technical limitations in the capture of valuable below-canopy point cloud data. Looking to minimize these tradeoffs, we explored a class of powerful ML algorithms called Deep Learning (DL) that show promise in recent research on 3-D point cloud reconstruction and interpolation. Our research details the efficacy of applying these DL techniques to reconstruct accurate below-canopy point clouds from space-borne and aerial remote sensing through learned patterns of tree species fractal symmetry properties and the supplementation of locally sourced bio-inventory metrics. From our dataset, consisting of tree point clouds obtained from TLS, we deconstructed the point clouds of each tree into those that would be obtained through ALS and satellite photogrammetry of varying resolutions. We fed this ALS/satellite point cloud dataset, along with the simulated local bio-inventory metrics, into the DL point cloud reconstruction architectures to generate the full 3-D tree point clouds (the truth values are denoted by the full TLS tree point clouds containing the below-canopy information). Point cloud reconstruction accuracy was validated both through the measurement of error from the original TLS point clouds as well as the error of extraction of key structural metrics, such as crown base height, diameter above root crown, and leaf/wood volume. The results of this research additionally demonstrate the supplemental performance gain of using minimum locally sourced bio-inventory metric information as an input in ML systems to reach specified accuracy thresholds of tree point cloud reconstruction. This research provides insight into methods for the rapid, cost-effective, and accurate construction of below-canopy tree 3-D point clouds, as well as the supported potential of ML and DL to learn complex, unmodeled patterns of fractal tree growth symmetry.

Keywords: deep learning, machine learning, satellite, photogrammetry, aerial laser scanning, terrestrial laser scanning, point cloud, fractal symmetry

Procedia PDF Downloads 68