Search results for: interface modeling

Authors: Samuel Asrat

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Infusion pumps have become indispensable tools in modern healthcare, allowing for precise and controlled delivery of fluids, medications, and nutrients to patients. This paper provides an overview of the historical development, measurement, and parts of infusion pumps. The historical development of infusion pumps can be traced back to the early 1960s when the first rudimentary models were introduced. These early pumps were large, cumbersome, and often unreliable. However, advancements in technology and engineering over the years have led to the development of smaller, more accurate, and user-friendly infusion pumps. Measurement of infusion pumps involves assessing various parameters such as flow rate, volume delivered, and infusion duration. Flow rate, typically measured in milliliters per hour (mL/hr), is a critical parameter that determines the rate at which fluids or medications are delivered to the patient. Accurate measurement of flow rate is essential to ensure the proper administration of therapy and prevent adverse effects. Infusion pumps consist of several key parts, including the pump mechanism, fluid reservoir, tubing, and control interface. The pump mechanism is responsible for generating the necessary pressure to push fluids through the tubing and into the patient's bloodstream. The fluid reservoir holds the medication or solution to be infused, while the tubing serves as the conduit through which the fluid travels from the reservoir to the patient. The control interface allows healthcare providers to program and adjust the infusion parameters, such as flow rate and volume. In conclusion, infusion pumps have evolved significantly since their inception, offering healthcare providers unprecedented control and precision in delivering fluids and medications to patients. Understanding the historical development, measurement, and parts of infusion pumps is essential for ensuring their safe and effective use in clinical practice.

Keywords: dip, ip, sp, is

Procedia PDF Downloads 54

Authors: Hoi-Lam Ma, Sai-Ho Chung

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In traditional integrated berth allocation with quay crane assignment models, time dimension is usually assumed in hourly based. However, nowadays, transshipment becomes the main business to many container terminals, especially in Southeast Asia (e.g. Hong Kong and Singapore). In these terminals, vessel arrivals are usually very frequent with small handling volume and very short staying time. Therefore, the traditional hourly-based modeling approach may cause significant berth and quay crane idling, and consequently cannot meet their practical needs. In this connection, a 15-minute-based modeling approach is requested by industrial practitioners. Accordingly, a Three-level Genetic Algorithm (3LGA) with Quay Crane (QC) shifting heuristics is designed to fulfill the research gap. The objective function here is to minimize the total service time. Preliminary numerical results show that the proposed 15-minute-based approach can reduce the berth and QC idling significantly.

Keywords: transshipment, integrated berth allocation, variable-in-time quay crane assignment, quay crane assignment

Procedia PDF Downloads 164

Authors: Mohammad Reza Zamanian

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The construction industry has always been recognized as one of the most dangerous available industries, and the statistics of accidents and injuries resulting from it say that the safety category needs more attention and the arrival of up-to-date technologies in this field. Building information modeling (BIM) is one of the relatively new and applicable technologies in Iran, that the necessity of using it is increasingly evident. The main purposes of this research are to evaluate the feasibility of using this technology in the safety sector of construction projects and to evaluate the effectiveness and operationality of its various applications in this sector. These applications were collected and categorized after reviewing past studies and researches then a questionnaire based on Delphi method criteria was presented to 30 experts who were thoroughly familiar with modeling software and safety guidelines. After receiving and exporting the answers to SPSS software, the validity and reliability of the questionnaire were assessed to evaluate the measuring tools. Fuzzy logic is a good way to analyze data because of its flexibility in dealing with ambiguity and uncertainty issues, and the implementation of the Delphi method in the fuzzy environment overcomes the uncertainties in decision making. Therefore, this method was used for data analysis, and the results indicate the usefulness and effectiveness of BIM in projects and improvement of safety status at different stages of construction. Finally, the applications and the sections discussed were ranked in order of priority for efficiency and effectiveness. Safety planning is considered as the most influential part of the safety of BIM among the four sectors discussed, and planning for the installation of protective fences and barriers to prevent falls and site layout planning with a safety approach based on a 3D model are the most important applications of BIM among the 18 applications to improve the safety of construction projects.

Keywords: building information modeling, safety of construction projects, Delphi method, fuzzy logic

Procedia PDF Downloads 161

Authors: Hadayat Ullah, Pervez Khalid, Saad Ahmed Mashwani, Zaheer Abbasi, Mubashir Mehmood, Muhammad Jahangir, Ehsan ul Haq

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The aim of the study is to explore subsurface structures through data that is acquired from the seismic survey to delineate the characteristics of the reservoir through petrophysical analysis. Ghazij Shale of Eocene age is regional seal rock in this field. In this research work, 3D property models of subsurface were prepared by applying Petrel software to identify various lithologies and reservoir fluids distribution throughout the field. The 3D static modeling shows a better distribution of the discrete and continuous properties in the field. This model helped to understand the reservoir properties and enhance production by selecting the best location for future drilling. A complete workflow is proposed for formation evaluation, electrofacies modeling, and structural interpretation of the subsurface geology. Based on the wireline logs, it is interpreted that the thickness of the Pab Sandstone varies from 250 m to 350 m in the entire study area. The sandstone is massive with high porosity and intercalated layers of shales. Faulted anticlinal structures are present in the study area, which are favorable for the accumulation of hydrocarbon. 3D structural models and various seismic attribute models were prepared to analyze the reservoir character of this clastic reservoir. Based on wireline logs and seismic data, clean sand, shaly sand, and shale are marked as dominant facies in the study area. However, clean sand facies are more favorable to act as a potential net pay zone.

Keywords: cretaceous, pab sandstone, petrophysics, electrofacies, hydrocarbon

Procedia PDF Downloads 136

Authors: Raed Kouta

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A fuel cell is a multi-physical system. Its electrical performance depends on chemical, electrochemical, fluid, and mechanical parameters. Many studies focus on physical and chemical aspects. Our study contributes to the evaluation of the influence of mechanical aspects on the performance of a fuel cell. This study is carried out as part of a reliability approach. Reliability modeling allows to consider the uncertainties of the incoming parameters and the probabilistic modeling of the outgoing parameters. The fuel cell studied is the one often used in land, sea, or air transport. This is the Low-Temperature Proton Exchange Membrane Fuel Cell (PEMFC). This battery can provide the required power level. One of the main scientific and technical challenges in mastering the design and production of a fuel cell is to know its behavior in its actual operating environment. The study proposes to highlight the influence on the production of electrical energy: Mechanical design and manufacturing parameters and their uncertainties (Young module, GDL porosity, permeability, etc.). The influence of the geometry of the bipolar plates is also considered. An experimental design is proposed with two types of materials as well as three geometric shapes for three joining pressures. Other experimental designs are also proposed for studying the influence of uncertainties of mechanical parameters on cell performance. - Mechanical (static, dynamic) and thermal (tightening - compression, vibrations (road rolling and tests on vibration-climatic bench, etc.) loads. This study is also carried out according to an experimental scheme on a fuel cell system for vibration loads recorded on a vehicle test track with three temperatures and three expected performance levels. The work will improve the coupling between mechanical, physical, and chemical phenomena.

Keywords: fuel cell, mechanic, reliability, uncertainties

Procedia PDF Downloads 181

Authors: Prasad Kalagura, B. Veeresh kumar

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We constructed an interface system that would allow a similarly paralyzed user to interact with a computer with almost full functional capability. A real-time tracking algorithm is implemented based on adaptive skin detection and motion analysis. The clicking of the mouse is activated by the user's eye blinking through a sensor. The keyboard function is implemented by voice recognition kit.

Keywords: embedded ARM7 processor, mouse pointer control, voice recognition

Procedia PDF Downloads 572

Authors: T. Wejrzanowski, M. Grybczuk, E. Tymicki, K. J. Kurzydlowski

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In the present study, numerical simulations of heat and mass transfer in Physical Vapor Transport reactor during silicon carbide single crystal growth are addressed. Silicon carbide is a wide bandgap material with unique properties making it highly applicable for high power electronics applications. Because of high manufacturing costs improvements of SiC production process are required. In this study, numerical simulations were used as a tool of process optimization. Computer modeling allows for cost and time effective analysis of processes occurring during SiC single crystal growth and provides essential information needed for improvement of the process. Quantitative relationship between process conditions, such as temperature or pressure, and crystal growth rate and shape of crystallization front have been studied and verified using experimental data. Basing on modeling results, several process improvements were proposed and implemented.

Keywords: Finite Volume Method, semiconductors, Physica Vapor Transport, silicon carbide

Procedia PDF Downloads 495

Authors: Dicko Ali Hamadi, Tong-Yette Nicolas, Gilles Benjamin, Faure Francois, Palombi Olivier

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A novel hybrid model of the lumbar spine, allowing fast static and dynamic simulations of the disc pressure and the spine mobility, is introduced in this work. Our contribution is to combine rigid bodies, deformable finite elements, articular constraints, and springs into a unique model of the spine. Each vertebra is represented by a rigid body controlling a surface mesh to model contacts on the facet joints and the spinous process. The discs are modeled using a heterogeneous tetrahedral finite element model. The facet joints are represented as elastic joints with six degrees of freedom, while the ligaments are modeled using non-linear one-dimensional elastic elements. The challenge we tackle is to make these different models efficiently interact while respecting the principles of Anatomy and Mechanics. The mobility, the intradiscal pressure, the facet joint force and the instantaneous center of rotation of the lumbar spine are validated against the experimental and theoretical results of the literature on flexion, extension, lateral bending as well as axial rotation. Our hybrid model greatly simplifies the modeling task and dramatically accelerates the simulation of pressure within the discs, as well as the evaluation of the range of motion and the instantaneous centers of rotation, without penalizing precision. These results suggest that for some types of biomechanical simulations, simplified models allow far easier modeling and faster simulations compared to usual full-FEM approaches without any loss of accuracy.

Keywords: hybrid, modeling, fast simulation, lumbar spine

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Authors: Ben Soltane Cheima, Ittansa Yonas Kelbesa

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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: feature extraction, speaker modeling, feature matching, Mel frequency cepstrum coefficient (MFCC), Gaussian mixture model (GMM), vector quantization (VQ), Linde-Buzo-Gray (LBG), expectation maximization (EM), pre-processing, voice activity detection (VAD), short time energy (STE), background noise statistical modeling, closed-set tex-independent speaker identification system (CISI)

Procedia PDF Downloads 303

Authors: Yang Yi-Fei, Luo Min-Zhou, Zhang Fu-Chun, He Nai-Bao, Xing Shao-Bang

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This paper presents an electromagnetic finite element model of permanent magnet synchronous linear motor and distortion rate of the air gap flux density waveform is analyzed in detail. By designing the sample space of the parameters, nonlinear regression modeling of the orthogonal experimental design is introduced. We put forward for possible air gap flux density waveform sine electromagnetic scheme. Parameters optimization of the permanent magnet synchronous linear motor is also introduced which is based on chaotic search and adaptation function. Simulation results prove that the pole shifting does not affect the motor back electromotive symmetry based on the structural parameters, it provides a novel way for the optimum design of permanent magnet synchronous linear motor and other engineering.

Keywords: permanent magnet synchronous linear motor, finite element analysis, chaotic search, optimization design

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Authors: M. I. Youssef, A. E. Emam, M. Abd Elghany

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The performance of wireless communication systems is affected mainly by the environment of its associated channel, which is characterized by dynamic and unpredictable behavior. In this paper, different statistical earth-satellite channel models are studied with emphasize on two main models, first is the Rice-Log normal model, due to its representation for the environment including shadowing and multi-path components that affect the propagated signal along its path, and a three-state model that take into account different fading conditions (clear area, moderate shadow and heavy shadowing). The provided models are based on AWGN, Rician, Rayleigh, and log-normal distributions were their Probability Density Functions (PDFs) are presented. The transmission system Bit Error Rate (BER), Peak-Average-Power Ratio (PAPR), and the channel capacity vs. fading models are measured and analyzed. These simulations are implemented using MATLAB tool, and the results had shown the performance of transmission system over different channel models.

Keywords: fading channels, MIMO communication, RNS scheme, statistical modeling

Procedia PDF Downloads 142

Authors: Pedro A. Marques, Francisco Monteiro, Alessandra Zumbo, Alessia Simonini, Miguel A. Mendez

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Cryogenic fuels such as Liquid Hydrogen (LH₂) must be transported and stored at extremely low temperatures. Without expensive active cooling solutions, preventing fuel boil-off over time is impossible. Hence, one must resort to venting systems at the cost of significant energy and fuel mass loss. These losses increase significantly in propellant tanks installed on vehicles, as the presence of external accelerations induces sloshing. Sloshing increases heat and mass transfer rates and leads to significant pressure oscillations, which might further trigger propellant venting. To make LH₂ economically viable, it is essential to minimize these factors by using advanced control techniques. However, these require accurate modelling and a full understanding of the tank's thermodynamics. The present research aims to implement a simple thermodynamic model capable of predicting the state of a cryogenic fuel tank under different operating conditions (i.e., filling, pressurization, fuel extraction, long-term storage, and sloshing). Since this model relies on a set of closure parameters to drive the system's transient response, it must be calibrated using experimental or numerical data. This work focuses on the former approach, wherein the model is calibrated through an experimental campaign carried out on a reduced-scale model of a cryogenic tank. The thermodynamic model of the system is composed of three control volumes: the ullage, the liquid, and the insulating walls. Under this lumped formulation, the governing equations are derived from energy and mass balances in each region, with mass-averaged properties assigned to each of them. The gas-liquid interface is treated as an infinitesimally thin region across which both phases can exchange mass and heat. This results in a coupled system of ordinary differential equations, which must be closed with heat and mass transfer coefficients between each control volume. These parameters are linked to the system evolution via empirical relations derived from different operating regimes of the tank. The derivation of these relations is carried out using an inverse method to find the optimal relations that allow the model to reproduce the available data. This approach extends classic system identification methods beyond linear dynamical systems via a nonlinear optimization step. Thanks to the data-driven assimilation of the closure problem, the resulting model accurately predicts the evolution of the tank's thermodynamics at a negligible computational cost. The lumped model can thus be easily integrated with other submodels to perform complete system simulations in real time. Moreover, by setting the model in a dimensionless form, a scaling analysis allowed us to relate the tested configurations to a representative full-size tank for naval applications. It was thus possible to compare the relative importance of different transport phenomena between the laboratory model and the full-size prototype among the different operating regimes.

Keywords: destratification, hydrogen, modeling, pressure-drop, pressurization, sloshing, thermodynamics

Procedia PDF Downloads 86

Authors: Bharatendra Rai

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Predictive data analysis and modeling involving machine learning techniques become challenging in presence of too many explanatory variables or features. Presence of too many features in machine learning is known to not only cause algorithms to slow down, but they can also lead to decrease in model prediction accuracy. This study involves housing dataset with 79 quantitative and qualitative features that describe various aspects people consider while buying a new house. Boruta algorithm that supports feature selection using a wrapper approach build around random forest is used in this study. This feature selection process leads to 49 confirmed features which are then used for developing predictive random forest models. The study also explores five different data partitioning ratios and their impact on model accuracy are captured using coefficient of determination (r-square) and root mean square error (rsme).

Keywords: housing data, feature selection, random forest, Boruta algorithm, root mean square error

Procedia PDF Downloads 315

Authors: Hossein Panahi, Firouz Fallahi, Sima Nasibparast

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Background & Aim: Unnecessary growth in health expenditures of developing countries in recent decades, and also the importance of physicians’ behavior in health market, have made the theory of physician-induced demand (PID) as one of the most important issues in health economics. Therefore, the main objective of this study is to investigate the hypothesis of induced demand among mental patients who receive services from either psychologists or psychiatrists in East Azerbaijan province. Methods: Using data from questionnaires in 2020 and employing the theoretical model of Jaegher and Jegers (2000) and hierarchical linear modeling (HLM), this study examines the PID hypothesis of selected psychologists and psychiatrists. The sample size of the study, after removing the questionnaires with missing data, is 45 psychologists and 203 people of their patients, as well as 30 psychiatrists and 160 people of their patients. Results: The results show that, although psychiatrists are ‘profit-oriented physicians’, there is no evidence of inducing unnecessary demand by them (PID), and the difference between the behavior of employers and employee doctors is due to differences in practice style. However, with regard to psychologists, the results indicate that they are ‘profit-oriented’, and there is a PID effect in this sector. Conclusion: According to the results, it is suggested that in order to reduce competition and eliminate the PID effect, the admission of students in the field of psychology should be reduced, patient information on mental illness should be increased, and government monitoring and control over the national health system must be increased.

Keywords: physician-induced demand, national health system, hierarchical linear modeling methods, multilevel modela

Procedia PDF Downloads 128

Authors: Takoua Soltani, Imen Soltani, Taoufik Aguili

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The communications' and radar systems' demands give rise to new developments in the domain of active integrated antennas (AIA) and arrays. The main advantages of AIA arrays are the simplicity of fabrication, low cost of manufacturing, and the combination between free space power and the scanner without a phase shifter. The integrated active antenna modeling is the coupling between the electromagnetic model and the transport model that will be affected in the high frequencies. Global modeling of active circuits is important for simulating EM coupling, interaction between active devices and the EM waves, and the effects of EM radiation on active and passive components. The current review focuses on the modeling of the active element which is a MESFET transistor immersed in a rectangular waveguide. The proposed EM analysis is based on the Method of Moments combined with the Generalised Equivalent Circuit method (MOM-GEC). The Method of Moments which is the most common and powerful software as numerical techniques have been used in resolving the electromagnetic problems. In the class of numerical techniques, MOM is the dominant technique in solving of Maxwell and Transport’s integral equations for an active integrated antenna. In this situation, the equivalent circuit is introduced to the development of an integral method formulation based on the transposition of field problems in a Generalised equivalent circuit that is simpler to treat. The method of Generalised Equivalent Circuit (MGEC) was suggested in order to represent integral equations circuits that describe the unknown electromagnetic boundary conditions. The equivalent circuit presents a true electric image of the studied structures for describing the discontinuity and its environment. The aim of our developed method is to investigate the antenna parameters such as the input impedance and the current density distribution and the electric field distribution. In this work, we propose a global EM modeling of the MESFET AsGa transistor using an integral method. We will begin by describing the modeling structure that allows defining an equivalent EM scheme translating the electromagnetic equations considered. Secondly, the projection of these equations on common-type test functions leads to a linear matrix equation where the unknown variable represents the amplitudes of the current density. Solving this equation resulted in providing the input impedance, the distribution of the current density and the electric field distribution. From electromagnetic calculations, we were able to present the convergence of input impedance for different test function number as a function of the guide mode numbers. This paper presents a pilot study to find the answer to map out the variation of the existing current evaluated by the MOM-GEC. The essential improvement of our method is reducing computing time and memory requirements in order to provide a sufficient global model of the MESFET transistor.

Keywords: active integrated antenna, current density, input impedance, MESFET transistor, MOM-GEC method

Procedia PDF Downloads 194

Authors: Benjamin Leiby, Darryl Ahner

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This study demonstrates an alternative stochastic imputation approach for large datasets when preferred commercial packages struggle to iterate due to numerical problems. A large country conflict dataset motivates the search to impute missing values well over a common threshold of 20% missingness. The methodology capitalizes on correlation while using model residuals to provide the uncertainty in estimating unknown values. Examination of the methodology provides insight toward choosing linear or nonlinear modeling terms. Static tolerances common in most packages are replaced with tailorable tolerances that exploit residuals to fit each data element. The methodology evaluation includes observing computation time, model fit, and the comparison of known values to replaced values created through imputation. Overall, the country conflict dataset illustrates promise with modeling first-order interactions while presenting a need for further refinement that mimics predictive mean matching.

Keywords: correlation, country conflict, imputation, stochastic regression

Procedia PDF Downloads 115

Authors: Wayan Widhiada, Cok Indra Partha, Gusti Ngurah Nitya Santhiarsa

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The purpose of this paper is to investigate the sophistication of the use of Proportional Integral and Derivative Control to control the kinematic motion of the mobile robot manipulator. Simulation and experimental methods will be used to investigate the sophistication of PID control to control the mobile robot arm in the collection and placement of several kinds of objects quickly, accurately and correctly. Mathematical modeling will be done by utilizing the integration of Solidworks and MATLAB / Simmechanics software. This method works by converting the physical model file into the xml file. This method is easy, fast and accurate done in modeling and design robotics. The automatic control design of this robot manipulator will be validated in simulations and experimental in control labs as evidence that the mobile robot manipulator gripper control design can achieve the best performance such as the error signal is lower than 5%, small overshoot and get steady signal response as quickly.

Keywords: control analysis, kinematics motion, mobile robot manipulator, performance

Procedia PDF Downloads 397

Authors: Aaron Liggett

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This research focuses on the visionary proposal made by the Olmsted Brothers Landscape Architecture firm in the 1920s for a network of interconnected parkways in Los Angeles. Their envisioned parkways aimed to address environmental and cultural strains by providing green space for recreation, wildlife habitat, and stormwater management while serving as multimodal transportation routes. Although the parkways were never constructed, through an evidence-based approach, this research presents a framework for evaluating the potential functionality and success of the parkways by modeling and visualizing their quantitative and qualitative landscape performance and benefits. Historical documents and innovative digital modeling tools produce detailed analysis, modeling, and visualization of the parkway designs. A set of 1928 construction documents are used to analyze and interpret the design intent of the parkways. Grading plans are digitized in CAD and modeled in Sketchup to produce 3D visualizations of the parkway. Drainage plans are digitized to model stormwater performance. Planting plans are analyzed to model urban forestry and biodiversity. The EPA's Storm Water Management Model (SWMM) predicts runoff quantity and quality. The USDA Forests Service tools evaluate carbon sequestration and air quality. Spatial and overlay analysis techniques are employed to assess urban connectivity and the spatial impacts of the parkway designs. The study reveals how the integration of blue infrastructure, green infrastructure, and transportation infrastructure within the parkway design creates a multifunctional landscape capable of offering alternative spatial and temporal uses. The analysis demonstrates the potential for multiple functional, ecological, aesthetic, and social benefits to be derived from the proposed parkways. The analysis of the Olmsted Brothers' proposed Los Angeles parkways, which predated contemporary ecological design and resiliency practices, demonstrates the potential for providing multiple functional, ecological, aesthetic, and social benefits within urban designs. The findings highlight the importance of integrated blue, green, and transportation infrastructure in creating a multifunctional landscape that simultaneously serves multiple purposes. The research contributes new methods for modeling and visualizing landscape performance benefits, providing insights and techniques for informing future designs and sustainable development strategies.

Keywords: landscape architecture, ecological urban design, greenway, landscape performance

Procedia PDF Downloads 121

Authors: K. E. Oyetade, S. D. Eyono Obono

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One of the fundamental characteristics of Information and Communication Technology (ICT) has been the ever-changing nature of continuous release and models of ICTs with its impact on the academic, social, and psychological benefits of its introduction in schools. However, there seems to be a growing concern about its negative impact on students when introduced early in schools for teaching and learning. This study aims to design a model of child development factors affecting the early introduction of ICTs in schools in an attempt to improve the understanding of child development and introduction of ICTs in schools. The proposed model is based on a sound theoretical framework. It was designed following a literature review of child development theories and child development factors. The child development theoretical framework that fitted to the best of all child development factors was then chosen as the basis for the proposed model. This study hence found that the Jean Piaget cognitive developmental theory is the most adequate theoretical frameworks for modeling child development factors for ICT introduction in schools.

Keywords: child development factors, child development theories, ICTs, theory

Procedia PDF Downloads 405

Authors: Nuchjaree Kidjawan, Orapan Thosingha, Pawinee Vaipatama, Prakrankiat Youngkong, Sirinapha Malangputhong, Kitti Thamrongaphichartkul, Phatcharaporn Phetcharat

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NPI uses technology sensorization of things and processed by AI system. The main features are an individual interface pressure sensor system in contact with the mattress and a position management system where the sensor detects the determined pressure with automatic pressure reduction and distribution. The role of NPI is to monitor, identify the risk and manage the interface pressure automatically when the determined pressure is detected. This study aims to evaluate the effects of “Never Pressure Injury (NPI),” an innovative mattress, on the incidence of pressure injuries in critically ill patients. An observational case-control study was employed to compare the incidence of pressure injury between the case and the control group. The control group comprised 80 critically ill patients admitted to a critical care unit of Phyathai3 Hospital, receiving standard care with the use of memory foam according to intensive care unit guidelines. The case group comprised 80 critically ill patients receiving standard care and with the use of the Never Pressure Injury (NPI) innovation mattress. The patients who were over 20 years old and showed scores of less than 18 on the Risk Assessment Pressure Ulcer Scale – ICU and stayed in ICU for more than 24 hours were selected for the study. The patients’ skin was assessed for the occurrence of pressure injury once a day for five consecutive days or until the patients were discharged from ICU. The sample comprised 160 patients with ages ranging from 30-102 (mean = 70.1 years), and the Body Mass Index ranged from 13.69- 49.01 (mean = 24.63). The case and the control group were not different in their sex, age, Body Mass Index, Pressure Ulcer Risk Scores, and length of ICU stay. Twenty-two patients (27.5%) in the control group had pressure injuries, while no pressure injury was found in the case group.

Keywords: pressure injury, never pressure injury, innovation mattress, critically ill patients, prevent pressure injury

Procedia PDF Downloads 109

Authors: Ayman Mutahar Alrassas, Shaoran Ren, Renyuan Ren, Hung Vo Thanh, Mohammed Hail Hakimi, Zhenliang Guan

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The significant effect of CO₂ on global climate and the environment has gained more concern worldwide. Enhance oil recovery (EOR) associated with sequestration of CO₂ particularly into the depleted oil reservoir is considered the viable approach under financial limitations since it improves the oil recovery from the existing oil reservoir and boosts the relation between global-scale of CO₂ capture and geological sequestration. Consequently, practical measurements are required to attain large-scale CO₂ emission reduction. This paper presents an integrated modeling workflow to construct an accurate 3D reservoir geological model to estimate the storage capacity of CO₂ under geological uncertainty in an unconventional oil reservoir of the Paleogene Shahejie Formation (Es1) in the block Nv32, Shenvsi oilfield, China. In this regard, geophysical data, including well logs of twenty-two well locations and seismic data, were combined with geological and engineering data and used to construct a 3D reservoir geological modeling. The geological modeling focused on four tight reservoir units of the Shahejie Formation (Es1-x1, Es1-x2, Es1-x3, and Es1-x4). The validated 3D reservoir models were subsequently used to calculate the theoretical CO₂ storage capacity in the block Nv32, Shenvsi oilfield. Well logs were utilized to predict petrophysical properties such as porosity and permeability, and lithofacies and indicate that the Es1 reservoir units are mainly sandstone, shale, and limestone with a proportion of 38.09%, 32.42%, and 29.49, respectively. Well log-based petrophysical results also show that the Es1 reservoir units generally exhibit 2–36% porosity, 0.017 mD to 974.8 mD permeability, and moderate to good net to gross ratios. These estimated values of porosity, permeability, lithofacies, and net to gross were up-scaled and distributed laterally using Sequential Gaussian Simulation (SGS) and Simulation Sequential Indicator (SIS) methods to generate 3D reservoir geological models. The reservoir geological models show there are lateral heterogeneities of the reservoir properties and lithofacies, and the best reservoir rocks exist in the Es1-x4, Es1-x3, and Es1-x2 units, respectively. In addition, the reservoir volumetric of the Es1 units in block Nv32 was also estimated based on the petrophysical property models and fund to be between 0.554368

Keywords: CO₂ storage capacity, 3D geological model, geological uncertainty, unconventional oil reservoir, block Nv32

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Authors: Sara A. Pakvis, Giulia Scalet, Stefania Marconi, Ferdinando Auricchio, Matthijs Langelaar

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In recent developments in the field of multi-material additive manufacturing, differences in material properties are exploited to create printed shape-memory structures, which are referred to as 4D-printed structures. New printing techniques allow for the deliberate introduction of prestresses in the specimen during manufacturing, and, in combination with the right design, this enables new functionalities. This research focuses on bi-polymer 4D-printed structures, where the transformation process is based on a heat-induced glass transition in one material lowering its Young’s modulus, combined with an initial prestress in the other material. Upon the decrease in stiffness, the prestress is released, which results in the realization of an essentially pre-programmed deformation. As the design of such functional multi-material structures is crucial but far from trivial, a systematic methodology to find the design of 4D-printed structures is developed, where a finite element model is combined with a density-based topology optimization method to describe the material layout. This modeling approach is verified by a convergence analysis and validated by comparing its numerical results to analytical and published data. Specific aspects that are addressed include the interplay between the definition of the prestress and the material interpolation function used in the density-based topology description, the inclusion of a temperature-dependent stiffness relationship to simulate the glass transition effect, and the importance of the consideration of geometric nonlinearity in the finite element modeling. The efficacy of topology optimization to design 4D-printed structures is explored by applying the methodology to a variety of design problems, both in 2D and 3D settings. Bi-layer designs composed of thermoplastic polymers are printed by means of the fused deposition modeling (FDM) technology. Acrylonitrile butadiene styrene (ABS) polymer undergoes the glass transition transformation, while polyurethane (TPU) polymer is prestressed by means of the 3D-printing process itself. Tests inducing shape transformation in the printed samples through heating are performed to calibrate the prestress and validate the modeling approach by comparing the numerical results to the experimental findings. Using the experimentally obtained prestress values, more complex designs have been generated through topology optimization, and samples have been printed and tested to evaluate their performance. This study demonstrates that by combining topology optimization and 4D-printing concepts, stimuli-responsive structures with specific properties can be designed and realized.

Keywords: 4D-printing, glass transition, shape memory polymer, topology optimization

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Authors: Talebi Aliasghar, Ebrahimpour Komeleh Hooman, Maghsoudi Ali Akbar

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In reinforced concrete (RC) structures, beam-column connection region has a considerable effect on the behavior of structures. Using fiber reinforcement polymer (FRP) for the strengthening of connections in RC structures can be one of the solutions to retrofitting this zone which result in the enhanced behavior of structure. In this paper, these changes in behavior by using FRP for high strength concrete beam-column connection have been studied by finite element modeling. The concrete damage plasticity (CDP) model has been used to analyze the RC. The results illustrated a considerable development in load-bearing capacity but also a noticeable reduction in ductility. The study also assesses these qualities for several modes of strengthening and suggests the most effective mode of strengthening. Using FRP in flexural zone and FRP with 45-degree oriented fibers in shear zone of joint showed the most significant change in behavior.

Keywords: HSC, beam-column connection, Fiber Reinforcement Polymer, FRP, Finite Element Modeling, FEM

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Authors: Kumlachew Zelalem Walle, Chun-Chen Yang

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Solid-state lithium metal batteries (SSLMBs) are considered promising candidates for next-generation energy storage devices due to their superior energy density and excellent safety. However, recent findings have shown that the formation of lithium (Li) dendrites in SSLMBs still exhibits a terrible growth ability, which makes the development of SSLMBs have to face the challenges posed by the Li dendrite problem. In this work, an inorganic/organic mixture coating material (g-C3N4/ZIF-8/PVDF) was used to modify the surface of lithium metal anode (LMA). Then the modified LMA (denoted as g-C₃N₄@Li) was assembled with lithium nafion (LiNf) coated commercial NCM811 (LiNf@NCM811) using a bilayer hybrid solid electrolyte (Bi-HSE) that incorporated 20 wt.% (vs. polymer) LiNf coated Li6.05Ga0.25La3Zr2O11.8F0.2 ([email protected]) filler faced to the positive electrode and the other layer with 80 wt.% (vs. polymer) filler content faced to the g-C₃N₄@Li. The garnet-type Li6.05Ga0.25La3Zr2O11.8F0.2 (LG0.25LZOF) solid electrolyte was prepared via co-precipitation reaction process from Taylor flow reactor and modified using lithium nafion (LiNf), a Li-ion conducting polymer. The Bi-HSE exhibited high ionic conductivity of 6.8  10–4 S cm–1 at room temperature, and a wide electrochemical window (0–5.0 V vs. Li/Li+). The coin cell was charged between 2.8 to 4.5 V at 0.2C and delivered an initial specific discharge capacity of 194.3 mAh g–1 and after 100 cycles it maintained 81.8% of its initial capacity at room temperature. The presence of a nano-sheet g-C3N4/ZIF-8/PVDF as a composite coating material on the LMA surface suppress the dendrite growth and enhance the compatibility as well as the interfacial contact between anode/electrolyte membrane. The g-C3N4@Li symmetrical cells incorporating this hybrid electrolyte possessed excellent interfacial stability over 1000 h at 0.1 mA cm–2 and a high critical current density (1 mA cm–2). Moreover, the in-situ formation of Li3N on the solid electrolyte interface (SEI) layer as depicted from the XPS result also improves the ionic conductivity and interface contact during the charge/discharge process. Therefore, these novel multi-layered fabrication strategies of hybrid/composite solid electrolyte membranes and modification of the LMA surface using mixed coating materials have potential applications in the preparation of highly safe high-voltage cathodes for SSLMBs.

Keywords: high-voltage cathodes, hybrid solid electrolytes, garnet, graphitic-carbon nitride (g-C3N4), ZIF-8 MOF

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Authors: L. Nouri Taiba, Y. Bouhamidi, F. Kaouah, Z. Bendjama, M. Trari

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In the present study, an ecofriendly biocomposite namely calcium alginate immobilized Ammi Visnaga (Khella) extraction waste (SWAV/CA) was prepared by electrostatic extrusion method and used on the cadmium biosorption from aqueous phase with and without the assistance of ultrasound in batch conditions. The influence of low frequency ultrasound (37 and 80 KHz) on the cadmium biosorption kinetics was studied. The obtained results show that the ultrasonic irradiation significantly enhances and improves the efficiency of the cadmium removal. The Pseudo first order, Pseudo-second-order, Intraparticle diffusion, and Elovich models were evaluated using the non-linear curve fitting analysis method. Modeling of kinetic results shows that biosorption process is best described by the pseudo-second order and Elovich, in both the absence and presence of ultrasound.

Keywords: biocomposite, biosorption, cadmium, non-linear analysis, ultrasound

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Authors: Muhammad Abu Bakar Tariq

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Construction industry plays a crucial role in the progress of societies and economies. Furthermore, construction projects have social as well as economic implications, thus, their success/failure have wider impacts. However, the industry is lagging behind in terms of efficiency and productivity. Building Information Modeling (BIM) is recognized as a revolutionary development in Architecture, Engineering and Construction (AEC) industry. There are numerous interest groups around the world providing definitions of BIM, proponents describing its advantages and opponents identifying challenges/barriers regarding adoption of BIM. This research is aimed at to determine what actually BIM is, along with its potential role in delivering successful construction projects. The methodology is critical analysis of secondary data sources i.e. information present in public domain, which include peer reviewed journal articles, industry and government reports, conference papers, books, case studies etc. It is discovered that clash detection and visualization are two major advantages of BIM. Clash detection option identifies clashes among structural, architectural and MEP designs before construction actually commences, which subsequently saves time as well as cost and ensures quality during execution phase of a project. Visualization is a powerful tool that facilitates in rapid decision-making in addition to communication and coordination among stakeholders throughout project’s life cycle. By eliminating inconsistencies that consume time besides cost during actual construction, improving collaboration among stakeholders throughout project’s life cycle, BIM can play a positive role to achieve efficiency and productivity that consequently deliver successful construction projects.

Keywords: building information modeling, clash detection, construction project success, visualization

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Authors: Elisaveta Doncheva, Jelena Djokikj, Ognen Tuteski, Bojana Hadjieva

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In the past decade, additive manufacturing technology or 3D printing has been promoted as an efficient method for fabricating hybrid composite materials and structures with superior mechanical properties and complex shape and geometry. Fused deposition modeling (FDM) process is commonly used additive manufacturing technique for production of polymer products. Therefore, many studies and experiments are focused on investigating the possibilities for improving the obtained results on product properties as a key factor for expanding the spectrum of their application. This article provides an extensive review on recent research advances in FDM and reports on studies that cover the effects of process parameters, material, and design of the product properties. The paper conclusions provide a clear up-to date information for optimum efficiency and enhancement of the mechanical properties of 3D printed samples and recommends further research work and investigations.

Keywords: additive manufacturing, critical parameters, filament, print orientation, 3D printing

Procedia PDF Downloads 184

Authors: Faezeh Aghazadeh, Mohammad Javad Sharifi

Abstract:

The application of neural networks to model a full-scale industrial acetylene hydrogenation in olefin plant has been studied. The operating variables studied are the, input-temperature of the reactor, output-temperature of the reactor, hydrogen ratio of the reactor, [C₂H₂]input, and [C₂H₆]input. The studied operating variables were used as the input to the constructed neural network to predict the [C₂H₆]output at any time as the output or the target. The constructed neural network was found to be highly precise in predicting the quantity of [C₂H₆]output for the new input data, which are kept unaware of the trained neural network showing its applicability to determine the [C₂H₆]output for any operating conditions. The enhancement of [C₂H₆]output as compared with [C₂H₆]input was a consequence of low selective acetylene hydrogenation to ethylene.

Keywords: acetylene hydrogenation, Pd-Ag/Al₂O₃, artificial neural network, modeling, optimal design

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Authors: Hadas Sopher, Davide Schaumann, Yehuda E. Kalay

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This paper addresses the shortcomings of architectural computation tools in representing human behavior in built environments, prior to construction and occupancy of those environments. Evaluating whether a design fits the needs of its future users is currently done solely post construction, or is based on the knowledge and intuition of the designer. This issue is of high importance when designing complex buildings such as hospitals, where the quality of treatment as well as patient and staff satisfaction are of major concern. Existing computational pre-occupancy human behavior evaluation methods are geared mainly to test ergonomic issues, such as wheelchair accessibility, emergency egress, etc. As such, they rely on Agent Based Modeling (ABM) techniques, which emphasize the individual user. Yet we know that most human activities are social, and involve a number of actors working together, which ABM methods cannot handle. Therefore, we present an event-based model that manages the interaction between multiple Actors, Spaces, and Activities, to describe dynamically how people use spaces. This approach requires expanding the computational representation of Actors beyond their physical description, to include psychological, social, cultural, and other parameters. The model presented in this paper includes cognitive abilities and rules that describe the response of actors to their physical and social surroundings, based on the actors’ internal status. The model has been applied in a simulation of hospital wards, and showed adaptability to a wide variety of situated behaviors and interactions.

Keywords: agent based modeling, architectural design evaluation, event modeling, human behavior simulation, spatial cognition

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Authors: Adriana M. Duquette, Derek P. Bornath

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Reaction Time (RT) and Movement Time (MT) are important components of everyday life that have an effect on the way in which we move about our environment. These measures become even more crucial when an event can be caused (or avoided) in a fraction of a second, such as the RT and MT required while driving. The purpose of this study was to develop a more simple method of testing RT and MT during simulated driving with or without text messaging, in a university-aged population (n = 170). In the control condition, a randomly-delayed red light stimulus flashed on a computer interface after the participant began pressing the ‘gas’ pedal on a foot switch mat. Simple RT was defined as the time between the presentation of the light stimulus and the initiation of lifting the foot from the switch mat ‘gas’ pedal; while MT was defined as the time after the initiation of lifting the foot, to the initiation of depressing the switch mat ‘brake’ pedal. In the texting condition, upon pressing the ‘gas’ pedal, a ‘text message’ appeared on the computer interface in a dialog box that the participant typed on their cell phone while waiting for the light stimulus to turn red. In both conditions, the sequence was repeated 10 times, and an average RT (seconds) and average MT (seconds) were recorded. Condition significantly (p = .000) impacted overall RTs, as the texting condition (0.47 s) took longer than the no-texting (control) condition (0.34 s). Longer MTs were also recorded during the texting condition (0.28 s) than in the control condition (0.23 s), p = .001. Overall increases in Response Time (RT + MT) of 189 ms during the texting condition would equate to an additional 4.2 meters (to react to the stimulus and begin braking) if the participant had been driving an automobile at 80 km per hour. In conclusion, increasing task complexity due to the dual-task demand of text messaging during simulated driving caused significant increases in RT (41%), MT (23%) and Response Time (34%), thus further strengthening the mounting evidence against text messaging while driving.

Keywords: simulated driving, text messaging, reaction time, movement time

Procedia PDF Downloads 518