Search results for: computational modeling

Authors: Weikang Gong, Chunhua Li

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Dynamics plays an essential role in function exertion of proteins. Elastic network model (ENM), a harmonic potential-based and cost-effective computational method, is a valuable and efficient tool for characterizing the intrinsic dynamical properties encoded in biomacromolecule structures and has been widely used to detect the large-amplitude collective motions of proteins. Gaussian network model (GNM) and anisotropic network model (ANM) are the two often-used ENM models. In recent years, many ENM variants have been proposed. Here, we propose a small but effective modification (denoted as modified mENM) to the multiscale ENM (mENM) where fitting weights of Kirchhoff/Hessian matrixes with the least square method (LSM) is modified since it neglects the details of pairwise interactions. Then we perform its comparisons with the original mENM, traditional ENM, and parameter-free ENM (pfENM) on reproducing dynamical properties for the six representative proteins whose molecular dynamics (MD) trajectories are available in http://mmb.pcb.ub.es/MoDEL/. In the results, for B-factor prediction, mENM achieves the best performance among the four ENM models. Additionally, it is noted that with the weights of the multiscale Kirchhoff/Hessian matrixes modified, interestingly, the modified mGNM/mANM still has a much better performance than the corresponding traditional ENM and pfENM models. As to dynamical cross-correlation map (DCCM) calculation, taking the data obtained from MD trajectories as the standard, mENM performs the worst while the results produced by the modified mENM and pfENM models are close to those from MD trajectories with the latter a little better than the former. Generally, ANMs perform better than the corresponding GNMs except for the mENM. Thus, pfANM and the modified mANM, especially the former, have an excellent performance in dynamical cross-correlation calculation. Compared with GNMs (except for mGNM), the corresponding ANMs can capture quite a number of positive correlations for the residue pairs nearly largest distances apart, which is maybe due to the anisotropy consideration in ANMs. Furtherly, encouragingly the modified mANM displays the best performance in capturing the functional motional modes, followed by pfANM and traditional ANM models, while mANM fails in all the cases. This suggests that the consideration of long-range interactions is critical for ANM models to produce protein functional motions. Based on the analyses, the modified mENM is a promising method in capturing multiple dynamical characteristics encoded in protein structures. This work is helpful for strengthening the understanding of the elastic network model and provides a valuable guide for researchers to utilize the model to explore protein dynamics.

Keywords: elastic network model, ENM, multiscale ENM, molecular dynamics, parameter-free ENM, protein structure

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Authors: Calorine Twebaze, Jesca Balinga

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Field X is located on the Eastern shores of L. Albert, Uganda, on the rift flank where the gross sedimentary fill is typically less than 2,000m. The field was discovered in 2006 and encountered about 20.4m of net pay across three (3) stratigraphic intervals within the discovery well. The field covers an area of 3 km2, with the structural configuration comprising a 3-way dip-closed hanging wall anticline that seals against the basement to the southeast along the bounding fault. Field X had been mapped on reprocessed 3D seismic data, which was originally acquired in 2007 and reprocessed in 2013. The seismic data quality is good across the field, and reprocessing work reduced the uncertainty in the location of the bounding fault and enhanced the lateral continuity of reservoir reflectors. The current study was a re-evaluation of Field X to refine fault interpretation and understand the structural uncertainties associated with the field. The seismic data, and three (3) wells datasets were used during the study. The evaluation followed standard workflows using Petrel software and structural attribute analysis. The process spanned from seismic- -well tie, structural interpretation, and structural uncertainty analysis. Analysis of three (3) well ties generated for the 3 wells provided a geophysical interpretation that was consistent with geological picks. The generated time-depth curves showed a general increase in velocity with burial depth. However, separation in curve trends observed below 1100m was mainly attributed to minimal lateral variation in velocity between the wells. In addition to Attribute analysis, three velocity modeling approaches were evaluated, including the Time-Depth Curve, Vo+ kZ, and Average Velocity Method. The generated models were calibrated at well locations using well tops to obtain the best velocity model for Field X. The Time-depth method resulted in more reliable depth surfaces with good structural coherence between the TWT and depth maps with minimal error at well locations of 2 to 5m. Both the NNE-SSW rift border fault and minor faults in the existing interpretation were reevaluated. However, the new interpretation delineated an E-W trending fault in the northern part of the field that had not been interpreted before. The fault was interpreted at all stratigraphic levels and thus propagates from the basement to the surface and is an active fault today. It was also noted that the entire field is less faulted with more faults in the deeper part of the field. The major structural uncertainties defined included 1) The time horizons due to reduced data quality, especially in the deeper parts of the structure, an error equal to one-third of the reflection time thickness was assumed, 2) Check shot analysis showed varying velocities within the wells thus varying depth values for each well, and 3) Very few average velocity points due to limited wells produced a pessimistic average Velocity model.

Keywords: 3D seismic data interpretation, structural uncertainties, attribute analysis, velocity modelling approaches

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Authors: Vadim Allheily, Rudiger Schmitt, Lionel Merlat, Gildas L'Hostis

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Inflight devices are nowadays major actors in both military and civilian landscapes. Among others, missiles, mortars, rockets or even drones this last decade are increasingly sophisticated, and it is today of prior manner to develop always more efficient defensive systems from all these potential threats. In this frame, recent High Energy Laser weapon prototypes (HEL) have demonstrated some extremely good operational abilities to shot down within seconds flying targets several kilometers off. Whereas test outcomes are promising from both experimental and cost-related perspectives, the deterioration process still needs to be explored to be able to closely predict the effects of a high-energy laser irradiation on typical structures, heading finally to an effective design of laser sources and protective countermeasures. Laser matter interaction researches have a long history of more than 40 years at the French-German Research Institute (ISL). Those studies were tied with laser sources development in the mid-60s, mainly for specific metrology of fast phenomena. Nowadays, laser matter interaction can be viewed as the terminal ballistics of conventional weapons, with the unique capability of laser beams to carry energy at light velocity over large ranges. In the last years, a strong focus was made at ISL on the interaction process of laser radiation with metal targets such as artillery shells. Due to the absorbed laser radiation and the resulting heating process, an encased explosive charge can be initiated resulting in deflagration or even detonation of the projectile in flight. Drones and Unmanned Air Vehicles (UAVs) are of outmost interests in modern warfare. Those aerial systems are usually made up of polymer-based composite materials, whose complexity involves new scientific challenges. Aside this main laser-matter interaction activity, a lot of experimental and numerical knowledge has been gathered at ISL within domains like spectrometry, thermodynamics or mechanics. Techniques and devices were developed to study separately each aspect concerned by this topic; optical characterization, thermal investigations, chemical reactions analysis or mechanical examinations are beyond carried out to neatly estimate essential key values. Results from these diverse tasks are then incorporated into analytic or FE numerical models that were elaborated, for example, to predict thermal repercussion on explosive charges or mechanical failures of structures. These simulations highlight the influence of each phenomenon during the laser irradiation and forecast experimental observations with good accuracy.

Keywords: composite materials, countermeasure, experimental work, high-energy laser, laser-matter interaction, modeling

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Authors: Soma Banerjee, Aamen Talukdar, Argha Mandal, Dipankar Chaudhuri

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Japanese Encephalitis is a major infectious disease with nearly half the world’s population living in areas where it is prevalent. Currently, treatment for it involves only supportive care and symptom management through vaccination. Due to the lack of antiviral drugs against Japanese Encephalitis Virus (JEV), the quest for such agents remains a priority. For these reasons, simulation studies of drug targets against JEV are important. Towards this purpose, docking experiments of the kinase inhibitors were done against the chosen target NS3 helicase as it is a nucleoside binding protein. Previous efforts regarding computational drug design against JEV revealed some lead molecules by virtual screening using public domain software. To be more specific and accurate regarding finding leads, in this study a proprietary software Schrödinger-GLIDE has been used. Druggability of the pockets in the NS3 helicase crystal structure was first calculated by SITEMAP. Then the sites were screened according to compatibility with ATP. The site which is most compatible with ATP was selected as target. Virtual screening was performed by acquiring ligands from databases: KinaseSARfari, KinaseKnowledgebase and Published inhibitor Set using GLIDE. The 25 ligands with best docking scores from each database were re-docked in XP mode. Protein structure alignment of NS3 was performed using VAST against MMDB, and similar human proteins were docked to all the best scoring ligands. The low scoring ligands were chosen for further studies and the high scoring ligands were screened. Seventy-three ligands were listed as the best scoring ones after performing HTVS. Protein structure alignment of NS3 revealed 3 human proteins with RMSD values lesser than 2Å. Docking results with these three proteins revealed the inhibitors that can interfere and inhibit human proteins. Those inhibitors were screened. Among the ones left, those with docking scores worse than a threshold value were also removed to get the final hits. Analysis of the docked complexes through 2D interaction diagrams revealed the amino acid residues that are essential for ligand binding within the active site. Interaction analysis will help to find a strongly interacting scaffold among the hits. This experiment yielded 21 hits with the best docking scores which could be investigated further for their drug like properties. Aside from getting suitable leads, specific NS3 helicase-inhibitor interactions were identified. Selection of Target modification strategies complementing docking methodologies which can result in choosing better lead compounds are in progress. Those enhanced leads can lead to better in vitro testing.

Keywords: antivirals, docking, glide, high-throughput virtual screening, Japanese encephalitis, ns3 helicase

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Authors: Rohini Sharma, Chandan Kumar Sahoo, Rama Krishna Gupta Potnuru

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Strong competitive forces and requirements to achieve efficiency are forcing the organizations to realize the necessity and inevitability of change. What's more, the trend does not appear to be abating. Researchers have estimated that about two thirds of change project fails. Empirical evidences further shows that organizations invest significantly in the planned change but people side is accounted for in a token or instrumental way, which is identified as one of the important reason, why change endeavours fail. However, whatever be the reason for change, organizational change readiness must be gauged prior to the institutionalization of organizational change. Hence, in this study the influence of employee voice and employee involvement on organizational change readiness via commitment-to-change is examined, as it is an area yet to be extensively studied. Also, though a recent study has investigated the interrelationship between leadership, organizational change readiness and commitment to change, our study further examined these constructs in relation with employee voice and employee involvement that plays a consequential role for organizational change readiness. Further, integrated conceptual model weaving varied concepts relating to organizational readiness with focus on commitment to change as mediator was found to be an area, which required more theorizing and empirical validation, and this study rooted in an Indian public sector organization is a step in this direction. Data for the study were collected through a survey among employees of Rourkela Steel Plant (RSP), a unit of Steel Authority of India Limited (SAIL); the first integrated Steel Plant in the public sector in India, for which stratified random sampling method was adopted. The schedule was distributed to around 700 employees, out of which 516 complete responses were obtained. The pre-validated scales were used for the study. All the variables in the study were measured on a five-point Likert scale ranging from “strongly disagree (1)” to “strongly agree (5)”. Structural equation modeling (SEM) using AMOS 22 was used to examine the hypothesized model, which offers a simultaneous test of an entire system of variables in a model. The study results shows that inter-relationship between employee voice and commitment-to-change, employee involvement and commitment-to-change and commitment-to-change and organizational change readiness were significant. To test the mediation hypotheses, Baron and Kenny’s technique was used. Examination of direct and mediated effect of mediators confirmed that commitment-to-change partially mediated the relation between employee involvement and organizational change readiness. Furthermore, study results also affirmed that commitment-to-change does not mediate the relation between employee involvement and organizational change readiness. The empirical exploration therefore establishes that it is important to harness employee’s valuable suggestions regarding change for building organizational change readiness. Regarding employee involvement, it was found that sharing information and involving people in decision-making, leads to a creation of participative climate, which educes employee commitment during change and commitment-to-change further, fosters organizational change readiness.

Keywords: commitment-to-change, change management, employee voice, employee involvement, organizational change readiness

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Authors: Shabnam Najafi, Metin Turkay

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Network design problem (NDP) is used to determine the set of optimal values for certain pre-specified decision variables such as capacity expansion of nodes and links by optimizing various system performance measures including safety, congestion, and accessibility. The designed transportation network should improve objective functions defined for the system by considering the route choice behaviors of network users at the same time. The NDP studies mostly investigated the random demand and route selection constraints separately due to computational challenges. In this work, we consider both random demand and route selection constraints simultaneously. This work presents a nonlinear stochastic model for land use and road network design problem to address the development of different functional zones in urban areas by considering both cost function and air pollution. This model minimizes cost function and air pollution simultaneously with random demand and stochastic route selection constraint that aims to optimize network performance via road capacity expansion. The Bureau of Public Roads (BPR) link impedance function is used to determine the travel time function in each link. We consider a city with origin and destination nodes which can be residential or employment or both. There are set of existing paths between origin-destination (O-D) pairs. Case of increasing employed population is analyzed to determine amount of roads and origin zones simultaneously. Minimizing travel and expansion cost of routes and origin zones in one side and minimizing CO emission in the other side is considered in this analysis at the same time. In this work demand between O-D pairs is random and also the network flow pattern is subject to stochastic user equilibrium, specifically logit route choice model. Considering both demand and route choice, random is more applicable to design urban network programs. Epsilon-constraint is one of the methods to solve both linear and nonlinear multi-objective problems. In this work epsilon-constraint method is used to solve the problem. The problem was solved by keeping first objective (cost function) as the objective function of the problem and second objective as a constraint that should be less than an epsilon, where epsilon is an upper bound of the emission function. The value of epsilon should change from the worst to the best value of the emission function to generate the family of solutions representing Pareto set. A numerical example with 2 origin zones and 2 destination zones and 7 links is solved by GAMS and the set of Pareto points is obtained. There are 15 efficient solutions. According to these solutions as cost function value increases, emission function value decreases and vice versa.

Keywords: epsilon-constraint, multi-objective, network design, stochastic

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Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yonggang Qian, Ning Wang

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Knowledge of land surface temperature (LST) is of crucial important in energy balance studies and environment modeling. Satellite thermal infrared (TIR) imagery is the primary source for retrieving LST at the regional and global scales. Due to the combination of atmosphere and land surface of received radiance by TIR sensors, atmospheric effect correction has to be performed to remove the atmospheric transmittance and upwelling radiance. Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) provides measurements every 15 minutes in 12 spectral channels covering from visible to infrared spectrum at fixed view angles with 3km pixel size at nadir, offering new and unique capabilities for LST, LSE measurements. However, due to its high temporal resolution, the atmosphere correction could not be performed with radiosonde profiles or reanalysis data since these profiles are not available at all SEVIRI TIR image acquisition times. To solve this problem, a two-part six-parameter semi-empirical diurnal temperature cycle (DTC) model has been applied to the temporal interpolation of ECMWF reanalysis data. Due to the fact that the DTC model is underdetermined with ECMWF data at four synoptic times (UTC times: 00:00, 06:00, 12:00, 18:00) in one day for each location, some approaches are adopted in this study. It is well known that the atmospheric transmittance and upwelling radiance has a relationship with water vapour content (WVC). With the aid of simulated data, the relationship could be determined under each viewing zenith angle for each SEVIRI TIR channel. Thus, the atmospheric transmittance and upwelling radiance are preliminary removed with the aid of instantaneous WVC, which is retrieved from the brightness temperature in the SEVIRI channels 5, 9 and 10, and a group of the brightness temperatures for surface leaving radiance (Tg) are acquired. Subsequently, a group of the six parameters of the DTC model is fitted with these Tg by a Levenberg-Marquardt least squares algorithm (denoted as DTC model 1). Although the retrieval error of WVC and the approximate relationships between WVC and atmospheric parameters would induce some uncertainties, this would not significantly affect the determination of the three parameters, td, ts and β (β is the angular frequency, td is the time where the Tg reaches its maximum, ts is the starting time of attenuation) in DTC model. Furthermore, due to the large fluctuation in temperature and the inaccuracy of the DTC model around sunrise, SEVIRI measurements from two hours before sunrise to two hours after sunrise are excluded. With the knowledge of td , ts, and β, a new DTC model (denoted as DTC model 2) is accurately fitted again with these Tg at UTC times: 05:57, 11:57, 17:57 and 23:57, which is atmospherically corrected with ECMWF data. And then a new group of the six parameters of the DTC model is generated and subsequently, the Tg at any given times are acquired. Finally, this method is applied to SEVIRI data in channel 9 successfully. The result shows that the proposed method could be performed reasonably without assumption and the Tg derived with the improved method is much more consistent with that from radiosonde measurements.

Keywords: atmosphere correction, diurnal temperature cycle model, land surface temperature, SEVIRI

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Authors: Mohammad Afkhami, Ali Hassanpour, Michael Fairweather

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The work described in this paper was undertaken to gain insight into fundamental aspects of turbulent gas-particle flows with relevance to processes employed in a wide range of applications, such as oil and gas flow assurance in pipes, powder dispersion from dry powder inhalers, and particle resuspension in nuclear waste ponds, to name but a few. In particular, the influence of particle interaction and fluid phase behavior in turbulent flow on particle dispersion in a horizontal channel is investigated. The mathematical modeling technique used is based on the large eddy simulation (LES) methodology embodied in the commercial CFD code FLUENT, with flow solutions provided by this approach coupled to a second commercial code, EDEM, based on the discrete element method (DEM) which is used for the prediction of particle motion and interaction. The results generated by LES for the fluid phase have been validated against direct numerical simulations (DNS) for three different channel flows with shear Reynolds numbers, Reτ = 150, 300 and 590. Overall, the LES shows good agreement, with mean velocities and normal and shear stresses matching those of the DNS in both magnitude and position. The research work has focused on the prediction of those conditions favoring particle aggregation and deposition within turbulent flows. Simulations have been carried out to investigate the effects of particle size, density and concentration on particle agglomeration. Furthermore, particles with different surface properties have been simulated in three channel flows with different levels of flow turbulence, achieved by increasing the Reynolds number of the flow. The simulations mimic the conditions of two-phase, fluid-solid flows frequently encountered in domestic, commercial and industrial applications, for example, air conditioning and refrigeration units, heat exchangers, oil and gas suction and pressure lines. The particle size, density, surface energy and volume fractions selected are 45.6, 102 and 150 µm, 250, 1000 and 2159 kg m-3, 50, 500, and 5000 mJ m-2 and 7.84 × 10-6, 2.8 × 10-5, and 1 × 10-4, respectively; such particle properties are associated with particles found in soil, as well as metals and oxides prevalent in turbulent bounded fluid-solid flows due to erosion and corrosion of inner pipe walls. It has been found that the turbulence structure of the flow dominates the motion of the particles, creating particle-particle interactions, with most of these interactions taking place at locations close to the channel walls and in regions of high turbulence where their agglomeration is aided both by the high levels of turbulence and the high concentration of particles. A positive relationship between particle surface energy, concentration, size and density, and agglomeration was observed. Moreover, the results derived for the three Reynolds numbers considered show that the rate of agglomeration is strongly influenced for high surface energy particles by, and increases with, the intensity of the flow turbulence. In contrast, for lower surface energy particles, the rate of agglomeration diminishes with an increase in flow turbulence intensity.

Keywords: agglomeration, channel flow, DEM, LES, turbulence

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Authors: Rafael do Amaral Teodoro, Leandro Augusto da Silva

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Originated from graphite, graphene is a two-dimensional (2D) material that promises to revolutionize technology in many different areas, such as energy, telecommunications, civil construction, aviation, textile, and medicine. This is possible because its structure, formed by carbon bonds, provides desirable optical, thermal, and mechanical characteristics that are interesting to multiple areas of the market. Thus, several research and development centers are studying different manufacturing methods and material applications of graphene, which are often compromised by the scarcity of more agile and accurate methodologies to characterize the material – that is to determine its composition, shape, size, and the number of layers and crystals. To engage in this search, this study proposes a computational methodology that applies deep learning to identify graphene oxide crystals in order to characterize samples by crystal sizes. To achieve this, a fully convolutional neural network called U-net has been trained to segment SEM graphene oxide images. The segmentation generated by the U-net is fine-tuned with a standard deviation technique by classes, which allows crystals to be distinguished with different labels through an object delimitation algorithm. As a next step, the characteristics of the position, area, perimeter, and lateral measures of each detected crystal are extracted from the images. This information generates a database with the dimensions of the crystals that compose the samples. Finally, graphs are automatically created showing the frequency distributions by area size and perimeter of the crystals. This methodological process resulted in a high capacity of segmentation of graphene oxide crystals, presenting accuracy and F-score equal to 95% and 94%, respectively, over the test set. Such performance demonstrates a high generalization capacity of the method in crystal segmentation, since its performance considers significant changes in image extraction quality. The measurement of non-overlapping crystals presented an average error of 6% for the different measurement metrics, thus suggesting that the model provides a high-performance measurement for non-overlapping segmentations. For overlapping crystals, however, a limitation of the model was identified. To overcome this limitation, it is important to ensure that the samples to be analyzed are properly prepared. This will minimize crystal overlap in the SEM image acquisition and guarantee a lower error in the measurements without greater efforts for data handling. All in all, the method developed is a time optimizer with a high measurement value, considering that it is capable of measuring hundreds of graphene oxide crystals in seconds, saving weeks of manual work.

Keywords: characterization, graphene oxide, nanomaterials, U-net, deep learning

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Authors: Benjamin Castillo, Luis Pastenes, Fernando Cordova

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The pathogen growth in animal source foods is a common problem in the food industry, causing monetary losses due to the spoiling of products or food intoxication outbreaks in the community. In this sense, the quality of the product is reflected by the population of deteriorating agents present in it, which are mainly bacteria. The factors which are likely associated with freshness in animal source foods are temperature and processing, storage, and transport times. However, the level of deterioration of products depends, in turn, on the characteristics of the bacterial population, causing the decomposition or spoiling, such as pH level and toxins. Knowing the growth dynamics of the agents that are involved in product contamination allows the monitoring for more efficient processing. This means better quality and reasonable costs, along with a better estimation of necessary time and temperature intervals for transport and storage in order to preserve product quality. The objective of this project is to design a secondary model that allows measuring the impact on temperature bacterial growth and the competition for pH adequacy and release of bacteriocins in order to describe such phenomenon and, thus, estimate food product half-life with the least possible risk of deterioration or spoiling. In order to achieve this objective, the authors propose an analysis of a three-dimensional ordinary differential which includes; logistic bacterial growth extended by the inhibitory action of bacteriocins including the effect of the medium pH; change in the medium pH levels through an adaptation of the Luedeking-Piret kinetic model; Bacteriocin concentration modeled similarly to pH levels. These three dimensions are being influenced by the temperature at all times. Then, this differential system is expanded, taking into consideration the variable temperature and the concentration of pulsed bacteriocins, which represent characteristics inherent of the modeling, such as transport and storage, as well as the incorporation of substances that inhibit bacterial growth. The main results lead to the fact that temperature changes in an early stage of transport increased the bacterial population significantly more than if it had increased during the final stage. On the other hand, the incorporation of bacteriocins, as in other investigations, proved to be efficient in the short and medium-term since, although the population of bacteria decreased, once the bacteriocins were depleted or degraded over time, the bacteria eventually returned to their regular growth rate. The efficacy of the bacteriocins at low temperatures decreased slightly, which equates with the fact that their natural degradation rate also decreased. In summary, the implementation of the mathematical model allowed the simulation of a set of possible bacteria present in animal based products, along with their properties, in various transport and storage situations, which led us to state that for inhibiting bacterial growth, the optimum is complementary low constant temperatures and the initial use of bacteriocins.

Keywords: bacterial growth, bacteriocins, mathematical modelling, temperature

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: T. S. Terence Ma, Irene T. Ho

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Conducting adequate assessment of the challenges students with ASD (Autism Spectrum Disorder) face and the support they need is imperative for promoting their school adjustment. Students with ASD often show deficits in communication, social interaction, emotional regulation, and self-management in learning. While targeting these areas in intervention is often helpful, we argue that not enough attention has been paid to weak self-regulation being a key factor underlying their manifest difficulty in all these areas. Self-regulation refers to one’s ability to moderate their behavioral or affective responses without assistance from others. Especially for students with high functioning autism, who often show problems not so much in acquiring the needed skills but rather in applying those skills appropriately in everyday problem-solving, self-regulation becomes a key to successful adjustment in daily life. Therefore, a greater understanding of the construct of self-regulation, its relationship with other daily skills, and its role in school functioning for students with ASD would generate insights on how students’ school adjustment could be promoted more effectively. There were two focuses in this study. Firstly, we examined the extent to which self-regulation is a distinct construct that is differentiable from other daily skills and the most salient indicators of this construct. Then we tested a model of relationships between self-regulation and other daily school skills as well as their relative and combined effects on school adjustment. A total of 1,345 Grade1 to Grade 6 students with ASD attending mainstream schools in Hong Kong participated in the research. In the first stage of the study, teachers filled out a questionnaire consisting of 136 items assessing a wide range of student skills in social, emotional and learning areas. Results from exploratory factor analysis (EFA) with 673 participants and subsequent confirmatory factor analysis (CFA) with another group of 672 participants showed that there were five distinct factors of school skills, namely (1) communication skills, (2) pro-social behavior, (3) emotional skills, (4) learning management, and (5) self-regulation. Five scales representing these skill dimensions were generated. In the second stage of the study, a model postulating the mediating role of self-regulation for the effects of the other four types of skills on school adjustment was tested with structural equation modeling (SEM). School adjustment was defined in terms of the extent to which the student is accepted well in school, with high engagement in school life and self-esteem as well as good interpersonal relationships. A 5-item scale was used to assess these aspects of school adjustment. Results showed that communication skills, pro-social behavior, emotional skills and learning management had significant effects on school adjustment only indirectly through self-regulation, and their total effects were found to be not high. The results indicate that support rendered to students with ASD focusing only on the training of well-defined skills is not adequate for promoting their inclusion in school. More attention should be paid to the training of self-management with an emphasis on the application of skills backed by self-regulation. Also, other non-skill factors are important in promoting inclusive education.

Keywords: autism, assessment, factor analysis, self-regulation, school adjustment

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Authors: Funda Erdem Şahnali, Ş. Özgür Atayılmaz, Tolga N. Aynur

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Almost all of the domestic refrigerators operate on the principle of the vapor compression refrigeration cycle and removal of heat from the refrigerator cabinets is done via one of the two methods: natural convection or forced convection. In this study, airflow and temperature distributions inside a 375L no-frost type larder cabinet, in which cooling is provided by forced convection, are evaluated both experimentally and numerically. Airflow rate, compressor capacity and temperature distribution in the cooling chamber are known to be some of the most important factors that affect the cooling performance and energy consumption of a refrigerator. The objective of this study is to evaluate the original temperature distribution in the larder cabinet, and investigate for better temperature distribution solutions throughout the refrigerator domain via system optimizations that could provide uniform temperature distribution. The flow visualization and airflow velocity measurements inside the original refrigerator are performed via Stereoscopic Particle Image Velocimetry (SPIV). In addition, airflow and temperature distributions are investigated numerically with Ansys Fluent. In order to study the heat transfer inside the aforementioned refrigerator, forced convection theories covering the following cases are applied: closed rectangular cavity representing heat transfer inside the refrigerating compartment. The cavity volume has been represented with finite volume elements and is solved computationally with appropriate momentum and energy equations (Navier-Stokes equations). The 3D model is analyzed as transient, with k-ε turbulence model and SIMPLE pressure-velocity coupling for turbulent flow situation. The results obtained with the 3D numerical simulations are in quite good agreement with the experimental airflow measurements using the SPIV technique. After Computational Fluid Dynamics (CFD) analysis of the baseline case, the effects of three parameters: compressor capacity, fan rotational speed and type of shelf (glass or wire) are studied on the energy consumption; pull down time, temperature distributions in the cabinet. For each case, energy consumption based on experimental results is calculated. After the analysis, the main effective parameters for temperature distribution inside a cabin and energy consumption based on CFD simulation are determined and simulation results are supplied for Design of Experiments (DOE) as input data for optimization. The best configuration with minimum energy consumption that provides minimum temperature difference between the shelves inside the cabinet is determined.

Keywords: air distribution, CFD, DOE, energy consumption, experimental, larder cabinet, refrigeration, uniform temperature

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Authors: Sanjeev Gupta, Ankit Prabhakar, K. Rajkumar Singh

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Sunni Dam Hydroelectric Project (382 MW) is a run of river type development with an underground powerhouse, proposed to harness the hydel potential of river Satluj in Himachal Pradesh, India. The project is located in the inner lesser Himalaya between Dhauladhar Range in the south and the higher Himalaya in the north. The project comprises two large underground caverns, a Powerhouse cavern (171m long, 22.5m wide and 51.2m high) and another transformer hall cavern (175m long, 18.7m wide and 27m high) and the rock pillar between the two caverns is 50m. The highly jointed, fractured, anisotropic rock mass is a key challenge in Himalayan geology for an underground structure. The concern for the stability of rock mass increases when weak/shear zones are encountered in the underground structure. In the Sunni Dam project, 1.7m to 2m thick weak/shear zone comprising of deformed, weak material with gauge has been encountered in powerhouse cavern at 70m having dip direction 325 degree and dip amount 38 degree which also intersects transformer hall at initial reach. The rock encountered in the powerhouse area is moderate to highly jointed, pink quartz arenite belonging to the Khaira Formation, a transition zone comprising of alternate grey, pink & white quartz arenite and shale sequence and dolomite at higher reaches. The rock mass is intersected by mainly 3 joint sets excluding bedding joints and a few random joints. The rock class in powerhouse mainly varies from poor class (class IV) to lower order fair class (class III) and in some reaches, very poor rock mass has also been encountered. To study the stability of the underground structure in weak/shear rock mass, a 3D numerical model analysis has been carried out using RS3 software. Field studies have been interpreted and analysed to derive Bieniawski’s RMR, Barton’s “Q” class and Geological Strength Index (GSI). The various material parameters, in-situ characteristics have been determined based on tests conducted by Central Soil and Materials Research Station, New Delhi. The behaviour of the cavern has been studied by assessing the displacement contours, major and minor principal stresses and plastic zones for different stage excavation sequences. For optimisation of the support system, the stability of the powerhouse cavern with different powerhouse orientations has also been studied. The numerical modeling results indicate that cavern will not likely face stress governed by structural instability with the support system to be applied to the crown and side walls.

Keywords: 3D analysis, Himalayan geology, shear zone, underground power house

Procedia PDF Downloads 90

Authors: Prabu Duplex

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Due to stringent emission regulation targets, large-scale transition to renewable energy sources is a global challenge, and wind power plays a significant role in the solution vector. This scenario has led to the construction of offshore wind farms, and several wind farms are planned in the shallow waters where the marine habitat exists. It raises concerns over impacts of underwater noise on marine species, for example bridge constructions in the ocean straits. Dangerous to aquatic life, the environmental organisations say, the bridge would be devastating, since ocean straits are important place of transit for marine mammals. One of the highest concentrations of biodiversity in the world is concentrated these areas. The investigation of ship noise and piling noise that may happen during bridge construction and in operation is therefore vital. Once the source levels are known the receiver levels can be modelled. With this objective this work investigates the key requirement of the software that can model transmission loss in high frequencies that may occur during construction or operation phases. Most propagation models are 2D solutions, calculating the propagation loss along a transect, which does not include horizontal refraction, reflection or diffraction. In many cases, such models provide sufficient accuracy and can provide three-dimensional maps by combining, through interpolation, several two-dimensional (distance and depth) transects. However, in some instances the use of 2D models may not be sufficient to accurately model the sound propagation. A possible example includes a scenario where an island or land mass is situated between the source and receiver. The 2D model will result in a shadow behind the land mass where the modelled transects intersect the land mass. Diffraction will occur causing bending of the sound around the land mass. In such cases, it may be necessary to use a 3D model, which accounts for horizontal diffraction to accurately represent the sound field. Other scenarios where 2D models may not provide sufficient accuracy may be environments characterised by a strong up-sloping or down sloping seabed, such as propagation around continental shelves. In line with these objectives by means of a case study, this work addresses the importance of 3D interactions in underwater acoustics. The methodology used in this study can also be used for other 3D underwater sound propagation studies. This work assumes special significance given the increasing interest in using underwater acoustic modeling for environmental impacts assessments. Future work also includes inter-model comparison in shallow water environments considering more physical processes known to influence sound propagation, such as scattering from the sea surface. Passive acoustic monitoring of the underwater soundscape with distributed hydrophone arrays is also suggested to investigate the 3D propagation effects as discussed in this article.

Keywords: underwater acoustics, naval, maritime, cetaceans

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Authors: Nawal Alawad, Passent Ibrahim Tantawi, Mohamed Abdel Salam Ragheb

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Providing customers with quality experiences has been confirmed to be a sustainable, competitive advantage with a distinct financial impact for companies. The success of service providers now relies on their ability to provide customer-centric services. The importance of perceived service quality and customer experience is widely recognized. The focus of this research is in the area of mobile and fixed broadband services. This study is of dual importance both academically and practically. Academically, this research applies a new model investigating the impact of customer experience quality on loyalty based on modifying the multiple-item scale for measuring customers’ service experience in a new area and did not depend on the traditional models. The integrated scale embraces four dimensions: service experience, outcome focus, moments of truth and peace of mind. In addition, it gives a scientific explanation for this relationship so this research fill the gap in such relations in which no one correlate or give explanations for these relations before using such integrated model and this is the first time to apply such modified and integrated new model in telecom field. Practically, this research gives insights to marketers and practitioners to improve customer loyalty through evolving the experience quality of broadband customers which is interpreted to suggested outcomes: purchase, commitment, repeat purchase and word-of-mouth, this approach is one of the emerging topics in service marketing. Data were collected through 412 questionnaires and analyzed by using structural equation modeling.Findings revealed that both outcome focus and moments of truth have a significant impact on loyalty while both service experience and peace of mind have insignificant impact on loyalty.In addition, it was found that 72% of the variation occurring in loyalty is explained by the model. The researcher also measured the net prompters score and gave explanation for the results. Furthermore, assessed customer’s priorities of broadband services. The researcher recommends that the findings of this research will extend to be considered in the future plans of Telecom Egypt Group. In addition, to be applied in the same industry especially in the developing countries that have the same circumstances with similar service settings. This research is a positive contribution in service marketing, particularly in telecom industry for making marketing more reliable as managers can relate investments in service experience directly with the performance closest to income for instance, repurchasing behavior, positive word of mouth and, commitment. Finally, the researcher recommends that future studies should consider this model to explain significant marketing outcomes such as share of wallet and ultimately profitability.

Keywords: broadband services, customer experience quality, loyalty, net promoters score

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Authors: Piotr Wisniewski, Sławomir Dykas

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Condensation has a negative impact on turbomachinery efficiency in many energy processes.In technical applications, it is often impossible to dry the working fluid at the nozzle inlet. One of the most popular working fluid is atmospheric air that always contains water in form of steam, liquid, or ice crystals. Moreover, it always contains some amount of suspended particles which influence the phase change process. It is known that the phenomena of evaporation or condensation are connected with release or absorption of latent heat, what influence the fluid physical properties and might affect the machinery efficiency therefore, the phase transition has to be taken under account. This researchpresents an attempt to evaluate the impact of solid and liquid particles suspended in the air on the expansion of moist air in a low expansion rate, i.e., with expansion rate, P≈1000s⁻¹. The numerical study supported by analytical and experimental research is presented in this work. The experimental study was carried out using an in-house experimental test rig, where nozzle was examined for different inlet air relative humidity values included in the range of 25 to 51%. The nozzle was tested for a supersonic flow as well as for flow with shock waves induced by elevated back pressure. The Schlieren photography technique and measurement of static pressure on the nozzle wall were used for qualitative identification of both condensation and shock waves. A numerical model validated against experimental data available in the literature was used for analysis of occurring flow phenomena. The analysis of the suspended particles number, diameter, and character (solid or liquid) revealed their connection with heterogeneous condensation importance. If the expansion of fluid without suspended particlesis considered, the condensation triggers so called condensation wave that appears downstream the nozzle throat. If the solid particles are considered, with increasing number of them, the condensation triggers upwind the nozzle throat, decreasing the condensation wave strength. Due to the release of latent heat during condensation, the fluid temperature and pressure increase, leading to the shift of normal shock upstream the flow. Owing relatively large diameters of the droplets created during heterogeneous condensation, they evaporate partially on the shock and continues to evaporate downstream the nozzle. If the liquid water particles are considered, due to their larger radius, their do not affect the expanding flow significantly, however might be in major importance while considering the compression phenomena as they will tend to evaporate on the shock wave. This research proves the need of further study of phase change phenomena in supersonic flow especially considering the interaction of droplets with the aerodynamic waves in the flow.

Keywords: aerodynamics, computational fluid dynamics, condensation, moist air, multi-phase flows

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Authors: Pawel Magryta, Tytus Tulwin, Paweł Karpiński

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The ASz62IR engine is a radial aircraft engine with 9 cylinders. This object is produced by the Polish company WSK "PZL-KALISZ" S.A. This is engine is currently being developed by the above company and Lublin University of Technology. In order to provide an effective work of the technological development of this unit it was decided to made the simulation model. The model of ASz-62IR was developed with AVL BOOST software which is a tool dedicated to the one-dimensional modeling of internal combustion engines. This model can be used to calculate parameters of an air and fuel flow in an intake system including charging devices as well as combustion and exhaust flow to the environment. The main purpose of this model is the analysis of the charge exchange and mixture formation in this engine. For this purpose, the model consists of elements such: as air inlet, throttle system, compressor connector, charging compressor, inlet pipes and injectors, outlet pipes, fuel injection and model of fuel mixing and evaporation. The model of charge exchange and mixture formation was based on the model of mass flow rate in intake and exhaust pipes, and also on the calculation of gas properties values like gas constant or thermal capacity. This model was based on the equations to describe isentropic flow. The energy equation to describe flow under steady conditions was transformed into the mass flow equation. In the model the flow coefficient μσ was used, that varies with the stroke/valve opening and was determined in a steady flow state. The geometry of the inlet channels and other key components was mapped with reference to the technical documentation of the engine and empirical measurements of the structure elements. The volume of elements on the charge flow path between the air inlet and the exhaust outlet was measured by the CAD mapping of the structure. Taken from the technical documentation, the original characteristics of the compressor engine was entered into the model. Additionally, the model uses a general model for the transport of chemical compounds of the mixture. There are 7 compounds used, i.e. fuel, O2, N2, CO2, H2O, CO, H2. A gasoline fuel of a calorific value of 43.5 MJ/kg and an air mass fraction for stoichiometric mixture of 14.5 were used. Indirect injection into the intake manifold is used in this model. The model assumes the following simplifications: the mixture is homogenous at the beginning of combustion, accordingly, mixture stoichiometric coefficient A/F remains constant during combustion, combusted and non-combusted charges show identical pressures and temperatures although their compositions change. As a result of the simulation studies based on the model described above, the basic parameters of combustion process, charge exchange, mixture formation in cylinders were obtained. The AVL Boost software is very useful for the piston engine performance simulations. This work has been financed by the Polish National Centre for Research and Development, INNOLOT, under Grant Agreement No. INNOLOT/I/1/NCBR/2013.

Keywords: aviation propulsion, AVL Boost, engine model, charge exchange, mixture formation

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Authors: Mballa Abanda Serge, Henda Gnakate Biba, Romaric Guemno Kuate, Akono Rufine Nicole, Petfiang Sidonie, Bella Sidonie

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The main hypotheses proposed around the definition of the syllable and of music, of the common origin of music and language, should lead the reader to reflect on the cross-cutting questions raised by the debate on the notion of universals in linguistics and musicology. These are objects of controversy, and there lies its interest: the debate raises questions that are at the heart of theories on language. It is an inventive, original and innovative research thesis. The main hypotheses proposed around the definition of the syllable and of music, of the common origin of music and language, should lead the reader to reflect on the cross-cutting questions raised by the debate on the notion of universals in linguistics and musicology. These are objects of controversy, and there lies its interest: the debate raises questions that are at the heart of theories on language. It is an inventive, original and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation and the question of modeling in the human sciences: mathematics, computer science, translation automation and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal and random music. The experimentation confirming the theorization, It designed a semi-digital, semi-analog application which translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music and deterministic and random music). To test this application, I use a music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). Translation is done (from writing to writing, from writing to speech and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz and world music or variety etc. The software runs, giving you the option to choose harmonies, and then you select your melody.

Keywords: music, entanglement, langauge, science

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Authors: Moser Stephan, Lukasser Gerald, Weitlaner Robert

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Urban structures will be used more intensively in the future through redensification or new planned districts with high building densities. Especially, to achieve positive energy balances like requested for Positive Energy Districts (PED) the single use of roofs is not sufficient for dense urban areas. However, the increasing share of window significantly reduces the facade area available for use in PV generation. Through the use of PV technology at other building components, such as external venetian blinds, onsite generation can be maximized and standard functionalities of this product can be positively extended. While offering advantages in terms of infrastructure, sustainability in the use of resources and efficiency, these systems require an increased optimization in planning and control strategies of buildings. External venetian blinds with PV technology require an intelligent control concept to meet the required demands such as maximum power generation, glare prevention, high daylight autonomy, avoidance of summer overheating but also use of passive solar gains in wintertime. Today, geometric representation of outdoor spaces and at the building level, three-dimensional geometric information is available for planning with Building Information Modeling (BIM). In a research project, a web application which is called HELLA DECART was developed to provide this data structure to extract the data required for the simulation from the BIM models and to make it usable for the calculations and coupled simulations. The investigated object is uploaded as an IFC file to this web application and includes the object as well as the neighboring buildings and possible remote shading. This tool uses a ray tracing method to determine possible glare from solar reflections of a neighboring building as well as near and far shadows per window on the object. Subsequently, an annual estimate of the sunlight per window is calculated by taking weather data into account. This optimized daylight assessment per window provides the ability to calculate an estimation of the potential power generation at the integrated PV on the venetian blind but also for the daylight and solar entry. As a next step, these results of the calculations as well as all necessary parameters for the thermal simulation can be provided. The overall aim of this workflow is to advance the coordination between the BIM model and coupled building simulation with the resulting shading and daylighting system with the artificial lighting system and maximum power generation in a control system. In the research project Powershade, an AI based control concept for PV integrated façade elements with coupled simulation results is investigated. The developed automated workflow concept in this paper is tested by using an office living lab at the HELLA company.

Keywords: BIPV, building simulation, optimized control strategy, planning tool

Procedia PDF Downloads 113

Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper discusses the recent advances and future prospects of spacecraft position and attitude control using Model Predictive Control (MPC). First, the challenges of the space missions are summarized, in particular, taking into account the errors, uncertainties, and constraints imposed by the mission, spacecraft and, onboard processing capabilities. The summary of space mission errors and uncertainties provided in categories; initial condition errors, unmodeled disturbances, sensor, and actuator errors. These previous constraints are classified into two categories: physical and geometric constraints. Last, real-time implementation capability is discussed regarding the required computation time and the impact of sensor and actuator errors based on the Hardware-In-The-Loop (HIL) experiments. The rationales behind the scenarios’ are also presented in the scope of space applications as formation flying, attitude control, rendezvous and docking, rover steering, and precision landing. The objectives of these missions are explained, and the generic constrained MPC problem formulations are summarized. Three key design elements used in MPC design: the prediction model, the constraints formulation and the objective cost function are discussed. The prediction models can be linear time invariant or time varying depending on the geometry of the orbit, whether it is circular or elliptic. The constraints can be given as linear inequalities for input or output constraints, which can be written in the same form. Moreover, the recent convexification techniques for the non-convex geometrical constraints (i.e., plume impingement, Field-of-View (FOV)) are presented in detail. Next, different objectives are provided in a mathematical framework and explained accordingly. Thirdly, because MPC implementation relies on finding in real-time the solution to constrained optimization problems, computational aspects are also examined. In particular, high-speed implementation capabilities and HIL challenges are presented towards representative space avionics. This covers an analysis of future space processors as well as the requirements of sensors and actuators on the HIL experiments outputs. The HIL tests are investigated for kinematic and dynamic tests where robotic arms and floating robots are used respectively. Eventually, the proposed algorithms and experimental setups are introduced and compared with the authors' previous work and future plans. The paper concludes with a conjecture that MPC paradigm is a promising framework at the crossroads of space applications while could be further advanced based on the challenges mentioned throughout the paper and the unaddressed gap.

Keywords: convex optimization, model predictive control, rendezvous and docking, spacecraft autonomy

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Authors: Fida Isam Abdulhafiz

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Traditional vernacular architecture in the United Arab Emirates constituted namely of adobe houses with a limited number of openings in their facades. The thick mud and rubble walls and wooden window screens protected its inhabitants from the harsh desert climate and provided them with privacy and fulfilled their comfort zone needs to an extent. However, with the rise of the immediate post petroleum era reinforced concrete villas with glass and steel technology has replaced traditional vernacular dwellings. And more load was put on the mechanical cooling systems to ensure the satisfaction of today’s more demanding doweling inhabitants. However, In the early 21at century professionals started to pay more attention to the carbon footprint caused by the built constructions. In addition, many studies and innovative approaches are now dedicated to lower the impact of the existing operating buildings on their surrounding environments. The UAE government agencies started to regulate that aim to revive sustainable and environmental design through Local and international building codes and urban design policies such as Estidama and LEED. The focus in this paper is on the reduction of the emissions resulting from the use of energy sources in the cooling and heating systems, and that would be through using innovative screen designs and façade solutions to provide a green footprint and aesthetic architectural icons. Screens are one of the popular innovative techniques that can be added in the design process or used in existing building as a renovation techniques to develop a passive green buildings. Preparing future architects to understand the importance of environmental design was attempted through physical modelling of window screens as an educational means to combine theory with a hands on teaching approach. Designing screens proved to be a popular technique that helped them understand the importance of sustainable design and passive cooling. After creating models of prototype screens, several tests were conducted to calculate the amount of Sun, light and wind that goes through the screens affecting the heat load and light entering the building. Theory further explored concepts of green buildings and material that produce low carbon emissions. This paper highlights the importance of hands on experience for student architects and how physical modelling helped rise eco awareness in Design studio. The paper will study different types of façade screens and shading devices developed by Architecture students and explains the production of diverse patterns for traditional screens by student architects based on sustainable design concept that works properly with the climate requirements in the Middle East region.

Keywords: building’s screens modeling, façade design, sustainable architecture, sustainable dwellings, sustainable education

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Authors: Katarina Pogacnik, Ursa Zakrajsek, Nejc Sirk, Ziga Lampret

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Due to an increase in living standards along with global population growth and a trend of urbanization, municipalities and regions are faced with an ever rising energy demand. A challenge has arisen for cities around the world to modify the energy supply chain in order to reduce its consumption and CO₂ emissions. The aim of our work is the development of a computational-analytical platform for dynamic support in decision-making and the determination of economic and technical indicators of energy efficiency in a smart city, named Energy Atlas. Similar products in this field focuse on a narrower approach, whereas in order to achieve its aim, this platform encompasses a wider spectrum of beneficial and important information for energy planning on a local or regional scale. GIS based interactive maps provide an extensive database on the potential, use and supply of energy and renewable energy sources along with climate, transport and spatial data of the selected municipality. Beneficiaries of Energy atlas are local communities, companies, investors, contractors as well as residents. The Energy Atlas platform consists of three modules named E-Planning, E-Indicators and E-Cooperation. The E-Planning module is a comprehensive data service, which represents a support towards optimal decision-making and offers a sum of solutions and feasibility of measures and their effects in the area of efficient use of energy and renewable energy sources. The E-Indicators module identifies, collects and develops optimal data and key performance indicators and develops an analytical application service for dynamic support in managing a smart city in regards to energy use and sustainable environment. In order to support cooperation and direct involvement of citizens of the smart city, the E-cooperation is developed with the purpose of integrating the interdisciplinary and sociological aspects of energy end-users. Interaction of all the above-described modules contributes to regional development because it enables for a precise assessment of the current situation, strategic planning, detection of potential future difficulties and also the possibility of public involvement in decision-making. From the implementation of the technology in Slovenian municipalities of Ljubljana, Piran, and Novo mesto, there is evidence to suggest that the set goals are to be achieved to a great extent. Such thorough urban energy planning tool is viewed as an important piece of the puzzle towards achieving a low-carbon society, circular economy and therefore, sustainable society.

Keywords: circular economy, energy atlas, energy management, energy planning, low-carbon society

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Authors: Abbas Mohammed, Felicitász Velledits

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Evaluating carbonate rocks is crucial for the petroleum industry as they often serve as major hydrocarbon reservoirs, where understanding their depositional and diagenetic characteristics directly influences exploration, production, and field development plans. The Early Cretaceous Yamama carbonates Formation in southern Iraq exhibits significant reservoir but heterogeneous. Detailed sedimentological investigations of drill cores and well logs have identified 14 distinct facies/microfacies within both reservoir and non-reservoir units, deposited in a shallow carbonate ramp setting. The grain-supported facies such as intertidal peloidal oncoidal grain/rudstones, backshoal pelletal pack/grainstones, shoal ooidal-peloidal grainstones, cortoidal-peloidal grainstones, in addition to the Lithocodium-Bacinella float/boundstones, and the reefal skeletal rudstones facies display favorable reservoir properties due to preserved interparticle porosity (reaches 25%) at depths greater than 4000 m. This preservation is attributed to early diagenetic circumgranular calcite cementation and limited scattered equant and syntaxial calcite overgrowths, which protected the grains from physical compaction. In contrast, mud-supported facies such as lagoonal skeletal mud/wackestones, skeletal cortoids wacke/packstones, skeletal dasyclads wacke/packstone, middle-ramp miliolidal pack/grainstone, bioturbated dolomitic wackestones, skeletal foraminiferal mud/wackestones, and outer-ramp spiculitic skeletal mud/wackestones exhibit reduced reservoir quality due to a combination of their fine-grain texture, physical and chemical compaction, and substantial amounts of equant calcite cement. This cement fills interparticle and moldic pores, and significantly reducing porosity and permeability in these facies. Reservoir heterogeneity of the formation is attributed to depositional facies, which control the texture of the sediments, and various types of diagenetic alterations. Particular attention to be directed toward the Lithocodium-Bacinella facies deposited as build-ups and the shoal barrier grain-supported facies. These findings underscore the importance of adapting exploration and development strategies to specific facies distributions and diagenetic pathways to mitigate heterogeneity risks. While potential limitations include the extrapolation of core and well log data to field-scale reservoir modeling and the challenge of investigating diagenetic variations at finer scales, the study provides a valuable framework for integrating facies and diagenetic analysis into hydrocarbon exploration workflows.

Keywords: depositional facies, grain-supported limestones, lithocoduim-bacinella, reservoir heterogeneity, yamama formation

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Authors: Bryan Low

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In the coming decades, the global maritime industry will face a most formidable environmental challenge -achieving net zero carbon emissions by 2050. To meet this target, the Maritime Port Authority of Singapore (MPA) has worked to establish green shipping and digital corridors with ports of several other countries around the world where ships will use low-carbon alternative fuels such as ammonia for power generation. While this paradigm shift to the bunkering of greener fuels is encouraging, fuels like ammonia will also introduce a new and unique type of environmental risk in the unlikely scenario of a spill. While numerous modelling studies have been conducted for oil spills and their associated environmental impact on coastal and marine ecosystems, ammonia spills are comparatively less well understood. For example, there is a knowledge gap regarding how the complex hydrodynamic conditions of the Singapore Straits may influence the dispersion of a hypothetical ammonia plume, which has different physical and chemical properties compared to an oil slick. Chemically, ammonia can be absorbed by phytoplankton, thus altering the balance of the marine nitrogen cycle. Biologically, ammonia generally serves the role of a nutrient in coastal ecosystems at lower concentrations. However, at higher concentrations, it has been found to be toxic to many local species. It may also have the potential to trigger eutrophication and harmful algal blooms (HABs) in coastal waters, depending on local hydrodynamic conditions. Thus, the key objective of this research paper is to support the development of a model-based forecasting system that can predict ammonia plume behaviour in coastal waters, given prevailing hydrodynamic conditions and their environmental impact. This will be essential as ammonia bunkering becomes more commonplace in Singapore’s ports and around the world. Specifically, this system must be able to assess the HAB-triggering potential of an ammonia plume, as well as its lethal and sub-lethal toxic effects on local species. This will allow the relevant authorities to better plan risk mitigation measures or choose a time window with the ideal hydrodynamic conditions to conduct ammonia bunkering operations with minimal risk. In this paper, we present the first part of such a forecasting system: a jointly coupled hydrodynamic-water quality model that can capture how advection-diffusion processes driven by ocean currents influence plume behaviour and how the plume interacts with the marine nitrogen cycle. The model is then applied to various ammonia spill scenarios where the results are discussed in the context of current ammonia toxicity guidelines, impact on local ecosystems, and mitigation measures for future bunkering operations conducted in the Singapore Straits.

Keywords: ammonia bunkering, forecasting, harmful algal blooms, hydrodynamics, marine nitrogen cycle, oceanography, water quality modeling

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Authors: Khodzhaberdi Allaberdiev

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In order to understand the interactions on the interface polyamide fibers and epoxy matrix in fiber- reinforced composites were investigated industrial aramid fibers: armos, svm, terlon using individual epoxy matrix components, epoxies: diglycidyl ether of bisphenol A (DGEBA), three- and diglycidyl derivatives of m, p-amino-, m, p-oxy-, o, m,p-carboxybenzoic acids, the models: curing agent, aniline and the compound, that depict of the structure the primary addition reaction the amine to the epoxy resin, N-di (oxyethylphenoxy) aniline. The chemical structure of the surface of untreated and treated polyamide fibers analyzed using Fourier transform infrared spectroscopy (FTIR). The impregnation of fibers with epoxy matrix components and N-di (oxyethylphenoxy) aniline has been carried out by heating 150˚C (6h). The optimum fiber loading is at 65%.The result a thermal treatment is the covalent bonds formation , derived from a combined of homopolymerization and crosslinking mechanisms in the interfacial region between the epoxy resin and the surface of fibers. The reactivity of epoxy resins on interface in microcomposites (MC) also depends from processing aids treated on surface of fiber and the absorbance moisture. The influences these factors as evidenced by the conversion of epoxy groups values in impregnated with DGEBA of the terlons: industrial, dried (in vacuum) and purified samples: 5.20 %, 4.65% and 14.10%, respectively. The same tendency for svm and armos fibers is observed. The changes in surface composition of these MC were monitored by X-ray photoelectron spectroscopy (XPS). In the case of the purified fibers, functional groups of fibers act as well as a catalyst and curing agent of epoxy resin. It is found that the value of the epoxy groups conversion for reinforced formulations depends on aromatic polyamides nature and decreases in the order: armos >svm> terlon. This difference is due of the structural characteristics of fibers. The interfacial interactions also examined between polyglycidyl esters substituted benzoic acids and polyamide fibers in the MC. It is found that on interfacial interactions these systems influences as well as the structure and the isomerism of epoxides. The IR-spectrum impregnated fibers with aniline showed that the polyamide fibers appreciably with aniline do not react. FTIR results of treated fibers with N-di (oxyethylphenoxy) aniline fibers revealed dramatically changes IR-characteristic of the OH groups of the amino alcohol. These observations indicated hydrogen bondings and covalent interactions between amino alcohol and functional groups of fibers. This result also confirms appearance of the exo peak on Differential Scanning Calorimetry (DSC) curve of the MC. Finally, the theoretical evaluation non-covalent interactions between individual epoxy matrix components and fibers has been performed using the benzanilide and its derivative contaning the benzimidazole moiety as a models of terlon and svm,armos, respectively. Quantum-topological analysis also demonstrated the existence hydrogen bond between amide group of models and epoxy matrix components.All the results indicated that on the interface polyamide fibers and epoxy matrix exist not only covalent, but and non-covalent the interactions during the preparation of MC.

Keywords: epoxies, interface, modeling, polyamide fibers

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Authors: Yuan-Jye Tseng, Jia-Shu Li

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To design a product with the given product requirement and design objective, there can be alternative ways to propose the detailed design specifications of the product. In the design modeling stage, alternative design cases with detailed specifications can be modeled to fulfill the product requirement and design objective. Therefore, in the design evaluation stage, it is required to perform an evaluation of the alternative design cases for deciding the final design. The purpose of this research is to develop a product evaluation model for evaluating the alternative design cases by integrated evaluating the criteria of functional design, Kansei design, and design for supply chain. The criteria in the functional design group include primary function, expansion function, improved function, and new function. The criteria in the Kansei group include geometric shape, dimension, surface finish, and layout. The criteria in the design for supply chain group include material, manufacturing process, assembly, and supply chain operation. From the point of view of value and cost, the criteria in the functional design group and Kansei design group represent the design value of the product. The criteria in the design for supply chain group represent the supply chain and manufacturing cost of the product. It is required to evaluate the design value and the supply chain cost to determine the final design. For the purpose of evaluating the criteria in the three criteria groups, a fuzzy analytic network process (FANP) method is presented to evaluate a weighted index by calculating the total relational values among the three groups. A method using the technique for order preference by similarity to ideal solution (TOPSIS) is used to compare and rank the design alternative cases according to the weighted index using the total relational values of the criteria. The final decision of a design case can be determined by using the ordered ranking. For example, the design case with the top ranking can be selected as the final design case. Based on the criteria in the evaluation, the design objective can be achieved with a combined and weighted effect of the design value and manufacturing cost. An example product is demonstrated and illustrated in the presentation. It shows that the design evaluation model is useful for integrated evaluation of functional design, Kansei design, and design for supply chain to determine the best design case and achieve the design objective.

Keywords: design for supply chain, design evaluation, functional design, Kansei design, fuzzy analytic network process, technique for order preference by similarity to ideal solution

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Authors: M. Invigorito, G. Elia, M. Panelli

Abstract:

Hybrid propulsion combines beneficial properties of both solid and liquid rockets, such as multiple restarts, throttability as well as simplicity and reduced costs. A nitrous oxide (N2O)/paraffin-based hybrid rocket engine demonstrator is currently under development at the Italian Aerospace Research Center (CIRA) within the national research program HYPROB, funded by the Italian Ministry of Research. Nitrous oxide belongs to the class of self-pressurizing propellants that exhibit a high vapor pressure at standard ambient temperature. This peculiar feature makes those fluids very attractive for space rocket applications because it avoids the use of complex pressurization systems, leading to great benefits in terms of weight savings and reliability. To avoid feed-system-coupled instabilities, the phase change is required to occur through the injectors. In this regard, the oxidizer is stored in liquid condition while target chamber pressures are designed to lie below vapor pressure. The consequent cavitation and flash vaporization constitute a remarkably complex phenomenology that arises great modelling challenges. Thus, it is clear that the design of the injection system is fundamental for the full exploitation of hybrid rocket engine throttability. The Analytical Hierarchy Process has been used to select the injection architecture as best compromise among different design criteria such as functionality, technology innovation and cost. The impossibility to use engineering simplified relations for the dimensioning of the injectors led to the needs of applying a numerical approach based on OpenFOAM®. The numerical tool has been validated with selected experimental data from literature. Quantitative, as well as qualitative comparisons are performed in terms of mass flow rate and pressure drop across the injector for several operating conditions. The results show satisfactory agreement with the experimental data. Modeling assumptions, together with their impact on numerical predictions are discussed in the paper. Once assessed the reliability of the numerical tool, the injection plate has been designed and sized to guarantee the required amount of oxidizer in the combustion chamber and therefore to assure high combustion efficiency. To this purpose, the plate has been designed with multiple injectors whose number and diameter have been selected in order to reach the requested mass flow rate for the two operating conditions of maximum and minimum thrust. The overall design has been finally verified through three-dimensional computations in cavitating non-reacting conditions and it has been verified that the proposed design solution is able to guarantee the requested values of mass flow rates.

Keywords: hybrid rocket, injection system design, OpenFOAM®, cavitation

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Authors: Teimuraz Manjapharashvili, Ketevani Manjaparashvili

Abstract:

Fuzzy logic is a modeling method for complex or ill-defined systems and is a relatively new mathematical approach. Its basis is to consider overlapping cases of parameter values and define operations to manipulate these cases. Fuzzy logic can successfully create operative automatic management or appropriate advisory systems. Fuzzy logic techniques in various operational control technologies have grown rapidly in the last few years. Fuzzy logic is used in many areas of human technological activity. In recent years, Fuzzy logic has proven its great potential, especially in the automation of industrial process control, where it allows the form of a control design based on the experience of experts and the results of experiments. The engineering of chemical technological processes uses fuzzy logic in optimal management, and it is also used in process control, including the operational control of continuous cycle chemical industrial, technological processes, where special features appear due to the continuous cycle and correct management acquires special importance. This paper discusses how intelligent systems can be developed, in particular, how Fuzzy logic can be used to build knowledge-based expert systems in chemical process engineering. The implemented projects reveal that the use of Fuzzy logic in technological process control has already given us better solutions than standard control techniques. Fuzzy logic makes it possible to develop an advisory system for decision-making based on the historical experience of the managing operator and experienced experts. The present paper deals with operational control and management systems of continuous cycle chemical technological processes, including advisory systems. Because of the continuous cycle, many features are introduced in them compared to the operational control of other chemical technological processes. Among them, there is a greater risk of transitioning to emergency mode; the return from emergency mode to normal mode must be done very quickly due to the impossibility of stopping the technological process due to the release of defective products during this period (i.e., receiving a loss), accordingly, due to the need for high qualification of the operator managing the process, etc. For these reasons, operational control systems of continuous cycle chemical technological processes have been specifically discussed, as they are different systems. Special features of such systems in control and management were brought out, which determine the characteristics of the construction of control and management systems. To verify the findings, the development of an advisory decision-making information system for operational control of a lime kiln using Fuzzy logic, based on the creation of a relevant expert-targeted knowledge base, was discussed. The control system has been implemented in a real lime production plant with a lime burn kiln, which has shown that suitable and intelligent automation improves operational management, reduces the risks of releasing defective products, and, therefore, reduces costs. The special advisory system was successfully used in the said plant both for the improvement of operational management and, if necessary, for the training of new operators due to the lack of an appropriate training institution.

Keywords: chemical process control systems, continuous cycle industrial technological processes, fuzzy logic, lime kiln

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Authors: Mohammad Anvari, Helen S. Joyner (Melito)

Abstract:

Camelina sativa (L.) Crantz is an oilseed crop currently used for the production of biofuels. However, the low price of diesel and gasoline has made camelina an unprofitable crop for farmers, leading to declining camelina production in the US. Hence, the ability to utilize camelina byproduct (defatted meal) after oil extraction would be a pivotal factor for promoting the economic value of the plant. Camelina defatted meal is rich in proteins and polysaccharides. The great diversity in the polysaccharide structural features provides a unique opportunity for use in food formulations as thickeners, gelling agents, emulsifiers, and stabilizers. There is currently a great degree of interest in the study of novel plant polysaccharides, as they can be derived from readily accessible sources and have potential application in a wide range of food formulations. However, there are no published studies on the polysaccharide extracted from camelina meal, and its potential industrial applications remain largely underexploited. Rheological properties are a key functional feature of polysaccharides and are highly dependent on the material composition and molecular structure. Therefore, the objective of this study was to evaluate the rheological properties of the polysaccharide extracted from camelina meal at different conditions to obtain insight on the molecular characteristics of the polysaccharide. Flow and dynamic mechanical behaviors were determined under different temperatures (5-50°C) and concentrations (1-6% w/v). Additionally, the zeta potential of the polysaccharide dispersion was measured at different pHs (2-11) and a biopolymer concentration of 0.05% (w/v). Shear rate sweep data revealed that the camelina polysaccharide displayed shear thinning (pseudoplastic) behavior, which is typical of polymer systems. The polysaccharide dispersion (1% w/v) showed no significant changes in viscosity with temperature, which makes it a promising ingredient in products requiring texture stability over a range of temperatures. However, the viscosity increased significantly with increased concentration, indicating that camelina polysaccharide can be used in food products at different concentrations to produce a range of textures. Dynamic mechanical spectra showed similar trends. The temperature had little effect on viscoelastic moduli. However, moduli were strongly affected by concentration: samples exhibited concentrated solution behavior at low concentrations (1-2% w/v) and weak gel behavior at higher concentrations (4-6% w/v). These rheological properties can be used for designing and modeling of liquid and semisolid products. Zeta potential affects the intensity of molecular interactions and molecular conformation and can alter solubility, stability, and eventually, the functionality of the materials as their environment changes. In this study, the zeta potential value significantly decreased from 0.0 to -62.5 as pH increased from 2 to 11, indicating that pH may affect the functional properties of the polysaccharide. The results obtained in the current study showed that camelina polysaccharide has significant potential for application in various food systems and can be introduced as a novel anionic thickening agent with unique properties.

Keywords: Camelina meal, polysaccharide, rheology, zeta potential

Procedia PDF Downloads 246