Search results for: Modular robot

Authors: Siwei Chang, Heng Li, Haitao Wu, Xin Fang

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Construction robots are receiving more and more attention as a promising solution to the manpower shortage issue in the construction industry. The development of intelligent control techniques that assist in controlling the robots to avoid transparency and reflected building obstacles is crucial for guaranteeing the adaptability and flexibility of mobile construction robots in complex construction environments. With the boom of computer vision techniques, a number of studies have proposed vision-based methods for transparent obstacle avoidance to improve operation accuracy. However, vision-based methods are also associated with disadvantages such as high computational costs. To provide better perception and value evaluation, this study aims to analyze the performance of vision-based techniques for avoiding transparent building obstacles. To achieve this, commonly used sensors, including a lidar, an ultrasonic sensor, and a USB camera, are equipped on the robotic platform to detect obstacles. A Raspberry Pi 3 computer board is employed to compute data collecting and control algorithms. The turtlebot3 burger is employed to test the programs. On-site experiments are carried out to observe the performance in terms of success rate and detection distance. Control variables include obstacle shapes and environmental conditions. The findings contribute to demonstrating how effectively vision-based obstacle avoidance strategies for transparent building obstacle avoidance and provide insights and informed knowledge when introducing computer vision techniques in the aforementioned domain.

Keywords: construction robot, obstacle avoidance, computer vision, transparent obstacle

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Authors: Yiping Meng, Yiming Sun

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The traditional construction industry is unable to meet the requirements for novel fabrication and construction. Automated construction and digital design have emerged as industry development trends that compensate for this shortcoming under the backdrop of Industrial Revolution 4.0. Benefitting from more flexible working space and more various end-effector tools compared to CNC methods, robot fabrication and construction techniques have been used in irregular architectural design. However, there is a lack of a systematic and comprehensive design and optimisation workflow considering geometric form, material, and fabrication methods. This paper aims to propose a design optimisation workflow for improving the rationality of a free-form timber structure fabricated by the robotic arm. Firstly, the free-form surface is described by NURBS, while its structure is calculated using the finite element analysis method. Then, by considering the characteristics and limiting factors of robotic timber fabrication, strain energy and robustness are set as optimisation objectives to optimise structural morphology by gradient descent method. As a result, an optimised structure with axial force as the main force and uniform stress distribution is generated after the structure morphology optimisation process. With the decreased strain energy and the improved robustness, the generated structure's bearing capacity and mechanical properties have been enhanced. The results prove the feasibility and effectiveness of the proposed optimisation workflow for free-form timber structure morphology design.

Keywords: robotic fabrication, free-form timber structure, Multi-objective optimisation, Structural morphology, rational design

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: Kyra Kannen, Sonja D. Roelen, Sebastian Schnieder, Jarek Krajewski, Steffen Holsteg, André Karger, Johanna Askeridis, Celina Slawik, Philip Mildner, Jens Piesk, Ruslan David, Holger Kürten, Benjamin Oster, Robert Malzan, Mike Ludemann

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Virtual Reality (VR) is increasingly recognized for its potential in transforming mental disorder treatment, offering advantages such as cost-effectiveness, time efficiency, accessibility, reduced stigma, and scalability. While the application of VR in the context of anxiety disorders has been extensively evaluated and demonstrated to be effective, the utilization of VR as a therapeutic treatment for depression remains under-investigated. Our goal is to pioneer immersive VR therapy modules for treating major depression, alongside a web-based system for home use. We develop a modular digital therapy platform grounded in psychodynamic therapy interventions which addresses stress reduction, exploration of social situations and relationship support, social skill training, avoidance behavior analysis, and psychoeducation. In addition, an automated depression monitoring system, based on acoustic voice analysis, is implemented in the form of a speech-based diary to track the affective state of the user and depression severity. The use of immersive VR facilitates patient immersion into complex and realistic interpersonal interactions with high emotional engagement, which may contribute to positive treatment acceptance and satisfaction. In a proof-of-concept study, 45 depressed patients were assigned to VR or web-platform modules, evaluating user experience, usability and additional metrics including depression severity, mindfulness, interpersonal problems, and treatment satisfaction. The findings provide valuable insights into the effectiveness and user-friendliness of VR and web modules for depression therapy and contribute to the refinement of more tailored digital interventions to improve mental health.

Keywords: virtual reality therapy, digital health, depression, psychotherapy

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Authors: Ana Elisa Ribeiro Costa, Sónia Daniela Ferreira Miranda, João Pedro De Carvalho Pereira, João Carlos Simões Bernardo

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Elastomeric thermoplastics (TPEs) have been widely used in the footwear industry over the years. Recently this industry has been requesting materials that can combine lightweight and high abrasion resistance. Although there are blowing agents on the market to improve the lightweight, when these are incorporated into molten polymers during the extrusion or injection molding, it is necessary to have some specific processing conditions (e.g. effect of temperature and hydrodynamic stresses) to obtain good properties and acceptable surface appearance on the final products. Therefore, it is a great advantage for the compounder industry to acquire compounds that already include the blowing agents. In this way, they can be handled and processed under the same conditions as a conventional raw material. In this work, the expandable TPEs compounds, namely a TPU and a SEBS, with the incorporation of blowing agents, have been developed through a co-rotating modular twin-screw parallel extruder. Different blowing agents such as thermo-expandable microspheres and an azodicarbonamide were selected and different screw configurations and temperature profiles were evaluated since these parameters have a particular influence on the expansion inhibition of the blowing agents. Furthermore, percentages of incorporation were varied in order to investigate their influence on the final product properties. After the extrusion of these compounds, expansion was tested by the injection process. The mechanical and physical properties were characterized by different analytical methods like tensile, flexural and abrasive tests, determination of hardness and density measurement. Also, scanning electron microscopy (SEM) was performed. It was observed that it is possible to incorporate the blowing agents on the TPEs without their expansion on the extrusion process. Only with reprocessing (injection molding) did the expansion of the agents occur. These results are corroborated by SEM micrographs, which show a good distribution of blowing agents in the polymeric matrices. The other experimental results showed a good mechanical performance and its density decrease (30% for SEBS and 35% for TPU). This study suggested that it is possible to develop optimized compounds for footwear applications (e.g., sole shoes), which only will be able to expand during the injection process.

Keywords: blowing agents, expandable thermoplastic elastomeric compounds, low density, footwear applications

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Authors: Patarasuda Chaisupa, R. Clay Wright

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The selection of appropriate biomolecular targets is a crucial aspect of biopharmaceutical development. The Auxin-Inducible Degron Degradation (AID) technology has demonstrated remarkable potential in efficiently and rapidly degrading target proteins, thereby enabling the identification and acquisition of drug targets. The AID system also offers a viable method to deplete specific proteins, particularly in cases where the degradation pathway has not been exploited or when the adaptation of proteins, including the cell environment, occurs to compensate for the mutation or gene knockout. In this study, we have engineered an improved AID system tailored to deplete proteins of interest. This AID construct combines the auxin-responsive E3 ubiquitin ligase binding domain, AFB2, and the substrate degron, IAA17, fused to the target genes. Essential genes of fungi with the lowest percent amino acid similarity to human and plant orthologs, according to the Basic Local Alignment Search Tool (BLAST), were cloned into the AID construct in S. cerevisiae (AID-tagged strains) using a modular yeast cloning toolkit for multipart assembly and direct genetic modification. Each E3 ubiquitin ligase and IAA17 degron was fused to a fluorescence protein, allowing for real-time monitoring of protein levels in response to different auxin doses via cytometry. Our AID system exhibited high sensitivity, with an EC50 value of 0.040 µM (SE = 0.016) for AFB2, enabling the specific promotion of IAA17::target protein degradation. Furthermore, we demonstrate how this improved AID system enhances quantitative functional studies of various proteins in fungi. The advancements made in auxin-inducible protein degradation in this study offer a powerful approach to investigating critical target protein viability in fungi, screening protein targets for drugs, and regulating intracellular protein abundance, thus revolutionizing the study of protein function underlying a diverse range of biological processes.

Keywords: synthetic biology, bioengineering, molecular biology, biotechnology

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Authors: Achim Kampker, Heiner H. Heimes, Mathias Ordung, Christoph Lienemann, Ansgar Hollah, Nemanja Sarovic

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Electric cars with their fast innovation cycles and their disruptive character offer a high degree of freedom regarding innovative design for remanufacturing. Remanufacturing increases not only the resource but also the economic efficiency by a prolonged product life time. The reduced power train wear of electric cars combined with high manufacturing costs for batteries allow new business models and even second life applications. Modular and intermountable designed battery packs enable the replacement of defective or outdated battery cells, allow additional cost savings and a prolongation of life time. This paper discusses opportunities for future remanufacturing value chains of electric cars and their battery components and how to address their potentials with elaborate designs. Based on a brief overview of implemented remanufacturing structures in different industries, opportunities of transferability are evaluated. In addition to an analysis of current and upcoming challenges, promising perspectives for a sustainable electric car circular economy enabled by design for remanufacturing are deduced. Two mathematical models describe the feasibility of pursuing a circular economy of lithium ion batteries and evaluate remanufacturing in terms of sustainability and economic efficiency. Taking into consideration not only labor and material cost but also capital costs for equipment and factory facilities to support the remanufacturing process, cost benefit analysis prognosticate that a remanufacturing battery can be produced more cost-efficiently. The ecological benefits were calculated on a broad database from different research projects which focus on the recycling, the second use and the assembly of lithium ion batteries. The results of this calculations show a significant improvement by remanufacturing in all relevant factors especially in the consumption of resources and greenhouse warming potential. Exemplarily suitable design guidelines for future remanufacturing lithium ion batteries, which consider modularity, interfaces and disassembly, are used to illustrate the findings. For one guideline, potential cost improvements were calculated and upcoming challenges are pointed out.

Keywords: circular economy, electric mobility, lithium ion batteries, remanufacturing

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Authors: Aneia Rajiel Busmente, Renato Gunio Jr., Jazin Mautante, Denise Joy Mendoza, Raymond Benedict Tagorio, Gabriel Uy, Natalie Quinn Valenzuela, Ma. Elayza Villa, Francine Yezha Vizcarra, Sofia Madelle Yapan, Eugene Kurt Yboa

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COVID-19’s rapid spread caused a dramatic change in the nation, especially the educational system. The Department of Education was forced to adopt a practical learning platform without neglecting health, a printed modular distance learning. The Philippines' K–12 curriculum includes Statistics and Probability as one of the key courses as it offers students the knowledge to evaluate and comprehend data. Due to student’s difficulty and lack of understanding of the concepts of Statistics and Probability in Normal Distribution. The Self-Learning Module in Statistics and Probability about the Normal Distribution created by the Department of Education has several problems, including many activities, unclear illustrations, and insufficient examples of concepts which enables learners to have a difficulty accomplishing the module. The purpose of this study is to determine the effectiveness of self-learning module on the academic performance of students in the subject Statistics and Probability, it will also explore students’ perception towards the quality of created Self-Learning Module in Statistics and Probability. Despite the availability of Self-Learning Modules in Statistics and Probability in the Philippines, there are still few literatures that discuss its effectiveness in improving the performance of Senior High School students in Statistics and Probability. In this study, a Self-Learning Module on Normal Distribution is evaluated using a quasi-experimental design. STEM students in Grade 11 from National University's Nazareth School will be the study's participants, chosen by purposive sampling. Google Forms will be utilized to find at least 100 STEM students in Grade 11. The research instrument consists of 20-item pre- and post-test to assess participants' knowledge and performance regarding Normal Distribution, and a Likert scale survey to evaluate how the students perceived the self-learning module. Pre-test, post-test, and Likert scale surveys will be utilized to gather data, with Jeffreys' Amazing Statistics Program (JASP) software being used for analysis.

Keywords: self-learning module, academic performance, statistics and probability, normal distribution

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Authors: P. R. Chauhan, S. K. Tyagi

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Adsorption refrigeration technology offers a sustainable and energy-efficient cooling alternative over traditional refrigeration technologies for meeting the fast-growing cooling demands. With its ability to utilize natural refrigerants, low-grade heat sources, and modular configurations, it has the potential to revolutionize the cooling industry. Despite these benefits, the commercial viability of this technology is hampered by several fundamental limiting constraints, including its large size, low uptake capacity, and poor performance as a result of deficient heat and mass transfer characteristics. The primary cause of adequate heat and mass transfer characteristics and magnitude of exergy loss in various real processes of adsorption cooling system can be assessed by the entropy generation rate analysis, i. e. Second law of Thermodynamics. Therefore, this article presents the second law of thermodynamic-based investigation in terms of entropy generation rate (EGR) to identify the energy losses in various processes of the HPCC-based adsorption system using MATLAB R2021b software. The adsorption technology-based cooling system consists of two beds made up of silica gel and arranged in a single stage, while the water is employed as a refrigerant, coolant, and hot fluid. The variation in process-wise EGR is examined corresponding to cycle time, and a comparative analysis is also presented. Moreover, the EGR is also evaluated in the external units, such as the heat source and heat sink unit used for regeneration and heat dump, respectively. The research findings revealed that the combination of adsorber and desorber, which operates across heat reservoirs with a higher temperature gradient, shares more than half of the total amount of EGR. Moreover, the EGR caused by the heat transfer process is determined to be the highest, followed by a heat sink, heat source, and mass transfer, respectively. in case of heat transfer process, the operation of the valve is determined to be responsible for more than half (54.9%) of the overall EGR during the heat transfer. However, the combined contribution of the external units, such as the source (18.03%) and sink (21.55%), to the total EGR, is 35.59%. The analysis and findings of the present research are expected to pinpoint the source of the energy waste in HPCC based adsorption cooling systems.

Keywords: adsorption cooling cycle, heat transfer, mass transfer, entropy generation, silica gel-water

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Authors: Pedro Esteban

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Most installations nowadays are exposed to many power quality problems, and they also face numerous challenges to comply with grid code and energy efficiency requirements. The reason behind this is that they are not designed to support nonlinear, non-balanced, and variable loads and generators that make up a large percentage of modern electric power systems. These problems and challenges become especially critical when designing green buildings and smart cities. These problems and challenges are caused by equipment that can be typically found in these installations like variable speed drives (VSD), transformers, lighting, battery chargers, double-conversion UPS (uninterruptible power supply) systems, highly dynamic loads, single-phase loads, fossil fuel generators and renewable generation sources, to name a few. Moreover, events like capacitor switching (from existing capacitor banks or passive harmonic filters), auto-reclose operations of transmission and distribution lines, or the starting of large motors also contribute to these problems and challenges. Active power filters (APF) are one of the fastest-growing power electronics technologies for solving power quality problems and meeting grid code and energy efficiency requirements for a wide range of segments and applications. They are a high performance, flexible, compact, modular, and cost-effective type of power electronics solutions that provide an instantaneous and effective response in low or high voltage electric power systems. They enable longer equipment lifetime, higher process reliability, improved power system capacity and stability, and reduced energy losses, complying with most demanding power quality and energy efficiency standards and grid codes. There can be found several types of active power filters, including active harmonic filters (AHF), static var generators (SVG), active load balancers (ALB), hybrid var compensators (HVC), and low harmonic drives (LHD) nowadays. All these devices can be used in applications in Smart Cities bringing several technical and economic benefits.

Keywords: power quality improvement, energy efficiency, grid code compliance, green buildings, smart cities

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Authors: Yu-Hsuan Liu, Ying-Fang Wang

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The objectives of the present study are to characterize nanoparticles generated from the laser metal deposition (LMD) process and to estimate particle concentrations deposited in the head (H), that the tracheobronchial (TB) and alveolar (A) regions, respectively. The studied LMD chamber (3.6m × 3.8m × 2.9m) is installed with a robot laser metal deposition machine. Direct-reading instrument of a scanning mobility particle sizer (SMPS, Model 3082, TSI Inc., St. Paul, MN, USA) was used to conduct static sampling inside the chamber for nanoparticle number concentration and particle size distribution measurements. The SMPS obtained particle number concentration at every 3 minutes, the diameter of the SMPS ranged from 11~372 nm when the aerosol and sheath flow rates were set at 0.6 and 6 L / min, respectively. The resultant size distributions were used to predict depositions of nanoparticles at the H, TB, and A regions of the respiratory tract using the UK National Radiological Protection Board’s (NRPB’s) LUDEP Software. Result that the number concentrations of nanoparticles in indoor background and LMD chamber were 4.8×10³ and 4.3×10⁵ # / cm³, respectively. However, the nanoparticles emitted from the LMD process was in the form of the uni-modal with number median diameter (NMD) and geometric standard deviation (GSD) as 142nm and 1.86, respectively. The fractions of the nanoparticles deposited on the alveolar region (A: 69.8%) were higher than the other two regions of the head region (H: 10.9%), tracheobronchial region (TB: 19.3%). This study conducted static sampling to measure the nanoparticles in the LMD process, and the results show that the fraction of particles deposited on the A region was higher than the other two regions. Therefore, applying the characteristics of nanoparticles emitted from LMD process could be provided valuable scientific-based evidence for exposure assessments in the future.

Keywords: exposure assessment, laser metal deposition process, nanoparticle, respiratory region

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Authors: Noury Bakrim

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From the point of view of language morphodynamics, interpretative Readability of the text-result (the stasis) is not the external hermeneutics of its various potential reading events but the paradigmatic, semantic immanence of its dynamics. In other words, interpretative Readability articulates the potential tension between projection (intentionality of the discursive event) and the result (Readability within the syntagmatic stasis). We then consider that translation represents much more a metalinguistic conversion of neurocognitive bilingual sub-routines and modular relations than a semantic equivalence. Furthermore, the actualizing Readability (the process of rewriting a target text within a target language/genre) builds upon the descriptive level between the generative syntax/semantic from and its paradigmatic potential translatability. Translation corpora reveal the evidence of a certain focusing on the positivist stasis of the source text at the expense of its interpretative Readability. For instance, Fluchere's brilliant translation of Miller's Tropic of cancer into French realizes unconsciously an inversion of the hierarchical relations between Life Thought and Fable: From Life Thought (fable) into Fable (Life Thought). We could regard the translation of Bernard Kreiss basing on Canetti's work die englischen Jahre (les annees anglaises) as another inversion of the historical scale from individual history into Hegelian history. In order to describe and test both translation process and result, we focus on the pedagogical practice which enables various principles grounding in interpretative/actualizing Readability. Henceforth, establishing the analytical uttering dynamics of the source text could be widened by other practices. The reversibility test (target - source text) or the comparison with a second translation in a third language (tertium comparationis A/B and A/C) point out the evidence of an impossible event. Therefore, it doesn't imply an uttering idealistic/absolute source but the irreducible/non-reproducible intentionality of its production event within the experience of world/discourse. The aim of this paper is to conceptualize translation as the tension between interpretative and actualizing Readability in a new approach grounding in morphodynamics of language and Translatability (mainly into French) within literary and non-literary texts articulating theoretical and described pedagogical corpora.

Keywords: readability, translation as deverbalization, translation as conversion, Tertium Comparationis, uttering actualization, translation pedagogy

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Authors: Scott Andersen

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Perhaps simply and rather unadornedly, consciousness is having multiple goals for action and the continuously adjudication of such goals to implement action, referred to as the Maps of Meaning (MoM) Consciousness Theory. The MoM theory triangulates through three parallel corollaries, action (behavior), mechanism (morphology/pathophysiology), and goals (teleology). (1) An organism’s consciousness contains a fluid, nested goals. These goals are not intentionality, but intersectionality, embodiment meeting the world. i.e., Darwinian inclusive fitness or randomization, then survival of the fittest. These goals form via gradual descent under inclusive fitness, the goals being the abstraction of a ‘match’ between the evolutionary environment and organism. Human consciousness implements the brain efficiency hypothesis, genetics, epigenetics, and experience crystallize efficiencies, not necessitating best or objective but fitness, i.e., perceived efficiency based on one’s adaptive environment. These efficiencies are objectively arbitrary, but determine the operation and level of one’s consciousness, termed extreme thrownness. Since inclusive fitness drives efficiencies in physiologic mechanism, morphology and behavior (action) and originates one’s goals, embodiment is necessarily entangled to human consciousness as its the intersection of mechanism or action (both necessitating embodiment) occurring in the world that determines fitness. Perception is the operant process of consciousness and is the consciousness’ de facto goal adjudication process. Goal operationalization is fundamentally efficiency-based via one’s unique neuronal mapping as a byproduct of genetics, epigenetics, and experience. Perception involves information intake and information discrimination, equally underpinned by efficiencies of inclusive fitness via extreme thrownness. Perception isn’t a ‘frame rate,’ but Bayesian priors of efficiency based on one’s extreme thrownness. Consciousness and human consciousness is a modular (i.e., a scalar level of richness, which builds up like building blocks) and dimensionalized (i.e., cognitive abilities become possibilities as emergent phenomena at various modularities, like stratified factors in factor analysis). The meta dimensions of human consciousness seemingly include intelligence quotient, personality (five-factor model), richness of perception intake, and richness of perception discrimination, among other potentialities. Future consciousness research should utilize factor analysis to parse modularities and dimensions of human consciousness and animal models.

Keywords: consciousness, perception, prospection, embodiment

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Authors: Van-Thanh Ho, Jaiyoung Ryu

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In soft robotics, the optimization of fluid dynamics through pneumatic methods plays a pivotal role in enhancing operational efficiency and reducing energy loss. This is particularly crucial when replacing conventional techniques such as cable-driven electromechanical systems. The pneumatic model employed in this study represents a sophisticated framework designed to efficiently channel pressure from a high-pressure reservoir to various muscle locations on the robot's body. This intricate network involves a branching system of tubes. The study introduces a comprehensive pneumatic model, encompassing the components of a reservoir, tubes, and Pneumatically Actuated Muscles (PAM). The development of this model is rooted in the principles of shock tube theory. Notably, the study leverages experimental data to enhance the understanding of the interplay between the PAM structure and the surrounding fluid. This improved interactive approach involves the use of morphing motion, guided by a contraction function. The study's findings demonstrate a high degree of accuracy in predicting pressure distribution within the PAM. The model's predictive capabilities ensure that the error in comparison to experimental data remains below a threshold of 10%. Additionally, the research employs a machine learning model, specifically a surrogate model based on the Kriging method, to assess and quantify uncertainty factors related to the initial reservoir pressure and tube diameter. This comprehensive approach enhances our understanding of pneumatic soft robotics and its potential for improved operational efficiency.

Keywords: pneumatic artificial muscles, pressure drop, morhing motion, branched network, surrogate model

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Authors: Francesca Spagnoli, Shenja van der Graaf, Pieter Ballon

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Humans do not behave rationally. We are emotional, easily influenced by others, as well as by our context. The study of human behaviour became a supreme endeavour within many academic disciplines, including economics, sociology, and clinical and social psychology. Understanding what motivates humans and triggers them to perform certain activities, and what it takes to change their behaviour, is central both for researchers and companies, as well as policy makers to implement efficient public policies. While numerous theoretical approaches for diverse domains such as health, retail, environment have been developed, the methodological models guiding the evaluation of such research have reached for a long time their limits. Within this context, digitisation, the Information and communication technologies (ICT) and wearable, the Internet of Things (IoT) connecting networks of devices, and new possibilities to collect and analyse massive amounts of data made it possible to study behaviour from a realistic perspective, as never before. Digital technologies make it possible to (1) capture data in real-life settings, (2) regain control over data by capturing the context of behaviour, and (3) analyse huge set of information through continuous measurement. Within this complex context, this paper describes a new framework for initiating behavioural change, capitalising on the digital developments in applied research projects and applicable both to academia, enterprises and policy makers. By applying this model, behavioural research can be conducted to address the issues of different domains, such as mobility, environment, health or media. The Modular Behavioural Analysis Approach (MBAA) is here described and firstly validated through a concrete use case within the domain of health. The results gathered have proven that disclosing information about health in connection with the use of digital apps for health, can be a leverage for changing behaviour, but it is only a first component requiring further follow-up actions. To this end, a clear definition of different 'behavioural profiles', towards which addressing several typologies of interventions, it is essential to effectively enable behavioural change. In the refined version of the MBAA a strong focus will rely on defining a methodology for shaping 'behavioural profiles' and related interventions, as well as the evaluation of side-effects on the creation of new business models and sustainability plans.

Keywords: behavioural change, framework, health, nudging, sustainability

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Authors: Wu Peng, Anders Liljerehn, Martin Magnevall

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In metal cutting, tool wear gradually changes the micro geometry of the cutting edge. Today there is a significant gap in understanding the impact these geometrical changes have on the cutting forces which governs tool deflection and heat generation in the cutting zone. Accurate models and understanding of the interaction between the work piece and cutting tool leads to improved accuracy in simulation of the cutting process. These simulations are useful in several application areas, e.g., optimization of insert geometry and machine tool monitoring. This study aims to develop an extended Kienzle force model to account for the effect of rake angle variations and tool flank wear have on the cutting forces. In this paper, the starting point sets from cutting force measurements using orthogonal turning tests of pre-machined flanches with well-defined width, using triangular coated inserts to assure orthogonal condition. The cutting forces have been measured by dynamometer with a set of three different rake angles, and wear progression have been monitored during machining by an optical measuring collaborative robot. The method utilizes the measured cutting forces with the inserts flank wear progression to extend the mechanistic cutting forces model with flank wear as an input parameter. The adapted cutting forces model is validated in a turning process with commercial cutting tools. This adapted cutting forces model shows the significant capability of prediction of cutting forces accounting for tools flank wear and different-rake-angle cutting tool inserts. The result of this study suggests that the nonlinear effect of tools flank wear and interaction between the work piece and the cutting tool can be considered by the developed cutting forces model.

Keywords: cutting force, kienzle model, predictive model, tool flank wear

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Authors: Alvin Chun Man Kwok, Wai Sun Chan, Wei Yuan, Joseph Tin Yum Wong

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Cellulose, the most abundant biopolymer, is the major constituent of plant and dinoflagellate cell walls. Thecate dinoflagellates, in particular, are renowned for their remarkable capacity to synthesize intricate cellulosic thecal plates (CTPs). Unlike the extracellular two-dimensional structure of plant cell walls, these CTPs are three-dimensional and reside within the cellular structure itself. The deposition of CTPs occurs with remarkable precision, and their arrangement serves as crucial taxonomic markers. It is noteworthy that these plates possess the hardness of wood, despite the absence of lignin. Partial and prolonged hydrolysis of CTPs results in the formation of uniform long bundles and lowdimensional, modular crystalline whiskers. This observation aligns with the consistent nanomechanical properties, suggesting a CTPboard structure. The unique composition and structural characteristics of CTPs distinguish them from other cellulose-based materials in the natural world. Spectroscopic studies using Raman and FTIR methods indicate a clear low crystallinity index, with the OH shift becoming more distinct following SDS treatment. Birefringence imaging confirms the highly organized structure of CTPs, demonstrating varying degrees of anisotropy in different regions, including both seaward and cytosolic passages. The knockdown of a cellulose synthase enzyme in dinoflagellates resulted in severe malformation of CTPs and hindered the life-cycle transition. Unlike certain other microalgal groups, these unique circum-spherical depositions of CTPs were not pre-fabricated and transported "to site," but synthesized within alveolar sacs at the specific site. Our research is particularly focused on unraveling the mechanisms underlying the biodeposition of CTPs and exploring their potential biotechnological applications. Understanding the processes involved in CTP formation can pave the way for harnessing their unique properties for various practical applications. Dinoflagellates play a crucial role as major agents of algal blooms and are also known for producing anti-greenhouse sulfur compounds such as DMS/DMSP, highlighting the significance of CTPs as a carbon-neutral source of cellulose. Grant acknowledgement: Research in the laboratory are supported by GRF16104523 from Research Grant Council to JTYW.

Keywords: cellulosic thecal plates, dinoflagellates, cellulose, cell wall

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Authors: Cristóbal Moënne-Loccoz, Rodrigo C. Vergara, Vladimir López, Domingo Mery, Diego Cosmelli

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Our daily interaction with computational interfaces is plagued of situations in which we go from inexperienced users to experts through self-motivated exploration of the same task. In many of these interactions, we must learn to find our way through a sequence of decisions and actions before obtaining the desired result. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion so that a specific sequence of actions must be performed in order to produce the expected outcome. But, as they become experts in the use of such interfaces, do users adopt specific search and learning strategies? Moreover, if so, can we use this information to follow the process of expertise development and, eventually, predict future actions? This would be a critical step towards building truly adaptive interfaces that can facilitate interaction at different moments of the learning curve. Furthermore, it could provide a window into potential mechanisms underlying decision-making behavior in real world scenarios. Here we tackle this question using a simple game interface that instantiates a 4-level binary decision tree (BDT) sequential decision-making task. Participants have to explore the interface and discover an underlying concept-icon mapping in order to complete the game. We develop a Hidden Markov Model (HMM)-based approach whereby a set of stereotyped, hierarchically related search behaviors act as hidden states. Using this model, we are able to track the decision-making process as participants explore, learn and develop expertise in the use of the interface. Our results show that partitioning the problem space into such stereotyped strategies is sufficient to capture a host of exploratory and learning behaviors. Moreover, using the modular architecture of stereotyped strategies as a Mixture of Experts, we are able to simultaneously ask the experts about the user's most probable future actions. We show that for those participants that learn the task, it becomes possible to predict their next decision, above chance, approximately halfway through the game. Our long-term goal is, on the basis of a better understanding of real-world decision-making processes, to inform the construction of interfaces that can establish dynamic conversations with their users in order to facilitate the development of expertise.

Keywords: behavioral modeling, expertise acquisition, hidden markov models, sequential decision-making

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Authors: Francesco Lubrano, Fabrizio Bertone, Federico Stirano

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Modern societies strongly depend on Critical Infrastructures (CI). Hospitals, power supplies, water supplies, telecommunications are just few examples of CIs that provide vital functions to societies. CIs like hospitals are very complex environments, characterized by a huge number of cyber and physical systems that are becoming increasingly integrated. Ensuring a high level of security within such critical infrastructure requires a deep knowledge of vulnerabilities, threats, and potential attacks that may occur, as well as defence and prevention or mitigation strategies. The possibility to remotely monitor and control almost everything is pushing the adoption of network-connected devices. This implicitly introduces new threats and potential vulnerabilities, posing a risk, especially to those devices connected to the Internet. Modern medical devices used in hospitals are not an exception and are more and more being connected to enhance their functionalities and easing the management. Moreover, hospitals are environments with high flows of people, that are difficult to monitor and can somehow easily have access to the same places used by the staff, potentially creating damages. It is therefore clear that physical and cyber threats should be considered, analysed, and treated together as cyber-physical threats. This means that an integrated approach is required. SAFECARE, an integrated cyber-physical security solution, tries to respond to the presented issues within healthcare infrastructures. The challenge is to bring together the most advanced technologies from the physical and cyber security spheres, to achieve a global optimum for systemic security and for the management of combined cyber and physical threats and incidents and their interconnections. Moreover, potential impacts and cascading effects are evaluated through impact propagation models that rely on modular ontologies and a rule-based engine. Indeed, SAFECARE architecture foresees i) a macroblock related to cyber security field, where innovative tools are deployed to monitor network traffic, systems and medical devices; ii) a physical security macroblock, where video management systems are coupled with access control management, building management systems and innovative AI algorithms to detect behavior anomalies; iii) an integration system that collects all the incoming incidents, simulating their potential cascading effects, providing alerts and updated information regarding assets availability.

Keywords: cyber security, defence strategies, impact propagation, integrated security, physical security

Procedia PDF Downloads 155

Authors: David L. Olson, Stephen B. H. Bruder, Adam S. Watkins, Cleon E. Davis

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In global navigation satellite systems (GNSS), denied settings such as indoor environments, autonomous mobile robots are often limited to dead-reckoning navigation techniques to determine their position, velocity, and attitude (PVA). Localization is typically accomplished by employing an inertial measurement unit (IMU), which, while precise in nature, accumulates errors rapidly and severely degrades the localization solution. Standard sensor fusion methods, such as Kalman filtering, aim to fuse precise IMU measurements with accurate aiding sensors to establish a precise and accurate solution. In indoor environments, where GNSS and no other a priori information is known about the environment, effective sensor fusion is difficult to achieve, as accurate aiding sensor choices are sparse. However, an opportunity arises by employing a depth camera in the indoor environment. A depth camera can capture point clouds of the surrounding floors and walls. Extracting attitude from these surfaces can serve as an accurate aiding source, which directly combats errors that arise due to gyroscope imperfections. This configuration for sensor fusion leads to a dramatic reduction of PVA error compared to traditional aiding sensor configurations. This paper provides the theoretical basis for the depth camera aiding sensor method, initial expectations of performance benefit via simulation, and hardware implementation, thus verifying its veracity. Hardware implementation is performed on the Quanser Qbot 2™ mobile robot, with a Vector-Nav VN-200™ IMU and Kinect™ camera from Microsoft.

Keywords: autonomous mobile robotics, dead reckoning, depth camera, inertial navigation, Kalman filtering, localization, sensor fusion

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Authors: Iyd Eqqab Maree, Habil Jurgen Bast

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Vibration control of machines and structures incorporating viscoelastic materials in suitable arrangement is an important aspect of investigation. The use of viscoelastic layers constrained between elastic layers is known to be effective for damping of flexural vibrations of structures over a wide range of frequencies. The energy dissipated in these arrangements is due to shear deformation in the viscoelastic layers, which occurs due to flexural vibration of the structures. Multilayered cantilever sandwich beam like structures can be used in aircrafts and other applications such as robot arms for effective vibration control. These members may experience parametric instability when subjected to time dependant forces. The theory of dynamic stability of elastic systems deals with the study of vibrations induced by pulsating loads that are parametric with respect to certain forms of deformation. The purpose of the present work is to investigate the dynamic stability of a three layered symmetric sandwich beam (Drone Aircraft wings ) subjected to an end periodic axial force . Equations of motion are derived using finite element method (MATLAB software). It is observed that with increase in core thickness parameter fundamental buckling load increases. The fundamental resonant frequency and second mode frequency parameter also increase with increase in core thickness parameter. Fundamental loss factor and second mode loss factor also increase with increase in core thickness parameter. Increase in core thickness parameter enhances the stability of the beam. With increase in core loss factor also the stability of the beam enhances. There is a very good agreement of the experimental results with the theoretical findings.

Keywords: steel cantilever beam, viscoelastic material core, loss factor, transition region, MATLAB R2011a

Procedia PDF Downloads 462

Authors: Volker Landersheim, Daria Manushyna, Thinh Pham, Dai-Duong Tran, Thomas Geury, Omar Hegazy, Steven Wilkins

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Air pollution is one of the emerging problems in our society. Targets of reduction of CO₂ emissions address low-carbon and resource-efficient transport. (Plug-in) hybrid electric propulsion concepts offer the possibility to reduce total cost of ownership (TCO) and emissions for public transport vehicles (e.g., bus application). In this context, typically, diesel engines are used to form the hybrid propulsion system of the vehicle. Though the technological development of diesel engines experience major advantages, some challenges such as the high amount of particle emissions remain relevant. Gaseous fuels (i.e., compressed natural gases (CNGs) or liquefied petroleum gases (LPGs) represent an attractive alternative to diesel because of their composition. In the framework of the research project 'Optimised Real-world Cost-Competitive Modular Hybrid Architecture' (ORCA), which was funded by the EU, two different hybrid-electric propulsion concepts have been investigated: one using a diesel engine as internal combustion engine and one using CNG as fuel. The aim of the current study is to analyze specific benefits for the aforementioned hybrid propulsion systems for predefined driving scenarios with regard to emissions and total cost of ownership in bus application. Engine models based on experimental data for diesel and CNG were developed. For the purpose of designing optimal energy management strategies for each propulsion system, maps-driven or quasi-static models for specific engine types are used in the simulation framework. An analogous modelling approach has been chosen to represent emissions. This paper compares the two concepts regarding their CO₂ and NOx emissions. This comparison is performed for relevant bus missions (urban, suburban, with and without zero-emission zone) and with different energy management strategies. In addition to the emissions, also the downsizing potential of the combustion engine has been analysed to minimize the powertrain TCO (pTCO) for plug-in hybrid electric buses. The results of the performed analyses show that the hybrid vehicle concept using the CNG engine shows advantages both with respect to emissions as well as to pTCO. The pTCO is 10% lower, CO₂ emissions are 13% lower, and the NOx emissions are more than 50% lower than with the diesel combustion engine. These results are consistent across all usage profiles under investigation.

Keywords: bus transport, emissions, hybrid propulsion, pTCO, CNG

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Authors: Jemini Vyas, Oluwatobi Adeyoe, Jenny Branagan, Chandran Tanabalan, John Beatty, Aakash Pai

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Introduction: The development of robotic surgery has accelerated centralisation to tertiary centres, where robotic radical prostatectomy (RP) is offered. The purpose of concentrating treatment in high volume specialist centres is to improve the quality of care and patient outcomes. The aim of this study was to assess the impact on clinical outcomes of centralisation for locally diagnosed patients undergoing RP. Methods: Clinical outcomes for 169 consecutive laparoscopic & open RP pre-centralisation were retrospectively compared with 50 consecutive robotic RP conducted over a similar period post-centralisation. Preoperative risk stratification and time to surgery were collected. Perioperative outcomes, including length of stay (LOS) and complications, were collated. Post-operative outcomes, including erectile dysfunction (ED), biochemical recurrence (BCR), and urinary continence, were assessed. Results: Preoperative risk stratification showed no difference between the two groups. The median time from diagnosis to treatment was similar between the two groups (pre-centralisation, 121 days, post-centralisation, 117 days). The mean length of stay (pre-centralisation, 2.1 days, post-centralisation, 1.6 days) showed no significant difference (p=0.073). Proportion of overall complications (pre-centralisation, 11.4%, post-centralisation, 8.7%) and complications, above Clavien-Dindo 2, were similar between the two groups (pre-centralisation1.2%, post-centralisation 2.2%). Post operative functional parameters, including continence and ED, were comparable. Five-year BCR free rate was 78% for the pre-centralisation group and 79% for the post centralisation group. Conclusion: For our cohort of patients, clinical outcomes have remained static during centralisation. It is imperative that centralisation is accompanied by increased capacity, streamlining of pathways, and training to ensure that improved quality of care is achieved. Our institution has newly acquired a robot, and prospectively studying this data may support the reversal of centralisation for RP surgery.

Keywords: prostate, cancer, prostatectomy, clinical

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Authors: Nozar Kishi, Babak Kamrani, Filmon Habte

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Natural hazards such as earthquakes and tropical storms, are very frequent and highly destructive in Japan. Japan experiences, every year on average, more than 10 tropical cyclones that come within damaging reach, and earthquakes of moment magnitude 6 or greater. We have developed stochastic catastrophe models to address the risk associated with the entire suite of damaging events in Japan, for use by insurance, reinsurance, NGOs and governmental institutions. KCC’s (Karen Clark and Company) catastrophe models are procedures constituted of four modular segments: 1) stochastic events sets that would represent the statistics of the past events, hazard attenuation functions that could model the local intensity, vulnerability functions that would address the repair need for local buildings exposed to the hazard, and financial module addressing policy conditions that could estimates the losses incurring as result of. The events module is comprised of events (faults or tracks) with different intensities with corresponding probabilities. They are based on the same statistics as observed through the historical catalog. The hazard module delivers the hazard intensity (ground motion or wind speed) at location of each building. The vulnerability module provides library of damage functions that would relate the hazard intensity to repair need as percentage of the replacement value. The financial module reports the expected loss, given the payoff policies and regulations. We have divided Japan into regions with similar typhoon climatology, and earthquake micro-zones, within each the characteristics of events are similar enough for stochastic modeling. For each region, then, a set of stochastic events is developed that results in events with intensities corresponding to annual occurrence probabilities that are of interest to financial communities; such as 0.01, 0.004, etc. The intensities, corresponding to these probabilities (called CE, Characteristics Events) are selected through a superstratified sampling approach that is based on the primary uncertainty. Region specific hazard intensity attenuation functions followed by vulnerability models leads to estimation of repair costs. Extensive economic exposure model addresses all local construction and occupancy types, such as post-linter Shinand Okabe wood, as well as concrete confined in steel, SRC (Steel-Reinforced Concrete), high-rise.

Keywords: typhoon, earthquake, Japan, catastrophe modelling, stochastic modeling, stratified sampling, loss model, ERM

Procedia PDF Downloads 259

Authors: M. Reza Roshandel, Tannaz Aghaei Badr, Batoul Khoundabi, Sara C. Lewis, Soroush Rais-Bahrami, John Sfakianos, Reza Mehrazin, Ash K. Tewari

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Introduction: Prostate biopsy is the most reliable diagnostic method for choosing the appropriate management of prostate cancer. However, discrepancies between Gleason grade groups (GG) of different biopsies remain a significant concern. This study aims to assess the association of the radiological factors with GG discrepancies in patients with index Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions, using radical prostatectomy (RP) specimens as the most accurate and informative pathology. Methods: This single-institutional retrospective study was performed on a total of 2289 consecutive prostate cancer patients with combined targeted and systematic prostate biopsy followed by radical prostatectomy (RP). The database was explored for patients with the index PI-RADS 3 lesions version 2 and 2.1. Cancers with PI-RADS 4 or 5 scoring were excluded from the study. Patient characteristics and radiologic features were analyzed by multivariable logistic regression. Number-density of lesions was defined as the number of lesions per prostatic volume. Results: Of the 151 prostate cancer cases with PI-RADS 3 index lesions, 27% and 17% had upgrades and downgrades at RP, respectively. Analysis of grade changes showed no significant associations between discrepancies and the number or the number density of PI-RADS 3 lesions. Moreover, the study showed no significant association of the GG changes with race, age, location of the lesions, or prostate volume. Conclusions: This study demonstrated that in PI-RADS 3 cancerous nodules, the chance of the pathology changes in the final pathology of RP specimens was low. Furthermore, having multiple PI-RADS 3 nodules did not change the conclusion, as the possibility of grade changes in patients with multiple nodules was similar to those with solitary lesions.

Keywords: prostate, adenocarcinoma, multiparametric MRI, Gleason score, robot-assisted surgery

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Authors: Martina Marinelli, Samanta Vellante, Francesco Pilotti, Daniele Di Valerio, Gaetanino Paolone

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Any development in web marketing technology requires changes in information engineering to identify instruments and techniques suitable for the production of software applications for informative marketing. Moreover, for large web solutions, designing an interface that enables human interactions is a complex process that must bridge between informative marketing requirements and the developed solution. A user-friendly interface in web marketing applications is crucial for a successful business. The paper introduces mkInfo - a software platform that implements informative marketing. Informative marketing is a new interpretation of marketing which places the information at the center of every marketing action. The creative team includes software engineering researchers who have recently authored an article on automatic code generation. The authors have created the mkInfo software platform to generate informative marketing web applications. For each web application, it is possible to automatically implement an opt in page, a landing page, a sales page, and a thank you page: one only needs to insert the content. mkInfo implements an autoresponder to send mail according to a predetermined schedule. The mkInfo platform also includes e-commerce for a product or service. The stakeholder can access any opt-in page and get basic information about a product or service. If he wants to know more, he will need to provide an e-mail address to access a landing page that will generate an e-mail sequence. It will provide him with complete information about the product or the service. From this point on, the stakeholder becomes a user and is now able to purchase the product or related services through the mkInfo platform. This paper suggests a possible definition for Informative Marketing, illustrates its basic principles, and finally details the mkInfo platform that implements it. This paper also offers some Informative Marketing models, which are implemented in the mkInfo platform. Informative marketing can be applied to products or services. It is necessary to realize a web application for each product or service. The mkInfo platform enables the product or the service producer to send information concerning a specific product or service to all stakeholders. In conclusion, the technical contributions of this paper are: a different interpretation of marketing based on information; a modular architecture for web applications, particularly for one with standard features such as information storage, exchange, and delivery; multiple models to implement informative marketing; a software platform enabling the implementation of such models in a web application. Future research aims to enable stakeholders to provide information about a product or a service so that the information gathered about a product or a service includes both the producer’s and the stakeholders' point of view. The purpose is to create an all-inclusive management system of the knowledge regarding a specific product or service: a system that includes everything about the product or service and is able to address even unexpected questions.

Keywords: informative marketing, opt in page, software platform, web application

Procedia PDF Downloads 122

Authors: Elena Petersen, Inna Kornienko, Svetlana Guryeva, Sergey Simakov

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In vitro organoid cultivation requires the simultaneous provision of necessary vascularization and nutrients perfusion of cells during organoid development. However, many aspects of this problem are still unsolved. The functionality of vascular network intergrowth is limited during early stages of organoid development since a function of the vascular network initiated on final stages of in vitro organoid cultivation. Therefore, a microchannel network should be created in early stages of organoid cultivation in hydrogel matrix aimed to conduct and maintain minimally required the level of nutrients perfusion for all cells in the expanding organoid. The network configuration should be designed properly in order to exclude hypoxic and necrotic zones in expanding organoid at all stages of its cultivation. In vitro vascularization is currently the main issue within the field of tissue engineering. As perfusion and oxygen transport have direct effects on cell viability and differentiation, researchers are currently limited only to tissues of few millimeters in thickness. These limitations are imposed by mass transfer and are defined by the balance between the metabolic demand of the cellular components in the system and the size of the scaffold. Current approaches include growth factor delivery, channeled scaffolds, perfusion bioreactors, microfluidics, cell co-cultures, cell functionalization, modular assembly, and in vivo systems. These approaches may improve cell viability or generate capillary-like structures within a tissue construct. Thus, there is a fundamental disconnect between defining the metabolic needs of tissue through quantitative measurements of oxygen and nutrient diffusion and the potential ease of integration into host vasculature for future in vivo implantation. A model is proposed for growth prognosis of the organoid perfusion based on joint simulations of general nutrient diffusion, nutrient diffusion to the hydrogel matrix through the contact surfaces and microchannels walls, nutrient consumption by the cells of expanding organoid, including biomatrix contraction during tissue development, which is associated with changed consumption rate of growing organoid cells. The model allows computing effective microchannel network design giving minimally required the level of nutrients concentration in all parts of growing organoid. It can be used for preliminary planning of microchannel network design and simulations of nutrients supply rate depending on the stage of organoid development.

Keywords: 3D model, consumption model, diffusion, spheroid, tissue organoid

Procedia PDF Downloads 306

Authors: Malte Brettel, Niklas Friederichsen, Michael Keller, Marius Rosenberg

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The German manufacturing industry has to withstand an increasing global competition on product quality and production costs. As labor costs are high, several industries have suffered severely under the relocation of production facilities towards aspiring countries, which have managed to close the productivity and quality gap substantially. Established manufacturing companies have recognized that customers are not willing to pay large price premiums for incremental quality improvements. As a consequence, many companies from the German manufacturing industry adjust their production focusing on customized products and fast time to market. Leveraging the advantages of novel production strategies such as Agile Manufacturing and Mass Customization, manufacturing companies transform into integrated networks, in which companies unite their core competencies. Hereby, virtualization of the process- and supply-chain ensures smooth inter-company operations providing real-time access to relevant product and production information for all participating entities. Boundaries of companies deteriorate, as autonomous systems exchange data, gained by embedded systems throughout the entire value chain. By including Cyber-Physical-Systems, advanced communication between machines is tantamount to their dialogue with humans. The increasing utilization of information and communication technology allows digital engineering of products and production processes alike. Modular simulation and modeling techniques allow decentralized units to flexibly alter products and thereby enable rapid product innovation. The present article describes the developments of Industry 4.0 within the literature and reviews the associated research streams. Hereby, we analyze eight scientific journals with regards to the following research fields: Individualized production, end-to-end engineering in a virtual process chain and production networks. We employ cluster analysis to assign sub-topics into the respective research field. To assess the practical implications, we conducted face-to-face interviews with managers from the industry as well as from the consulting business using a structured interview guideline. The results reveal reasons for the adaption and refusal of Industry 4.0 practices from a managerial point of view. Our findings contribute to the upcoming research stream of Industry 4.0 and support decision-makers to assess their need for transformation towards Industry 4.0 practices.

Keywords: Industry 4.0., mass customization, production networks, virtual process-chain

Procedia PDF Downloads 267

Authors: Christian Doppler, Gernot Hirschl, Gerhard Zsiga

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Starting from 2020, an EU-wide CO2-limitation of 95g/km is scheduled for the average of an OEMs passenger car fleet. Considering that, further measures of optimization on the diesel cycle will be necessary in order to reduce fuel consumption and emissions while keeping performance values adequate at the least. The present article deals with charge air cooling (CAC) on the basis of a diesel passenger car model in a 0D/1D-working process calculation environment. The considered engine is a 2.4 litre EURO VI diesel engine with variable geometry turbocharger (VGT) and low-pressure exhaust gas recirculation (LP EGR). The object of study was the impact of charge air cooling on the engine working process at constant boundary conditions which could have been conducted with an available and validated engine model in AVL BOOST. Part load was realized with constant power and NOx-emissions, whereas full load was accomplished with a lambda control in order to obtain maximum engine performance. The informative results were used to implement a simulation model in Matlab/Simulink which is further integrated into a full vehicle simulation environment via coupling with ICOS (Independent Co-Simulation Platform). Next, the dynamic engine behavior was validated and modified with load steps taken from the engine test bed. Due to the modular setup in the Co-Simulation, different CAC-models have been simulated quickly with their different influences on the working process. In doing so, a new cooler variation isn’t needed to be reproduced and implemented into the primary simulation model environment, but is implemented quickly and easily as an independent component into the simulation entity. By means of the association of the engine model, longitudinal dynamics vehicle model and different CAC models (air/air & water/air variants) in both steady state and transient operational modes, statements are gained regarding fuel consumption, NOx-emissions and power behavior. The fact that there is no more need of a complex engine model is very advantageous for the overall simulation volume. Beside of the simulation with the mentioned demonstrator engine, there have also been conducted several experimental investigations on the engine test bench. Here the comparison of a standard CAC with an intake-manifold-integrated CAC was executed in particular. Simulative as well as experimental tests showed benefits for the water/air CAC variant (on test bed especially the intake manifold integrated variant). The benefits are illustrated by a reduced pressure loss and a gain in air efficiency and CAC efficiency, those who all lead to minimized emission and fuel consumption for stationary and transient operation.

Keywords: air/water-charge air cooler, co-simulation, diesel working process, EURO VI fuel consumption

Procedia PDF Downloads 261

Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservices are a software development methodology in which applications are built by composing a set of independently deploy-able, small, modular services. Each service runs a unique process and it gets instantiated and deployed in one or more machines (we assume that different microservices are deployed into different machines). Microservices are becoming the de facto standard for developing distributed cloud applications due to their reduced release cycles. In principle, the responsibility of a microservice can be as simple as implementing a single function, which can lead to the following issues: - Resource fragmentation due to the virtual machine boundary. - Poor communication performance between microservices. Two composition techniques can be used to optimize resource fragmentation and communication performance: aggregation and embedding of microservices. Aggregation allows the deployment of a set of microservices on the same machine using a proxy server. Aggregation helps to reduce resource fragmentation, and is particularly useful when the aggregated services have a similar scalability behavior. Embedding deals with communication performance by deploying on the same virtual machine those microservices that require a communication channel (localhost bandwidth is reported to be about 40 times faster than cloud vendor local networks and it offers better reliability). Embedding can also reduce dependencies on load balancer services since the communication takes place on a single virtual machine. For example, assume that microservice A has two instances, a1 and a2, and it communicates with microservice B, which also has two instances, b1 and b2. One embedding can deploy a1 and b1 on machine m1, and a2 and b2 are deployed on a different machine m2. This deployment configuration allows each pair (a1-b1), (a2-b2) to communicate using the localhost interface without the need of a load balancer between microservices A and B. Aggregation and embedding techniques are complex since different microservices might have incompatible runtime dependencies which forbid them from being installed on the same machine. There is also a security concern since the attack surface between microservices can be larger. Luckily, container technology allows to run several processes on the same machine in an isolated manner, solving the incompatibility of running dependencies and the previous security concern, thus greatly simplifying aggregation/embedding implementations by just deploying a microservice container on the same machine as the aggregated/embedded microservice container. Therefore, a wide variety of deployment configurations can be described by combining aggregation and embedding to create an efficient and robust microservice architecture. This paper presents a formal method that receives a declarative definition of a microservice architecture and proposes different optimized deployment configurations by aggregating/embedding microservices. The first prototype is based on i2kit, a deployment tool also submitted to ICWS 2018. The proposed prototype optimizes the following parameters: network/system performance, resource usage, resource costs and failure tolerance.

Keywords: aggregation, deployment, embedding, resource allocation

Procedia PDF Downloads 196